Datasets:

knc6
/

diffractgpt_dft

license: mit
task_categories:
  - text-generation
language:
  - en
tags:
  - materials
  - xrd
  - diffraction
  - crystal-structure
  - inverse-design
  - jarvis
pretty_name: DiffractGPT-DFT (XRD to crystal structure)

DiffractGPT-DFT

Alpaca-format dataset for the inverse powder-XRD problem: given a chemical formula and the main 2-theta peaks of a Cu-K-alpha pattern, generate the crystal structure. 73,374 train / 8,152 validation structures from JARVIS-DFT dft_3d. Same text format as knc6/diffractgpt_jarvis_dft, rebuilt on a fixed split used to benchmark multiple base LLMs for XRD-to-structure.

Record format (4 fields)

field	content
`instruction`	`Below is a description of a material.`
`input`	formula + top-20 XRD peaks `<2theta>deg(<rel intensity>)` + a request for the structure
`id`	JARVIS identifier
`output`	`a b c` (A) / `alpha beta gamma` (deg) / one `Element x y z` line per atom

Models: https://huggingface.co/knc6/diffractgpt_dft_models ; code: https://github.com/atomgptlab/diffractgpt ; underlying data: JARVIS-DFT (https://doi.org/10.1038/s41524-020-00440-1).