# Queryable Gaseous Adsorption Properties of Pure Components and Mixtures in Metal–Organic Frameworks

## TL;DR

This paper introduces a new database for predicting gas adsorption in metal-organic frameworks under various conditions, enabling faster material screening and separation analysis.

## Contribution

A novel MPD-based adsorption database that allows reweighting to any pressure and temperature conditions and supports mixture isotherms via IAST.

## Key findings

- MPD-based database enables instant adsorption predictions for CO2, N2, CH4, and CO in 2900 MOFs.
- Database supports mixture isotherms for multicomponent separations using IAST.
- Structure-performance relationships for separation behavior are uncovered efficiently.

## Abstract

Grand canonical Monte
Carlo (GCMC) has been the most common simulation
method for high-throughput screening of metal–organic frameworks
(MOFs) in adsorption applications. However, GCMC results are inevitably
limited to specific pressure and temperature conditions, limiting
their applicability across the varying conditions in industrial operations.
To address this, we develop a macrostate-probability-distribution-based
(MPD-based) adsorption database for several key gas molecules (i.e.,
CO2, N2, CH4, and CO) in approximately
2900 rigid MOF structures. Crucially, MPD computed from flat histogram
Monte Carlo can be analytically reweighted to any pressures and temperatures,
enabling instant access to adsorption uptakes under any desired conditions.
By integrating the ideal adsorbed solution theory (IAST), the database
also provides mixture isotherms at user-defined compositions to allow
efficient assessment of multicomponent separations. With the MPD-based
database, we demonstrate its capability in rapid screening and uncovering
structure-performance relationships that govern separation behavior
under different operational conditions. Overall, by employing MPD,
we present a versatile and interactive adsorption database to facilitate
the future discovery of optimal MOFs.