Integrating machine learning-based classification and regression models for solvent regeneration prediction in post-combustion carbon capture: An absorption-based case

Integrating machine learning-based classification and regression models for solvent regeneration prediction in post-combustion carbon capture: An absorption-based case

As an industrialized nation with substantial greenhouse gas emissions, Iran faces an urgent need to implement post-combustion carbon capture (PCC) technology. However, conventional PCC systems often struggle with inefficiencies, particularly in solvent selection and regeneration, leading to high ene...

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Bibliographic Details
Main Authors: Farzin Hosseinifard, Mostafa Setak, Majid Amidpour
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Results in Engineering
Subjects:
Post-combustion carbon capture
Solvent regeneration energy
Solvent selection
Machine learning models
Aspen HYSYS simulation
Online Access:http://www.sciencedirect.com/science/article/pii/S2590123025009314
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