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Search Publications by: Howie Joress (Fed)

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Displaying 1 - 22 of 22

Workshop Report on Autonomous Methodologies for Accelerating X-ray Measurements

November 5, 2024
Author(s)
Zachary Trautt, Austin McDannald, Brian DeCost, Howard Joress, A. Gilad Kusne, Francesca Tavazza, Tom Blanton
The National Institute of Standards and Technology and the International Centre for Diffraction Data co-hosted a workshop on 17-18 October 2023 to identify and prioritize the goals, challenges, and opportunities for critical and emerging technology needs

Microstructure and mechanical properties of laser powder bed fusion Ti-6Al-4V after HIP treatments with varied temperatures and cooling rates

October 22, 2024
Author(s)
Nicholas Derimow, Jake Benzing, Howard Joress, Austin McDannald, Ping Lu, Frank DelRio, Newell Moser, Matthew Connolly, Alec Saville, Orion Kafka, Chad Beamer, Ryan Fishel, Chris Hadley, Nikolas Hrabe
This work investigated non-standard HIP cycles for PBF-L Ti-6Al-4V and characterized microstructure and tensile properties to compare between material that originated from the same build. For 920 °C, faster cooling rates (100 °C/min, 2000 °C/min) were

Driving U.S. Innovation in Materials and Manufacturing using AI and Autonomous Labs

August 14, 2024
Author(s)
Howie Joress, Zachary Trautt, Austin McDannald, Brian DeCost, A. Gilad Kusne, Francesca Tavazza
With the goal of advancing US competitiveness and excellence in the materials and manufacturing industries, we present our vision for the National Center for Autonomous Materials Science. The objective of this center is to enable and promote the use of

Autonomous cementitious materials formulation for critical infrastructure repair

January 17, 2024
Author(s)
Howie Joress, Rachel Cook, Austin McDannald, Mark Kozdras, Jason hattrick-simpers, Aron Newman, Scott Jones
Despite the long history of cement and concrete, there are still large gaps in fundamental knowledge of their properties development. The dire need for improved cementitious repair materials, requires a revolution in the way they are formulated and tested

Flexible formulation of value for experiment interpretation and design

December 12, 2023
Author(s)
Matthew Carbone, Hyeong Jin Kim, Chandima Fernando, Shinjae Yoo, Daniel Olds, Howie Joress, Brian DeCost, Bruce D. Ravel, Yugang Zhang, Phillip Michael Maffettone
The challenge of optimal design of experiments pervades materials science, physics, chemistry, and biology. Bayesian optimization has been used to address this challenge but requires framing experimental campaigns through the lens of maximizing some

Understanding and Leveraging Short Range Order in Compositionally Complex Alloys

November 20, 2023
Author(s)
Mitra Taheri, Elaf Anber, Annie Barnett, Nick Birbilis, Brian DeCost, Daniel Foley, Emily Holcombe, Jonathan Hollenbach, Howie Joress, Yevgeny Rakita, James Rondinelli, Nathan Smith, Michael Waters, Chris Wolverton
In this article, we review the opportunities and challenges associated with complex concentrated materials that exhibit short-range order. Although the presence of such phenomena has been theorized, accurate computational representation, characterization

An Experimental High-Throughput to High-Fidelity Study Towards Discovering Al-Cr Containing Corrosion-Resistant Compositionally Complex Alloys.

November 8, 2023
Author(s)
Debashish Sur, Emily Holcombe, William Blades, Daniel Foley, Brian DeCost, Elaf Anber, Jason Hattrick-Simpers, Karl Sieradzki, Howie Joress, John Scully, Mitra Taheri
Compositionally complex alloys hold the promise of simultaneously attaining superior combinations of properties, such as corrosion resistance, light-weighting, and strength. Achieving this goal is a challenge due in part to a large number of possible

What is missing in autonomous discovery: Open challenges for the community

October 16, 2023
Author(s)
Philip Maffetone, Howie Joress, Shijing Sun
Self-driving labs (SDLs) leverage combinations of artificial intelligence, automation, and advanced computing to accelerate scientific discovery. The promise of this field has given rise to a rich community of passionate scientists, engineers, and social

Why is EXAFS for complex concentrated alloys so hard? Challenges and opportunities for measuring ordering with X-ray absorption spectroscopy

October 16, 2023
Author(s)
Howie Joress, Bruce D. Ravel, Elaf Anber, Jonathan Hollenbach, Debashish Sur, Mitra Taheri, Brian DeCost
Short-range order (SRO) is a critical driver of properties (e.g., corrosion resistance and tensile strength) in multicomponent alloys such as complex concentrated alloys (CCAs). Extended X-ray absorption fine structure (EXAFS) is a powerful technique well

Self-driving Multimodal Studies at User Facilities

January 22, 2023
Author(s)
Bruce D. Ravel, Phillip Michael Maffettone, Daniel Allan, Stuart Campbell, Matthew Carbone, Brian DeCost, Howie Joress, Dmitri Gavrilov, Marcus Hanwell, Joshua Lynch, Stuart Wilkins, Jakub Wlodek, Daniel Olds
Multimodal characterization is commonly required for understanding materials. User facilities possess the infrastructure to perform these measurements, albeit in serial over days to months. In this paper, we describe a unified multimodal measurement of a

Reproducible Sorbent Materials Foundry for Carbon Capture at Scale

September 22, 2022
Author(s)
Austin McDannald, Howie Joress, Brian DeCost, Avery Baumann, A. Gilad Kusne, Kamal Choudhary, Taner N. Yildirim, Daniel Siderius, Winnie Wong-Ng, Andrew J. Allen, Christopher Stafford, Diana Ortiz-Montalvo
We envision an autonomous sorbent materials foundry (SMF) for rapidly evaluating materials for direct air capture of carbon dioxide ( CO2), specifically targeting novel metal organic framework materials. Our proposed SMF is hierarchical, simultaneously

Development of an automated millifluidic platform and data-analysis pipeline for rapid electrochemical corrosion measurements: a pH study on Zn-Ni

July 25, 2022
Author(s)
Howie Joress, Brian DeCost, Najlaa Hassan, Trevor Braun, Justin Gorham, Jason Hattrick-Simpers
We describe the development of a millifluidic based scanning droplet cell platform for rapid and automated corrosion. This system allows for measurement of corrosion properties (e.g., open circuit potential, corrosion current through Tafel and linear

Demonstration of a laser powder bed fusion combinatorial sample for high-throughput microstructure and indentation characterization

August 3, 2021
Author(s)
Jordan Weaver, Adam L. Pintar, Carlos R. Beauchamp, Howard Joress, Kil-Won Moon, Thien Q. Phan
High-throughput experiments that use combinatorial samples with rapid measurements can be used to provide process-structure-property information at reduced time, cost, and effort. Developing these tools and methods is essential in additive manufacturing

An Open Combinatorial Diffraction Dataset Including Consensus Human and Machine Learning Labels with Quantified Uncertainty for Training New Machine Learning Models

June 9, 2021
Author(s)
Jason Hattrick-Simpers, Brian DeCost, Aaron Gilad Kusne, Howard Joress, Winnie Wong-Ng, Debra Kaiser, Andriy Zakutayev, Caleb Phillips, Tonio Buonassisi, Shijing Sun, Janak Thapa
Modern machine learning and autonomous experimentation schemes in materials science rely on accurate analysis of the data ingested by these models. Unfortunately, accurate analysis of the underlying data can be difficult, even for domain experts

Exploring the First High Entropy Thin Film Libraries: Composition spread-controlled Crystalline Structure

March 19, 2021
Author(s)
Thi X. Nguyen, Yen-Hsun Su, Jason Hattrick-Simpers, Takahiro Nagata, Howard Joress, Kao-Shuo Chang, Suchismita Sarker, Apurva Mehta, Jyh-Ming Ting
Thin films of two types of high-entropy oxides (HEOs) have been deposited on 76.2 mm Si wafers using combinatorial sputter deposition. In one type of the oxides, (MgZnMnCoNi)Ox, all the metals have a stable divalent oxidation state and similar cationic

{A high-throughput structural and electrochemical study of metallic glass formation in Ni-Ti-Al

June 4, 2020
Author(s)
Howard L. Joress, Brian L. DeCost, Suchismita Sarker, Trevor M. Braun, Logan T. Ward, Kevin Laws, Apurva Mehta, Jason R. Hattrick-Simpers
Based on a set of machine learning predictions of glass formation in the Ni-Ti-Al system, we have undertaken a high-throughput experimental study of that system. We utilized rapid synthesis followed by high- throughput structural and electrochemical

APPLICATIONS OF HIGH-THROUGHPUT SCREENING TOOLS FOR THERMOELECTRIC MATERIALS

June 21, 2011
Author(s)
Winnie K. Wong-Ng, Howard L. Joress, Joshua B. Martin, Yonggao Y. Yan, Jihui Yang, Makoto Otani, Evan L. Thomas, Martin L. Green, Jason Hattrick-Simpers
The increased research and development on thermoelectric materials in recent years has been driven primarily by the need for improved efficiency in the global utilization of energy resources. To facilitate the search for new thermoelectric materials, we