Leveraging machine learning for prediction and optimization of texture properties of sustainable activated carbon derived from waste materials

Leveraging machine learning for prediction and optimization of texture properties of sustainable activated carbon derived from waste materials

Abstract The increasing demand for sustainable waste management has driven innovation in the production of activated carbon (AC) from waste. AC’s textural properties, including its surface area (SA), total pore volume (TPV), and micropore volume (MPV), are critical for applications such as gas purif...

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Bibliographic Details
Main Authors: Ahmed Farid Ibrahim, Mohamed Abdrabou Hussein
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Porous carbon
Activated carbon
Machine learning
Surface area
Sustainable waste management
Online Access:https://doi.org/10.1038/s41598-025-95061-3
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