Data and Model Dissemination

Machine Learning in Network Modeling and Simulation

The integration of Machine Learning (ML) in network modeling and simulations is key to evaluating ML-based solutions and algorithms used to configure and

A digital object is composed of Data, Metadata, Protocols & Operations, and Persistent Identifiers.

Facilitating the Adoption of the FAIR Digital Object Framework in Material Science

With increasing use of data-driven methodologies, concerns around data discovery, data access, and data interoperability have come to the forefront. Communities

Developing a Materials Innovation Infrastructure

Develop a materials innovation infrastructure for the design and discovery of inorganic materials to reduce the time and cost for deploying new materials into

Atomistic tools for structure-property investigations

This project provides and develops novel computational infrastructure (i.e. data archives, open-source codes, APIs) that support the design, execution, and

Advanced Materials Design: Electronic and Functional Applications

Using methods such as electronic structure (such as density functional theory, tight-binding, quantum Monte Carlo), force-field, machine-learning and quantum

Strategy for extensible, evolving terminology for MGI efforts

Current terminology used to describe materials data is heterogeneous, redundant, and often ambiguous. The lack of common, community-based terminology hinders

Data Models for Expression of Uncertainty in Materials Data

One of the major goals of the Materials Genome Initiative (MGI) is to facilitate the exchange of materials data to speed material discovery and development. The

Stochastic Network Growth Simulation for Photopolymerization

Photopolymerization, particularly in crosslinked systems, proceeds via a complex reaction-diffusion process. Initiation, propagation (including those leading to

WebFF: Force-field repository for organic and soft materials

The vision of the Materials Genome Initiative (MGI) is a new R&D paradigm enabling accelerated materials development at lower cost via an increased reliance on

Modeling Photon Absorption in Composite Resin Systems

Control over spatial uniformity in a photopolymerized material is important for homogenous physical properties. Unintended spatial variations in polymeric

NIST Materials-focused Empirical Potentials Repositories and Efforts

Because classical empirical potentials/force-fields are widely used to model material behavior via Molecular Dynamics or Monte Carlo simulations, NIST

CALPHAD Data Informatics

The Materials Genome Initiative (MGI) creates a new era of materials innovation that will serve as a foundation for strengthening domestic industries in these

Materials Data Curation System

Semi-Automatic Curation

Lattice constant for AI using various exchange-correlation functionals

DFT Benchmarking

DFT is a widely used computational technique in the material science community and it provides interpretative tools for understanding experimental results as

Materials Data Repository

The NIST Materials Data Repository is open to the research community interested in developing best practices in the management of materials data. We are

Facilitating the Development of Modular Data Models in Materials Science

The Materials Data Curation System has the potential to accelerate interoperable data exchange within materials science and engineering. This platform is

ASM Structural Materials Data Demonstration Project

The ASM Structural Materials Data Demonstration Project SMDDP) is a cooperative research project with the NIST Materials Measurement Laboratory (MML) that is

MGI Code Catalog

The MGI Code Catalog represents an extensive collection of information about software relevant to computational materials science and materials data analysis

Machine Learning for Materials Research: Bootcamps and Workshops

Over the last several years machine learning has gained increased attention in the material science community. The ability to perform high throughput in silico

Computational Design of Photopolymerized Materials

The Biomaterials Group develops advanced measurement capabilities and measurement assurance strategies for characterizing biomaterials, biological systems, and

NIST Materials Resource Registry

Materials Resource Registry allows for the registration of materials resources, bridging the gap between existing resources, software and repositories and end