The influence of the drop-casted nickel boride catalyst loading on glassy carbon electrodes was investigated in a spectroelectrochemical ATR-FTIR thin-film flow cell applied in alkaline glycerol electrooxidation.The c...The influence of the drop-casted nickel boride catalyst loading on glassy carbon electrodes was investigated in a spectroelectrochemical ATR-FTIR thin-film flow cell applied in alkaline glycerol electrooxidation.The continuously operated radial flow cell consisted of a borehole electrode positioned 50μm above an internal reflection element enabling operando FTIR spectroscopy.It is identified as a suitable tool for facile and reproducible screening of electrocatalysts under well-defined conditions,additionally providing access to the selectivities in complex reaction networks such as glycerol oxidation.The fast product identification by ATR-IR spectroscopy was validated by the more time-consuming quantitative HPLC analysis of the pumped electrolyte.High degrees of glycerol conversion were achieved under the applied laminar flow conditions using 0.1 M glycerol and 1 M KOH in water and a flow rate of 5μL min^(–1).Conversion and selectivity were found to depend on the catalyst loading,which determined the catalyst layer thickness and roughness.The highest loading of 210μg cm^(–2)resulted in 73%conversion and a higher formate selectivity of almost 80%,which is ascribed to longer residence times in rougher films favoring readsorption and C–C bond scission.The lowest loading of 13μg cm^(–2)was sufficient to reach 63%conversion,a lower formate selectivity of 60%,and,correspondingly,higher selectivities of C_(2)species such as glycolate amounting to 8%.Thus,only low catalyst loadings resulting in very thin films in the fewμm thickness range are suitable for reliable catalyst screening.展开更多
Scanning electrochemical cell microscopy(SECCM)is increasingly applied to determine the intrinsic catalytic activity of single electrocatalyst particle.This is especially feasible if the catalyst nanoparticles are lar...Scanning electrochemical cell microscopy(SECCM)is increasingly applied to determine the intrinsic catalytic activity of single electrocatalyst particle.This is especially feasible if the catalyst nanoparticles are large enough that they can be found and counted in post-SECCM scanning electron microscopy images.Evidently,this becomes impossible for very small nanoparticles and hence,a catalytic current measured in one landing zone of the SECCM droplet cannot be correlated to the exact number of catalyst particles.We show,that by introducing a ruler method employing a carbon nanoelectrode decorated with a countable number of the same catalyst particles from which the catalytic activity can be determined,the activity determined using SECCM from many spots can be converted in the intrinsic catalytic activity of a certain number of catalyst nanoparticles.展开更多
Despite outstanding accomplishments in catalyst discovery,finding new,more efficient,environmentally neutral,and noble metalfree catalysts remains challenging and unsolved.Recently,complex solid solutions consisting o...Despite outstanding accomplishments in catalyst discovery,finding new,more efficient,environmentally neutral,and noble metalfree catalysts remains challenging and unsolved.Recently,complex solid solutions consisting of at least five different elements and often named as high-entropy alloys have emerged as a new class of electrocatalysts for a variety of reactions.The multicomponent combinations of elements facilitate tuning of active sites and catalytic properties.Predicting optimal catalyst composition remains difficult,making testing of a very high number of them indispensable.We present the high-throughput screening of the electrochemical activity of thin film material libraries prepared by combinatorial co-sputtering of metals which are commonly used in catalysis(Pd,Cu,Ni)combined with metals which are not commonly used in catalysis(Ti,Hf,Zr).Introducing unusual elements in the search space allows discovery of catalytic activity for hitherto unknown compositions.Material libraries with very similar composition spreads can show different activities vs.composition trends for different reactions.In order to address the inherent challenge of the huge combinatorial material space and the inability to predict active electrocatalyst compositions,we developed a high-throughput process based on co-sputtered material libraries,and performed high-throughput characterization using energy dispersive X-ray spectroscopy(EDS),scanning transmission electron microscopy(SEM),X-ray diffraction(XRD)and conductivity measurements followed by electrochemical screening by means of a scanning droplet cell.The results show surprising material compositions with increased activity for the oxygen reduction reaction and the hydrogen evolution reaction.Such data are important input data for future data-driven materials prediction.展开更多
文摘The influence of the drop-casted nickel boride catalyst loading on glassy carbon electrodes was investigated in a spectroelectrochemical ATR-FTIR thin-film flow cell applied in alkaline glycerol electrooxidation.The continuously operated radial flow cell consisted of a borehole electrode positioned 50μm above an internal reflection element enabling operando FTIR spectroscopy.It is identified as a suitable tool for facile and reproducible screening of electrocatalysts under well-defined conditions,additionally providing access to the selectivities in complex reaction networks such as glycerol oxidation.The fast product identification by ATR-IR spectroscopy was validated by the more time-consuming quantitative HPLC analysis of the pumped electrolyte.High degrees of glycerol conversion were achieved under the applied laminar flow conditions using 0.1 M glycerol and 1 M KOH in water and a flow rate of 5μL min^(–1).Conversion and selectivity were found to depend on the catalyst loading,which determined the catalyst layer thickness and roughness.The highest loading of 210μg cm^(–2)resulted in 73%conversion and a higher formate selectivity of almost 80%,which is ascribed to longer residence times in rougher films favoring readsorption and C–C bond scission.The lowest loading of 13μg cm^(–2)was sufficient to reach 63%conversion,a lower formate selectivity of 60%,and,correspondingly,higher selectivities of C_(2)species such as glycolate amounting to 8%.Thus,only low catalyst loadings resulting in very thin films in the fewμm thickness range are suitable for reliable catalyst screening.
基金funding from the European Research Council(ERC)under the European Unions Horizon 2020 research and innovation programme(grant agreement CasCat[833408])well as from the European Unions Horizon 2020 research and innovation program under the Marie Sktodowska-Curie MSCA-ITN Single-Entity Nanoelectrochemistry,Sentinel[812398]+2 种基金S.S.and C.A.acknowledge the Deutsche Forschungsgemeinschaft(DFG,German Research Foundation)within the project[440951282]X.X.C.acknowledges financial support from the Liaoning BaiQianWan Talents Program,China(No.2019B042)the Excellent Young Scientific and Technological Talents Project of Educational Department of Liaoning Province,China(No.2020LNQN07).
文摘Scanning electrochemical cell microscopy(SECCM)is increasingly applied to determine the intrinsic catalytic activity of single electrocatalyst particle.This is especially feasible if the catalyst nanoparticles are large enough that they can be found and counted in post-SECCM scanning electron microscopy images.Evidently,this becomes impossible for very small nanoparticles and hence,a catalytic current measured in one landing zone of the SECCM droplet cannot be correlated to the exact number of catalyst particles.We show,that by introducing a ruler method employing a carbon nanoelectrode decorated with a countable number of the same catalyst particles from which the catalytic activity can be determined,the activity determined using SECCM from many spots can be converted in the intrinsic catalytic activity of a certain number of catalyst nanoparticles.
基金support by the German Research Foundation(Deutsche Forschungsgemeinschaft,DFG)in the framework of the projects AN 1570/2-1(C.A.,S.S.)and LU 1175/31-1)(A.L)the European Research Council(ERC)under the European Union’s Horizon 2020 research and innovation programme(grant agreement CasCat[833408],W.S.).
文摘Despite outstanding accomplishments in catalyst discovery,finding new,more efficient,environmentally neutral,and noble metalfree catalysts remains challenging and unsolved.Recently,complex solid solutions consisting of at least five different elements and often named as high-entropy alloys have emerged as a new class of electrocatalysts for a variety of reactions.The multicomponent combinations of elements facilitate tuning of active sites and catalytic properties.Predicting optimal catalyst composition remains difficult,making testing of a very high number of them indispensable.We present the high-throughput screening of the electrochemical activity of thin film material libraries prepared by combinatorial co-sputtering of metals which are commonly used in catalysis(Pd,Cu,Ni)combined with metals which are not commonly used in catalysis(Ti,Hf,Zr).Introducing unusual elements in the search space allows discovery of catalytic activity for hitherto unknown compositions.Material libraries with very similar composition spreads can show different activities vs.composition trends for different reactions.In order to address the inherent challenge of the huge combinatorial material space and the inability to predict active electrocatalyst compositions,we developed a high-throughput process based on co-sputtered material libraries,and performed high-throughput characterization using energy dispersive X-ray spectroscopy(EDS),scanning transmission electron microscopy(SEM),X-ray diffraction(XRD)and conductivity measurements followed by electrochemical screening by means of a scanning droplet cell.The results show surprising material compositions with increased activity for the oxygen reduction reaction and the hydrogen evolution reaction.Such data are important input data for future data-driven materials prediction.
