Aspirin, Water, and H₂ Combustion Molecular Dynamics Data and Models for ML Potentials

A 6.7 GB repository of datasets, trained models, and simulation scripts for molecular dynamics and metadynamics. The data spans three chemical systems—aspirin, water, and H₂ combustion reactions—and includes training, sampling, and simulation workflows. Author Eric Yuan uploaded the collection to figshare in April 2026 under a CC-BY-4.0 license.

Use Cases

• Benchmarking machine learning interatomic potentials based on the described training and fine-tuning strategies.
• Running molecular dynamics simulations on aspirin and water systems using the provided Python scripts and NewtonNet-trained models.
• Conducting metadynamics simulations on H₂ combustion reactions using the included PLUMED-driven input files and trajectories.
• Generating diverse molecular configurations via rattled sampling for aspirin, water, and H₂ combustion systems.

Strengths

• Data spans three distinct chemical systems: aspirin, water, and H₂ combustion reactions.
• Includes trained NewtonNet models, simulation scripts, and analysis notebooks alongside raw data.
• Total size is 6.7 GB, indicating substantial simulation outputs and model files.

Limitations

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

Provenance

Source

figshare

Collection Method

Likely generated from computational chemistry simulations and machine learning model training.

Time Range

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Freshness

Last updated 2026-04-16 23:21:37; freshness should be verified.

Geography

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