The oxygen reduction reaction(ORR)is a vitally important process in fuel cells.The development of high‐performance and low‐cost ORR electrocatalysts with outstanding stability is essential for the commercialization ...The oxygen reduction reaction(ORR)is a vitally important process in fuel cells.The development of high‐performance and low‐cost ORR electrocatalysts with outstanding stability is essential for the commercialization of the electrochemical energy technology.Herein,we report a facile synthesis of cobalt(Co)and nitrogen(N)co‐doped carbon nanotube@porous carbon(Co/N/CNT@PC‐800)electrocatalyst through a one‐step pyrolysis of waste paper,dicyandiamide,and cobalt(II)acetylacetonate.The surface of the hierarchical porous carbon supported a large number of carbon nanotubes(CNTs),which were derived from dicyandiamide through the catalysis of Co.The addition of Co resulted in the formation of a hierarchical micro/mesoporous structure,which was beneficial for the exposure of active sites and rapid transportation of ORR‐relevant species(O2,H+,OH?,and H2O).The doped N and Co formed more active sites to enhance the ORR activity of the electrocatalyst.The Co/N/CNT@PC‐800 material exhibited optimal ORR performance with an onset potential of 0.005 V vs.Ag/AgCl and a half‐wave potential of?0.173 V vs.Ag/AgCl.Meanwhile,the electrocatalyst showed an excellent methanol tolerance and a long‐term operational durability than that of Pt/C,as well as a quasi‐four‐electron reaction pathway.The low‐cost and simple synthesis approach makes the Co/N/CNT@PC‐800 a prospective electrocatalyst for the ORR.Furthermore,this work provides an alternative approach for exploring the use of biomass‐derived electrocatalysts for renewable energy applications.展开更多
The accurate prediction of displacement is crucial for landslide deformation monitoring and early warning.This study focuses on a landslide in Wenzhou Belt Highway and proposes a novel multivariate landslide displacem...The accurate prediction of displacement is crucial for landslide deformation monitoring and early warning.This study focuses on a landslide in Wenzhou Belt Highway and proposes a novel multivariate landslide displacement prediction method that relies on graph deep learning and Global Navigation Satellite System(GNSS)positioning.First model the graph structure of the monitoring system based on the engineering positions of the GNSS monitoring points and build the adjacent matrix of graph nodes.Then construct the historical and predicted time series feature matrixes using the processed temporal data including GNSS displacement,rainfall,groundwater table and soil moisture content and the graph structure.Last introduce the state-of-the-art graph deep learning GTS(Graph for Time Series)model to improve the accuracy and reliability of landslide displacement prediction which utilizes the temporal-spatial dependency of the monitoring system.This approach outperforms previous studies that only learned temporal features from a single monitoring point and maximally weighs the prediction performance and the priori graph of the monitoring system.The proposed method performs better than SVM,XGBoost,LSTM and DCRNN models in terms of RMSE(1.35 mm),MAE(1.14 mm)and MAPE(0.25)evaluation metrics,which is provided to be effective in future landslide failure early warning.展开更多
Electrocatalysis enables the industrial transition to sustainable production of chemicals using abundant precursors and electricity from renewable sources.De-centralized production of hydrogen peroxide(H_(2)O_(2))from...Electrocatalysis enables the industrial transition to sustainable production of chemicals using abundant precursors and electricity from renewable sources.De-centralized production of hydrogen peroxide(H_(2)O_(2))from water and oxygen of air is highly desirable for daily life and industry.We report an effective electrochemical refinery(e-refinery)for H_(2)O_(2)by means of electrocatalysis-controlled comproportionation reaction(2_(H)O+o→2HO),feeding pure water and oxygen only.Mesoporous nickel(Ⅱ)oxide(NiO)was used as electrocatalyst for oxygen evolution reaction(OER),producing oxygen at the anode.Conducting polymer poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)(PEDOT:PSS)drove the oxygen reduction reaction(ORR),forming H_(2)O_(2)on the cathode.The reactions were evaluated in both half-cell and device configurations.The performance of the H_(2)O_(2)e-refinery,assembled on anion-exchange solid electrolyte and fed with pure water,was limited by the unbalanced ionic transport.Optimization of the operation conditions allowed a conversion efficiency of 80%.展开更多
基金supported by the National Nature Science Foundation of China(21476098,21471069,21576123)International Postdoctoral Exchange Fellowship Program of China Postdoctoral Council(20150060)~~
文摘The oxygen reduction reaction(ORR)is a vitally important process in fuel cells.The development of high‐performance and low‐cost ORR electrocatalysts with outstanding stability is essential for the commercialization of the electrochemical energy technology.Herein,we report a facile synthesis of cobalt(Co)and nitrogen(N)co‐doped carbon nanotube@porous carbon(Co/N/CNT@PC‐800)electrocatalyst through a one‐step pyrolysis of waste paper,dicyandiamide,and cobalt(II)acetylacetonate.The surface of the hierarchical porous carbon supported a large number of carbon nanotubes(CNTs),which were derived from dicyandiamide through the catalysis of Co.The addition of Co resulted in the formation of a hierarchical micro/mesoporous structure,which was beneficial for the exposure of active sites and rapid transportation of ORR‐relevant species(O2,H+,OH?,and H2O).The doped N and Co formed more active sites to enhance the ORR activity of the electrocatalyst.The Co/N/CNT@PC‐800 material exhibited optimal ORR performance with an onset potential of 0.005 V vs.Ag/AgCl and a half‐wave potential of?0.173 V vs.Ag/AgCl.Meanwhile,the electrocatalyst showed an excellent methanol tolerance and a long‐term operational durability than that of Pt/C,as well as a quasi‐four‐electron reaction pathway.The low‐cost and simple synthesis approach makes the Co/N/CNT@PC‐800 a prospective electrocatalyst for the ORR.Furthermore,this work provides an alternative approach for exploring the use of biomass‐derived electrocatalysts for renewable energy applications.
基金funded by the National Natural Science Foundation of China (Grant No.41902240).
文摘The accurate prediction of displacement is crucial for landslide deformation monitoring and early warning.This study focuses on a landslide in Wenzhou Belt Highway and proposes a novel multivariate landslide displacement prediction method that relies on graph deep learning and Global Navigation Satellite System(GNSS)positioning.First model the graph structure of the monitoring system based on the engineering positions of the GNSS monitoring points and build the adjacent matrix of graph nodes.Then construct the historical and predicted time series feature matrixes using the processed temporal data including GNSS displacement,rainfall,groundwater table and soil moisture content and the graph structure.Last introduce the state-of-the-art graph deep learning GTS(Graph for Time Series)model to improve the accuracy and reliability of landslide displacement prediction which utilizes the temporal-spatial dependency of the monitoring system.This approach outperforms previous studies that only learned temporal features from a single monitoring point and maximally weighs the prediction performance and the priori graph of the monitoring system.The proposed method performs better than SVM,XGBoost,LSTM and DCRNN models in terms of RMSE(1.35 mm),MAE(1.14 mm)and MAPE(0.25)evaluation metrics,which is provided to be effective in future landslide failure early warning.
基金the competence centre Fun Mat-II funded by the Swedish Agency for Innovation Systems(Vinnova,grant no 2016-05156)Swedish Energy Agency(project no 42022-1)+3 种基金Swedish Research Council(VR 2021-04427,VR 2019-05577,VR 2016–05990)the Centre in Nanoscience and Technology(CeNano,Linkoping Institute of Technology(LiTH),Linkoping University,2020,2021)the Swedish Government Strategic Research Area in Materials Science on Advanced Functional Materials at Linkoping University(Faculty Grant SFO-Mat-Li U No.2009-00971)the Knut and Alice Wal enberg Foundation(H2O2,KAW 2018.0058),for support
文摘Electrocatalysis enables the industrial transition to sustainable production of chemicals using abundant precursors and electricity from renewable sources.De-centralized production of hydrogen peroxide(H_(2)O_(2))from water and oxygen of air is highly desirable for daily life and industry.We report an effective electrochemical refinery(e-refinery)for H_(2)O_(2)by means of electrocatalysis-controlled comproportionation reaction(2_(H)O+o→2HO),feeding pure water and oxygen only.Mesoporous nickel(Ⅱ)oxide(NiO)was used as electrocatalyst for oxygen evolution reaction(OER),producing oxygen at the anode.Conducting polymer poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)(PEDOT:PSS)drove the oxygen reduction reaction(ORR),forming H_(2)O_(2)on the cathode.The reactions were evaluated in both half-cell and device configurations.The performance of the H_(2)O_(2)e-refinery,assembled on anion-exchange solid electrolyte and fed with pure water,was limited by the unbalanced ionic transport.Optimization of the operation conditions allowed a conversion efficiency of 80%.
