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Machine learning–guided CO2 methanation: From catalyst design optimization to techno-economic and life cycle assessment analyses

Milad Golvirdizadeh, Seyyed Alireza Ghafarian Nia, Hossein Shahbeik, Alireza Shafizadeh, Homa Hosseinzadeh‐Bandbafha, Mohammadali Kiehbadroudinezhad, Seyed Aryan Seyedalikhani, Maryam Ahmadi, Ali Hajiahmad, Sheikh Ahmad Faiz Sheikh Ahmad Tajuddin, Meisam Tabatabaei, Mortaza Aghbashlo

2025Energy7 citationsDOI

Topics & Concepts

MethanationProcess engineeringFlue gasCatalysisRenewable energyGeneralizability theoryEnvironmental scienceHydrogenLife-cycle assessmentProcess optimizationPower to gasChemistryWaste managementComputer scienceVolume (thermodynamics)Process integrationExothermic reactionProcess (computing)Service lifeMaterials scienceMethaneSubstitute natural gasEngineeringCarbon fibersEfficient energy useChemical engineeringMetal-organic frameworkGradient boostingEnergy transformationResponse surface methodologyCatalysts for Methane ReformingCarbon dioxide utilization in catalysisCatalysis and Oxidation Reactions
Machine learning–guided CO2 methanation: From catalyst design optimization to techno-economic and life cycle assessment analyses | Litcius