Machine learning and computational chemistry to improve biochar fertilizers : a review

• Main Authors: Ahmed I., Osman, Yubing, Zhang, Lai, Zhi Ying, Ahmed K., Rashwan, Mohamed, Farghali, Ashour A., Ahmed, Liu, Yunfei, Fang, Bingbing, Chen, Zhonghao, Ahmed, Al-Fatesh, David W., Rooney, Yiin, Chung Loong, Yap, Pow Seng
• Format: Article
• Language: English
• Published: Springer Nature 2023
• Subjects: T Technology (General); TA Engineering (General). Civil engineering (General); TP Chemical technology
• Online Access: http://ir.unimas.my/id/eprint/42613/1/Environmental_Chemistry_Letters.pdf; http://ir.unimas.my/id/eprint/42613/; https://link.springer.com/article/10.1007/s10311-023-01631-0; https://doi.org/10.1007/s10311-023-01631-0
• Institution: Universiti Malaysia Sarawak

Traditional fertilizers are highly inefficient, with a major loss of nutrients and associated pollution. Alternatively, biochar loaded with phosphorous is a sustainable fertilizer that improves soil structure, stores carbon in soils, and provides plant nutrients in the long run, yet most biochars ar...