Multi-objective genetic algorithm optimization with an artificial neural network for CO2/CH4 adsorption prediction in metal–organic framework-Reference-Cited by-同舟云学术

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Multi-objective genetic algorithm optimization with an artificial neural network for CO2/CH4 adsorption prediction in metal–organic framework

Published:2021-10 Issue: Volume:25 Page:100967
ISSN:2451-9049
Container-title:Thermal Science and Engineering Progress
language:en
Short-container-title:Thermal Science and Engineering Progress

Author:

Yulia Fayza,Chairina Intan,Zulys Agustino,Nasruddin

Funder

Osaka Gas Group Welfare Foundation

Kementerian Riset Teknologi dan Pendidikan Tinggi Republik Indonesia

Universitas Indonesia

Publisher

Elsevier BV

Subject

Fluid Flow and Transfer Processes

Reference43 articles.

1. Improved SAPO-34 membranes for CO2/CH4 separations;Li;Adv. Mater.,2006

2. Amine versus ammonia absorption of CO 2 as a measure of reducing GHG emission: a critical analysis;Bandyopadhyay;Clean Technol. Environ.,2011

3. Progress and trends in CO2 capture/separation technologies: A review;Mondal;Energy,2012

4. A benchmark for CO2 uptake onto newly synthesized biomass-derived activated carbons;Pal;Appl. Energy,2020

5. Improved CO2 adsorption onto chemically activated spherical phenol resin;Uddin;J. CO2 Utiliz.,2020

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1. Optimizing the prediction of adsorption in metal–organic frameworks leveraging Q‐learning;AIChE Journal;2024-09-12

2. Recent progress on advanced solid adsorbents for CO2 capture: From mechanism to machine learning;Materials Today Sustainability;2024-09

3. Computational and Machine Learning Methods for CO₂ Capture Using Metal–Organic Frameworks;ACS Nano;2024-08-22

4. Multi-objective optimization of lignocellulolytic enzyme cocktail production from Pseudolagarobasidium acaciicola TDW-48 by artificial neural network-genetic algorithm (ANN-GA) strategy and its application in lignocellulose waste bioconversion;Biomass Conversion and Biorefinery;2024-06-12

5. Machine learning insights into predicting biogas separation in metal-organic frameworks;Communications Chemistry;2024-05-08

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