Data-driven modeling using machine learning to investigate the desulfurization performance by zeolitic adsorbents

This work introduces an experimentally validated, data-driven machine learning (ML) framework for predicting the adsorptive desulfurization (ADS) performance of zeolite-based materials. A curated dataset of 700 entries was compiled from diverse sources, incorporating key structural and operational p...

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Bibliographic Details

Published in:	Cleaner Engineering and Technology
Main Authors:	Mahyar Mansouri, Mohsen Shayanmehr, Ahad Ghaemi
Format:	Article
Language:	English
Published:	Elsevier 2025-09-01
Subjects:	Zeolite Desulfurization Adsorption Machine learning Thiophenic compounds
Online Access:	http://www.sciencedirect.com/science/article/pii/S266679082500196X