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Generalized, Adsorbent-Agnostic, Artificial Neural Network Framework for Rapid Simulation, Optimization, and Adsorbent Screening of Adsorption Processes
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/aic.14435openalex-snapshot
CO 2 capture from dry flue gas by vacuum swing adsorption: A pilot plant study
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Measurement of competitive CO2 and N2 adsorption on Zeolite 13X for post-combustion CO2 capture
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On the use of the dual process Langmuir model for binary gas mixture components that exhibit single process or linear isotherms
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Surrogate based Optimisation for Design of Pressure Swing Adsorption Systems
inferredcites →https://doi.org/10.1016/c2013-0-04269-7openalex-snapshot
Gas Separation by Adsorption Processes
inferredcites →https://doi.org/10.1016/j.ces.2016.06.033openalex-snapshot
Simulation and optimization of a 6-step dual-reflux VSA cycle for post-combustion CO2 capture
inferredcites →https://doi.org/10.1016/j.ces.2016.11.041openalex-snapshot
A rigorous criterion for approach to cyclic steady-state in PSA simulations
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Multi-objective optimisation using surrogate models for the design of VPSA systems
inferredcites →https://doi.org/10.1016/j.ijggc.2013.01.009openalex-snapshot
A new simplified pressure/vacuum swing adsorption model for rapid adsorbent screening for CO2 capture applications
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Do adsorbent screening metrics predict process performance? A process optimisation based study for post-combustion capture of CO2
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Improving the performance of vacuum swing adsorption based CO2 capture under reduced recovery requirements
inferredcites →https://doi.org/10.1016/j.seppur.2012.11.018openalex-snapshot
A parametric study of a PSA process for pre-combustion CO2 capture
inferredcites →https://doi.org/10.1016/j.seppur.2018.10.015openalex-snapshot
Evaluation of diamine-appended metal-organic frameworks for post-combustion CO2 capture by vacuum swing adsorption
inferredcites →https://doi.org/10.1016/j.seppur.2019.05.039openalex-snapshot
Experimental validation of multi-objective optimization techniques for design of vacuum swing adsorption processes
inferredcites →https://doi.org/10.1016/j.seppur.2020.116651openalex-snapshot
Experimentally validated machine learning frameworks for accelerated prediction of cyclic steady state and optimization of pressure swing adsorption processes
inferredcites →https://doi.org/10.1016/s0015-1882(97)84188-2openalex-snapshot
Pressure swing adsorption
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Fast solution-adaptive finite volume method for PSA/VSA cycle simulation; 1 single step simulation
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Big-Data Science in Porous Materials: Materials Genomics and Machine Learning
inferredcites →https://doi.org/10.1021/acs.est.9b07407openalex-snapshot
Prediction of MOF Performance in Vacuum Swing Adsorption Systems for Postcombustion CO2 Capture Based on Integrated Molecular Simulations, Process Optimizations, and Machine Learning Models
inferredcites →https://doi.org/10.1021/acs.iecr.5b03122openalex-snapshot
Optimization of Two-Stage Pressure/Vacuum Swing Adsorption with Variable Dehydration Level for Postcombustion Carbon Capture
inferredcites →https://doi.org/10.1021/acs.iecr.5b04531openalex-snapshot
Adsorbent Screening for Postcombustion CO2 Capture: A Method Relating Equilibrium Isotherm Characteristics to an Optimum Vacuum Swing Adsorption Process Performance
inferredcites →https://doi.org/10.1021/acs.iecr.8b00207openalex-snapshot
MO-MCS, a Derivative-Free Algorithm for the Multiobjective Optimization of Adsorption Processes
inferredcites →https://doi.org/10.1021/acs.iecr.8b03065openalex-snapshot
From Crystal to Adsorption Column: Challenges in Multiscale Computational Screening of Materials for Adsorption Separation Processes
inferredcites →https://doi.org/10.1021/acs.iecr.9b02383openalex-snapshot
110th Anniversary : Surrogate Models Based on Artificial Neural Networks To Simulate and Optimize Pressure Swing Adsorption Cycles for CO 2 Capture
inferredcites →https://doi.org/10.1021/acs.iecr.9b04173openalex-snapshot
Machine Learning-Based Multiobjective Optimization of Pressure Swing Adsorption
inferredcites →https://doi.org/10.1021/acs.iecr.9b05363openalex-snapshot
How Well Do Approximate Models of Adsorption-Based CO2 Capture Processes Predict Results of Detailed Process Models?
inferredcites →https://doi.org/10.1021/acs.iecr.9b05579openalex-snapshot
A New Equilibrium Shortcut Temperature Swing Adsorption Model for Fast Adsorbent Screening
inferredcites →https://doi.org/10.1021/acssuschemeng.9b01418openalex-snapshot
Development of a General Evaluation Metric for Rapid Screening of Adsorbent Materials for Postcombustion CO2 Capture
inferredcites →https://doi.org/10.1021/acssuschemeng.9b04124openalex-snapshot
Process Optimization-Based Screening of Zeolites for Post-Combustion CO2 Capture by Vacuum Swing Adsorption
inferredcites →https://doi.org/10.1021/ie302658yopenalex-snapshot
Multiobjective Optimization of a Four-Step Adsorption Process for Postcombustion CO 2 Capture Via Finite Volume Simulation
inferredcites →https://doi.org/10.1021/ie900873jopenalex-snapshot
Superstructure-Based Optimal Synthesis of Pressure Swing Adsorption Cycles for Precombustion CO2 Capture
inferredcites →https://doi.org/10.1038/nchem.1192openalex-snapshot
Large-scale screening of hypothetical metal–organic frameworks
inferredcites →https://doi.org/10.1038/nmat3336openalex-snapshot
In silico screening of carbon-capture materials
inferredcites →https://doi.org/10.1039/c9ee03977eopenalex-snapshot
Exploring new sources of efficiency in process-driven materials screening for post-combustion carbon capture
inferredcites →https://doi.org/10.1039/c9me00102fopenalex-snapshot
Exploring the limits of adsorption-based CO 2 capture using MOFs with PVSA – from molecular design to process economics
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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