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Our Atomistic Line Graph Neural Network (ALIGNN) models are designed to predict atomistic properties with high accuracy. They can successfully predict single
The Polymer Analytics project was established with the goal of accelerating the discovery of new polymer physics through the development of datasets, methods
The integration of Machine Learning (ML) in network modeling and simulations is key to evaluating ML-based solutions and algorithms used to configure and
We are educating the next generation workforce with MGI skills and providing tools to rapidly deploy these skills. This includes knowledge and tools for machine
With increasing use of data-driven methodologies, concerns around data discovery, data access, and data interoperability have come to the forefront. Communities
Computational materials design requires a variety of tools to model processing-structure-property relationships across a range of time and length scales. This
Develop a materials innovation infrastructure for the design and discovery of inorganic materials to reduce the time and cost for deploying new materials into
Many photocrosslinked polymers and composites start with a mixture of low molecular mass / viscosity resins containing one or more reactive functionalities. The
Atomic arrangements underpin the properties of all solids and, as such, are fundamentally important for materials development. The power of computational
This framework provides the generic environment for materials design. The ICME (Integrating Computational Materials Engineering) approach is implemented for
OOF is a collaborative effort between the Information Technology Laboratory and the Material Measurement Laboratory at NIST. The intended audience of the OOF
OpenCalphad (OC) is an informal international collaboration of scientists and researchers interested in the development of high quality software and databases
The Biomaterials Group develops advanced measurement capabilities and measurement assurance strategies for characterizing biomaterials, biological systems, and
An important part of the NIST (National Institute of Science and Technology) MGI (Materials Genome Initiative) effort is to investigate infrastructure and tools
Many computational programs exist that are being used by industry for predicting properties of polymer composites, but their general predictive power is limited