Due to the superiority of machine learning(ML)data processing,it is widely used in research of solid waste(SW).This study analyzed the research and developmental progress of the applications of ML in the life cycle of...Due to the superiority of machine learning(ML)data processing,it is widely used in research of solid waste(SW).This study analyzed the research and developmental progress of the applications of ML in the life cycle of SW.Statistical analyses were undertaken on the literature published between 1985 and 2021 in the Science Citation Index Expanded and Social Sciences Citation Index to provide an overview of the progress.Based on the articles considered,a rapid upward trend from 1985 to 2021 was found and international cooperatives were found to have strengthened.The three topics of ML,namely,SW categories,ML algorithms,and specific applications,as applied to the life cycle of SW were discussed.ML has been applied during the entire SW process,thereby affecting its life cycle.ML was used to predict the generation and characteristics of SW,optimize its collection and transportation,and model the processing of its energy utilization.Finally,the current challenges of applying ML to SW and future perspectives were discussed.The goal is to achieve high economic and environmental benefits and carbon reduction during the life cycle of SW.ML plays an important role in the modernization and intellectualization of SW management.It is hoped that this work would be helpful to provide a constructive overview towards the state-of-the-art development of SW disposal.展开更多
Tailor-made advanced electrocatalysts with high active and stable for hydrogen evolution reaction(HER)play a key role in the development of hydrogen economy.Herein,a N,P-co-doped molybdenum carbide confined in porous ...Tailor-made advanced electrocatalysts with high active and stable for hydrogen evolution reaction(HER)play a key role in the development of hydrogen economy.Herein,a N,P-co-doped molybdenum carbide confined in porous carbon matrix(N,P-Mo_(2)C/NPC)with a hierarchical structure is prepared by a resources recovery process.The N,P-Mo_(2)C/NPC compound exhibits outstanding HER activity with a low overpotential of 84 mV to achieve 10 mA/cm^(2),and excellent stability in alkaline media.The electrochemical measurements confirm that the enhanced HER activity of N,P-Mo_(2)C/NPC is ascribe to the synergy of N,P-codoped and porous carbon matrix.Density functional theory calculations further reveal that the electron density of active sites on Mo_(2)C can be regulated by the N/P doping,leading to optimal H adsorption strength.In this work,the proof-of-concept resource utilization,a microorganism derived molybdenum carbide electrocatalyst for HER is fabricated,which may inaugurate a new way for designing electrocatalysts by the utilization of solid waste.展开更多
基金This research was supported by the National Natural Science Foundation of China(No.52100157).
文摘Due to the superiority of machine learning(ML)data processing,it is widely used in research of solid waste(SW).This study analyzed the research and developmental progress of the applications of ML in the life cycle of SW.Statistical analyses were undertaken on the literature published between 1985 and 2021 in the Science Citation Index Expanded and Social Sciences Citation Index to provide an overview of the progress.Based on the articles considered,a rapid upward trend from 1985 to 2021 was found and international cooperatives were found to have strengthened.The three topics of ML,namely,SW categories,ML algorithms,and specific applications,as applied to the life cycle of SW were discussed.ML has been applied during the entire SW process,thereby affecting its life cycle.ML was used to predict the generation and characteristics of SW,optimize its collection and transportation,and model the processing of its energy utilization.Finally,the current challenges of applying ML to SW and future perspectives were discussed.The goal is to achieve high economic and environmental benefits and carbon reduction during the life cycle of SW.ML plays an important role in the modernization and intellectualization of SW management.It is hoped that this work would be helpful to provide a constructive overview towards the state-of-the-art development of SW disposal.
基金Taishan Scholars Project Special Funds(No.tsqn201812083)Natural Science Foundation of Shandong Province(Nos.ZR2019YQ20,2019JMRH0410)the National Natural Science Foundation of China(Nos.51972147,52022037,52002145)。
文摘Tailor-made advanced electrocatalysts with high active and stable for hydrogen evolution reaction(HER)play a key role in the development of hydrogen economy.Herein,a N,P-co-doped molybdenum carbide confined in porous carbon matrix(N,P-Mo_(2)C/NPC)with a hierarchical structure is prepared by a resources recovery process.The N,P-Mo_(2)C/NPC compound exhibits outstanding HER activity with a low overpotential of 84 mV to achieve 10 mA/cm^(2),and excellent stability in alkaline media.The electrochemical measurements confirm that the enhanced HER activity of N,P-Mo_(2)C/NPC is ascribe to the synergy of N,P-codoped and porous carbon matrix.Density functional theory calculations further reveal that the electron density of active sites on Mo_(2)C can be regulated by the N/P doping,leading to optimal H adsorption strength.In this work,the proof-of-concept resource utilization,a microorganism derived molybdenum carbide electrocatalyst for HER is fabricated,which may inaugurate a new way for designing electrocatalysts by the utilization of solid waste.
