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chem-sorption-gcmc

Run BVT/GCMC Monte Carlo adsorption isotherm calculations with MLIPs.

144|21|Updated Jan 8, 2026
Search Tags:#mlip#porous materials#gcmc#adsorption isotherm#grand canonical monte carlo#competitive adsorption
One-click install
npx skills add https://github.com/learningmatter-mit/AtomisticSkills --skill chem-sorption-gcmc
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: chem-sorption-gcmc
Source: https://github.com/learningmatter-mit/AtomisticSkills/tree/main/.agents/skills/chem-sorption-gcmc
Command: npx skills add https://github.com/learningmatter-mit/AtomisticSkills --skill chem-sorption-gcmc

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires ase, ase-mc, numpy, matplotlib, scipy, torch, and includes scripts (resource) and examples (resource) components.

What problem does it solve?

This Skill removes the manual effort of setting up and running adsorption-isotherm simulations for porous materials by automatically executing MLIP-based GCMC calculations and generating uptake/convergence outputs.

Core Features & Use Cases

  • Grand Canonical Monte Carlo (GCMC) for host–guest adsorption in porous frameworks using an MLIP backend (MACE, FairChem, MatGL).
  • Isotherm point predictions for a single gas at a target temperature/pressure, producing molecule-count and energy traces plus a results JSON.
  • Competitive adsorption for a gas mixture via multi-component GCMC to model separation/selectivity at given partial pressures.

Quick Start

Use the chem-sorption-gcmc skill to run a single-component GCMC isotherm point for CO2 at 298 K and 1 bar on a relaxed porous framework CIF file.

Frequently Asked Questions about chem-sorption-gcmc

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I predict gas adsorption isotherms in porous materials using machine learning potentials?▼

You can predict gas adsorption isotherms by running MLIP-based GCMC Monte Carlo simulations on a relaxed framework structure, which calculates host–guest and guest–guest interactions to produce uptake points and energy traces.

Can I simulate competitive adsorption for gas mixtures in porous frameworks?▼

Yes, you can simulate competitive adsorption for gas mixtures by running multi-component GCMC to model separation and selectivity at specified temperatures, partial pressures, and gas compositions.

What input files do I need to run GCMC adsorption calculations?▼

You need a relaxed framework structure in CIF or XYZ format and a supported MLIP calculator with model checkpoints, such as MACE, FairChem, or MatGL, to execute the GCMC adsorption calculations.

Does this GCMC simulation method work with MACE and FairChem calculators?▼

Yes, the GCMC simulation method supports MACE, FairChem, and MatGL as MLIP calculator backends to evaluate host–guest and guest–guest interactions during the Monte Carlo sampling process.

What outputs do I get from an MLIP GCMC isotherm point prediction?▼

MLIP GCMC isotherm point predictions produce trajectory-derived molecule-count and energy traces, convergence checks, and JSON/plot artifacts detailing the adsorption uptake results.

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