A hydrogen evolution-assisted one-pot aqueous approach was developed for facile synthesis of trimetallic Pd Ni Ru alloy nanochain-like networks（Pd Ni Ru NCNs） by only using KBHas the reductant, without any specific ...A hydrogen evolution-assisted one-pot aqueous approach was developed for facile synthesis of trimetallic Pd Ni Ru alloy nanochain-like networks（Pd Ni Ru NCNs） by only using KBHas the reductant, without any specific additive（e.g. surfactant, polymer, template or seed）. The products were mainly investigated by transmission electron microscopy（TEM）, X-ray diffraction（XRD） and X-ray photoelectron spectroscopy（XPS）. The hierarchical architectures were formed by the oriented assembly growth and the diffusioncontrolled deposition in the presence of many in-situ generated hydrogen bubbles. The architectures had the largest electrochemically active surface area（ECSA） of 84.32 mgPdthan Pd Ni nanoparticles(NPs,65.23 mgPd), Pd Ru NPs(23.12 mgPd), Ni Ru NPs（nearly zero）, and commercial Pd black(6.01 mgPd), outperforming the referenced catalysts regarding the catalytic characters for hydrazine oxygen reaction（HOR）. The synthetic route provides new insight into the preparation of other trimetallic nanocatalysts in fuel cells.展开更多
A prediction model for Current Efficiency (CE) of low temperature aluminum electrolysis (LTAE) with the low molar ratioelectfolyte of Na3AIF6-AIF3 - CaF2-MgF2-LiF -Al2O3 system was investigated based on artificial neu...A prediction model for Current Efficiency (CE) of low temperature aluminum electrolysis (LTAE) with the low molar ratioelectfolyte of Na3AIF6-AIF3 - CaF2-MgF2-LiF -Al2O3 system was investigated based on artificial neural network principles. The nonlinearmapping between CE of LATE and various electrolytic conditions was obtained from a number of experimental data and used to predictCE of LATE. The trsined neural networks possessed high precision and resulted in a good predicting effect. As a result, attificial neuralnetworks as a new cooperating and predicting technology provide a new approach to the further studies on low temperature aluminumelectrolysis.展开更多
基金financially supported by the Nation Natural Science Foundation of China(No.21475118)
文摘A hydrogen evolution-assisted one-pot aqueous approach was developed for facile synthesis of trimetallic Pd Ni Ru alloy nanochain-like networks（Pd Ni Ru NCNs） by only using KBHas the reductant, without any specific additive（e.g. surfactant, polymer, template or seed）. The products were mainly investigated by transmission electron microscopy（TEM）, X-ray diffraction（XRD） and X-ray photoelectron spectroscopy（XPS）. The hierarchical architectures were formed by the oriented assembly growth and the diffusioncontrolled deposition in the presence of many in-situ generated hydrogen bubbles. The architectures had the largest electrochemically active surface area（ECSA） of 84.32 mgPdthan Pd Ni nanoparticles(NPs,65.23 mgPd), Pd Ru NPs(23.12 mgPd), Ni Ru NPs（nearly zero）, and commercial Pd black(6.01 mgPd), outperforming the referenced catalysts regarding the catalytic characters for hydrazine oxygen reaction（HOR）. The synthetic route provides new insight into the preparation of other trimetallic nanocatalysts in fuel cells.
文摘A prediction model for Current Efficiency (CE) of low temperature aluminum electrolysis (LTAE) with the low molar ratioelectfolyte of Na3AIF6-AIF3 - CaF2-MgF2-LiF -Al2O3 system was investigated based on artificial neural network principles. The nonlinearmapping between CE of LATE and various electrolytic conditions was obtained from a number of experimental data and used to predictCE of LATE. The trsined neural networks possessed high precision and resulted in a good predicting effect. As a result, attificial neuralnetworks as a new cooperating and predicting technology provide a new approach to the further studies on low temperature aluminumelectrolysis.
