Chem Sorption Widom

chem-sorption-widom

Goal

To determine the initial affinity of a porous material (e.g., MOFs, COFs) for a specific gas molecule at infinite dilution. This is done by computing the Henry coefficient ($KH$) and the isosteric heat of adsorption ($\Delta H{ads}$) using Widom insertion, calculating interaction energies with a generic Machine Learning Interatomic Potential (MLIP) such as MACE, FairChem, or MatGL.

Prerequisites

• Input: A relaxed framework structure in CIF (or XYZ) format. The structure should ideally be processed by [chem-sorption-relax](../chem-sorption-relax/SKILL.md) to ensure proper supercell dimensions.
• Conda environment: Depends on the MLIP used (e.g., fairchem-agent, mace-agent, matgl-agent).

Instructions

1. Perform Widom Insertion: Use the run_widom.py script, specifying the structure, gas, temperature, and your MLIP of choice.

# Env: fairchem-agent (if using fairchem), mace-agent (if using mace), etc.
python .agents/skills/chem-sorption-widom/scripts/run_widom.py \
    --structure path/to/relaxed_supercell.cif \
    --name MY_FRAMEWORK \
    --calculator fairchem \
    --model-name uma-s-1p2 \
    --task-name omol \
    --gas CO2 \
    --temperature 298 \
    --output-dir ./results

Parameters

• --structure: Path to the relaxed host framework (must be large enough, see [Constraints](#constraints)).
• --name: Identifier for the output files.
• --calculator: The backend MLIP (fairchem, mace, matgl).
• --model-name: Name or path to the MLIP weights (e.g., uma-s-1p1.pt, MACE-MH-1).
• --task-name: Optional, but highly recommended for multi-task models (e.g., omol for FairChem UMA and MACE-MH).
• --gas: The adsorbate gas (e.g., CO2, N2, CH4).
• --temperature: Temperature in Kelvin.
• --num-insertions: Number of Monte Carlo insertion attempts (default: 50,000).
• --output-dir: Directory to save the widom_results.json.

Examples

Example 1: Using FairChem UMA-S-1p2 for CO2 adsorption at 298K

# Env: fairchem-agent
python .agents/skills/chem-sorption-widom/scripts/run_widom.py \
    --structure ./results/COF-1_supercell.cif \
    --name COF-1 \
    --calculator fairchem \
    --model-name uma-s-1p2 \
    --task-name omol \
    --gas CO2 \
    --temperature 298 \
    --output-dir ./results

Constraints

• Cell Size: The periodic boundary conditions of the framework must be large enough ($> 12$ Å minimum interplanar distance) to prevent artificial self-interactions of the inserted gas molecules across boundaries. It is highly recommended to use [chem-sorption-relax](../chem-sorption-relax/SKILL.md) first.
• Statistical Noise: Increasing --num-insertions (e.g., to 100,000) improves the convergence of $KH$ and $\Delta H{ads}$, at the cost of increased computation time.
• Model Compatibility: Ensure the selected MLIP and its corresponding task-name are suitable for non-covalent interactions (e.g., omol for UMA, or dispersion-corrected MACE/MatGL models).

---

Author: Artur Lyssenko Contact: GitHub @arturlyssenko12

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: learningmatter-mit
• Source: learningmatter-mit/AtomisticSkills
• License: MIT
• Homepage: https://arxiv.org/abs/2605.24002

Install and usage instructions live in the source repository linked above.