High-Throughput DFT Screening of Double Transition Metal MXene Precursors

Density functional theory results for a set of double-transition metal MXene precursors. The dataset was contributed by Kat Nykiel from Purdue University West Lafayette and is available via the paperswithcode platform. The specific size, temporal coverage, and last update date are not provided in the input.

Use Cases

• Predicting material stability based on DFT-calculated properties
• Screening candidate MXene precursors for electronic applications
• Training machine learning models for materials discovery using DFT results
• Analyzing structure-property relationships in double transition metal systems

Strengths

• Data is derived from density functional theory, a foundational computational chemistry method
• Focuses on double-transition metal MXenes, a specific and active research area

Limitations

• Row count and dataset scale are unknown, which may limit suitability assessment
• Column-level documentation is absent; field semantics must be inferred after download
• Last update date is unknown; freshness unverified

Provenance

Source

Kat Nykiel, Purdue University West Lafayette

Collection Method

Computational results from density functional theory screening