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
Collect adsorption isotherm data from the NIST/ARPA-E Database
Fit temperature-dependent isotherms to equilibrium data.
Automatically applies betsi criteria to a group of isotherms, and doesn't give up!
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
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