Multi-scale design of MOF-based membrane separation for CO₂/CH₄ mixture via integration of molecular simulation, machine learning and process modeling and simulation

Keyphrases

• Activation Energy 33%
• Adsorption Capacity 33%
• Adsorption Isotherm 33%
• Artificial Neural Network 33%
• Artificial Neural Network Model 33%
• CO2 Capture 33%
• CO2 Permeation 33%
• CO2-CH4 Separation 33%
• Coefficient of Determination 33%
• Design Framework 33%
• Finite Volume Method 33%
• High Efficiency 33%
• High Porosity 33%
• High Surface Area 33%
• Hollow Fiber Membrane 33%
• IRMOF-1 33%
• Isosteric Adsorption Heat 33%
• Isotherm 33%
• Machine Learning Modeling 100%
• Machine Learning Techniques 33%
• Machine Process 100%
• Mean Squared Error 33%
• Membrane Separation 100%
• Metal-organic Framework Membrane 33%
• Metal-organic Frameworks (MOFs) 100%
• Molecular Simulation 100%
• Multiscale Design 100%
• Open Metal Sites 33%
• Operating Conditions 66%
• Pore Size 33%
• Prediction Model 33%
• Process Modeling 100%
• Process Simulation 100%
• Selective Activation 33%
• Self-diffusivity 66%
• Simulation Machine 100%
• Tanks-in-series Model 33%

Engineering

• Activation Energy 33%
• Adsorption 66%
• Adsorption Capacity 33%
• Artificial Neural Network 33%
• Artificial Neural Network Model 33%
• Carbon Dioxide Capture 33%
• Diffusivity 66%
• Experimental Result 33%
• Finite Volume Method 33%
• High Surface Area 33%
• Hollow-Fiber Membrane 33%
• Illustrates 33%
• Machine Learning Method 33%
• Mean-Squared-Error 33%
• Membranes Separation 100%
• Methane 100%
• Multiscale 100%

Chemical Engineering

• Adsorption 50%
• Adsorption Isotherm 25%
• Diffusion 50%
• Learning System 100%
• Membranes Separation 100%
• Metal-Organic Frameworks 100%
• Methane 100%
• Neural Network 50%