Modeling & computational material science

News and Updates

Side-by-side photos show twin brothers posing with arms crossed in lab or office settings.

Spotlight: Two Brothers, One Passion for Mechanical Engineering

September 20, 2022

This is a tale of two brothers who both found a passion for mechanical engineering research, separated to pursue their own interests in graduate school, and

Illustrated cube has crystal framework in gray with red balls interspersed in the open spaces.

To Remove CO₂ From the Atmosphere, Imagine the Possibilities

August 24, 2022

Computer simulation methods from NIST help speed up the search for carbon capture materials.

Race Logic: Novel Circuitry Solves a Myriad of Computationally Intensive Problems With a Minimum of Energy

May 11, 2021

From the branching pattern of leaf veins to the variety of interconnected pathways that spread the coronavirus, nature thrives on networks — grids that link the

Projects and Programs

Measuring Intermolecular Interactions with Electro-Acoustic Spectroscopy

Ongoing

NIST’s Material Measurement Laboratory and Communications Technology Laboratory are developing a new spectroscopy for intermolecular interactions. The team is

Polymer Analytics

Ongoing

The Polymer Analytics project was established with the goal of accelerating the discovery of new polymer physics through the development of datasets, methods

JARVIS-ML

Ongoing

JARVIS-ML is a repository of machine learning (ML) model parameters, descriptors, and ML related input and target data. JARVIS-ML is a part of the NIST-JARVIS

Advanced Materials Design: Electronic and Functional Applications

Ongoing

Using atomistic-level calculations (density functional theory and classical molecular dynamics), this project aims at increasing our knowledge of electronic and

Publications

Unified graph neural network force-field for the periodic table: solid state applications

February 23, 2023

Author(s)

Kamal Choudhary, Brian DeCost, Lily Major, Keith Butler, Jeyan Thiyagalingam, Francesca Tavazza

Classical force fields (FFs) based on machine learning (ML) methods show great potential for large scale simulations of solids. MLFFs have hitherto largely been

Community Resource for Innovation in Polymer Technology (CRIPT): A Scalable Polymer Material Data Structure

February 20, 2023

Author(s)

Dylan Walsh, Weizhong Zou, Ludwig Schneider, Reid Mello, Michael Deagen, Joshua Mysona, Tzyy-Shyang Lin, Juan de Pablo, Klavs Jensen, Debra Audus, Bradley Olsen

Polymeric materials are integral components of nearly every aspect of modern life. However, developing cheminformatic solutions for polymers has been difficult

Efficient Computational Design of 2D van der Waals Heterostructures: Band-Alignment, Lattice-Mismatch, Web-app Generation and Machine-learning

February 13, 2023

Author(s)

Kamal Choudhary, Kevin Garrity, Francesca Tavazza, Ghanshyam Pilania

We develop a computational database, web-apps and machine-learning (ML) models to accelerate the design and discovery of two-dimensional (2D)-heterostructures

Designing High-Tc Superconductors with BCS-inspired Screening, Density Functional Theory and Deep-learning

February 13, 2023

Author(s)

Kamal Choudhary, Kevin Garrity

Recent advances in first principles calculations and machine learning techniques allow a systematic search for phonon-mediated superconductors. We develop a

Modeling & computational material science

News and Updates

Spotlight: Two Brothers, One Passion for Mechanical Engineering

To Remove CO₂ From the Atmosphere, Imagine the Possibilities

Race Logic: Novel Circuitry Solves a Myriad of Computationally Intensive Problems With a Minimum of Energy

Projects and Programs

Measuring Intermolecular Interactions with Electro-Acoustic Spectroscopy

Polymer Analytics

JARVIS-ML

Advanced Materials Design: Electronic and Functional Applications

Publications

Unified graph neural network force-field for the periodic table: solid state applications

Community Resource for Innovation in Polymer Technology (CRIPT): A Scalable Polymer Material Data Structure

Efficient Computational Design of 2D van der Waals Heterostructures: Band-Alignment, Lattice-Mismatch, Web-app Generation and Machine-learning

Designing High-Tc Superconductors with BCS-inspired Screening, Density Functional Theory and Deep-learning

Software

NANOP

BBEST Bayesian Estimation of Incoherent Neutron Scattering Backgrounds

RMCPROFILE

GSAS_USE (Bayesian Statistics Approach to Accounting for Unknown Systematic Errors)