Published November 13, 2024 | Version 2.0.0
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3d Transition Metal K-edge XANES Dataset for Machine Learning Models

  • 1. ROR icon Brookhaven National Laboratory
  • 2. ROR icon Clemson University

Description

Data

This dataset contains machine learning data for K-edge X-ray Absorption Near-Edge Structure (XANES) prediction models for eight 3d transition metals (Ti -Cu).

  • features_and_spectra: Material features (X) and corresponding XAS spectra (y) for each dataset split: training (train), validation (val), and test.
  •  material_id_and_site: Material identifiers and site indices (according to Lightshow) for each dataset split. 

Funding

This research is based upon work supported by the U.S. Department of Energy, Office of Science, Office Basic Energy Sciences, under Award Number FWP PS-030. This research also used theory and computational resources of the Center for Functional Nanomaterials, which is a U.S. Department of Energy Office of Science User Facility, and the Scientific Data and Computing Center, at Brookhaven National Laboratory under Contract No. DE-SC0012704 and by Brookhaven National Laboratory (BNL), Laboratory Directed Research and Development (LDRD) grant no. 24-004.

 

Files

Files (160.1 MB)

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md5:c9eebebe312b3cfc9699a6c78a4d0664
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Additional details

Dates

Available
2024-11-13

Software

Repository URL
https://github.com/AI-multimodal/OmniXAS
Development Status
Active