| 1 | Low-loading gold in situ doped with sulfur by biomolecule-assisted approach for promoted electrochemical carbon dioxide reduction显示文摘For electrochemical carbon dioxide reduction(CO_(2)RR),CO_(2)-to-CO conversion is considered an ideal route towards carbon neutrality for practical applications.Gold(Au)is known as a promising catalyst with high selectivity for CO;however,it suffers from high cost and low mass-specific activity.In this study,we design and prepare a catalyst featuring uniform S-doped Au nanoparticles on N-doped carbon support(denoted as S-Au/NC)by an in situ synthesis strategy using biomolecules.The S-Au/NC displays high activity and selectivity for CO in CO_(2)RR with a Au loading as low as 0.4 wt.%.The Faradaic efficiency of CO(FECO)for S-Au/NC is above 95%at−0.75 V(vs.RHE);by contrast,the FECO of Au/NC(without S)is only 58%.The Tafel slope is 77.4 mV·dec−1,revealing a favorable kinetics process.Furthermore,S-Au/NC exhibits an excellent long-term stability for CO_(2)RR.Density functional theory(DFT)calculations reveal that the S dopant can boost the activity by reducing the free energy change of the potential-limiting step(formation of the*COOH intermediate).This work not only demonstrates a model catalyst featuring significantly reduced use of noble metals,but also establishes an in situ synthesis strategy for preparing high-performance catalysts. | Meijie Tan Xiaoqian Han Sen Ru Chao Zhang Zhouru Ji Zhaolin Shi Guomeng Qiao Yunying Wang Ruixue Cui Qiquan Luo Jiqing Jiao Yaguang Li Tongbu Lu | 2023 | Nano Research2023，16，2： | 1 |
| 2 | A Bi-population Cooperative Optimization Algorithm Assisted by an Autoencoder for Medium-scale Expensive Problems显示文摘This study presents an autoencoder-embedded optimization(AEO)algorithm which involves a bi-population cooperative strategy for medium-scale expensive problems(MEPs).A huge search space can be compressed to an informative lowdimensional space by using an autoencoder as a dimension reduction tool.The search operation conducted in this low space facilitates the population with fast convergence towards the optima.To strike the balance between exploration and exploitation during optimization,two phases of a tailored teaching-learning-based optimization(TTLBO)are adopted to coevolve solutions in a distributed fashion,wherein one is assisted by an autoencoder and the other undergoes a regular evolutionary process.Also,a dynamic size adjustment scheme according to problem dimension and evolutionary progress is proposed to promote information exchange between these two phases and accelerate evolutionary convergence speed.The proposed algorithm is validated by testing benchmark functions with dimensions varying from 50 to 200.As indicated in our experiments,TTLBO is suitable for dealing with medium-scale problems and thus incorporated into the AEO framework as a base optimizer.Compared with the state-of-the-art algorithms for MEPs,AEO shows extraordinarily high efficiency for these challenging problems,t hus opening new directions for various evolutionary algorithms under AEO to tackle MEPs and greatly advancing the field of medium-scale computationally expensive optimization. | Meiji Cui Li Li MengChu Zhou Jiankai Li Abdullah Abusorrah Khaled Sedraoui | 2022 | IEEE/CAA Journal of Automatica Sinica2022，9，11： | 1 |
| 3 | Energy-efficient removal of carbamazepine in solution by electrocoagulation-electrofenton using a novel P-rGO cathode显示文摘In this study,carbamazepine(CBZ)decay in solution has been studied by coupling electro-coagulation with electro-Fenton(EC-EF)with a novel P-rGO/carbon felt(CF)cathode,aiming to accelerate the in-situ generation of·OH,instead of adding Fe2+and H2O2.Firstly,the fabri-cated P-rGO and its derived cathode were characterized by XRD,SEM,AFM,XPS and electro-chemical test(EIS,CV and LSV).Secondly,it was confirmed that the performance in removal efficiency and electric energy consumption(EEC)by EC-EF(kobs=0.124 min^(-1),EEC=43.98 kWh/kg CBZ)was better than EF(kobs=0.069 min^(-1),EEC=61.04 kWh/kg CBZ).Then,P-rGO/CF(kobs=0.248 min^(-1),EEC=29.47 kWh/kg CBZ,CE=61.04%)showed the best performance in EC-EF,among all studied heteroatom-doped graphene/CF.This superior performance may be associated with its largest layer spacing and richest C=C,which can promote the electron transfer rate and conductivity of the cathode.Thus,more H2O2 and·OH could be produced to degrade CBZ,and almost 100%CBZ was removed with kobs being 0.337 min^(-1) and the EEC was only 24.18 kWh/kg CBZ,under the optimal conditions(P-rGO loading was 6.0 mg/cm^(2),the current density was 10.0 mA/cm^(2),the gap between electrode was 2.0 cm).Additionally,no matter the influent is acidic,neutral or alkaline,no additional pH adjustment is required for the effluent of EC-EF.At last,an inconsecutive empirical kinetic model was firstly estab-lished to predict the effect of operating parameters on CBZ removal. | Zhihui Xiao Tingyu Cui Zhenbei Wang Yan Dang Meijie Zheng Yixinfei Lin Zilong Song YipingWang Chao Liu Bingbing Xu Amir Ikhlaq Jolanta Kumirska Ewa Maria Siedlecka Fei Qi | 2022 | Journal of Environmental Sciences2022，34，5： | 0 |
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