• Organization: National Institute of Standards and Technology
• Updated: 2024-02-07 00:00:00

Graph neural networks (GNN) have been shown to provide substantial performance improvements for atomistic material representation and modeling compared with descriptor-based machine learning...

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• Organization: National Institute of Standards and Technology
• Updated: 2024-08-27 00:00:00

This dataset consists of characterization of telechelic functional polyethylene oligomers, precursors, and resultant step-growth polyethylene with urethane-linkages between segments of different...

• Organization: National Institute of Standards and Technology
• Updated: 2016-10-01 00:00:00

The NIST Computational Chemistry Comparison and Benchmark Database is a collection of experimental and ab initio thermochemical properties for a selected set of gas-phase molecules. The goals are...

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• Organization: National Institute of Standards and Technology
• Updated: 2018-10-19 00:00:00

Materials discovery and development necessarily begins with the preparation and identification of product phase(s). Crystalline compounds can be identified by their characteristic diffraction...

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