MD Trajectories for Metal-Zeolite Adsorption Studies with ML Potentials

Molecular dynamics trajectory data from a study combining electronic structure methods and machine learning interatomic potentials for adsorption research. The ZIP archive contains trajectories from AIMD and MLIP-based MD simulations for a FAU-type zeolite with metal cations, adsorbed mercaptopurine, and co-adsorbed water. The data was authored by Sujon Kumar Mitro and uploaded to figshare in May 2026.

Use Cases

• Benchmarking MLIP model performance based on trajectories from eSEN-MP, MACE-MP, and orb-MPA models mentioned in the description
• Analyzing adsorption dynamics of mercaptopurine on metal-zeolite systems based on the described simulation conditions
• Studying the effect of co-adsorbed water molecules on adsorption based on trajectories labeled with '32H2O'
• Comparing short (12.5 ps) and long (1.5 ns) simulation timescales based on the eSEN-MP folder contents

Strengths

• Includes long-timescale trajectories covering 1.5 nanoseconds, which may capture rare events
• Provides comparative data from four distinct simulation methods (AIMD, eSEN-MP, MACE-MP, orb-MPA)
• Simulations are conducted at a controlled temperature of 298 K, enabling consistent thermodynamic comparisons

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment
• Description metadata is limited; actual data quality requires manual inspection after download

Provenance

Source

figshare

Collection Method

Data generated from ab initio molecular dynamics (AIMD) and machine learning interatomic potential (MLIP) based molecular dynamics simulations.

Freshness

Last updated 2026-05-28 13:05:48; freshness should be verified