Applied machine learning for predicting the properties and carbon and phosphorus fate of pristine and engineered hydrochar

Applied machine learning for predicting the properties and carbon and phosphorus fate of pristine and engineered hydrochar

Abstract Application of advanced techniques and machine learning (ML) for designing and predicting the properties of engineered hydrochar/biochar is of great agro-environmental concern. Carbon (C) stability and phosphorus (P) availability in hydrochar (HC) are among the key limitations as they canno...

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Bibliographic Details
Main Authors: Shiyu Xie, Tao Zhang, Siming You, Santanu Mukherjee, Mingjun Pu, Qing Chen, Yaosheng Wang, Esmat F. Ali, Hamada Abdelrahman, Jörg Rinklebe, Sang Soo Lee, Sabry M. Shaheen
Format: Article
Language:English
Published: Springer 2025-01-01
Series:Biochar
Subjects:
Engineered hydrochar
Hydrothermal carbonization
Ferric chloride impregnation
Nutrients stability and availability
Machine learning
Online Access:https://doi.org/10.1007/s42773-024-00404-4
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