GOMC - GPU Optimized Monte Carlo is a parallel molecular simulation code designed for high-performance simulation of large systems
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Updated
May 23, 2025 - C++
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
AIM (Adsorption Integrated Modules) is a collection of MATLAB based GUI modules for adsorption isotherm based fixed bed process modelling
Fluid dynamics for chemical applications
Collect adsorption isotherm data from the NIST/ARPA-E Database and train a ML model to predict uptake from pressure
Automatically applies betsi criteria to a group of isotherms, and doesn't give up!
Fit temperature-dependent isotherms to equilibrium data.
for adsorption related research
Model hydrogen adsorption on the surface of nanostructures based on the “Random rain” algorithm
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
HTA磁吸多窗口模板
Numerical implementation of the Multicomponent Potential Theory of Adsorption in Python
R package for processing isotherm experiment data & predicting sorption processes using empirical models.
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