SURF Program Research Opportunities in Gaithersburg, Maryland

Communications Technology Laboratory (CTL)

The CTL serves as an independent, unbiased arbiter of trusted measurements and standards to government and industry and focuses on developing precision instrumentation and creating test protocols, models, and simulation tools to enable a range of emerging wireless technologies. The CTL is also home to the National Advanced Spectrum and Communications Test Network (NASCTN), which provides a neutral forum for addressing spectrum-sharing challenges. Learn more about CTL.

Contacts

Lotfi Benmohamed, (301) 975-3650, lotfi.benmohamed [at] nist.gov (lotfi[dot]benmohamed[at]nist[dot]gov)
Wesley Garey, (301) 975-5190, wesley.garey [at] nist.gov (wesley[dot]garey[at]nist[dot]gov)
David W. Griffith, (301) 975-3512, david.griffith [at] nist.gov (david[dot]griffith[at]nist[dot]gov)
Jian Wang, (301) 975-8012, jian.wang [at] nist.gov (jian[dot]wang[at]nist[dot]gov)

CTL Research Opportunities (2024 Projects)

Wireless Networks Division (Div 673)

673-1 Simulation and Modeling of Future Wireless Communication Systems
Wesley Garey, (301) 975-5190, wesley.garey [at] nist.gov (wesley[dot]garey[at]nist[dot]gov)
Every new generation of wireless communication technologies is more capable but more complex than the previous generation. Wireless systems require collaboration by hundreds of organizations worldwide and take years to design, test, and implement. An important part of the development process is computer simulations of proposed network technologies using tools like ns3 (https://www.nsnam.org/). NIST actively works with the ns3 developer community to create new modules that incorporate the latest wireless technologies. The SURF applicant selected to work on this project will help extend the simulation models of the psc-ns3 codebase (https://github.com/usnistgov/psc-ns3) that WND has developed and that researchers use to investigate existing and emerging wireless communication technologies. These include Public Safety Communication (PSC) applications, Fifth Generation (5G) New Radio (NR) Sidelink (SL) communication, Proximity Services (ProSe), and simulation visualization tools (https://github.com/usnistgov/NetSimulyzer). This task involves working with a team of developers to design, implement, document, and test new capabilities in the psc-ns3 codebase, and will primarily involve using the C++ programing language and Linux to implement and run ns-3 simulations. [In-person or virtual opportunity]

673-2 Deployment and Evaluation of 5G Open RAN Testbed
Fernando Cintron, 301-975-6353, fernando.cintron [at] nist.gov (fernando[dot]cintron[at]nist[dot]gov)
The Wireless Networks Division (WND) works with industry, academia, and other government entities to develop, deploy, and promote emerging technologies and standards for wireless networks. One area of interest within WND is the evaluation of next generation networks based on open-source solutions compliant with the Open Radio Access Network (O-RAN) Alliance specifications. The selected candidate will work on the performance assessment of Fifth Generation (5G) testbed deployments, and the interaction of individual components within the network, such as the RAN Intelligent Controller (RIC). The selected candidate will help the team evaluate some of the components and interfaces capabilities and compliance to O-RAN Alliance specifications. In addition, the selected candidate may work on the testbed towards specific features of 5G RAN, such as RAN slicing and resource orchestration.
Desired skills/tools: Linux shell scripting, git, LaTeX, communication skills, writing skills, programming skills, networking tools experience (iperf3, Wireshark), experience with Software Defined Radios (SDR) is preferred but not essential. [In-person opportunity]

673-3 Machine Learning Assisted Radio Frequency Sensing
Jack Chuang and Jian Wang, 301-975-4171 and 301-975-8012, jack.chuang [at] nist.gov (jack[dot]chuang[at]nist[dot]gov) and jian.wang [at] nist.gov (jian[dot]wang[at]nist[dot]gov)
Artificial intelligence (AI) has been in the news a lot since the debut of ChatGPT a year ago, because of the power of large language models like it to perform functions previously restricted to humans such as generating prose and writing programs. But AI is a powerful tool that is being used in other areas of science and engineering, including developing the next generation of wireless communications systems. In addition to supporting very high speed and very low latency data transmissions, tomorrow’s wireless networks will also integrate sensing capabilities that can detect the presence of nearby people and objects, such as cars, obstacles, and Uncrewed Aerial Vehicles (UAVs). The Wireless Networks Division in the Communications Technology Laboratory at NIST is investigating how to automate sensing so that an Integrated Sensing and Communications (ISAC) system can identify the major features of its environment and adapt to changing conditions. This will involve training AI systems to recognize the signatures of radio waves reflected from nearby objects and distinguish them from background noise. The student will use data collected from NIST’s sensing experiments involving radio waves at the frequencies in the 10s of Gigahertz that will be used by future wireless networks to train AI systems to identify and locate clusters of reflected radio waves and then validate the performance of the AI system that they trained.
Desired Skills: Applied machine learning, MATLAB and/or Python programming languages, Git version control, and strong communication abilities. [In-person opportunity]

673-4 Deployment and Evaluation of Secure Virtualization Environments for 5G O-RANs
Doug Montgomery and Scott Rose, 301-960-3630 and 301-975-8439, dougm [at] nist.gov (dougm[at]nist[dot]gov) and scott.rose [at] nist.gov (scott[dot]rose[at]nist[dot]gov)
5G Open-Radio Access Networks (O-RAN) technologies seek to transform radio access networks from single vendor solutions based upon proprietary appliances to a disaggregated network architecture of components and functions, with standardized open interfaces, and designed to be deployed in virtualized and cloud native environments. 
NIST has recently actively engaged in O-RAN Alliance standards development, focusing on enhancing the security of virtualized, cloud native O-RAN functions. This area has both the greatest potential to increase overall network security and the greatest potential risk to the eventual commercial viability of O-RAN technologies. This project will involve enhancing existing 5G O-RAN laboratory testbeds to support emerging security standards, recommendations, and technologies for cloud native virtualization environments (e.g., Kubernetes, OpenShift, etc.), evaluating the ability of existing open-source virtualization environments to support such security requirements, and employing existing open-source tools to actively test the security of virtualized network environments to evaluate and verify secure configurations.
Desired skills / experience:  Linux, Kubernetes / Docker, service-based architectures, Python, dev-ops / network programming, network protocols / tools / technologies (http, TLS, PKI, OAUTH, Wireshark), penetration testing concepts and tools. [In-person opportunity]

673-5 Development of a Web Based Test Systems for Internet Security Routing Technologies
Doug Montgomery and Oliver Borchert, 301-960-3630 and 301-975-4856, dougm [at] nist.gov (dougm[at]nist[dot]gov) and oliver.borchert [at] nist.gov (oliver[dot]borchert[at]nist[dot]gov)
NIST is actively involved in the design of standardization of technologies to detect and mitigate “route leaks” in the Internet’s global routing infrastructure. Such route leaks lead to catastrophic outages in large subsets of the Internet that can last for several hours or days. NIST has been instrumental in standardizing a route leak mitigation technique called Autonomous System Provider Authorization (ASPA) and has developed stand-alone test tools and reference data sets to test implementations of ASPA in commercial routers. This project will take these initial stand-alone ASPA test tools and implement a web-based front end to evolve the tools into a distributed testing service that enables remote testing and automated results evaluation of remote ASPA implementations.
Desired skills: web front-end development (HTML, CSS, CSS frameworks), Python, Flask, network programming, SQL, Git, Linux, working knowledge of Internet protocols (DNS, BGP). [In-person opportunity]

Smart Connected Systems Division (Div 674)

674-1 easyEXPRESS - NIST’s First Visual Studio Code Extension
Allison Barnard Feeney, 301-975-3181, allison.barnardfeeney [at] nist.gov (allison[dot]barnardfeeney[at]nist[dot]gov)
STEP (STandard for the Exchange of Product data) is a neutral file format primarily used to move engineering design data between CAD (Computer-Aided Design) systems and from CAD systems to CAM (Computer-Aided Manufacturing) and CAI (Computer-Aided Inspection) systems, eliminating the need for paper drawings and error-prone re-entry of design information into CAM and CAI planning systems. You will be developing new features for an already published Visual Studio Code extension (NIST’s easyEXPRESS) that implements language support for the EXPRESS (ISO 10303-11 ed2) information modeling language that is used in the widely implemented STEP standard. 
Billions of STEP files are in use world-wide, and  many are freely available on sites like GrabCAD. We are doing our best to build modern tools to support this decades-old, but still used, language. In doing so, we are supporting both standards developers who are adding new capabilities to STEP, and innovators who want to leverage use of the STEP ecosystem to build exciting new products and business models. In this project, you will learn how to develop Visual Studio Code extensions and how to implement a language server.
Desired skills: computer science major or minor, experience with JavaScript/TypeScript, exposure to information modeling is a plus. [In-person or virtual opportunity]

674-2 Industrial Artificial Management and Metrology: Process Simulation Testing and Development
Michael Sharp, 301-975-0476, michael.sharp [at] nist.gov (michael[dot]sharp[at]nist[dot]gov)
This work will present a student with an opportunity to assist in the testing and development of novel software tools designed to evaluate risks and opportunities for AI tools in an industrial production process. 
This project will focus on evaluating a multistage a production process through both simulated and physical sensing methods. The effort will center on tools for assisting in efforts of digital twin technologies and systems monitoring. The student will work closely under the direction and supervision of software development experts and NIST AI experts to create and test a process simulation for a major government manufacturing center. Experiments and tasks may include, but are not limited to: (a) Implementing an AI driven COTS monitoring system, (b) Developing best practice methods for the design and creation of high-level digital simulators, (c) Determining mechanisms and methods for rapidly executing process redesigns and ‘what if’ scenarios, (d) Creating measures and metrics for capturing the risks and returns of AI driven technologies on an industrial manufacturing process. The goal of this project is to help lower barriers and provide intuitive recommendations for US manufacturers looking to enhance their productivity through AI monitoring, controls, and design technologies.
Required skills: Python coding and/or significant coding experience; beyond high school level classes in engineering, computer science, or statistics; ability to work with a team. Recommended: good communication skills; writing experience; knowledge of technical risk & reliability for production processes; understanding of basic AI methodologies; AI software packages. [In-person or virtual opportunity]

674-3 P4 Programming for 5G QoS
Lotfi Benmohamed, (301) 975-3650, lotfi.benmohamed [at] nist.gov (lotfi[dot]benmohamed[at]nist[dot]gov)
This project seeks to develop an SDN based solution to classify and prioritize 5G network traffic, using the P4 programming language. We are deploying an experimental 5G network, using both open-source and proprietary components. A major benefit of 5G network is 5G slicing, which allows different types of traffic (e.g., general Internet browsing, remote driving, industrial sensing) to share the same physical network with minimal interference with each other. A requirement for 5G slicing is the enforcement of Quality-of-Service (QoS), so that high priority traffic does not suffer slowdowns due to higher volume of low priority traffic. Unfortunately, the current software 5G implementations do not natively support dataplane QoS. The goal of this project is to explore a potential solution based on using SDN switches to enforce 5G QoS. In particular, a P4 program installed on a physical SDN switch would recognize 5G packet headers, classify each packet into different traffic classes, and enforce QoS through egress queuing and advanced scheduling methods. 
The applicant must have prior experience in P4 programming including how to write a protocol parser and how to perform QoS enforcements, a deep understanding of common network protocols such as IP and UDP, as well as prior knowledge in 5G network and its protocols. Note that packet traces for the relevant protocols will be provided, and the applicant is expected to learn about the protocol structure by reading these packet traces using tools such as Wireshark. [In-person or virtual opportunity]

674-4 Internet of Things (IoT) Device Interoperability
Eugene Song, 301-975-6542, ysong [at] nist.gov (ysong[at]nist[dot]gov)
Internet of Things (IoT) devices serve key functions in intelligent transportation systems, such as providing sensed data or data received from external networks to perception systems using sensors and embedded devices (e.g., on-board units, road-side units). However, this data is received from a large diversity of sources, and one major challenge is ensuring interoperability between the different IoT devices and systems that generate, transmit, and use the data. Interoperability is the ability of two or more systems to exchange information and to use the information exchanged based on the standardized communication protocol to achieve the functions and goals. Several interoperability challenges for intelligent transportation systems include diverse cellular vehicle-to-everything (C-V2X) connectivity (e.g., 3GPP LTE/4G/5G), diverse proprietary and standardized protocols adopted by different vendors and manufacturers, and diverse use cases and contexts. Interoperability testing, measurement, and assessment methodologies are keys to overcoming these challenges to assure the interoperability of IoT devices.
This project will focus on developing an interoperability analysis methodology for IoT devices in automated vehicles. The student will learn about the concept of device and system interoperability, research interoperability testing methods, and develop an open-source software tool to analyze the interoperability of IoT devices based on standard communication protocols. The tool will be validated against use cases and packet data provided by NIST researchers working collaboratively on the project.
Desired skills: Java or Python programming experience required; computer science or computer engineering major preferred; experience using Extensible Markup Language (XML) preferred. [In-person opportunity]

674-5 Developing Simulation Tools for Automated Vehicles
Thomas Roth, 301-975-3014, tpr1 [at] nist.gov (tpr1[at]nist[dot]gov)
An automated vehicle is expected to be competent in planning, monitoring, and performing behaviors that today are executed by human drivers. These behaviors include maintaining a lane under various adverse operating conditions, navigating an intersection including pedestrian traffic, and others. The automated execution of these behaviors must be both safe and predictable to meet the expectations of human drivers and other humans in the driving environment. The use of network communications between vehicles and between a vehicle and other devices (including road-side infrastructure and smaller devices such as cell phones) is expected to improve the safety and reliability of automated vehicles. One approach to validate these claims is simulation, with the network dynamics modeled in simulators such as ns-3 and the traffic dynamics modeled in simulators such as CARLA, SUMO, or MATLAB. Simulations can be used to test vehicle behaviors in a virtual environment prior to field deployment with low cost and low risk to humans.
This project is focused on the development of a simulation environment that combines ns-3 (network simulation) with CARLA (vehicle simulation) for vehicle-to-vehicle communication scenarios. The student will learn about the challenges preventing the widespread adoption of automated vehicles, receive training in the NIST simulation tools for automated vehicles, design simulations of driving scenarios in CARLA to stress test these tools, and develop C++ extensions to add support for new types of driving scenarios. This work will be performed collaboratively with a team of NIST researchers.
Desired skills: experience with object-oriented programming required; experience with C++ programming language preferred; computer science major preferred. [In-person preferred]

674-6 Simulation of Emergency Traffic Management for Smart Cities
Wendy Guo, 301-975-5855, wguo [at] nist.gov (wguo[at]nist[dot]gov)
The generation and effective communication of evacuation plans are critical requirements during civil emergencies and disasters. In emergency situations, managing traffic is of utmost importance to the safety of both road users and first responders, facilitating unrestricted egress for evacuations and road access for emergency personnel. The traffic management system plays a vital role in establishing and maintaining control points, restricting area access, and facilitating controlled transit through the incident site. Simulation of the potential response of road traffic to different disaster situations can help ensure that evacuation plans are robust and effective for a given community. These simulations can be conducted using SUMO, a software tool to model and analyze traffic, together with network simulators such as OMNeT++ that model the different cyber and social networks used to coordinate disaster response. These simulators can be synchronized to exchange data at runtime, enabling online simulations that model the impact of communication networks on road traffic (and the reverse). A software package called Veins provides this integration between SUMO and OMNeT++ with a comprehensive suite of realistic network models.
This project focuses on developing a traffic network simulation for emergency situations. The objective is to guide the student in setting up a simulation platform comprising SUMO, OMNet++, and Veins. The student will learn how to design simulations with real map settings under various scenarios, collect data from the simulations, and analyze it to derive meaningful insights for guiding emergency evacuations. The work will be a collaborative effort with a team of NIST researchers.
Desired skills: experience with object-oriented programming is required; computer science major or experience with network design/simulation is preferred; interested in smart city topics and traffic network management. [In-person preferred]

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Engineering Laboratory (EL)

The EL promotes the development and dissemination of advanced manufacturing and construction technologies, guidelines, and services to the U.S. manufacturing and construction industries through various activities in areas such as fire prevention and control; national earthquake hazards reduction; national windstorm impact reduction; national construction safety teams; and building materials and structures. Learn more about EL.

Contacts

Kathleen Hoffman, (301) 975-6585, cartier.murrill [at] nist.gov (kathleen[dot]hoffman[at]nist[dot]gov)
Cartier P. Murrill, (301) 975-5738, cartier.murrill [at] nist.gov (cartier[dot]murrill[at]nist[dot]go)

EL Research Opportunities (2024 Projects)

Engineering Laboratory Office (Div 730)

730-1 Community Resilience Planning Sentiments Following a Natural Hazard Event
Christina Gore, christina.gore [at] nist.gov (christina[dot]gore[at]nist[dot]gov), and Jennifer Helgeson, jennifer.helgeson [at] nist.gov (jennifer[dot]helgeson[at]nist[dot]gov)
This project will evaluate changes in discussions surrounding increasing resilience to future natural hazard events immediately following a community experiencing a natural hazard event. The analysis will include data from Google Trends as well as X (formerly known as Twitter) data. Google trends data will be used to show the key words that are commonly searched for following a natural hazard event. Those keywords will also help inform the data set of tweets used for analysis. The tweets will then be coded based on the types of sentiments that are expressed by the tweets and that data will be analyzed. 
Required Qualifications/Skills: Experience with statistics is highly encouraged. Qualitative text analysis experience is valued. Strong analytical skills and writing skills are preferred. Familiarity with community resilience through economics, psychology, sociology, engineering, or other related disciplinary or interdisciplinary courses. Interest in community resilience and sustainability. [In-person opportunity]

730-2 Climate Change Sentiments Following a Natural Hazard Event
Jennifer  Helgeson, jennifer.helgeson [at] nist.gov (jennifer[dot]helgeson[at]nist[dot]gov) and Christina Gore, christina.gore [at] nist.gov (christina[dot]gore[at]nist[dot]gov)
This project will evaluate if there is an increase in discussions surrounding the impact of climate change immediately following a community experiencing a natural hazard event. The analysis will include data from Google Trends as well as X (formerly known as Twitter) data. Google trends data will be used to show the key words related to climate change that are commonly searched for following a natural hazard event (a shock or a stress type) versus during periods without such events. Those keywords will also help inform the data set of tweets used for analysis. The tweets will then be coded based on the types of sentiments that are expressed by the tweets and that data will be analyzed. 
Required Qualifications/Skills: Experience with statistics is highly encouraged. Qualitative text analysis experience is valued. Strong analytical skills and writing skills are preferred. Familiarity with climate change through economics, psychology, sociology, engineering, or other related disciplinary or interdisciplinary courses. Interest in natural hazards and climate change. [Virtual opportunity]

730-3 Technical Communications for the Engineering Laboratory
Kirk Dohne, kirk.dohne [at] nist.gov (kirk[dot]dohne[at]nist[dot]gov), and Kristy Thompson, kristy.thompson [at] nist.gov (kristy[dot]thompson[at]nist[dot]gov)
The Engineering Laboratory communications plan is currently in outline form and the Laboratory currently has as many different ways of communicating our work as we do Projects that do work. The complexity of communication narratives requires scientific and technical communicators to manage communication processes, developing and easing content development and communications design. Working closely with the Associate Director of the Laboratory, the SURF student will assist in moving the laboratory communications plan to the next stage and work to provide an exemplary by working through the optimization of communications for a project. Additionally, the student may be asked to provide feedback on the Laboratory web pages.
Required Qualifications/Skills: Student that is working toward becoming a versatile communicator through study in a program that seeks to make scientific, technical, and practical knowledge accessible to a wide range of audiences in a variety of media. Relevant coursework includes: introduction to scientific and technical communication, digital media, public speaking, usability writing/communications, professional communication, and general engineering courses. [In-person opportunity]

Materials and Structural Systems Division (Div 731)

731-1 Advancing the Nation’s Risk Communication Strategies during Risk, Crisis, and Disaster
Emina Herovic, emina.herovic [at] nist.gov (emina[dot]herovic[at]nist[dot]gov), and Katherine Johnson, katherine.johnson [at] nist.gov (katherine[dot]johnson[at]nist[dot]gov)
Social science understandings of risk, crisis, and disaster can provide important and valuable insights into means by which to prevent injuries and save lives. This work will involve investigation into some of the nation’s most pressing risk, crisis, and disaster communication problems and questions helping to strengthen and advance best practices and standards for which to best communicate and inform about protective actions across various modes and hazard types.
Required Qualifications/Skills:
• Attention to detail, and ability to follow research protocol and direction 
• Interest or experience in social scientific problems, especially those related to the influence of messages on human behavior.
• Eagerness to learn or strengthen skillsets in social scientific methodology and theory
• Excellent oral and written communication skills
• Ability to work well with others on a team project
 [Virtual opportunity]

731-2 Sulfur Analysis Pyrrhotite in Aggregate and Concrete
Stephanie Watson, stephanie.watson [at] nist.gov (stephanie[dot]watson[at]nist[dot]gov), and Lipiin Sung, li-piin.sung [at] nist.gov (li-piin[dot]sung[at]nist[dot]gov)
Damage to concrete building structures in Connecticut was attributed to iron sulfide mineral pyrrhotite and results in decomposition and structure cracking. States (CT, MA) are passing building and DOT codes to prevent this issue, but there are no standardized methods or concentration limits to assess pyrrhotite abundance. NIST developed reference standards (RM) to provide an accurate, consistent pyrrhotite analysis in concrete. This project focuses on optimizing sulfur analysis using an induction furnace combustion method to quantify total sulfur species in RMs and foundation specimens.  This study will optimize the use of chemical reagents to ensure complete burn for cementitious systems.
Required Qualifications/Skills: Background knowledge and training in engineering or physics, or chemistry. Courses in chemistry (general and organic) and/or physics, and mathematics courses (algebra and calculus) are required. Computer skills, Microsoft Office programs such as Word, Excel and Powerpoint, are also required. Skill for "data analysis, interpretation of measurements results; plotting data" is a plus. [In-person opportunity]

731-3 Investigation of Sulfide Mortar Bar Expansion
Patrick Dixon, patrick.dixon [at] nist.gov (patrick[dot]dixon[at]nist[dot]gov), and Stephanie Watson, stephanie.watson [at] nist.gov (stephanie[dot]watson[at]nist[dot]gov)
Concrete foundations of buildings in Connecticut have undergone extensive deterioration, which has been attributed to aggregate containing pyrrhotite, a set of iron sulfide minerals, deficient in sulfur and reactive compared to pyrite. Pyrrhotite’s reactivity, variable structure, and similarity with pyrite present challenges in the quantification of its tolerable content in concrete aggregate. Thus, investigations often use mortar bar expansion tests to assess pyrrhotite reactivity. Mortar bar tests subject a specimen composed of cement and the aggregate of interest to exposure conditions. Specimen expansion is measured over time. This project focuses on the expansion measurement of mortar bars with pyrrhotite-bearing aggregate.
Required Qualifications/Skills: Background knowledge and training in engineering or physics, or chemistry. Courses in chemistry (general and organic) and/or physics, and mathematics courses (algebra and calculus) are required. Computer skills, Microsoft Office programs such as Word, Excel, and PowerPoint, are also required.  Skill for "data analysis, interpretation of measurements results; plotting data" is a plus. [In-person opportunity]

731-4 Study of Degradation Mechanism and Failure Mode of Polymers Used in Photovoltaics
Xiaohong Gu, xiaohong.gu [at] nist.gov (xiaohong[dot]gu[at]nist[dot]gov), and Ashlee Aiello, ashlee.aiello [at] nist.gov (ashlee[dot]aiello[at]nist[dot]gov)
Understanding the degradation modes of polymeric components used in solar cells during services is critical to the development and assurance of photovoltaic technology. In this study, the degradation of polymeric backsheets aged in the accelerated laboratory conditions will be analyzed using spectroscopic, microscopic and mechanical techniques such as attenuated total reflection Fourier-transform infrared spectroscopy (ATR-FTIR), laser scanning confocal microscopy and tensile tester. The mechanisms of chemical, microstructural and mechanical degradation will be studied.  The results will be used to understand the root causes of the backsheet failure and provide scientific basis for material selection and product development.
Required Qualifications/Skills: Background knowledge and training in engineering or physics, or chemistry. Courses in chemistry (general and organic) and/or physics, and mathematics courses (algebra and calculus) are required. Computer skills, Microsoft Office programs such as Word, Excel, and PowerPoint, are also required.  Skill for "data analysis, interpretation of measurements results; plotting data" is a plus. [In-person opportunity]

731-5 Documenting and Analyzing Tornado Strikes on Critical Facilities
Marc Levitan, marc.levitan [at] nist.gov (marc[dot]levitan[at]nist[dot]gov), and Long Phan, long.phan [at] nist.gov (long[dot]phan[at]nist[dot]gov)
Despite the significant hazard that tornadoes pose, there is a major lack of knowledge about the cumulative national impacts of tornadoes on critical facilities like schools and hospitals. We are creating a database of tornado strikes on critical facilities to fill this knowledge gap and aid communities in making decisions about whether to adopt tornado-resistant design codes and standards and/or require storm shelters in critical facilities. The SURF researcher will methodically analyze National Weather Service data for tornado strikes on critical facilities, and/or perform a geospatial analysis of tornado strikes on these facilities to contribute to the database.
Required Qualifications/Skills: 
1) Interest in disaster resilience and public safety
2) Attention to detail and appreciation of the importance of accuracy and consistency in data collection and analysis
3) Familiarity with Google Sheets or Microsoft Excel required. Experience with GIS software is a plus.
 [Virtual opportunity]

731-6 Mitigation Efforts for Pyrrhotite in Concrete
Stephanie Watson, stephanie.watson [at] nist.gov (stephanie[dot]watson[at]nist[dot]gov), and Patrick Dixon, patrick.dixon [at] nist.gov (patrick[dot]dixon[at]nist[dot]gov)
In parts of Connecticut and Massachusetts, aggregate containing pyrrhotite was unknowingly used in concrete mixtures used to build thousands of structures over several decades. As these structures age, the pyrrhotite has begun to oxidize resulting in damage ranging from stains and popouts to severe cracking and loss of structural integrity. Several aggregate screening frameworks have been proposed; however, little research is available regarding mitigation techniques for already placed structures. This study aims to evaluate several types of sealants and their ability to mitigation water absorption and oxygen permeability after initial application and after accelerated aging laboratory protocols. 
Required Qualifications/Skills: Background in engineering, physics, or chemistry. Courses in chemistry (general and organic) and/or physics, and mathematic courses (algebra and calculus) are required. Computer skills, Microsoft Office (e.g., Word, Excel, and PowerPoint) are also required. Previous laboratory experience is a preferred. Skill for “data analysis”, “interpretation of measurement results”, and “plotting data” is a plus. [In-person opportunity]

731-7 Development of Non-Destructive Polymer Degradation Measurements for Photovoltaic Cells
Ashlee Aiello, ashlee.aiello [at] nist.gov (ashlee[dot]aiello[at]nist[dot]gov), and Xiaohong Gu, xiaohong.gu [at] nist.gov (xiaohong[dot]gu[at]nist[dot]gov)
Prevention and understanding of early failure mechanisms in photovoltaic modules is needed to economize solar energy.  The polymeric components in photovoltaic modules degrade during outdoor exposure, which can result in multiple failure mechanisms including cracking, delamination, and discoloration. While many characterization methods are well suited for polymer degradation studies, they require disassembly of the module and are limited to post-mortem analysis. This project will focus on the development of new non-destructive measurements to study polymer degradation in either fully assembled modules or under in-situ conditions (e.g. during exposure to temperature, humidity, or mechanical strain).
Required Qualifications/Skills: Background in Chemical Engineering, Materials Science and Engineering, or Polymer Science/Chemistry is required (Chemistry or Physics majors may also be considered). Computer skills, Microsoft Office programs including Word and Powerpoint are required. Laboratory experience and previous experience with Raman spectroscopy is preferred. Data analysis skills and knowledge of Origin software are preferred. [In-person opportunity] 

731-8 Analysis of Fiber Reinforced Polymer (FRP) Retrofitted Shear Walls with Openings
Jazalyn Dukes, jazalyn.dukes [at] nist.gov (jazalyn[dot]dukes[at]nist[dot]gov), and Siamak Sattar, siamak.sattar [at] nist.gov (siamak[dot]sattar[at]nist[dot]gov)
Fiber reinforced polymer (FRP) composites have been used and researched extensively for retrofit of concrete components such as columns and beams. However, less research has been devoted to reinforced concrete (RC) shear walls retrofitted with FRP. In order to understand the landscape of research on the topic, a database of experimentally-tested FRP-retrofitted shear walls has been developed. For this project, the student will begin investigating a particular type of wall found in the database: walls with openings. This project will demonstrate the benefits of FRP retrofit for RC walls with openings, as well as prepare the groundwork for developing modeling parameters for these walls in the future.
Required Qualifications/Skills: Background knowledge in civil or mechanical engineering, physics, or statistics. Familiarity with spreadsheet software (i.e. Excel), Matlab, or statistical software (i.e. R). Skills with statistical analysis, data analysis, or plotting data is preferred. [Virtual opportunity]

731-9 Verification and Validation of Computational Models for Analyzing Future Impacts of Sea Level Rise, Hurricanes, and Adaptation in Galveston, Texas
Dylan Sanderson, dylan.sanderson [at] nist.gov (dylan[dot]sanderson[at]nist[dot]gov), and Terri McAllister, therese.mcallister [at] nist.gov (therese[dot]mcallister[at]nist[dot]gov)
This project will contribute to the verification and validation (V&V) of new computational models for community resilience planning. Community resilience planning aims to reduce both the immediate impacts of a disaster and the time it takes to recover. The project will utilize Galveston, Texas as a testbed community as it is subject to both sea level rise and hurricanes. Under the guidance of the project advisor, the SURF student will first learn how to run the computational model for evaluating future community resilience. Once familiar with the model, the student will identify and perform model tests to assist with V&V. This SURF project will contribute to a larger research project aimed at developing new models for community resilience planning under future climate conditions.
Required Qualifications/Skills:
• Interest in natural hazard engineering and community resilience
• Majoring in civil engineering, geology, computer science, or a related field
• Familiarity with programming languages (e.g., python, julia, matlab)
• Familiarity with GIS software (e.g., ArcGIS, QGIS) – preferred but not required
[Virtual opportunity]

731-10 Study of Fluorescence Microscopy and Related Petrographic Methods Applied to Concrete Materials
Cody Strack, cody.strack [at] nist.gov (cody[dot]strack[at]nist[dot]gov), and Scott Jones, scott.jones [at] nist.gov (scott[dot]jones[at]nist[dot]gov)
Examination of hardened concrete using petrographic methods is necessary to adequately understand the material and potential degradation methods. Many techniques are available to the concrete petrographer, including the use of light and fluorescence to better illuminate specific features, such as the air void system. Specific equipment and software tailored to petrographic examination can enhance conclusions, benefit the presentation of data, or decrease required analysis time. This project will examine multiple methods in the determination of phase fractions present in concrete samples to determine their capabilities.
Required Qualifications/Skills: Background in Geology, Material Sciences, and/or Civil Engineering is preferred. Laboratory experience and previous experience in microscopy methods is preferred. Computer skills and familiarity with Microsoft Office (Word, Excel, Powerpoint) is required. [Virtual opportunity]

731-11 Degradation Study of Post-Consumer PET Water Bottle Using the NIST SPHERE 
Lipiin Sung, li-piin.sung [at] nist.gov (li-piin[dot]sung[at]nist[dot]gov), and Rachel Cook, rachel.cook [at] nist.gov (rachel[dot]cook[at]nist[dot]gov)
PET (polyethylene terephthalate) has been widely used as in food packaging, beverage containers and textile industries. Plastic wastes are a potential risk for the ecosystem and pose some public health concerns following degraded plastics particles release into environments. Understanding how weathering affects PET and its interaction with environment is important to mitigate this issue. The selected materials are post-consumer PET water bottles. This project will focus on generating weathered plastic particles with the NIST SPHERE, where macro-samples or films of plastics are UV-weathered while immersed in water (or simulated ocean water) or under high humidity, dry conditions. Fourier transform infrared spectroscopy (FTIR) and laser scanning confocal microscopy will be used to characterize chemical properties of UV-degraded surface and the size and distribution nano-/micro- plastics particles as a function of UV exposure time. The outcome of this project would provide spectral database (FTIR) of weathered plastics, particles sizes of the microparticles at various temp and generation of more relevant, weathered microplastic particles. The outcome of this project would provide spectral database (FTIR) of weathered plastics, generation of more relevant, weathered plastics and microplastic particles. These weathered plastic particles will be used to evaluate key toxicological assays, and develop microplastic and nanoplastic characterization methods (e.g., microscopy, pyrolysis GC-MS) in collaboration with other NIST scientists in this program.
Required Qualifications/Skills:
• Physics, Chemical or Materials, Mechanical, bio-Engineering background
• Hand-on Laboratory experience 
• Experience using analysis software (e.g., Excel, Origin)
• Experience using R or python for database and data analysis is a plus
[In-person opportunity]

Building Energy and Environment Division (Div 732)

732-1 Digital  Building Twins 
Parastoo Delgoshaei, parastoo.delgoshaei [at] nist.gov (parastoo[dot]delgoshaei[at]nist[dot]gov), and Amanda J. Pertzborn, amanda.pertzborn [at] nist.gov (amanda[dot]pertzborn[at]nist[dot]gov)
Semantic Web technologies offer new possibilities for efficiently managing information and knowledge in the built environment. Employing semantic models of buildings reduces analytics costs and enhances intelligent control across structures. This project aims to utilize and develop a suite of software tools to generate RDF (semantic) models of prototype buildings, utilizing Building Information Models (BIM) in accordance with the evolving ASHRAE 223 Semantic schema for Analytics and Automation Applications in Buildings. The digital twin model will be applied to various building functionalities, including Fault Detection and Diagnostics (FDD), context aware control, and indoor air monitoring.
Required Qualifications/Skills: Python programming skills and a major in computer science, engineering, electrical, or mechanical engineering. Students with advanced programming backgrounds from different disciplines are also suitable candidates. [In-person or virtual opportunity]

732-2 Investigating Building Performance Using Cx Software
Michael Galler, michael.galler [at] nist.gov (michael[dot]galler[at]nist[dot]gov), and Amanda J. Pertzborn, amanda.pertzborn [at] nist.gov (amanda[dot]pertzborn[at]nist[dot]gov)
This project will improve the performance of building heating, ventilation, and air-conditioning (HVAC) systems by identifying and addressing equipment performance faults. The student will work with NIST advisors to develop and carry out operation monitoring using NIST HVAC-Cx building commissioning software, document findings, and contribute to the economic analysis to determine the impact of faults. The student will learn how to: 1) use HVAC-Cx and execute test scripts coded in XML, 2) analyze selected field data from ventilation systems and/or chilled water systems, and 3) prepare a report and presentation documenting the findings.
Required Qualifications/Skills:

• Preferred major: Engineering/Computer Science
• Essential skill: Organization, Data analysis
• Desirable skill: Experience using XML
  [Virtual opportunity]

Fire Research Division (Div 733)

733-1 Measuring Soot Deposition on Surfaces Using Grayscale Image Analysis
Amy Mensch, amy.mensch [at] nist.gov (amy[dot]mensch[at]nist[dot]gov), and Ryan Falkenstein-Smith, ryan.falkenstein-smith [at] nist.gov (ryan[dot]falkenstein-smith[at]nist[dot]gov)
This project is the final component of a project exploring non-invasive ways to measure how much soot has deposited on surfaces after a fire has occurred. This is important to enable fire investigators to obtain reliable measurements of soot deposition for forensic fire reconstruction.  Direct methods to measure soot involve placing pre-weighed targets on the surface and then measuring the change in mass after the fire.  We will test a grayscale image analysis method, where photos of soot-laden surfaces will be processed to compare the grayscale value to the amount of soot deposition determined from pre-weighed target measurements. The performance of the grayscale image method will be compared to a non-invasive photoacoustic method that the investigators have previously tested.
Required Qualifications/Skills: Matlab or similar, major in Fire Prot. Engineering/Chemical Engineering/Mechanical Engineering/Chemistry/Physics/Computer Science [In-person opportunity]

733-2 Comparison of Modeling Approaches for Simulating Wildland Fire Spread
Eric Mueller, eric.mueller [at] nist.gov (eric[dot]mueller[at]nist[dot]gov), and Randall J. McDermott, randall.mcdermott [at] nist.gov (randall[dot]mcdermott[at]nist[dot]gov)
Advanced fire models have the potential to serve as valuable tools for guiding fuel management decisions in wildland and wildland-urban interface areas. With such tools, managers can explore design scenarios and plan activities such as prescribed fires. However, it is still unclear what level of model complexity is necessary to capture the key processes of fire behavior, which would allow confidence in model predictions, while reducing the challenge for end-users to set up and run such a model. This project will support efforts to evaluate and compare the predictions of physics-based fire behavior models at varying levels of complexity.
Required Qualifications/Skills: Background in Mechanical Engineering, Environmental/Civil Engineering, Chemical Engineering, Chemistry, Physics, or Computer Science. Familiarity with some form of computer programming.  Experience with data analysis/plotting (eg. Matlab or Python) is also preferred. [Virtual opportunity]

733-3 Material Flammability Apparatus Development and Testing
Isaac Leventon, isaac.leventon [at] nist.gov (isaac[dot]leventon[at]nist[dot]gov), and Michael Heck, michael.heck [at] nist.gov (michael[dot]heck[at]nist[dot]gov)
The Engineered Fire Safe Products (EFSP) Project in the Fire Research Division at NST is focused on the development and application of the capabilities (experimental & computational analysis tools) to enable quantitative prediction of material flammability behavior (e.g., ignition, steady burning, fire growth).
This SURF project will focus on the construction and calibration of a miniaturized gasification apparatus (one of the bench scale apparatus needed to maintain these capabilities).
Required Qualifications/Skills: Mechanical Engineering, Fire Protection Engineering, Physics, Hands-on lab experience (calibrating equipment, running experiments, electrical/circuit work) [In-person opportunity] 

733-4 Experimental Characterization of Flame Heat Transfer Mechanisms
Isaac Leventon, isaac.leventon [at] nist.gov (isaac[dot]leventon[at]nist[dot]gov), and Michael Heck, michael.heck [at] nist.gov (michael[dot]heck[at]nist[dot]gov)
The Engineered Fire Safe Products (EFSP) Project in the Fire Research Division at NST is focused on the development and application of the capabilities (experimental & computational analysis tools) to enable quantitative prediction of material flammability behavior (e.g., ignition, steady burning, fire growth).
This SURF project will focus on preparing samples and running tests in some of the bench- and intermediate-scale apparatus needed to maintain these capabilities, with a special emphasis on g-scale calorimetry experiments and intermediate-scale wall flame experiments.
Required Qualifications/Skills: Mechanical / Civil / Fire Protection Engineering, Hands-on lab experience (calibrating equipment, running experiments, electrical/circuit work, shop/lab experience), MATLAB [In-person opportunity] 

733-5 Characterization of Material Flammability (Experimental)
Isaac Leventon, isaac.leventon [at] nist.gov (isaac[dot]leventon[at]nist[dot]gov), and Michael Heck, michael.heck [at] nist.gov (michael[dot]heck[at]nist[dot]gov)
The Engineered Fire Safe Products (EFSP) Project in the Fire Research Division at NST is focused on the development and application of the capabilities (experimental & computational analysis tools) to enable quantitative prediction of material flammability behavior (e.g., ignition, steady burning, fire growth).
This SURF project will focus on building, calibrating, and running tests in some of the bench scale apparatus needed to maintain these capabilities, with a special emphasis on mg- and g-scale thermal decomposition experiments.
Required Qualifications/Skills: Mechanical / Civil / Fire Protection Engineering, Hands-on lab experience (calibrating equipment, running experiments, electrical/circuit work, shop/lab experience), High precision (small components) testing/calibration/construction, MATLAB [In-person opportunity] 

Systems Integration Division (Div 734)

734-1 Digital Twin Development for a Coordinate Measuring Machine
 Guodong Shao, guodong.shao [at] nist.gov (guodong[dot]shao[at]nist[dot]gov), and Rishabh Venketesh, rishabh.venketesh [at] nist.gov (rishabh[dot]venketesh[at]nist[dot]gov)
A manufacturing workcell to support digital twin research has been established at NIST. The workcell comprises robots, a CNC machine tool, and a coordinate measuring machine (CMM). A digital twin of the workcell is being built using data collection and communication protocols, modeling tools, and interface standards currently used in industry. The data pipeline is supported by MTConnect standard, which enables modeling of the physical equipment and the streamed data as the digital twin input. Digital twins of individual equipment are being developed and will be integrated. The digital twin of the robots and machine tool have been built using different tools. Efforts are now underway for the CMM digital twin. CMMs are machines that perform product quality conformance regarding their designs through geometric measurements of the parts. The SURF student will work with the NIST team to build and validate the CMM digital twin and implement a method for inputting streamed data into the model of the CMM to update the developed models with the real-time status of the CMM.
Required Qualifications/Skills: Background in computer science or engineering, knowledge of computer programing (e.g., Python), geometrical design (CAD), modeling, and data analytics, familiar with manufacturing processes and applications [In-person opportunity]

734-2 Forecasting Rare Earth Element (REE) Demand for Use in Clean Energy Technologies
Nehika Mathur, nehika.mathur [at] nist.gov (nehika[dot]mathur[at]nist[dot]gov), and Matthew Triebe, matthew.triebe [at] nist.gov (matthew[dot]triebe[at]nist[dot]gov)
Clean energy technologies (e.g., solar, wind, EVs) are vital in our transition to a decarbonized energy grid. Many clean energy technologies rely on Rare Earth Elements (REEs) several of which are prone to supply chain risks. As the demand for clean energy technologies grows, so will the demand for REEs. Anticipating REE market dynamics becomes crucial for change makers in developing effective strategies to scale up the implementation of clean energy generating technologies. This project aims to identify REEs critical to a clean economy and subsequently aims to determine demand quantities (till 2040) for these materials via a forecasting model.
Required Qualifications/Skills: The ideal candidate will be pursuing a degree in mechanical, industrial or chemical engineering with experience coding in R and/or Python. An understanding of the manufacturing sector is desirable. An interest in the circular economy will be beneficial. [Virtual opportunity]

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Information Technology Laboratory (ITL)

The ITL focuses on information technology (IT) measurements, testing, and standards and is a globally recognized and trusted source of high-quality, independent, and unbiased research and data. As a world-class measurement and testing laboratory encompassing a wide range of areas of computer science, mathematics, statistics, and systems engineering, ITL’s strategy is to maximize the benefits of IT to society through a balanced IT measurement science and standards portfolio of three main activities: fundamental research in mathematics, statistics, and IT; applied IT research and development; and standards development and technology transfer. Learn more about ITL.

Contacts

Yolanda Bursie, (301) 975-6738, yolanda.bursie [at] nist.gov (yolanda[dot]bursie[at]nist[dot]gov)
Derek Juba,(301) 975-5518 derek.juba [at] nist.gov (derek[dot]juba[at]nist[dot]gov)

ITL Research Opportunities (2024 Projects)

Explore and Apply NIST/NCCoE Security Standards in a Student Experience Lab
The student will explore various NIST/NCCoE computer security standards, guidelines, practice guides to plan, design, test, and implement repeatable/reusable activities to demonstrate the feasibility of simulation tools when compared to physical devices.

The Structure of Quadratic Residues Modulo an RSA Number
The graph of a quadratic function modulo a composite N is expected to look largely like a scatter diagram. This assumption is used in cryptography to generate pseudo-random numbers. It also underlies the security of RSA. However, if you plot X2  modulo N for small (in the thousands) N, you can visualize parabolic patterns. Previous work has determined that various patterns are caused by the multiplicative structure of numbers close to N (e.g. N + 1).  The project is to read report YALEU/DCS/TR-1252 and expand on the set of patterns by algebraic or other means. The methods to use will largely be decided by the student and myself. These can include i) algebraic analysis; ii) pattern recognition techniques. Of particular interest is whether the identified patterns can help in the search for X > sqrt(N) such that X2 mod N is small (<sqrt(N)). This would yield a factoring algorithm potentially faster than the Quadratic Sieve Algorithm. An intriguing possibility is that current AI-based tool might say something interesting about these plots. Can some of their properties be "learned"?

Image Restoration to Improve Face Recognition Outcomes – Looks Good, But Does It Really Work (and How Do We Know)?
Image restoration techniques have been developed with goals of recovering an original image from a degraded one, with degradations caused by blur, distortion, compression, poor illumination, etc.  Technology advancements in automated face recognition has motivated its ubiquitous deployment in a number of applications, including those where the input imagery may be degraded (e.g., by atmospheric turbulence at long range).  When applying image restoration methods to recover degraded facial imagery, a restored face may be visually convincing (subjective), but does it actually improve biometric matching outcomes?  The goal of this project is to investigate and develop metrics and methodologies for objectively measuring the performance and impact of different image restoration techniques on face recognition outcomes.

Ellipsoidal Harmonic Instability Analysis of Riemann S-type Ellipsoids
This project is to work with the original Fortran 77 code developed by Norman Lebovitz and Alexander Lifschitz to perform a high resolution numerical ellipsoidal harmonic instability analysis of the Riemann S-type ellipsoids. The Riemann S-type ellipsoids are uniform density (incompressible) inviscid self-gravitating equilibrium triaxial rotating fluid ellipsoids. These ellipsoids which have been studied for many centuries were popularized by Nobel Laureate Subrahmanyan Chandrasekhar in his 1969 book "Ellipsoidal Figures of Equilibrium". It was noticed by Chandrasekhar and Lebovitz (Chandrasekhar's student) that these equilibrium fluid ellipsoids become unstable to a dynamical shape changing instability as the angular momentum of the ellipsoids (eccentricity) is increased. Using a numerical code originally developed by Lebovitz and Lifschitz, we would like to further explore the beautiful properties of these nonlinear instabilities by exploiting the original Lebovitz-Lifschitz code. To find more detail about the instability analysis, code and algorithms which are due to Norman Lebovitz (d.2022) and Alexander Lifschitz (now Alexander Lipton), see the following papers: (1) Lebovitz & Lifschitz, New Global Instabilities of the Riemann ellipsoids, The Astrophysical Journal (1996) 458, 699-713; (2) Lebovitz & Lifschitz, Short-wavelength instabilities of Riemann ellipsoids, Philosophical Transactions of the Royal Society of London. Series A. Mathematical, Physical Sciences and Engineering, 354 (1996), no. 1709, 927–950.

Web Based Interface for Customization of Generated Graphs
Implement a Web based interface in C# for customization of parameters to generated graphical representations.

Variational Problems in Biophysics
The calculus of variations is an indispensable tool of applied mathematics that allows one to calculate optimal solutions to complicated mechanical problems. The student will work with the mentor on bioinspired modifications of classical variational problems. Applicants should have experience with classical mechanics, differential equations, and scientific computing. Expected tasks to be performed with the mentor include: physical modeling, mathematical analysis, and numerical simulation.

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Material Measurement Laboratory (MML) and the NIST Center for Neutron Research (NCNR)

The MML serves as the national reference laboratory for measurement research, standards, and data in the chemical, biological and material sciences, and conducts research in analytical chemistry, biochemical science, ceramics, chemical and biochemical reference data, materials reliability, metallurgy, polymers, surface and microanalysis science, and thermophysical properties of materials. MML research supports areas of national importance including but not limited to advanced materials, electronics, energy, the environment, food safety and nutrition, and health care. Learn more about MML.

The NCNR is a major national user facility and resource for industry, universities, and government agencies with merit-based access made available to the entire U.S. technological community. Neutron-based research covers a broad spectrum of disciplines, including engineering, biology, materials science, chemistry, physics, and computer science. Current experimental and theoretical research is focused on materials such as polymers, metals, ceramics, magnetic materials, porous media, fluids and gels, and biological molecules. Learn more about the NCNR.

The MML/NCNR program is specifically designed to provide hands-on research experience in three topic areas: Chemical/Biochemical Sciences, Computational Materials Science, and Materials Science. All SURF projects at the NCNR will be conducted in person.

Contacts

MML
Katherine Gettings, (301) 975-6401, katherine.gettings [at] nist.gov (katherine[dot]gettings[at]nist[dot]gov)
Nathan A. Mahynski, (301) 975-6836, nathan.mahynski [at] nist.gov (nathan[dot]mahynski[at]nist[dot]gov)

NCNR
Julie A. Borchers, (301) 975-6597, julie.borchers [at] nist.gov (julie[dot]borchers[at]nist[dot]gov)
Leland Harriger, (301) 975-8360, leland.harriger [at] nist.gov (leland[dot]harriger[at]nist[dot]gov)
Yimin Mao, (301)975-6017, yimin.mao [at] nist.gov (yimin[dot]mao[at]nist[dot]gov)
Susana Teixeira, (301)975-4404, scm5 [at] nist.gov (scm5[at]nist[dot]gov)

MML & NCNR Research Opportunities (2024 Projects)

CHEMICAL/BIOCHEMICAL SCIENCES: This concentration addresses the nation's needs for measurements, standards, technology development, and reference data in the areas broadly encompassed by chemistry, biotechnology, and chemical engineering.

NIST Center for Neutron Research - Neutron Condensed Matter Science Group (Div 610.02)

610.02-1 Constructing Native Extracellular Scaffolds for Tissue Repairs
Sushil Satija and Minh Phan, (301)975-6708, minhdinh.phan [at] nist.gov (minhdinh[dot]phan[at]nist[dot]gov)
Biocompatible polymers and tissue-derived scaffolds are commonly used in clinics for tissue repairs. However, these come with complications. Non-native polymers often fail to produce cell-cell intact, while native scaffolds from tissues risk disease transmission and immunological rejection due to incomplete cell removal. Cell-derived extracellular matrix (ECM) overcomes those obstacles, but the low-yield ECM production limits its advancements in clinical applications. This project aims to engineer ECM pre-scaffolds that match cell requirements and feed them into the cell culture to facilitate ECM production. We utilize lipid membranes to unfold proteins and make them ready to assemble into larger structures. The pre-scaffolds comprise single or multiple ECM’s key components, including collagen type I, elastin, fibronectin, and laminin. Langmuir isotherms, adsorption assays, and X-ray reflectometry will elucidate the membrane's physical properties and capture detailed structures of the pre-scaffolds forming on the membrane surface. These results will create a comprehensive knowledge of ECM nanoscopic fibrillar textures that would guide future ECM-mimetic material development in the tissue engineering community. [In-person opportunity]

610.02-2 Characterization of Protein Assembly at the Air-Water Interface by X-Ray Reflection
Yun Liu and Guangcui Yuan, (301)975-5098, guangcui.yuan [at] nist.gov (guangcui[dot]yuan[at]nist[dot]gov)
Proteins composed of polar and non-polar amino acids are amphiphilic and have surface activity. The surface activity of proteins allows them to be quickly adsorbed on the liquid surface, thereby reducing the surface tension of the solution. However, the interfacial adsorption property causes interactions between hydrophobic regions in proteins, which are exposed during the adsorption process, leading to structural changes in proteins and even aggregation. The aim of this research is to investigate the structural and thermodynamic properties of protein assembly at the air-water interface using x-ray reflection. Thin films of a protein will be formed at the air-aqueous solution interface. The surface tension is introduced as a characteristic parameter, the hydrophobicity and structure of proteins will be evaluated by x-ray reflection. The effect of protein concentration, ionic strength, sucrose, and temperature on surface assembly will be investigated. The research is expected to provide valuable insights into the pre-formulation of therapeutic proteins. [In-person opportunity]

Materials Measurement Science Division (Div 643)

643-1 Drop-on-Demand Point-of-Care Pharmaceutical Manufacturing for Precision Medicine
Thomas Forbes, tforbes [at] nist.gov (tforbes[at]nist[dot]gov)
The project will investigate drop-on-demand dispensing technologies for distributed and point-of-care manufacturing of personalized and precision medicine. Research avenues may focus on process analytical technologies for atline/inline measurement of pharmaceutical (small drugs, antibiotics, etc.) and nanomedicine (drug loaded liposomes) production or personalized dosing. Analytical technologies including UV-Vis, fluorescence, and Raman spectroscopy, liquid chromatography, electrophoresis, mass spectrometry, microscopy, and more will be employed. Opportunities for investigating directed polymorph creation, drug delivery avenues (orodispersible films, aerosol generation for inhalation, capsules, etc), and various critical quality attributes are available. Opportunities also exist for developing/applying data analysis schemes and machine learning for process monitoring and anomaly detection, identifying compounds and/or processes out of specification. [In-person opportunity]

643-6 Microplastic and Nanoplastic Particles from Consumer Products
Justin Gorham, jgorham [at] nist.gov (jgorham[at]nist[dot]gov)
Micro and nanoplastic (MNP) particles are emerging contaminants posing with potential environmental and human health concerns. This project aims to develop protocols for detecting and identifying MNPs released from consumer products. The student will wash and filter consumer products, use light and electron microscopy to image released particles, and use vibrational spectroscopy to identify the particles. The skills required for this project are better suited for sophomores or more senior students who have taken chemistry classes including a chemistry laboratory. Special consideration to students with experience doing wet-bench chemistry, using light and electron microscopy and vibrational spectroscopy. [In-person opportunity]

643-9 Textile Fiber Blends Recycling Routes to Combated Textile Waste Crisis
Charlotte Wentz, cmw15 [at] nist.gov (cmw15[at]nist[dot]gov)
Global textile consumption leads to increased CO2 emissions, burdens landfills, and pollutes water. Although there are a wide variety of technologies for recycling textiles such as mechanical, chemical, thermomechanical, and biochemical processes, major challenges in each category persist and hinder the scalability, applicability, and practicality of these methodologies. More specifically, fabric blends with multi-material compositions make these recycling processes difficult. This project uses chemical recycling, hydrolysis, to understand the impact of mixed fiber blends, such as polyester-cotton-spandex, employing analytical lab techniques like Fourier transform infrared (FTIR), thermogravimetric analysis (TGA), and viscometry measurements. [In-person opportunity]

643-10 Measuring the Environmental Degradation of Traditional Drug and Novel Psychoactive Substance (NPS) Residues
Elizabeth Robinson, elr1 [at] nist.gov (elr1[at]nist[dot]gov)
The ability to predict the lifetime and degradation products of drug residues after exposure to environmental conditions is a crucial aspect of trace drug residue collection and detection that is often overlooked. This project will involve investigating the stability of trace drug deposits when exposed to different environmental conditions. Quantitative analysis will be performed using electrospray ionization mass spectrometry (ESI-MS), along with full mass spectral analysis using thermal desorption direct analysis in real-time mass spectrometry (DART-MS). The student should be familiar with basic analytical chemistry and mass spectrometry concepts. Training for each of the instrumental techniques will be provided. The student will also receive training and review of the associated safety protocols to ensure safe laboratory operations. [In-person opportunity]

643-11 Developing Methods to Improve Chemical Identification of Secondary Micro and Nanoplastics
John Pettibone, jpettibo [at] nist.gov (jpettibo[at]nist[dot]gov)
To better predict how current and emerging plastics will perform and age in use and in disposal scenarios, the analytical tools and methods to detect and chemically identify secondary micro and nanoplastics (MNP) are needed, specifically to quantify both-mass based and number-based values. The SURF student in our lab would focus on extraction of MNP from simulated media to help develop sampling methods to evaluate physical and chemical transformations to particle populations in simulated media. The student would work in multi-use labs that contain different hazards from compressed gas to oxygen deficiency spaces. The student will be well versed on HRAs, have walkthroughs in the space prior to conducting research to explain any hazards, and have the PIs available to answer any questions regarding the risks that are associated with the space and equipment. [In-person opportunity]

Biosystems and Biomaterials Division (Div 644)

644-2 Develop Methods and Tools To Get NIST Data Resources Chat-GPT Ready and Mitigate Misinformation
Talapady Bhat, bhat [at] nist.gov (bhat[at]nist[dot]gov)
Chat-GPT, LLM and AI has become a common household topic of interest to everyone. During the year 2023 my SURF and SHIP students worked to evaluate the performance of Chat-GPT to approximately 500 Covid-19 related question and answers. This study revealed that Chat-GPT answers are just about 30% accurate to the question. Use the result of the study to develop new standards to build Chat-GPT NIST webpages. [Virtual opportunity]

Biomolecular Measurement Division (Div 645)

645-2 Evaluation of NISTmAb Peptide Mapping Reproducibility and Method Transfer
Catherine Mouchahoir, caf1 [at] nist.gov (caf1[at]nist[dot]gov)
The NISTmAb monoclonal antibody is perhaps NIST’s most “popular” reference material used by the biopharmaceutical industry.  NISTmAb is representative of the biggest class of protein therapeutics on the market and has been used by companies worldwide to advance the development of new analytical and measurement capabilities applicable to antibody drug characterization and quality control.  To ensure the quality of the reference material itself, NIST scientists must regularly evaluate samples for signs of degradation.  The reproducibility of the sample preparation and analytical methods used to monitor NISTmAb quality must be well understood so that any year-to-year variations that result from degradation may be distinguished from those caused by inherent method variation.  The intern will perform experiments to evaluate the reproducibility of sample preparation and analytical methods used for peptide mapping analysis of the NISTmAb, and to compare the variability of manual versus automated sample preparation methods.  The intern will learn basic laboratory skills required for preparing protein samples for mass spectrometry (MS) analysis, liquid-chromatography (LC)-MS analytical techniques, software processing and analysis of LC-MS data, and use of automated liquid handling (robotic) systems for sample preparation. [In-person opportunity]

645-3 Labeled Protein Expression in Yeast and Bacteria
Zvi Kelman, zkelman [at] nist.gov (zkelman[at]nist[dot]gov)
In order to obtain high-resolution NMR structural data, proteins need to be isotopically labeled with stable isotopes. As labeling in mammalian cells is not practical, we are expressing and labeling proteins in E. coli and yeast.  The student will join our effort in labeling monoclonal antibodies and other proteins in yeast and bacteria.  Before starting the work, the student will be trained on lab safety and the equipment to be used. In addition, the student will be supervised by the Mentor or the Alternate Mentor. [In-person opportunity]

Chemical Sciences Division (Div 646)

646-1 Developing Tools to Help BBD/MML Web Pages AI Ready
T N Bhat, 301-975-5448, talapady.bhat [at] nist.gov (talapady[dot]bhat[at]nist[dot]gov)
Chat-GPT, LLM and AI has become a common household topic of interest to everyone. During the year 2023 my SURF and SHIP students worked to evaluate the performance of Chat-GPT to approximately 500 Covid-19 related question and answers. This study revealed that Chat-GPT answers are just about 30% accurate to the question. A primary reason for this poor performance of Chat-HPT is poor quality of the reference documents available for LLM to generate accurate answers. In 2024 students will develop tools to further evaluate Chat-GPT and LLM and suggest mitigative measures to alter reference documents. [Virtual opportunity]

646-7 Measuring Hydrogen Chloride (HCl) in Liquid Media
Cassie Goodman, cag [at] nist.gov (cag[at]nist[dot]gov)
The student intern will be working in the Gas Sensing Metrology Group assisting with the further development of methods for the capture and measurement of HCl in liquid media substrates. This work will include exploring different variables such as flow rates, collection times, capture times, and collection media in an effort to optimize measurement capabilities. [In-person opportunity]

646-8 Method Development for the Determination of Marker Compounds in Dietary Supplement Reference Materials
Hugh Hayes, hvh [at] nist.gov (hvh[at]nist[dot]gov)
NIST has developed suites of Reference Materials (RMs) for natural product dietary supplements to promote experimental rigor and support manufacturing quality control efforts. These botanical RMs include value assignments for marker compounds with biological activities and/or used for supplement product standardization. This project will focus on the method development for the separation and detection of marker compounds in botanical dietary supplement RMs such as kava and echinacea. The SURF applicant will work with NIST researchers to develop and optimize liquid chromatography separation methods with mass spectrometry and/or fluorescence spectroscopy detection. The student will also conduct extraction studies to optimize sample preparation protocols for marker compounds from the raw botanical materials. The final methods will be used to determine mass fraction values in botanical RMs which the dietary supplement analytical communities use to help ensure consumer safety and accurate product labeling. [In-person opportunity]

646-10 Measurement Methods for Carbon in Cements
Brian Lang, brlang [at] nist.gov (brlang[at]nist[dot]gov)
Sequestration of atmospheric carbon dioxide and the lowering of carbon dioxide emissions during the manufacture of cementitious materials have become processes of interest in the effort to mitigate climate change.  This has driven a variety of ideas on methodologies to accomplish this from injecting emitted carbon dioxide into traditional hydraulic cements to creating and implementing non-hydraulic cements which cure by carbonation.  The determination of the amount of carbon dioxide which has been sequestered into the cement or the concrete and other construction materials is an important aspect of the whole effort.  This helps to inform in the comparison of products and processes, product labeling and governmental regulations and carbon credit systems.  The NIST inorganic chemical metrology group has been tasked with establishing a standardized quantitative measurement methodology using combustion analysis to measure carbon/carbonate content in cementitious and construction materials as well as to support the development of other methodologies, such as thermogravimetric analysis.  Our inorganic group also supports a significant portion of the NIST Standard Reference Material® program.  These reference materials are used within the United States and globally to support measurement quality control.  We are currently in the process of developing an ASTM method to determine sequestered carbon mass fraction in cements and are in the early phase of developing reference materials to support these types of measurements. [In-person opportunity]

COMPUTATIONAL MATERIALS SCIENCE: This concentration includes the application of modeling, simulation, and computational methods to enhance our understanding of innovative materials and devices. This concentration includes projects within the Materials Genome Initiative.

NIST Center for Neutron Research - Reactor Operations and Engineering Group (Div 610.01)

610.01-1 Development of an Intelligent Monitoring System for the Cold Neutron Source Cryogenics System at the NBSR
Robert Newby and David Hix, (301)975-8645, rnn1 [at] nist.gov (rnn1[at]nist[dot]gov)
The student will work towards the development of an intelligent and user-friendly monitoring system for the cold neutron source (CNS). The student will mainly be responsible for understanding the existing CNS system and its sensors and alarms, and then leveraging that knowledge to develop an intelligent condition monitoring system that can discern alarm causes and report them to reactor engineering and operations staff in an accessible manner. Depending on the student’s capabilities, a machine learning algorithm may also be pursued for analyzing historical data logs to develop automated early fault prediction capabilities for the CNS. The student will be gaining experience in developing front-end and back-end of applications for engineering systems. The student will also be gaining valuable insight into the operation of a state-of-the-art CNS at a nuclear test reactor. [In-person opportunity]

610.01-2 Verification of Thermal-hydraulics Subchannel Models for Nuclear Reactors with Plate-type Fuels
Abdullah Weiss and Anil Gurgen, (301)975-6267, abdullah.weiss [at] nist.gov (abdullah[dot]weiss[at]nist[dot]gov)
The student will familiarize themselves with the pre-conceptual design of the NIST Neutron Source (NNS) and the National Bureau of Standards Reactor (NBSR), and they would develop models for both using existing subchannel codes. The student will utilize any one or more of the following codes to develop the models: COBRA-TF, Pronghorn, PLTEMP, STAT7, and in-house codes. Results from each of the codes will be compared against existing in-house data and models. Depending on the student’s abilities, they may also work on coupling some of their models to neutronics or other Multiphysics models. The student will learn about nuclear reactor thermal-hydraulics safety margins and will learn principles for performing safety assessments of nuclear reactors. The student will also gain experience in verification of computational models for nuclear reactor safety assessments. [In-person or virtual opportunity]

610.01-3 NIST Neutron Source Initial Startup Core Loading Analysis
Abdullah Weiss and Osman S. Celikten, (301)975-6267, abdullah.weiss [at] nist.gov (abdullah[dot]weiss[at]nist[dot]gov)
The student will familiarize themselves with the pre-conceptual design of the NIST Neutron Source (NNS), and they would attempt to find the initial startup core loading for the NNS. The student will utilize analytical models and then progress to MCNP computational models for analyzing the effects of different fuel configurations on core behavior. The student will analyze the enrichment equivalence of the equilibrium core uranium amounts by considering fission products that adversely affect the excess reactivity of the NNS Core in the burned assemblies. The student will then determine the number of fuel plates that will be loaded with uranium and their possible positions in the assemblies that would correspond to the desired uranium loading determined in their earlier analysis.   Depending on the student’s capabilities, the student will then utilize MCNP to perform the criticality safety assessment of the NNS core during the initial startup core loading. [In-person or virtual opportunity]

610.01-4 Configuration Management of the National Bureau of Standards Reactor Structures, Systems, and Components
Abdullah Weiss and Daniil L. Sokol, (301)975-6267, abdullah.weiss [at] nist.gov (abdullah[dot]weiss[at]nist[dot]gov)
The student will familiarize themselves with the National Bureau of Standards Reactor (NBSR), and the NBSR’s structures, systems, and components (SSCs). The student will then review available engineering drawings, and they will tour the different SSCs to support their computer aided design (CAD) efforts in digitizing the actual geometries of the SSCs to support configuration management efforts. The student will use CAD software such as SolidWorks to develop the 3-dimensional models of the geometry, and they will review the models with the NBSR engineering and operations staff. The project will start by focusing on the SSCs underneath the NBSR core, and then it will progress to other systems depending on the student’s capabilities. The student will develop practical experience with detailed CAD modeling, and they will learn about configuration management and reliability engineering concepts. [In-person opportunity]

NIST Center for Neutron Research - Neutron Condensed Matter Science Group (Div 610.02)

610.02-3 Triple-axis Automation
William Ratcliff, (301)975-4316, william.ratcliff [at] nist.gov (william[dot]ratcliff[at]nist[dot]gov)
In this project, you will work on using AI to automate the use of an instrument at our international user facility.  The instrument is a thermal triple axis, which measures superconductors, magnetic materials, and materials for quantum information.  You will use Bayesian optimization and reinforcement learning to automate the alignment of crystals and the taking of data.  Your work will accelerate the pace of science and discovery. [In-person opportunity]

610.02-4 Design of a Low-temperature In-field Polarized Small-angle Neutron Scattering Experiment
Jonathan Gaudet and Julie Borchers, (301)975-5010, jonathan.gaudet [at] nist.gov (jonathan[dot]gaudet[at]nist[dot]gov)
Polarized small-angle neutron scattering (SANS) is a technique capable of characterizing magnetic correlations of a material on a 1-1000 nm length scale. The NIST Center for Neutron Research (NCNR) has several SANS beamlines available for the scientific community. The polarized SANS setups at the NCNR are currently restricted to experiments performed at temperatures higher than 4 K, but plenty of interesting phenomena can be probed at lower temperatures. This project aims to design a polarized SANS setup at dilution temperatures (~0.1 K) with an applied magnetic field up to ~ 0.1 T. In particular, the SURF student will use the COMSOL software to calculate the spatial distribution of the magnetic field across various neutron optic devices. [In-person opportunity]

Materials Science and Engineering Division (Div 642)

642-1 Density Functional Theory Study of the Electronic and Magnetic Properties of Two-dimensional (2D) Materials
Daniel Wines, 301-975-2542, %20daniel.wines [at] nist.gov (daniel[dot]wines[at]nist[dot]gov)
Two-dimensional (2D) materials such as monolayer transition metal dichalcogenides and transition metal dihalides are an emerging class of nanomaterials that can be used for a wide variety of electronic and magnetic applications. This project will focus on systematically studying the 2D structures using density functional theory (DFT). The results of these calculations will be uploaded as a part of the Joint Automated Repository for Various Integrated Simulations (JARVIS, https://jarvis.nist.gov) DFT database hosted here at NIST. The student will specifically focus on 2D magnetic materials such as VSe2 and NiI2, using a variety of approximations in DFT to benchmark how different levels of theory impact the material properties. These properties include the preferred magnetic ground state, electronic band structure and magnetic transition temperatures. The student will also assist in writing high-throughput workflow scripts to carry out these DFT calculations and post-processing of calculated data. [In-person opportunity]

642-3 Spatially Resolved Ion Distribution Profiles in Block Copolymers Via Resonant Soft X-ray Scattering
Priyanka Ketkar, pmk [at] nist.gov (pmk[at]nist[dot]gov)
Block copolymers (BCPs) comprise two or more distinct polymer chains that are covalently connected. These materials can assemble into highly tunable structures upon nanoscale phase separation of the component chains. The mixture of BCPs with additives, such as ionic liquids (ILs), can enhance BCP assembly, but it is important to characterize IL distributions throughout a BCP phase to understand material performance. In this project, IL distributions in BCPs will be studied using resonant soft X-ray scattering (RSoXS). The SURF student will analyze the RSoXS data via simulations to quantify component distributions. This analysis will advance knowledge of BCP assembly and also enable development of more accurate simulations for RSoXS data. [Either In-person or Virtual opportunity; Virtual preferred]

642-8 Automated Simulation Protocol for the Thermal Analysis of Glass Forming Polymers
Frederick Phelan Jr., phelan [at] nist.gov (phelan[at]nist[dot]gov)
The student will assist on the development of an automated workflow for the molecular dynamics (MD) analysis of glass forming polymers on High Performance Computing (HPC) systems. The scripting protocol will use the Signac framework to run Python scripts for the high-temperature equilibration, rate-controlled thermal cooling, and output analysis of both structural and dynamic properties. The protocol will be tested by performing MD simulations of Kuhn mapped coarse-grained (CG) systems of different stiffness in both confined and bulk systems to look at the effect of entanglements on picosecond diffusive properties and qualitatively compare with QENS experiments conducted in the Composites Project of the Functional Polymers Group. [Virtual opportunity]

Materials Measurement Science Division (Div 643)

643-3 Augmented / Virtual Reality for Human-AI Interaction with Autonomous Physical Scientist
Aaron Kusne, gkusne [at] nist.gov (gkusne[at]nist[dot]gov)
The student will investigate augmented and/or virtual reality tools to build a human interface for human-AI interaction tools developed at NIST. These interaction tools allow experts to interact in real time with autonomous materials research systems developed at NIST. [Either In-person or Virtual opportunity; Virtual preferred]

643-8 Modeling and Measurements of the Nanoscale Thermomechanical Behavior of Thin Films
Yvonne Gerbig,gyvonne [at] nist.gov ( gyvonne[at]nist[dot]gov)
High-temperature atomic force microscopy (HT-AFM) and nanoindentation (HT-NI) have been attracting growing interest in recent years as means to measure the mechanical properties of small structures, such as thin films, at practical service temperatures but also to probe thermally activated phenomena on the micro and nanoscale.  To better analyze and interpret experimental data collected using HT-AFM and HT-NI, combined thermal and mechanical model need to be developed.  In this project, the student will assist in developing and testing such a model and will be involved in finite-element modelling (FEM), conducting HT-AFM experiments to compare the experimental data with the simulation results.  The student will be provided with the necessary training, equipment, and environment to conduct their research safely and in adherence to NIST safety rules. [In-person opportunity]

Biosystems and Biomaterials Division (Div 644)

644-1 Evaluate Chat-GPT Performance Using Detect, Measure and Verify Method
Talapady Bhat, bhat [at] nist.gov (bhat[at]nist[dot]gov)
Chat-GPT, LLM and AI has become a common household topic of interest to everyone. During the year 2023 my SURF and SHIP students worked to evaluate the performance of Chat-GPT to approximately 500 Covid-19 related question and answers. This study revealed that Chat-GPT answers are just about 30% accurate to the question. A primary reason for this poor performance of Chat-HPT is poor quality of the reference documents available for LLM to generate accurate answers. In 2024 students will develop tools to further evaluate Chat-GPT and LLM and suggest mitigative measures to alter reference documents. [Virtual opportunity]

Biomolecular Measurement Division (Div 645)

645-1 Structure Refinement of Nucleic Acids
Christina Bergonzo, 240-314-6333, christina.bergonzo [at] nist.gov (christina[dot]bergonzo[at]nist[dot]gov)
Structures of nucleic acids that have been solved by Nuclear Magnetic Resonance (NMR) spectroscopy are derived from a combination of data collected experimentally, and the computational tools used to combine all of those experimental observables into a group of structures, called an ensemble. Students will work on creating best practices guidelines for NMR refinement protocols using molecular dynamics (MD) simulations, which have advanced electrostatic and solvent descriptions, to refine a sample nucleic acid. Students will learn the basics of solution state molecular dynamics simulations, including structural biology of nucleic acids and analysis of NMR data and trajectory data. They will contribute to the authorship of publicly available NMR refinement tutorials. [Virtual opportunity]

Chemical Sciences Division (Div 646)

646-2 Modeling Carbon Capture with Aqueous Solutions of Multi-functional Amines
Alexandros Chremos, 301-975-5891, alexandros.chremos [at] nist.gov (alexandros[dot]chremos[at]nist[dot]gov)
Growing concerns about the impact of carbon dioxide (CO2) emissions on the climate and fragile bio-ecosystems necessitate the development of technologies for carbon capture. Such technologies require the development of robust models that accurately predict the thermodynamic behavior of CO2 and other participating components, such as water, over a wide range of temperatures and pressures as well as compositions. We will utilize a molecular-based equation of state (SAFT) to evaluate its theoretical models to describe the CO2 absorption by aqueous mixtures having ethanolamine (considered the benchmark), which are often utilized in carbon capture and the speciation reactions with CO2. Additional amine-based molecules will be evaluated for their performance in capturing CO2. [In-person opportunity]

646-3 Modeling and Measurements of Nanoscale Thermomechanical Behavior of Thin Films
Yvonne Gerbig, 301-975-6130, gyvonne [at] nist.gov (gyvonne[at]nist[dot]gov)
High-temperature atomic force microscopy (HT-AFM) and nanoindentation (HT-NI) have been attracting growing interest in recent years as means to measure mechanical properties of small structures, such as thin films, at elevated temperatures but also to probe thermally activated phenomena at the micro and nanoscale.  To better analyze and interpret experimental data collected by HT-AFM and HT-NI, combined thermal and mechanical models need to be developed.  In this project, the student will assist in developing and testing such models and will be involved in finite-element modelling (FEM) and conducting HT-AFM experiments to compare experimental data with simulation results.  The student will be provided with the necessary training, equipment, and environment to conduct their research safely and in adherence to NIST safety rules. [In-person opportunity]

646-9 Software Development for the IUPAC "Adsorption Information Format"
Daniel Siderius, dsideriu [at] nist.gov (dsideriu[at]nist[dot]gov)
The objective of this project is to develop two software tools critical to the "Adsorption Information Format" (AIF) in the Python language. One tool is a GUI form for generating an AIF file from user-supplied data; it will run in a web browser and include validation steps, file upload, and links to outside APIs to streamline the user experience. The second tool is a "check AIF" program that will validate the contents of an AIF file and confirm that the file satisfies the standard and vocabulary. This project will be coordinated with the IUPAC AIF Team, including collaboration with scientists in the United Kingdom, Australia, and Japan. [In-person opportunity]

MATERIALS SCIENCE: This concentration focuses on synthesis, measurements, and theory of innovative materials and devices. Note: This concentration includes projects from the NCNR. Additionally, a limited number of projects are available at the NCNR for students with interest in nuclear engineering and/or reactor operations.

NIST Center for Neutron Research - Neutron Condensed Matter Science Group (Div 610.02)

610.02-5 Quantum Materials: Synthesis and Property Characterization
Nicholas Butch and Sylvia Lewin, (301)975-4863, nicholas.butch [at] nist.gov (nicholas[dot]butch[at]nist[dot]gov)
The applicant will participate in synthesis of quantum materials with a choice of materials that host novel magnetism, superconductivity or other electronic phases, which are being studied by the Butch group at the NCNR-affiliated Quantum Materials Center at the University of Maryland. Applicant will utilize x-ray diffraction, magnetometry, and other electronic property probes to characterize the structure and properties of synthesized samples. If available, NCNR facilities will also be utilized. Applicant will learn data analysis and interpretation. This project will involve work both at NIST, in Gaithersburg, and at the University of Maryland in College Park. [In-person opportunity]

610.02-6 Voltage-driven Control of Giant Magnetoresistance for Magnetoresistive Random Access Memories (MRAM)
Shane Lindemann and Peter Gehring, (301)975-6279, shane.lindemann [at] nist.gov (shane[dot]lindemann[at]nist[dot]gov)
Voltage control of magnetism is a promising candidate for use in the next generation of Magnetoresistive Random Access Memories (MRAM).  Here we aim to utilize strain-mediated coupling by fabricating magnetic thin films on substrates possessing piezoelectricity, a material property that allows electrical energy to be converted into strain.  By applying an electric field across the substrate, the generated strain is transferred to the thin films resulting in changes in magnetism that can alter the electrical resistance of spin valves that consist of alternating layers of magnetic/nonmagnetic films.  This mechanism is expected to provide higher storage densities, faster writing times, and orders of magnitude lower power consumption than today’s magnetic-field-write RAM. This summer, we invite a SURF student to join our investigation of voltage-driven changes in spin valve devices.  The student’s role in this project will include: 1) Designing Giant Magnetoresistance (GMR) spin valves which will be patterned from magnetic thin films on piezoelectric substrates. 2) Measurement and analysis of voltage-induced changes of magnetism in thin films using a B-H measurement system.  3) Experimentally testing changes of resistance in GMR spin valves using a 4-probe resistance measurement system, followed by analysis and correlation with the observed changes in magnetic hysteresis. [In-person opportunity]

610.02-7 Revealing the Magnetism of Topological Magnets with Neutron Scattering
Jonathan Gaudet and Julie Borchers, (301)975-5010, jonathan.gaudet [at] nist.gov (jonathan[dot]gaudet[at]nist[dot]gov)
Topological magnets are materials whose properties are dictated by the topology of their electronic wavefunctions, which are highly intertwined with their spin structure and spin excitations. The goal of this project is to fully characterize the magnetic properties of a topological magnet using neutron scattering techniques. The SURF student will get familiar with the different neutron scattering techniques and apply one of them to study the magnetism of a topological magnet. [In-person opportunity]

610.02-8 Capillary Rheology of Soft Nanoparticles
Katie Weigandt and Kelsi Rehmann, (301)975-8396, kathleen.weigandt [at] nist.gov (kathleen[dot]weigandt[at]nist[dot]gov)
The new capillary rheoSAS developed at NIST is an instrument capable of measuring the structure of nanomaterials at very high speeds and deformation rates. Many consumer products consist of soft, structured nanomaterials that experience these high deformation rates during processing or end-use. However, commercial instruments rarely measure water-based samples at such high shear rates. Rheology is the measurement of a fluid’s response to deformation.  We will be measuring the rheology of soft nanoparticles made of polymers and lipids in water as part of a larger program using capillary rheoSAS. Rheology measurements will include high shear capillary measurements and complementary low shear and oscillatory measurements.  Sample preparation, which affects the final structure, will be a major part of this project; this includes different preparation methods for self-assembly as well as polymerization. Depending on availability, we will also study these materials with light, x-ray, and/or neutron scattering. In scattering techniques, an incident beam of light, x-ray, or neutrons is scattered after interacting with the sample, and the scattering pattern is measured. A model is fit to the scattering data to back out the nanoscale structure of materials. We will introduce the concepts of scattering but will focus on rheology measurements. [In-person opportunity]

Materials Science and Engineering Division (Div 642)

642-2 Understanding Partial Remelting/Crystallization Cycles in Fused Filament Fabrication
Paul Roberts,pjr1 [at] nist.gov ( pjr1[at]nist[dot]gov)
Advanced processing often requires complex crystallization and remelting processes for polymers. One example is in material extrusion 3D printing processes like fused filament fabrication (FFF). In this project, the student will use FFF to fabricate structures from two semicrystalline polymers, isotactic polypropylene and polylactic acid, for an array of thermal conditions measured by inline IR thermography. The student will then measure the mechanical properties of the printed structures, including print fidelity, weld strength, and fracture toughness. Finally, the student will replicate the FFF print histories on a polarized optical microscope using image analysis to characterize semicrystalline morphology along with spherulite size and distribution. [In-person opportunity]

642-4 Analysis of High-speed In-situ X-ray Images to Understand Particle Impact Behavior in Laser, Powder-blown Directed Energy Deposition (DED)
Samantha Webster, saw6 [at] nist.gov (saw6[at]nist[dot]gov)
High-speed X-ray images were collected at the Advanced Photon Source (APS) at Argonne National Lab using a mini-DED experimental setup in order to observe powder particle impact behavior on the melt pool surface. Different powder particle speeds were used under different processing conditions to observe the effect of powder velocity on vapor cavity formation and collapse behind the powder particle. Image and data analysis using a combination of ImageJ, Matlab, or Python will be used to make connections between powder velocity and diameter with cavity formation and collapse.  [Either In-person or Virtual opportunity; In-person preferred]

642-5 Effect of Multi-mode Laser Beam Shapes on Microstructure of 17-4 using Laser, Powder-blown DED
Samantha Webster, saw6 [at] nist.gov (saw6[at]nist[dot]gov)
Laser powder-blown DED consists of a nozzle that uses carrier gas, such as argon, to blow powders onto a substrate where a laser melts the deposited powders and substrate. A new DED system developed at NIST consists of a coaxial ring nozzle, two electrostatic powder feeders, and it is built on a hybrid manufacturing platform with machining capabilities. Two lasers can be used with the system: (1) a single-mode laser with a Gaussian distribution and (2) a multi-mode laser with both Gaussian and ring mode distributions. A comparison of materials deposited with the single-mode and multi-mode laser is needed to observe the effect of beam shape on microstructure. Student must take required laser safety training as well as hazard review/hands-on training for the DED lab. [In-person opportunity]

642-6 Evaluating the Performance of Additively Manufactured Alloys
Mark Stoudt, stoudt [at] nist.gov (stoudt[at]nist[dot]gov)
The student work will be part of a larger project designed to characterize the structure/process/property relationships in additively processed alloys as compared to wrought processed counterparts.  The overall goal of this work will be to examine how differences in the material microstructure influence the electrochemical and mechanical properties in a simulated petroleum and natural gas environment.  Property measurements are likely to include free corrosion potential and potentiodynamic polarization measurements, slow strain rate tensile tests (w/assistance) and evaluation of experimental results (i.e., metallography, microhardness measurements, optical and scanning electron microscopy and failure analysis). [In-person opportunity]

642-7 Morphology Analysis in Sheared Polyolefin Blends
McKenzie Coughlin, mlc1 [at] nist.gov (mlc1[at]nist[dot]gov)
Polyolefins, such as polypropylene (PP) and polyethylene (PE), contribute to the largest share of the plastics waste stream. Post-consumer polyolefins are typically mixed when they enter the waste stream and are often processed together. Blends of PE and PP form micro-separated domains when melted together due to thermodynamic incompatibilities, and the morphology of these domains will affect the final material properties. We are interested in studying how the domain morphology changes when polyolefin blends have been processed under shear. We will primarily be using scanning electron microscopy (SEM) to image blend samples and analyzing changes that occur after samples have been sheared. The student’s role in this project will include sample preparation for SEM imaging, characterizing blend morphology using SEM, and image analysis to understand changes in domain size, shape, and size distribution. [In-person opportunity]

Materials Measurement Science Division (Div 643)

643-2 Fiber Composition Detection for Textile Sorting via Spectroscopy
Katarina Goodge, keg6 [at] nist.gov (keg6[at]nist[dot]gov)
This project is focused on advancing the textile sorting efforts as a part of the Circular Economy of Textiles program. The SURF student will be developing, modifying, and debugging a Python-based algorithm to process and analyze collected electromagnetic spectral data. The goal of the algorithm is to perform discriminatory analysis to detect differences between known sample compositions and recognition analysis to identify unknown sample compositions through machine-learning-based techniques. The major focus of this SURF project is the algorithm development and validation aspect; however, this will be augmented by hands-on data collection of dyed fabric samples with known fiber content, dyes, and finishes in the near-IR, mid-IR, and visible ranges of the electromagnetic spectrum. The SURF researcher is expected to participate in all the research activities related to this project, including literature search, hands-on experiments (including safety training), data analysis, and interpreting and presenting results. [In-person opportunity]

643-4 Accelerating MOF development for Carbon Capture
Howard Joress, hjoress [at] nist.gov (hjoress[at]nist[dot]gov)
Metal organic frameworks (MOFs) have shown great promise for a variety of applications including Direct Air Capture. However, development and optimization of MOF synthesis remains a challenge. To address this gap, we are starting a program to synthesize MOFs using an autonomous platform, coupled with high-throughput characterization (x-ray diffraction and FTIR). Specific projects for students will be decided based on interest and skillset, but may include experimentally demonstrating proof-of-concept ML algorithms, developing and testing new characterization pipelines, and prototyping automated synthesis steps. Students should be comfortable with wet chemistry, have a basic background in programming (preferably python/julia), and have some background in materials structures. [In-person opportunity]

643-5 Develop Tiny Lab Environmental Monitoring Computer Using LoRa Radio to Transmit Data
Marcus Mendenhall, mhm [at] nist.gov (mhm[at]nist[dot]gov)
Many NIST laboratories have needed a small environmental (temperature, humidity, and maybe some auxiliary variables) that can be inexpensively deployed and which will transmit the data to a central server where it can be monitored.  A technology called LoRa radio, which operates on an unlicensed 915 MHz band, can penetrate walls, and provide low-data-rate, secure transmission.  The project will start with building two LoRa stations, using off-the-shelf modules, and moving them around to various labs to see how the signal propagates.  If it is suitable, attaching sensors to the units is straightforward. The units would not need REN or NIST network access, so they would not create a security hazard. Only the central server would be a regular NIST computer. [In-person opportunity]

643-7 Advanced Ceramic Manufacturing – Rheology and 3D printing Ceramic Slurries
Lynnora Grant, log [at] nist.gov (log[at]nist[dot]gov)
The NIST Material Measurement Laboratory (MML) is leading research efforts in ceramic additive manufacturing (ceramic AM). The first step of ceramic AM often involves forming ceramic powder and organic additives into porous agglomerates which are then densified through postprocessing. Understanding the property-process-structure relationship during the distinct forming and postprocessing steps is crucial for manufacturing ceramic structures which exhibit dimensional accuracy and suitable mechanical properties. A 2024 NIST SURF student will use newly commissioned ceramic 3D printers to assist ongoing NIST MML efforts to measure and understand the relationships between slurry rheology, print process parameters, printability, and stability of printed ceramic structures. Structural ceramics e.g. alumina will be printed via either direct ink write or vat photopolymerization processes. The print geometry will be monitored in situ with mounted cameras, and process maps will be developed to guide selection of slurry composition and print parameters. The student will undergo general lab safety training, project specific trainings, and will review the project specific hazards and appropriate PPE prior to beginning work in the lab. [In-person opportunity]

Chemical Sciences Division (Div 646)

646-4 Enhancing AI Readiness of NIST/MML/BBD Webpages
T N Bhat, 301-975-5448, talapady.bhat [at] nist.gov (talapady[dot]bhat[at]nist[dot]gov)
Chat-GPT, LLM and AI has become a common household topic of interest to everyone. During the year 2023 my SURF and SHIP students worked to evaluate the performance of Chat-GPT to approximately 500 Covid-19 related question and answers. This study revealed that Chat-GPT answers are just about 30% accurate to the question. A primary reason for this poor performance of Chat-HPT is poor quality of the reference documents available for LLM to generate accurate answers. In 2024 students will develop tools to further evaluate Chat-GPT and LLM and suggest mitigative measures to alter reference documents. This second project focusses on data-analysis. The first SURF project is on tools development. [Virtual opportunity]

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Physical Measurement Laboratory (PML)

The PML sets the definitive U.S. standards for nearly every kind of measurement in modern life, sometimes across more than 20 orders of magnitude. PML is a world leader in the science of physical measurement, devising procedures and tools that make continual progress possible. Learn more about PML.

Contacts

Physics
Uwe Arp, (301) 975-3233, uwe.arp [at] nist.gov (uwe[dot]arp[at]nist[dot]gov)
Maritoni Litorja, (301) 975-8095, maritoni.litorja [at] nist.gov (maritoni[dot]litorja[at]nist[dot]gov)

PML Research Opportunities (2024 Projects)

Office of Weights and Measures ( Div 680)

680-01 Legal Metrology Calibration Research
Elizabeth Koncki, (301) 975-4895, elizabeth.koncki [at] nist.gov (elizabeth[dot]koncki[at]nist[dot]gov)
Candidate will research, design and develop Office of Weights and Measures (OWM) Laboratory Metrology Program Proficiency Testing (PT) tools (e.g., statistical analysis, process management, artifact inventory management and tracking, and quality system improvements) to support calibration laboratory Recognition and Accreditation requirements. Candidate will collaborate to develop measurement science training and professional development resources. [In-person opportunity]

680-02 Metric System Learning Resources
Elizabeth Benham, (301) 975-3690, elizabeth.benham [at] nist.gov (elizabeth[dot]benham[at]nist[dot]gov)
Candidate will research, design and develop engaging website content, classroom activities, illustrations and graphic artwork, posters, and videos. This project supports NIST efforts to seek out ways to increase understanding of the International System of Units (SI, metric system) through educational information and guidance in government publications. This project aligns with the NIST Metric Program objective to implement the national policy to establish the SI as the preferred system of weights and measures for U.S. trade and commerce, which originates from the Metric Conversion Act and Presidential Executive Order 12770. [In-person opportunity]

Microsystems and Nanotechnology Division (Div 681)

681-01 Biomolecular Dosimetry for Precision Radiation Oncology
Joseph Robertson, 301-975-2506, joseph.robertson [at] nist.gov (joseph[dot]robertson[at]nist[dot]gov)
Determining the biologically effective dose delivered to irradiated biological samples is challenging. This is exacerbated by limitations of the sievert (the SI unit) for biological radiation dose in its application to radiology. This work will involve developing new tools for studying DNA damage at the single-molecule level by fabricating nanopores in a dielectric membrane and observing molecular translocation by measuring ionic current signatures (resistive pulses). These resistive pulses will be decoded using machine learning and other artificial intelligence tools to determine the amount and type of ionizing radiation damage the DNA has received. [In-person opportunity]

681-02 Bioelectronic Sensors for Tissue/Organ-on-a-Chip Systems
Darwin Reyes, (301) 975-5466, darwin.reyes [at] nist.gov (darwin[dot]reyes[at]nist[dot]gov)
The use of tissue/organ-on-a-chip systems is limited to endpoint and destructive measurements. Integration of electronic elements in these systems have proven to be a huge challenge and only a few demonstrations have been shown. Contrary to endpoint biochemical methods, continuous electronic monitoring of cellular behavior provides an approach for real-time and non-destructive methods that support acute and chronic studies within the same assay. Therefore, we are developing microfluidic-based tissue/organ-on-a-chip devices with embedded electronic elements. Our goal is to fabricate systems and demonstrate their efficacy in delivering real-time, continuous monitoring of cellular responses under stress and disease conditions. [In-person opportunity]

681-03 Photonic Nanopore Sensors
Henri Lezec, (301) 975-8612, henri.lezec [at] nist.gov (henri[dot]lezec[at]nist[dot]gov)
Driven by advances in material processing, nanofabrication and photonics, it is now possible do build and utilize nanopore sensors that are enhanced through the manipulation of light. Through this project the student will develop nanopore devices that incorporate purpose built plasmonics, or embedded photoemitters to add additional multidimensional sensing capabilities to a traditional resistive pulse sensor. [In-person opportunity]

681-04 Development of a Graphene Field-effect Biosensor for Detection and Quantification of Extracellular Vesicles
Derrick Butler, (301) 975-3167, derrick.butler [at] nist.gov (derrick[dot]butler[at]nist[dot]gov)
Organ- and heart-on-a-chip platforms have been regarded as a new paradigm in clinical drug evaluation and cardiac research. Myocardial infarction (MI) is one of the most common cardiovascular diseases, which in total, account for 1 out of 4 deaths in the US.  To help improve patient outcome after a MI event, various therapeutic interventions are under investigation to reduce the chance of heart failure later in life. In particular, intercellular communication through extracellular vesicles (EVs), such as exosomes, has been recognized as an integral component of many physiological processes in the body, including organ function, disease progression, and tissue repair. The goal of this project is to develop graphene field effect transistors (gFET) to better understand the behavior and dynamics of the heart under normal, pathological, and therapeutic conditions in a controlled and reproducible setting.  In this project the student will fabricate gFETs on a separate Si/SiO2 substrate to later be placed downstream from a polyester (PET) membrane/interdigitated microelectrodes (IDMs). The gFET sensors will be functionalized by attaching a chemical that will link molecules like proteins, antibodies, aptamers and others via surface amine groups.  The student will characterize the gFETs after binding antibodies specific for EVs, by electrically measuring known concentrations of antibodies. [In-person opportunity]

Radiation Physics Division (Div 682)

682-01 Contact Angle Measurements for Substrate Optimization in Drop-on-demand Patterning of Microgram Quantities of Aqueous Solutions
Denis Bergeron, 301-975-2282, denis.bergeron [at] nist.gov (denis[dot]bergeron[at]nist[dot]gov)
NIST scientists have developed advanced instruments and methods for drop-on-demand deposition of picoliter quantities of solution with mass traceability. These technologies are now being applied with radioactive materials to prepare sources for decay energy spectrometry (DES), alpha spectrometry, and autoradiography, with activity linked to primary liquid scintillation measurements. The student will work with NIST scientists to assess materials compatibility of various substrates (nanoporous gold, gold foils, various grades of stainless steel) with the acidic carrier solutions commonly encountered with radioactive material. The student will prepare substrates using different methods and deposit non-radioactive solutions in different patterns. Microscopy and contact angle measurements will be used to characterize surface interactions. [In-person opportunity]

682-02 Thermal Modeling of Cryogenic Radiation Detectors
Max Carlson, 301-975-5608, max.carlson [at] nist.gov (max[dot]carlson[at]nist[dot]gov)
The NIST True Bq project aims to create a system that can detect and quantify virtually any radioactive material. To do this, True Bq uses cryogenic transition edge sensors (TES) for decay energy spectrometry (DES). The TES operates at a temperature of 0.1 K and directly measures sub-pJ thermal energy emitted by the radioactive decay of a single atom. We are looking to improve computational models of the heat flows in the TES, which include non-linear temperature dependence at mK temperatures. This project focuses mainly on computer modelling, with the opportunity for lab work as well. The resultant model will be used to optimize the next-generation of cryogenic sensors for applications such as nuclear medicine, environmental monitoring, and nuclear security. Lab work may include installing and verifying performance of TES chips in our He-3 dilution refrigerator. [In-person opportunity]

682-03 Monte Carlo Simulations of Yttrium-90 Source Geometry and Experimental Validation
Brittany Broder, (301)975-4059, brittany.broder [at] nist.gov (brittany[dot]broder[at]nist[dot]gov)
Yttrium-90 (Y-90) is a beta-emitting radionuclide that is often used to treat liver cancers. It has a short range, allowing it to treat tumors effectively while sparing nearby healthy tissues. However, it’s short range poses a problem in measuring its radioactivity. An accurate, reliable measurement of the activity is necessary for precision imaging and dosimetry for therapy treatments. Many factors impact the activity measurement, including the chemical form of the Y-90, the container it’s placed in, and aspects of the measurement instrument itself. Such measurements are usually made with radionuclide radionuclide calibrators, a common utility in nuclear medicine to determine the initial activity administered to the patient. NIST is responsible for making sure radionuclide calibrator measurements can be made with traceability to a common National standard, making radionuclide calibrators an important tool in disseminating activity standards. Modelling radionuclide calibrators allows us to explore how changes in the radionuclide form and containment vessel impact the instrument response. In this project, the student will use a model of a radionuclide calibrator to explore the Y-90 response and explain experimental data. The student will assist in Y-90 source measurements using a radionuclide calibrator to validate their simulations. [In-person opportunity]

682-04 Water Calorimetry for Ultra-high Dose Rate (UHDR) Electron Beams Using Ultrasound
Ron Tosh, (301)975-5591, ronald.tosh [at] nist.gov (ronald[dot]tosh[at]nist[dot]gov)
The project has both experimental and computational aspects, and a SURF intern would be welcome to contribute to either or both.  The experimental work entails instrumenting a water phantom with ultrasonic transducers for testing in a UHDR electron beam at NIST and related testing or simulation using signal generators and spectrum analyzers.  Computational modeling of detector response is used to validate data analysis methods and to guide the interpretation of acquired signals. [In-person opportunity]

682-05 Studying Charged Particle Thermal Kinetic Inductance Detectors for Nuclear Physics Applications
Shannon Hoogerheide, (301) 975-8582, shannon.hoogerheide [at] nist.gov (shannon[dot]hoogerheide[at]nist[dot]gov)
The neutron physics group is investigating Charged Particle Thermal Kinetic Inductance Detectors (CP-TKIDS) for use in neutron beta decay experiments. CP-TKIDS are cryogenic sensors that can detect incoming particles across a range of energies, with excellent energy resolution. The geometry of the CP-TKID can be optimized for different types of particles and experiments. The student will work with NIST scientists to analyze data in order to understand things like position-dependent effects of various CP-TKID designs. There may also be opportunity to participate in the design of new CP-TKID geometries or work with electronics required for data acquisition. [In-person opportunity]

Nanoscale Device Characterization Division (Div 683)

683-01 Developing and Testing Cryogenic COTS (Commercial, Off the Shelf) Circuits for Improved Measurements of Quantum Devices
Josh Pomeroy, (301)975-5508, Joshua.pomeroy [at] nist.gov (joshua[dot]pomeroy[at]nist[dot]gov)
This project is aimed at developing electronic circuits to operate and measure quantum devices, placed only a few centimeters (or less) from the quantum devices, which requires the circuits to be at cryogenic temperatures. Specifically, this project uses cryogenically characterized, commercial electronic components to build, test and pair voltage regulating, current amplifying, and voltage amplifying circuits to prototype quantum devices and evaluate improvements in measurement fidelity and speed. [In-person opportunity]

Quantum Measurement Division (Div 684)

684-01 Nonlinear Optics of a Rb Vapor Cell in 3+1D
Zachary H. Levine, 301-975-5453, zlevine [at] nist.gov (zlevine[at]nist[dot]gov)
Lasers interact with the hyperfine-split levels of certain atoms such as Rb.  The dielectric response of such systems is highly dispersive, nonlinear, and depends on time and space.  The student will compute, using code written by the advisor, one or more of these phenomena:  (a) entanglement generation in a double lambda system, (b) soliton formation in systems with feedback, and (c) focusing and defocusing characteristic of the saturated Kerr effect.  For (c) the science question is whether the standard analysis of the optics in the Kerr effect based on perturbation theory yields accurate parameter values in the non-perturbative regime. [In-person or virtual opportunity]

684-02 Laser Vibrometry for Dynamic Mechanical Metrology
Jared Strait, (301)975-2240, jared.strait [at] nist.gov (jared[dot]strait[at]nist[dot]gov)
Laser Doppler vibrometers measure velocity through frequency shifts in light and are the gold standard for accurate characterization of motion. The student will contribute to ongoing research in accelerometry and dynamic force metrology by applying Doppler vibrometry to assess primary and parasitic motions of linear vibration excitation systems. Elements of this project will include hands-on putting together, evaluation, and readjustment of the measurement system and instrumentation, data collection and analysis, and possible comparison with finite-element simulations of structural dynamics. [In-person opportunity]

684-03 Developing a DC Power and Energy Calibration Service for Car Chargers
Richard Steiner, (301) 975-4226, richard.steiner [at] nist.gov (richard[dot]steiner[at]nist[dot]gov)
A DC Power and Energy calibration service is needed by State Weights and Measurements Offices to ascertain the accuracy of the monetary assessment for electric vehicle (EV) charging stations. In the project, a simulated EV battery charging signal using separate voltage and current sources must be generated, and then accurately measured for power and energy, relative to International Standards (SI). This measurement uses several digital multimeters and current transducers, along with various SI transfer standards. The calibrated signal will in turn be measured by commercial power meters, and a custom-assembled box of measurement instruments for eventual transfer to field stations. The student will participate in, and learn, instrumentation programming, signal analysis, electrical measurement techniques, EV charging station dynamic signals, and various issues in metrology. [In-person opportunity]

684-04 Spectroscopy of Highly-charged Ions from EBITs
Yuri Ralchenko, (301) 975-3210, yuri.ralchenko [at] nist.gov (yuri[dot]ralchenko[at]nist[dot]gov)
We plan a series of measurements of spectral lines from highly-charged ions of heavy elements to provide benchmark atomic data for optical atomic clocks, determination of variation of fundamental constants, and tests of modern atomic theories, to name a few. A SURF student will support the experimental work and/or participate in theoretical calculations of atomic parameters relevant to the planned measurements. [In-person opportunity]

684-05 Experiments with Highly Charged Ions Stored in a Trap
Joseph Tan, (301) 975-8985,Joseph.tan [at] nist.gov ( joseph[dot]tan[at]nist[dot]gov)
Certain excited atomic states in highly charged ions are unusually long-lived, with characteristics that are potentially useful for developing optical atomic clocks and for determining fundamental constants.  Experiments can utilize a compact electron beam ion trap (mini-EBIT) or the NIST superconductive EBIT to facilitate the generation of such exotic charge states. [In-person opportunity]

684-06 Suppression of Entanglement Loss in Weakly Measured Fermi Gases
Ian B. Spielman, (301) 975-8664, ian.spielman [at] nist.gov (ian[dot]spielman[at]nist[dot]gov)
Quantum entanglement is a resource for measurement, computation and simulation that is easily lost to the environment.  We will explore theoretical techniques to use measurement to limit this growth.  More specifically, the environment itself can be understood as a sort of measurement, and the way that information is stored forms a sort of ``quantum lens'' defining how the system is impacted by measurement.  This project will focus on new ways that system-reservoir coupling and the subsequent measurement can be used to inoculate the system against decoherence. [In-person opportunity]

Sensor Science Division (Div 685)

685-01 Ionization of Rydberg Atoms by Blackbody Radiation
Eric Norrgard, (301) 975-2185, eric.norrgard [at] nist.gov (eric[dot]norrgard[at]nist[dot]gov)
Project involves performing experimental research to study the effects of ionization rate of Rydberg atoms as a function of blackbody radiation temperature and other environmental factors.  Researcher will quantify ionization rate by spectroscopic and electronic methods. [In-person opportunity]

685-02 Laser Cooling and Trapping of MgF for Blackbody Thermometry
Nickolas Pilgram, (301)975-4809, nickolas.pilgram [at] nist.gov (nickolas[dot]pilgram[at]nist[dot]gov)
Current blackbody thermometry techniques suffer from a number of systematic effects and require long calibration chains. The use of an ideal quantum system can circumvent these issues and provide a calibration-free, direct-to-SI measurement of blackbody radiation temperature. Cold polar molecules, which strongly interact with blackbody radiation, are an ideal quantum system for such a detector. The student will assist in the experimental laser cooling and trapping of MgF molecules for use in measurements of blackbody radiation temperature. [In-person opportunity]

685-03 Directional Reflectance Measurements from the UV to IR
Maritoni Litorja, (301)975-8095, litorja [at] nist.gov (litorja[at]nist[dot]gov)
How we visually perceive surface texture is due in part on how materials reflect light in different directions. This property is important in a variety of measurement applications, from satellite-based earth remote sensing, to promoting efficacy of disinfecting ultraviolet radiation to keep a healthy indoor environment, and even to graphical rendering.  NIST is creating an open access database of the optical directional reflectance of materials of interest to various application communities. We will use a new commercial instrument to measure the directional reflectance, specifically the bidirectional reflectance distribution function (BRDF), of a wide range of materials across the wavelength range of 200 nm to 2400 nm. We will thoroughly characterize the new commercial instrument by validating it against other NIST instruments and will improve its performance as necessary. A key part of this validation will be formulating an uncertainty budget. One of the main challenges anticipated with this project will be ensuring the results are accurate when measuring materials with varied and unusual optical properties. There will also be opportunities to explore new methods to visualize and share BRDF data, as our goal is to eventually build an interactive, online data viewer where users can explore and download BRDF data. [In-person opportunity]

685-04 Developing Fast Readout Schemes for Optomechanical Pressure Sensors
Daniel Barker, (301)975-0544, daniel.barker [at] nist.gov (daniel[dot]barker[at]nist[dot]gov)
Engineered optomechanical systems are simple and robust pressure gauges that operate from the high vacuum to atmospheric pressure. Such sensors work by measuring the gas-induced damping of microfabricated mechanical oscillators. Under vacuum conditions, the damping time can be minutes long, limiting the sensor’s precision and its sensitivity to pressure dynamics. In this project, we will implement fast readout schemes based on coherent motion control of our optomechanical sensors. Achieving this goal involves upgrading the sensor’s optical interferometer, setting up fast feedback systems, and extending the sensor control software. By realizing measurements faster than the mechanical damping time, we will remove a significant impediment to adoption of optomechanical pressure sensors beyond the lab. [In-person opportunity]

685-05 Machine Learning for Automated Forensic Classification of Firearm Marks on Cartridge Cases
Xiaoyu Alan Zheng, (301) 975-4095, alan.zheng [at] nist.gov (alan[dot]zheng[at]nist[dot]gov)
Firearm and toolmark analysis has been an important part of forensic investigations for over a century. However, in the last decade, it has come under scrutiny due to the subjective nature of the pattern matching evaluations that it utilizes to determine whether two ballistic samples were marked by the same firearm. Reports, such as the 2009 National Academy of Science “Strengthening Forensic Science in the United States,” called for the use of more objective comparison methods and statistically-sound statements for the strength of evidence. In collaboration with the forensics community, NIST is addressing these concerns through research on 3D imaging of firearm toolmarks, objective comparisons algorithms, and statistical analysis frameworks. Statistical modeling of comparison scores requires assessment of the toolmark’s class characteristics. Currently this is still based on a subjective human evaluation of the marks generated by a firearm. In the 2024 SURF project, the student will learn the basics of firearm and toolmark analysis with a focus on the types of class characteristics commonly used by forensic practitioners. They will then utilize existing databases of pre-classified toolmarks and build a Machine Learning model to automatically classify these characteristics. Once the model is built, testing will be conducted on its performance using a validation set of toolmarks. This project will help improve the objectivity, speed and accuracy of future firearm toolmark database development. [In-person opportunity]

685-06 Field Spectroscopy of Algae Blooms
Aaron Goldfain, (301) 975-2338, aaron.goldfain [at] nist.gov (aaron[dot]goldfain[at]nist[dot]gov)
Harmful algal blooms are becoming increasingly common in lakes and ponds. Interest is growing in using remotely sensed hyperspectral data to identify harmful algal blooms. However, doing so requires comparing remotely sensed data to trusted ground-based measurements of algal blooms. This project aims to develop field protocols for collecting hyperspectral measurements of algae blooms using handheld spectrometers. The student will develop these protocols by working closely with a small team of researchers in both field and lab settings. The protocols will ultimately enable researchers to routinely collect ground-based spectra of algae to validate and inform remotely sensed data. [In-person opportunity]

685-07 Modeling of Thermal Systems for 3D Thermal Imaging
Solomon Woods, (301) 975-2382, solomon.woods [at] nist.gov (solomon[dot]woods[at]nist[dot]gov)
Our group is currently developing a method for 3D thermal imaging, based on measurements of magnetic nanoparticle tracers. For the first time, such a system could enable real-time remote thermal imaging and heating inside biological, chemical, and physical systems. We are looking for a student to model and simulate thermal phantoms and material systems, which will also be experimentally imaged using our imaging scanner. Heat sources and isothermal surfaces will be defined, along with material properties and boundary conditions, and then the 3D temperature map will be determined. Both time-dependent and equilibrium states will be computed using a finite element analysis (FEA) solver. Computing resources will be provided, including access to COMSOL Multiphysics. Previous experience with COMSOL and familiarity with Python programming preferred. [In-person opportunity]

685-08 Building a Portable Laser System for Laser Cooling Lithium
Stephen Eckel, (301) 975-8571, stephen.eckel [at] nist.gov (stephen[dot]eckel[at]nist[dot]gov)
Over the past several years, NIST’s cold atom vacuum standard has been demonstrated to be both a sensor and a standard for vacuum pressures in the ultra-high (<10^{-6} Pa) vacuum regime.  The CAVS works by laser cooling atoms to less than 1 mK temperatures and placing them into a conservative, magnetic trap.  While in the trap, they undergo collisions with background gases that eject them from the trap.  Counting the remaining atoms in the trap after a certain period of time gives us an excellent measurement on the density of background gas molecules through first-principles quantum scattering calculation. NIST’s portable cold atom vacuum standard currently consists of a sensor head, about 1 L in volume that attaches to a vacuum chamber under test.  At the same time, the lasers, electronics and computer control which are used to control the sensor head are spread out across the laboratory, hindering its portability.  Our project involves building a new, portable laser and control elecrtronics system that is mounted on a portable 19” equipment rack.  In order to do so, the student will help to assemble necessary electronics into smaller packages and align laser systems used for frequency locking.  Over the course of the summer, the student will gain experience in laser stabilization, control electronics and control systems, and will be constantly looking for new ways to improve and simplify our experimental design. [In-person opportunity]

Past PML SURF Projects

• PML 2021 SURF Projects
• PML 2020 SURF Projects

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Special Projects

Public Affairs Office (PAO) (Div 107) (2024 Project)

107-1 Science Writing
Ben Stein and Robin Materese, 301-975-2763 and 301-975-4158, benjamin.stein [at] nist.gov (benjamin[dot]stein[at]nist[dot]gov) and robin.materese [at] nist.gov (robin[dot]materese[at]nist[dot]gov)
From AI to biological drugs, chip manufacturing to emergency communications, and disaster resilience to quantum computing, NIST conducts research in a broad range of topics that are critically important to people and society. NIST’s Public Affairs Office communicates our research and other activities to a broad audience through news articles, social media, videos, website explainers, and many other formats. If you enjoy sharing your knowledge about science with nonscientist friends and family, have written about science for your school newspaper, or taken a class in science writing, this could be the perfect fit for you. The selected student will gain experience in writing profiles, science explainers, news articles, and other NIST web content for the general public. You will collaborate with communications professionals in social media, graphic design, and video production. You will learn interviewing skills, participate in brainstorming sessions, accompany our video crews for film shoots in our research labs, and gain valuable experience writing published pieces under the supervision of NIST’s science editors.

How to apply: In the “online questions” (particularly #11-13, 18 and 24) of the SURF application, please indicate your interest in applying to PAO as a science writing intern. Prior coursework in writing, journalism, or other communications fields is desirable but not required. Interested applicants will subsequently be required to provide two writing samples that demonstrate the ability to translate chemistry, engineering, physics, biology, computer science or other science research concepts into journalistic lay language. [In-person opportunity]

Standards Coordination Office (SCO) (Potential 2024 Projects)

The Standards Coordination Office provides guidance and coordination to the federal government and to private entities on documentary standards and conformity assessment.  Documentary standards effect our daily lives by guiding the production of nearly everything we purchase and use. Examples range from agricultural products such as milk, consumer products such as electronics, clothing, toys, to innumerable products still to be created.  Our goal is to equip U.S. industry and the federal government with the standards-related tools and information necessary to effectively compete in the global marketplace. SURF participants engage in research opportunities that advance the development or assessment of performance standards and test methods of benefit to manufacturers, end users, and federal agencies, and explore the economic analysis of the impacts of standards and conformity assessment. Learn more about SCO.

How to apply - In the special skills section of the application, please indicate your interest in applying to SCO. SCO welcomes uniqueness and diversity!  Background training or an interest in economics, international relations, and/or political science as well as in other science and engineering fields is desirable but not required.

SCO will work with a SURF intern to develop a research plan tailored to enhancing their knowledge and capabilities in documentary (written) standardization activities. This work will be appealing to those interested in public policy, international standards, and/or the relationship between documentary standards and the development of technology.

    Some policy project ideas to explore are in the following areas:

• NIST’s role in coordinating the U.S. government’s standards development activities
• U.S.-EU Trade and Technology Council (areas of interest include Technology Standards Working Group (WG1) on Digital Identity, Additive Manufacturing, Plastics Recycling, Heavy Duty Charing, etc.)
• Quad (U.S., Australia, Japan, India) Critical and Emerging Technologies Working Group, Standards Sub-group participation.
• NIST’s participation in the International Telecommunications Union - Telecommunication Standardization Sector
  
  Some examples of past projects:
• China’s Changing Standards Infrastructure: A New Approach to the Global Stage
• Harmonizing Standards: Reviewing Military and Law Enforcement PPE Performance Standards
• Development of Standards within ISO/TC 276-Biotechnology
• What is the Meaning of Life? Terminology and Measurement Assurance for Biotechnology Standards
• Harmonizing Standards: Reviewing Military and Law Enforcement PPE Performance Standards
• Development of Standards within ISO/TC 276-Biotechnology
• What is the Meaning of Life? Terminology and Measurement Assurance for Biotechnology Standards

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