AIMD Trajectory: CO2 Electroreduction Simulations for Single Atom Catalysts

423.7 MB of source data and trajectory files supporting a manuscript on CO2 electroreduction. The data was authored by YUXIAO MENG and last updated on May 15, 2026. It is shared under a CC-BY-4.0 license on figshare.

Use Cases

• Training machine learning models for catalyst property prediction based on trajectory data.
• Validating ab initio molecular dynamics (AIMD) simulation methods for electrochemical interfaces.
• Analyzing the decoupling of intrinsic and external contributions to catalytic activity as described in the manuscript.
• Benchmarking computational workflows for single atom catalyst design.

Strengths

• The 423.7 MB size suggests a substantial volume of simulation data.
• The data is directly linked to a peer-reviewed manuscript, providing research context.
• It is shared under a permissive CC-BY-4.0 license for reuse.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• The row count is unknown, which may limit suitability assessment for specific tasks.

Provenance

Source

YUXIAO MENG

Collection Method

Likely generated via ab initio molecular dynamics (AIMD) simulations.

Freshness

Last updated 2026-05-15 06:30:05