AdsorPy: Lattice-Based Random Sequential Adsorption Simulations for Molecular Packing

AdsorPy is a Python package for simulating the random packing of molecular shapes on a surface. The script performs lattice-based random sequential adsorption (RSA) simulations to provide quantitative data on packing density and arrangement, which are critical for processes like area-selective atomic layer deposition in semiconductor manufacturing. The package was authored by Joost F. W. Maas and last updated on June 3, 2026.

Use Cases

• Simulating molecular packing density and arrangement on crystalline surfaces based on the described RSA methodology.
• Informing inhibitor species selection for area-selective atomic layer deposition processes based on simulated packing properties.
• Integrating simulation results with other computational methods like density functional theory calculations as mentioned in the description.
• Matching simulation conditions to experimental dosing schemes as demonstrated in the provided case scenarios.

Strengths

• The package is specifically designed for lattice-based RSA simulations, a method described as key for investigating molecular adsorption.
• It provides easy integration with other computational methods used in material science, such as density functional theory.
• The package file size is 810.7 KB, making it lightweight and quick to download.

Limitations

• The dataset's row count and specific column structure are unknown, limiting suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The license is CC-BY-NC-4.0, which restricts commercial use.

Provenance

Source

figshare

Collection Method

Simulation output from a Python package performing lattice-based random sequential adsorption calculations.

Freshness

Last updated 2026-06-03 23:44:06