Heterojunction construction,especially S-scheme heterojunction,represents an efficient universal strategy to achieve high-performance photocatalytic materials.For further performance stimulation of these well-designed...Heterojunction construction,especially S-scheme heterojunction,represents an efficient universal strategy to achieve high-performance photocatalytic materials.For further performance stimulation of these well-designed heterojunctions,modulating the interfacial internal electric field(IEF)to steer dynamic charge transfer represents a promising approach.Herein,we realized the precise regulation of Fermi level(E_(F))of the oxidation semiconductor(mesoporous WO_(3-x))by tailoring the concentration of oxygen vacancies(V_(O)),maximizing the IEF intensity in Cs_(2)CuBr_(4)@WO_(3-x)(CCB@WO_(3-x))S-scheme heterojunction.The augmented IEF affords a robust driving force for directional electron delivery,leading to boosted charge separation.Hence,the developed CCB@WO_(3-x)S-scheme heterojunction demonstrated outstanding photocatalytic CO_(2)reduction performance,with the electron consumption rate(Relectron)up to 390.34μmol g^(-1)h^(-1),which is 3.28 folds higher than that of pure CCB.An in-depth analysis of the S-scheme electron transfer mode was presented via theoretical investigations,electron spin resonance(ESR),photo-irradiated Kelvin probe force microscopy(KPFM),and in-situ X-ray photoelectron spectroscopy(XPS).Finally,the CO_(2)photoconversion route was explored in detail using in-situ diffuse reflectance infrared Fourier transform spectroscopy(DRIFTS)and DFT theoretical calculations.展开更多
Traditional transistors confront severe challenges of insufficient computing capability and excessive power consumption in large-scale neuromorphic systems.To address these critical bottlenecks,we propose an optoelect...Traditional transistors confront severe challenges of insufficient computing capability and excessive power consumption in large-scale neuromorphic systems.To address these critical bottlenecks,we propose an optoelectronic memristor based on zinc oxide-indium tin oxide/tungsten oxide(ZnO-ITO/WO_(3-x))heterojunctions as a promising solution.Through applying different types of electrical and optical signals,the device successfully emulates diverse synaptic functions including short-term/long-term synaptic plasticity,alongside short-term and long-term memory.Introducing the ZnO-ITO functional layer enhances the photoresponse of the WO_(3-x)-based memristor and demonstrates“learning-forgetting-relearning”behavior under optical modulation.Furthermore,based on the photoelectric cooperative memristor array,a convolutional neural network for vehicle type recognition is constructed,which solves the problem of zero weight and negative weight complexity.In regard to energy efficiency,the neural network built with this device operates at a power level of only 10^(-3)W,representing a reduction of more than 4 orders of magnitude compared with a standard central processor.Hence,the photoelectric memristor proposed in this work provides a new idea for neuromorphic computing and is expected to promote the development of energy-efficient brain-like computing.展开更多
基金This work was financially supported by the National Natural Science Foundation of China(51972213)Natural Science Foundation of Shanghai(22ZR1460700).
文摘Heterojunction construction,especially S-scheme heterojunction,represents an efficient universal strategy to achieve high-performance photocatalytic materials.For further performance stimulation of these well-designed heterojunctions,modulating the interfacial internal electric field(IEF)to steer dynamic charge transfer represents a promising approach.Herein,we realized the precise regulation of Fermi level(E_(F))of the oxidation semiconductor(mesoporous WO_(3-x))by tailoring the concentration of oxygen vacancies(V_(O)),maximizing the IEF intensity in Cs_(2)CuBr_(4)@WO_(3-x)(CCB@WO_(3-x))S-scheme heterojunction.The augmented IEF affords a robust driving force for directional electron delivery,leading to boosted charge separation.Hence,the developed CCB@WO_(3-x)S-scheme heterojunction demonstrated outstanding photocatalytic CO_(2)reduction performance,with the electron consumption rate(Relectron)up to 390.34μmol g^(-1)h^(-1),which is 3.28 folds higher than that of pure CCB.An in-depth analysis of the S-scheme electron transfer mode was presented via theoretical investigations,electron spin resonance(ESR),photo-irradiated Kelvin probe force microscopy(KPFM),and in-situ X-ray photoelectron spectroscopy(XPS).Finally,the CO_(2)photoconversion route was explored in detail using in-situ diffuse reflectance infrared Fourier transform spectroscopy(DRIFTS)and DFT theoretical calculations.
基金supported by the National Natural Science Foundation of China(62174068,62311540155,62174068,and 61804063)Jinan City-University Integrated Development Strategy Project(JNSX2023017)+2 种基金Taishan Scholars Project Special Funds(tsqn202312035)the National Key Research and Development Program of China(2019YFA0705900)funded by MOSTthe Natural Science Foundation of Jilin Province(20220201070GX)。
文摘Traditional transistors confront severe challenges of insufficient computing capability and excessive power consumption in large-scale neuromorphic systems.To address these critical bottlenecks,we propose an optoelectronic memristor based on zinc oxide-indium tin oxide/tungsten oxide(ZnO-ITO/WO_(3-x))heterojunctions as a promising solution.Through applying different types of electrical and optical signals,the device successfully emulates diverse synaptic functions including short-term/long-term synaptic plasticity,alongside short-term and long-term memory.Introducing the ZnO-ITO functional layer enhances the photoresponse of the WO_(3-x)-based memristor and demonstrates“learning-forgetting-relearning”behavior under optical modulation.Furthermore,based on the photoelectric cooperative memristor array,a convolutional neural network for vehicle type recognition is constructed,which solves the problem of zero weight and negative weight complexity.In regard to energy efficiency,the neural network built with this device operates at a power level of only 10^(-3)W,representing a reduction of more than 4 orders of magnitude compared with a standard central processor.Hence,the photoelectric memristor proposed in this work provides a new idea for neuromorphic computing and is expected to promote the development of energy-efficient brain-like computing.
