GOMC - GPU Optimized Monte Carlo is a parallel molecular simulation code designed for high-performance simulation of large systems

A framework for processing adsorption data and isotherm fitting

GPU Monte Carlo Simulation Code with a taste of RASPA

Input script for Monte Carlo (GCMC) simulations

A machine learning model based on gradient boosting decision tree for predicting heavy metal adsorption in soil.

BET surface area analysis from adsorption data

An Active learning algorithm for multi-component adsorption prediction in MOF

Fluid dynamics for chemical applications

Fit temperature-dependent isotherms to equilibrium data.

Automatically applies betsi criteria to a group of isotherms, and doesn't give up!

Collect adsorption isotherm data from the NIST/ARPA-E Database

HTA磁吸多窗口模板

for adsorption related research

A collection of Python code used for carbon dioxide adsorption analysis

Streamline the process of adsorption modeling for researchers, by automating the fitting of theoretical adsorption models to empirical isotherm data

Model hydrogen adsorption on the surface of nanostructures based on the “Random rain” algorithm

R package for processing isotherm experiment data & predicting sorption processes using empirical models.

TPD and prefactor BE functions and library

Numerical implementation of the Multicomponent Potential Theory of Adsorption in Python