Diffraction Patterns and DFT Data for Materials Analysis

DiffractGPT and JARVIS DFT data provides information for materials science and computational chemistry. The dataset, created by author 'crhysc', was last updated in March 2026. It is hosted on Hugging Face and includes parquet files optimized for efficient data processing.

Use Cases

• Predict material properties from diffraction pattern features using regression models.
• Classify crystal structures based on calculated Density Functional Theory (DFT) parameters.
• Train generative models to propose new materials by learning from structural and electronic feature correlations.

Strengths

• Dataset is hosted in an optimized parquet format for fast loading and processing.
• Last update was in March 2026, indicating recent maintenance.

Limitations

• Specific row count, column names, and data size are unknown.
• The scope and completeness of the DFT calculations and diffraction data are unclear.

Provenance

Source

Hugging Face, author crhysc.

Collection Method

Likely compiled from computational chemistry simulations (e.g., JARVIS-DFT) and associated analyses.

Freshness

Last updated 2026-03-07.

Geography

Region tags suggest a US focus, but specific geography is unknown.