A machine learning assisted prediction of potential biochar and its applications in anaerobic digestion for valuable chemicals and energy recovery from organic waste

• DOI: 10.1007/s43979-023-00078-0
• Publication Date: 2024-01-08T05:02:25Z
• Authors: Pengshuai Zhang; Tengyu Zhang; Jingxin Zhang; Huaiyou Liu; Cristhian Chicaiz...; Jonathan T. E. Lee; Yiliang He; Yanjun Dai; Yen Wah Tong
• Keywords: Energy Recovery

Abstract The utilization of biochar derived from biomass residue to enhance anaerobic digestion (AD) for bioenergy recovery offers a sustainable approach advance energy and mitigate climate change. However, conducting comprehensive research on the optimal conditions AD experiments with addition poses challenge due diverse experimental objectives. Machine learning (ML) has demonstrated its effectiveness in addressing this issue. Therefore, it is essential provide an overview current ML-optimized processes biochar-enhanced order facilitate more systematic ML tools. This review comprehensively examines material flow preparation impact comprehension reviewed optimize production process perspective. Specifically, summarizes application techniques, based artificial intelligence, predicting yield properties residues, as well their AD. Overall, analysis address challenges recovery. In future research, crucial tackle that hinder implementation pilot-scale reactors. It recommended further investigate correlation between physicochemical process. Additionally, enhancing role throughout entire holds promise achieving economically environmentally optimized efficiency. Graphical