Electrochemical conversion of CO_(2)into liquid fuels and value-added chemicals is a promising approach for closing the carbon cycle.Copper(Cu)is considered one of the most effective catalysts for the electrocatalytic...Electrochemical conversion of CO_(2)into liquid fuels and value-added chemicals is a promising approach for closing the carbon cycle.Copper(Cu)is considered one of the most effective catalysts for the electrocatalytic CO_(2)reduction reaction(CO_(2)RR).However,its utilization potential is limited by poor selectivity for hydrocarbon products and the competing hydrogen evolution reaction(HER).In this study,we present a strategy to suppress the HER process and enhance the CH_(4) selectivity of large-scale Cu foil toward the CO_(2)RR.By coating the Cu foil surface with a porous polyaniline(PANI)layer,the H_(2)faradaic efficiency(FE)reduces from 60%to 18%.Moreover,the FE of hydrocarbons increases dramatically from 25%to 80%,and the FE of the dominant product CH_(4) is high up to 62%.In situ electrochemical attenuated total reflection Fourier transform infrared spectroscopy(in situ ATR-FTIR)and density functional theory(DFT)calculations are conducted to elucidate the mechanism.The enhanced performance of Cu-PANI in the CO_(2)RR is mainly attributed to the porous PANI layer,which facilitates CO_(2)adsorption and mass transport.This leads to a reversal in the energy barrier for the rate-determining steps between the HER and the CO_(2)RR,significantly inhibiting the HER and enhancing the CO_(2)RR activity.Additionally,Cu-PANI promotes the hydrogenation of^(*)CO to^(*)CHO,resulting in higher methane selectivity.This work provides a promising strategy for designing efficient large-scale Cu-based catalysts with high CH_(4) catalytic activity and selectivity.展开更多
BIM(Building Information Modeling)是基于三维数字设计解决方案所构建的"可视化"数字建筑模型,而网页处理大规模3D场景有一定的性能缺陷。现在探索提出了BIM与Web大规模场景结合的绘制方案。首先,对大规模BIM数据进行体素...BIM(Building Information Modeling)是基于三维数字设计解决方案所构建的"可视化"数字建筑模型,而网页处理大规模3D场景有一定的性能缺陷。现在探索提出了BIM与Web大规模场景结合的绘制方案。首先,对大规模BIM数据进行体素化处理,然后通过区域划分将数据划分为多个连通区域,最后使用基于视锥增量式关注域(Frustum Of Interests)对一个连通区域的数据加载进行进一步的性能优化,提出了一整套的加载方案。最终通过实验,证明了方案的有效性。展开更多
基金financial support from the National Key Research and Development Program of China(2022YFA1505700 and 2023YFA1508300)the NSFC(22171265,22201286,22220102005 and 22033008)the Fujian Science&Technology Innovation Laboratory for Optoelectronic Information of China(2021ZZ103).
文摘Electrochemical conversion of CO_(2)into liquid fuels and value-added chemicals is a promising approach for closing the carbon cycle.Copper(Cu)is considered one of the most effective catalysts for the electrocatalytic CO_(2)reduction reaction(CO_(2)RR).However,its utilization potential is limited by poor selectivity for hydrocarbon products and the competing hydrogen evolution reaction(HER).In this study,we present a strategy to suppress the HER process and enhance the CH_(4) selectivity of large-scale Cu foil toward the CO_(2)RR.By coating the Cu foil surface with a porous polyaniline(PANI)layer,the H_(2)faradaic efficiency(FE)reduces from 60%to 18%.Moreover,the FE of hydrocarbons increases dramatically from 25%to 80%,and the FE of the dominant product CH_(4) is high up to 62%.In situ electrochemical attenuated total reflection Fourier transform infrared spectroscopy(in situ ATR-FTIR)and density functional theory(DFT)calculations are conducted to elucidate the mechanism.The enhanced performance of Cu-PANI in the CO_(2)RR is mainly attributed to the porous PANI layer,which facilitates CO_(2)adsorption and mass transport.This leads to a reversal in the energy barrier for the rate-determining steps between the HER and the CO_(2)RR,significantly inhibiting the HER and enhancing the CO_(2)RR activity.Additionally,Cu-PANI promotes the hydrogenation of^(*)CO to^(*)CHO,resulting in higher methane selectivity.This work provides a promising strategy for designing efficient large-scale Cu-based catalysts with high CH_(4) catalytic activity and selectivity.
文摘BIM(Building Information Modeling)是基于三维数字设计解决方案所构建的"可视化"数字建筑模型,而网页处理大规模3D场景有一定的性能缺陷。现在探索提出了BIM与Web大规模场景结合的绘制方案。首先,对大规模BIM数据进行体素化处理,然后通过区域划分将数据划分为多个连通区域,最后使用基于视锥增量式关注域(Frustum Of Interests)对一个连通区域的数据加载进行进一步的性能优化,提出了一整套的加载方案。最终通过实验,证明了方案的有效性。
