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Projects/Programs

Displaying 1 - 25 of 27

Classification Methods for the NIST Biorepository

Ongoing
NIST has been archiving biological and environmental specimens, including marine animal and environmental samples, for over 40 years. Currently, these biospecimens are stored at cryogenic temperatures in the NIST Biorepository located at the Hollings Marine Laboratory in Charleston, SC. Various

Climate Science

Ongoing
This program encompasses multifaceted efforts to advance the metrology of climate science. Projects include: development of ultra-high accuracy optical standards and technologies to determine greenhouse gases (GHGs) concentrations, atmospheric lifetimes, and aerosol radiative forcing development of

Consistency Analysis and Uncertainty in ‘omic Data

Ongoing
‘Omics is increasingly moving out of the laboratory and towards use in industrial and commercial applications. For instance, in biomanufacturing, there is a need for quality control when developing biotherapeutics, which will almost certainly require a machine-learning classifier to separate

Density Functional Tight Binding Methods

Presently the study by quantum chemistry techniques of large (several thousands of atoms) molecular systems is limited by large computer time and space (memory, disk) requirements. The required time, memory, and disk space to solve the requisite equations typically increase exponentially with the

Explosives Decomposition Chemistry

Completed
Intended Impact Computational modeling and simulation will help in the invention of new explosives, the design of compounded mixtures of existing materials, and the engineering of delivered systems such as military ordnance. Objective Detailed chemistry is a necessary part of computational

Free Energy and Advanced Sampling Simulation Toolkit (FEASST)

Ongoing
Intended Impact While flat-histogram Monte Carlo simulations have been shown to be a promising method for the direct calculation of complex fluid phase behavior with a variety of applications, most open-source Monte Carlo simulation packages do not support this method. We have therefore made FEASST

Machine Learning Fluid Equations of State

Ongoing
Understanding the thermodynamic properties of fluids and fluid mixtures is of central importance in many fields of science and engineering ranging from medicine to consumer products. The nature of the particles in a fluid can vary greatly depending on the type of interactions present, e.g., dipole

Machine Learning to Predict Food Provenance

Ongoing
Adulteration of food and food products is a pernicious problem which is difficult to solve as supply chains and international trade routes become increasingly complex; yet agriculture contributed over $1 trillion to the US GDP in 2017, [1] illustrating the importance of protecting this and related

Machine Learning to Predict Multicomponent Colloidal Crystals

Ongoing
There is a direct link between a material’s macroscopic properties and its microscopic structure, which makes rational bottom-up self-assembly a powerful tool for engineering properties of materials. In general, colloids are facile material building blocks whose shape, charge, and surface

METIS

Ongoing
A Metrology Exchange to Innovate in Semiconductors

NIST Data Resources for Adsorption

Ongoing
NIST/ARPA-e Database of Novel and Emerging Adsorbent Materials A centralized resource for the scientific community to find and compare single- and multi-component adsorption isotherms reported in the literature. The database sorts data according to adsorbent material, adsorbate species

NIST Standard Reference Simulation Website

Ongoing
Molecular simulations, in particular Monte Carlo Molecular Simulation and Molecular Dynamics Simulation, are methods for computing the properties of some kind of system, for which the intermolecular interactions are specified via mathematical relationships derived from statistical mechanics. Since

Per- and Polyfluoroalkyl Substances (PFAS)

Ongoing
Perfluorinated and polyfluorinated alkyl substances (PFAS) constitute a family of compounds that are distinguished by partial or complete fluorination of alkyl hydrocarbons. Dubbed “forever chemicals”, the unique chemistry of PFAS imparts a high level of stability, making the compounds resistant to

Prediction of Global Warming Potential

Ongoing
Goals Use ANN models to fit RF and .OH rate constant data k(.OH). Be able to predict RF, k(.OH), and GWP with reasonable accuracy using readily available information. Create a screening tool based on the ANNs.  Research Activities Improve the performance of rate constant prediction. Compare rate

Reactivity of Nanoparticle Catalysts

Ongoing
Goals: Provide mechanisms for various prototypical electrocatalytic reactions on different metallic surfaces an nanoparticles. Validate the results of DFT calculations versus experimental data. Research Activities: Studying the methanol oxidation reaction on Pt and PtRu surfaces. Studying the effect

Solvation Thermodynamics

Ongoing
Solvation thermodynamics data are essential in the characterization and interpretation of any process carried out in the liquid phase. The data have application in the study of biochemical processes such as protein folding and protein-protein association in aqueous fluids and are useful as

Theoretical Mass Spectrometry

Ongoing
No Description Intended Impact Unknown compounds will be identified more reliably. Quality control for the NIST Mass Spectrometry Database will be enhanced. Goals Develop software tools for predicting microcanonical branching fractions automatically. This is currently too laborious and too technical

Thermodynamics of ATP in Solution

Goals: Demonstrate the validity of DFT methods for computing thermodynamics of biomolecules in solution. Identify new families of biomolecules for further study. Research Activities: Seek improvements to the present methodology to improve results and reduce uncertainties.

Understanding Protein Solution Phase Behavior via Coarse-Grained Modeling

Ongoing
Intended Impact Because biological systems span a broad range of length and time scales, they cannot be studied effectively using conventional all-atom simulations. While hardware advances represent one route to improving the computational tractability of simulating biological systems, significant