Electrocatalytic overall water splitting(OWS),a pivotal approach in addressing the global energy crisis,aims to produce hydrogen and oxygen.However,most of the catalysts in powder form are adhesively bounding to the e...Electrocatalytic overall water splitting(OWS),a pivotal approach in addressing the global energy crisis,aims to produce hydrogen and oxygen.However,most of the catalysts in powder form are adhesively bounding to the electrodes,resulting in catalyst detachment by bubble generation and other uncertain interference,and eventually reducing the OWS performance.To surmount this challenge,we synthesized a hybrid material of Co_(3)S_(4)-pyrolysis lotus fiber(labeled as Co_(3)S_(4)-p LF)textile by hydrothermal and hightemperature pyrolysis processes for electrocatalytic OWS.Owing to the natural LF textile exposing the uniformly distributed functional groups(AOH,ANH_(2),etc.)to anchor Co_(3)S_(4)nanoparticles with hierarchical porous structure and outstanding hydrophily,the hybrid Co_(3)S_(4)-p LF catalyst shows low overpotentials at 10 m A cm^(-2)(η_(10,HER)=100 m Vη_(10,OER)=240 mV)alongside prolonged operational stability during electrocatalytic reactions.Theoretical calculations reveal that the electron transfer from p LF to Co_(3)S_(4)in the hybrid Co_(3)S_(4)-p LF is beneficial to the electrocatalytic process.This work will shed light on the development of nature-inspired carbon-based materials in hybrid electrocatalysts for OWS.展开更多
The high dimensions of hyperspectral imagery have caused burden for further processing. A new Fast Independent Component Analysis (FastICA) approach to dimensionality reduction for hyperspectral imagery is presented. ...The high dimensions of hyperspectral imagery have caused burden for further processing. A new Fast Independent Component Analysis (FastICA) approach to dimensionality reduction for hyperspectral imagery is presented. The virtual dimensionality is introduced to determine the number of dimensions needed to be preserved. Since there is no prioritization among independent components generated by the FastICA,the mixing matrix of FastICA is initialized by endmembers,which were extracted by using unsupervised maximum distance method. Minimum Noise Fraction (MNF) is used for preprocessing of original data,which can reduce the computational complexity of FastICA significantly. Finally,FastICA is performed on the selected principal components acquired by MNF to generate the expected independent components in accordance with the order of endmembers. Experimental results demonstrate that the proposed method outperforms second-order statistics-based transforms such as principle components analysis.展开更多
基金supported by the Scientific Research Foundation of Hunan Provincial Education Department,China(22B0893)the Scientific Research Foundation of Hunan Provincial Education Department,China(20A060)。
文摘Electrocatalytic overall water splitting(OWS),a pivotal approach in addressing the global energy crisis,aims to produce hydrogen and oxygen.However,most of the catalysts in powder form are adhesively bounding to the electrodes,resulting in catalyst detachment by bubble generation and other uncertain interference,and eventually reducing the OWS performance.To surmount this challenge,we synthesized a hybrid material of Co_(3)S_(4)-pyrolysis lotus fiber(labeled as Co_(3)S_(4)-p LF)textile by hydrothermal and hightemperature pyrolysis processes for electrocatalytic OWS.Owing to the natural LF textile exposing the uniformly distributed functional groups(AOH,ANH_(2),etc.)to anchor Co_(3)S_(4)nanoparticles with hierarchical porous structure and outstanding hydrophily,the hybrid Co_(3)S_(4)-p LF catalyst shows low overpotentials at 10 m A cm^(-2)(η_(10,HER)=100 m Vη_(10,OER)=240 mV)alongside prolonged operational stability during electrocatalytic reactions.Theoretical calculations reveal that the electron transfer from p LF to Co_(3)S_(4)in the hybrid Co_(3)S_(4)-p LF is beneficial to the electrocatalytic process.This work will shed light on the development of nature-inspired carbon-based materials in hybrid electrocatalysts for OWS.
基金Supported by the National Natural Science Foundation of China (No. 60572135)
文摘The high dimensions of hyperspectral imagery have caused burden for further processing. A new Fast Independent Component Analysis (FastICA) approach to dimensionality reduction for hyperspectral imagery is presented. The virtual dimensionality is introduced to determine the number of dimensions needed to be preserved. Since there is no prioritization among independent components generated by the FastICA,the mixing matrix of FastICA is initialized by endmembers,which were extracted by using unsupervised maximum distance method. Minimum Noise Fraction (MNF) is used for preprocessing of original data,which can reduce the computational complexity of FastICA significantly. Finally,FastICA is performed on the selected principal components acquired by MNF to generate the expected independent components in accordance with the order of endmembers. Experimental results demonstrate that the proposed method outperforms second-order statistics-based transforms such as principle components analysis.
