Memristors have received much attention for their ability to achieve multi-level storage and synaptic learning.However,the main factor that hinders the application of memristors to simulate neural synapses is the inst...Memristors have received much attention for their ability to achieve multi-level storage and synaptic learning.However,the main factor that hinders the application of memristors to simulate neural synapses is the instability of the formation and breakage of conductive filaments inside traditional memristors,which makes it difficult to simulate the function of biological synapses in practice.However,the resistance change of ferroelectric memristors relies on the polarization inversion of the ferroelectric thin film,thus avoiding the above problem.In this study,a Pd/HfAlO/LSMO/STO/Si ferroelectric memristor is proposed,which can achieve resistive switching properties through the combined action of ferroelectricity and oxygen vacancies.The I−V curves show that the device has good stability and uniformity.In addition,the effect of pulse sequence modulation on the conductance was investigated,and the biological synaptic function and learning behavior were simulated successfully.The results of the above studies provide a basis for the development of ferroelectric memristors with neurosynaptic-like behaviors.展开更多
As the emerging member of zero-dimension transition metal dichalcogenide,WSe2 quantum dots(QDs)have been applied to memristors and exhibited better resistance switching characteristics and miniaturization size.However...As the emerging member of zero-dimension transition metal dichalcogenide,WSe2 quantum dots(QDs)have been applied to memristors and exhibited better resistance switching characteristics and miniaturization size.However,low power consumption and high reliability are still challenges for WSe_(2) QDs-based memristors as synaptic devices.展开更多
A huge amount of data requires the non-volatile memory(NVM)technology to exhibit large-capacity storage and fast calculation speed.To further solve the bottleneck of storage capacity and speed,nano-memristors based on...A huge amount of data requires the non-volatile memory(NVM)technology to exhibit large-capacity storage and fast calculation speed.To further solve the bottleneck of storage capacity and speed,nano-memristors based on two-dimensional(2D)layered materials are expected to realize NVM.This study proposes the fabrication of an Ag/2D-TiOx/Pt high-performance memristor device based on the 2D titania nanosheet material.The device demonstrates stable electrical characteristics under the direct current(DC)mode,including bipolar resistive switching(RS)behavior,multi-level memristive modes,and retention property.Also,it exhibits low switching voltage(0.42 V/–0.2 V),high R_(OFF)/R_(ON)resistance ratio(105),low switching power(10–9 W/10−5 W),and fast response speed.More importantly,the device realizes information encoding and decoding through a multi-level storage performed by different compliance currents.Multiple devices are connected to the actual circuit to realize a storage function with information processing and programmable characteristics.This work provides a powerful platform for the 2D titania nanosheet application in NVM and information processing.展开更多
Realization of functional flexible artificial synapse is a significant step toward neuromorphic computing.Herein,a flexible artificial synapse based on ferroelectric tunnel junctions(FTJs)is demonstrated,using BiFeO_(...Realization of functional flexible artificial synapse is a significant step toward neuromorphic computing.Herein,a flexible artificial synapse based on ferroelectric tunnel junctions(FTJs)is demonstrated,using BiFeO_(3)(BFO)thin film as the functional layer.The inorganic single crystalline FTJs grown on rigid perovskite substrates at high temperatures are integrated with the flexible plastic substrates,by using the water-soluble Sr_(3)Al_(2)O_(6)(SAO)as the sacrificial layer and the following transfer.The transferred freestanding BFO thin film exhibits excellent ferroelectric properties.Moreover,the memristive properties and the brain-like synaptic learning performance of the flexible FTJs are investigated.The results show that multilevel resistance states were maintained well of the flexible artificial synapse,together with their stable synaptic learning properties.Our work indicates the promising opportunity of ferroelectric thin film based flexible synapse used in the future neuromorphic computing system.展开更多
Diffusion tensor imaging(DTI)provides a unique method to reveal the integrity of white matter microstructure noninvasively.Voxel-based analysis(VBA),which is a highly reproducible and user-independent technique,has be...Diffusion tensor imaging(DTI)provides a unique method to reveal the integrity of white matter microstructure noninvasively.Voxel-based analysis(VBA),which is a highly reproducible and user-independent technique,has been used to analyze DTI data in a number of studies.Fractional anisotropy(FA),which is derived from DTI,is the most frequently used parameter.The parameter setting during the DTI data preprocessing might affect the FA analysis results.However,there is no reliable evidence on how the parameters affect the results of FA analysis.This study sought to quantitatively investigate the factors that might affect the voxel-based analysis of FA;these include the interpolation during spatial normalization,smoothing kernel and statistical threshold.Because it is difficult to obtain the true information of the lesion in the patients,we simulated lesions on the healthy FA maps.The DTI data were obtained from 20 healthy subjects.The FA maps were calculated using DTIStudio.We randomly divided these FA maps into two groups.One was used as a model patient group,and the other was used as a normal control group.Simulated lesions were added to the model patient group by decreasing the FA intensities in a specified region by 5%–50%.The model patient group and the normal control group were compared by two-sample t test statistic analysis voxelby-voxel to detect the simulated lesions.We evaluated these factors by comparing the difference between the detected lesion through VBA and the simulated lesion.The result showed that the space normalization of FA image should use the trilinear interpolation,and the smoothing kernel should be 2–3 times the voxel size of spatially normalized FA image.For lesions with small intensity change,FWE correction must be cautiously used.This study provided an important reference to the analysis of FA with VBA method.展开更多
基金supported by the National Key R&D Plan“Nano Frontier”Key Special Project(2021YFA1200502)the National Natural Science Foundation of China(62004056,61874158,and 62104058)+12 种基金the Cultivation Projects of National Major R&D Project(92164109)the Special Project of Strategic Leading Science and Technology of Chinese Academy of Sciences(XDB44000000-7)Hebei Basic Research Special Key Project(F2021201045)the Support Program for the Top Young Talents of Hebei Province(70280011807)the Supporting Plan for 100 Excellent Innovative Talents in Colleges and Universities of Hebei Province(SLRC2019018)the Interdisciplinary Research Program of Natural Science of Hebei University(DXK202101)the Institute of Life Sciences and Green Development(521100311)the Natural Science Foundation of Hebei Province(F2022201054 and F2021201022)the Outstanding Young Scientific Research and Innovation Team of Hebei University(605020521001)the Special Support Funds for National High Level Talents(041500120001)the Advanced Talents Incubation Program of the Hebei University(521000981426,521100221071,and 521000981363)the Science and Technology Project of Hebei Education Department(QN2020178 and QN2021026)Baoding Science and Technology Plan Project(2172P011)。
基金financially supported by the National Natural Science Foundation of China(61674050,62004056,and 61874158)the Project of Distinguished Young of Hebei Province(A2018201231)+7 种基金the Support Program for the Top Young Talents of Hebei Province(70280011807)the Hundred Persons Plan of Hebei Province(E2018050004 and E2018050003)the Supporting Plan for 100 Excellent Innovative Talents in Colleges and Universities of Hebei Province(SLRC2019018)the Special Project of Strategic Leading Science and Technology of Chinese Academy of Sciences(XDB44000000-7)the Special Support Funds for National High Level Talents(041500120001)Hebei Basic Research Special Key Project(F2021201045)the Science and Technology Project of Hebei Education Department(QN2020178 and QN2021026)Singapore Ministry of Education(Ac RF TIER 2-MOE2019-T2-2-075)。
基金supported by the Natural Science Foundation of Hebei Province (No.F2021201009)the National Natural Science Foundation of China (No.62104058)+3 种基金the Natural Science Foundation of Hebei Province (No.F2021201022)the Science and Technology Project of Hebei Education Department (No.QN2020178)the Foundation of President of Hebei University (No.XZJJ201910)Advanced Talents Incubation Program of the Hebei University (No.521000981362).
文摘Memristors have received much attention for their ability to achieve multi-level storage and synaptic learning.However,the main factor that hinders the application of memristors to simulate neural synapses is the instability of the formation and breakage of conductive filaments inside traditional memristors,which makes it difficult to simulate the function of biological synapses in practice.However,the resistance change of ferroelectric memristors relies on the polarization inversion of the ferroelectric thin film,thus avoiding the above problem.In this study,a Pd/HfAlO/LSMO/STO/Si ferroelectric memristor is proposed,which can achieve resistive switching properties through the combined action of ferroelectricity and oxygen vacancies.The I−V curves show that the device has good stability and uniformity.In addition,the effect of pulse sequence modulation on the conductance was investigated,and the biological synaptic function and learning behavior were simulated successfully.The results of the above studies provide a basis for the development of ferroelectric memristors with neurosynaptic-like behaviors.
基金This work was financially supported by the National Natural Science Foundation of China(No.62104058)the Natural Science Foundation of Hebei Province(No.F2021201022)+14 种基金the Science and Technology Project of Hebei Education Department(No.QN2020178)the Advanced Talents Incubation Program of the Hebei University(No.521000981363)This work was also supported by the National Key R&D Plan“Nano Frontier”Key Special Project(No.2021YFA1200502)Cultivation Projects of National Major R&D Project(No.92164109)National Natural Science Foundation of China(Nos.61874158 and 62004056)Special Project of Strategic Leading Science and Technology of Chinese Academy of Sciences(No.XDB44000000-7)HebeiBasic Research Special KeyProject(No.F2021201045)the Support Program for the Top Young Talents of Hebei Province(No.70280011807)the Supporting Plan for 100 Excellent Innovative Talents in Colleges and Universities of Hebei Province(No.SLRC2019018)Outstanding Young Scientific Research and Innovation Team of Hebei University(No.605020521001)Special Support Funds for National High Level Talents(No.041500120001)High-level Talent Research Startup Project of Hebei University(No.521000981426)the Science and Technology Project of Hebei Education Department(No.QN2021026)the Advanced Talents Incubation Program of the Hebei University(No.521000981426)the Natural Science Foundation of Hebei Province(No.F2021201009).
文摘As the emerging member of zero-dimension transition metal dichalcogenide,WSe2 quantum dots(QDs)have been applied to memristors and exhibited better resistance switching characteristics and miniaturization size.However,low power consumption and high reliability are still challenges for WSe_(2) QDs-based memristors as synaptic devices.
基金financially supported by the National Key R&D Plan“Nano Frontier”Key Special Project(2021YFA1200502)the Cultivation Projects of National Major R&D Project(92164109)+9 种基金the National Natural Science Foundation of China(61874158,62004056 and 62104058)the Special Project of Strategic Leading Science and Technology of Chinese Academy of Sciences(XDB44000000-7)Hebei Basic Research Special Key Project(F2021201045)the Support Program for the Top Young Talents of Hebei Province(70280011807)the Supporting Plan for 100 Excellent Innovative Talents in Colleges and Universities of Hebei Province(SLRC2019018)the Outstanding Young Scientific Research and Innovation Team of Hebei University(605020521001)the Special Support Funds for National High Level Talents(041500120001)the High-level Talent Research Startup Project of Hebei University(521000981426)the Science and Technology Project of Hebei Education Department(QN2020178 and QN2021026)the Post-graduate’s Innovation Fund Project of Hebei Province(CXZZBS2022020)。
基金financially supported by the National Natural Science Foundation of China(61674050 and 61874158)the Project of Distinguished Youth of Hebei Province(A2018201231)+5 种基金the Hundred Persons Plan of Hebei Province(E2018050004 and E2018050003)the Supporting Plan for 100 Excellent Innovative Talents in Colleges and Universities of Hebei Province(SLRC2019018)the Special Project of Strategic Leading Science and Technology of Chinese Academy of Sciences(XDB44000000-7)the Outstanding Young Scientific Research and Innovation Team of Hebei Universitythe Highlevel Talent Research Startup Project of Hebei University(521000981426)the Special Support Funds for National High Level Talents(041500120001 and 521000981429)。
基金supported by the National Natural Science Foundation of China(61674050 and 61874158)the Outstanding Youth Funding of Hebei University(A2018201231)+2 种基金the Support Program for the Top Young Talents of Hebei Province(70280011807)the Hundred Persons Plan of Hebei Province(E2018050004 and E2018050003)the Supporting Plan for 100 Excellent Innovative Talents in Colleges and Universities of Hebei Province(SLRC2019018)。
基金the National Key R&D Program of China(No.2021YFA1200502)Cultivation Projects of National Major R&D Project(No.92164109)+12 种基金the National Natural Science Foundation of China(Nos.61674050 and 61874158)Special Project of Strategic Leading Science and Technology of Chinese Academy of Sciences(No.XDB44000000-7)Hebei Basic Research Special Key Project(No.F2021201045)the Project of Distinguished Young of Hebei Province(No.A2018201231)the Support Program for the Top Young Talents of Hebei Province(No.70280011807)the Hundred Persons Plan of Hebei Province(Nos.E2018050004 and E2018050003)the Supporting Plan for 100 Excellent Innovative Talents in Colleges and Universities of Hebei Province(No.SLRC2019018)Outstanding Young Scientific Research and Innovation Team of Hebei University(No.605020521001)Special Support Funds for National High Level Talents(No.041500120001)High-level Talent Research Startup Project of Hebei University(No.521000981426)Funded by Science and Technology Project of Hebei Education Department(Nos.QN2020178 and QN2021026)Interdisciplinary Key Research Program of Natural Science of Hebei University(No.DXK202101)Project of Institute of Life Sciences and Green Development(No.521100311).
文摘A huge amount of data requires the non-volatile memory(NVM)technology to exhibit large-capacity storage and fast calculation speed.To further solve the bottleneck of storage capacity and speed,nano-memristors based on two-dimensional(2D)layered materials are expected to realize NVM.This study proposes the fabrication of an Ag/2D-TiOx/Pt high-performance memristor device based on the 2D titania nanosheet material.The device demonstrates stable electrical characteristics under the direct current(DC)mode,including bipolar resistive switching(RS)behavior,multi-level memristive modes,and retention property.Also,it exhibits low switching voltage(0.42 V/–0.2 V),high R_(OFF)/R_(ON)resistance ratio(105),low switching power(10–9 W/10−5 W),and fast response speed.More importantly,the device realizes information encoding and decoding through a multi-level storage performed by different compliance currents.Multiple devices are connected to the actual circuit to realize a storage function with information processing and programmable characteristics.This work provides a powerful platform for the 2D titania nanosheet application in NVM and information processing.
基金the National Natural Science Foundation of China(No.62004056)the Hundred Persons Plan of Hebei Province(Nos.E2018050004 and E2018050003)+5 种基金This work was also supported by National Natural Science Foundation of China(Nos.61674050 and 61874158)the Outstanding Youth Project of Hebei Province(No.F2016201220)the Project of Distinguished Young of Hebei Province(No.A2018201231)he Support Program for the Top Young Talents of Hebei Province(No.70280011807)the Training and Introduction of High-level Innovative Talents of Hebei University(No.801260201300)the Supporting Plan for 100 Excellent Innovative Talents in Colleges and Universities of Hebei Province(No.SLRC2019018).
文摘Realization of functional flexible artificial synapse is a significant step toward neuromorphic computing.Herein,a flexible artificial synapse based on ferroelectric tunnel junctions(FTJs)is demonstrated,using BiFeO_(3)(BFO)thin film as the functional layer.The inorganic single crystalline FTJs grown on rigid perovskite substrates at high temperatures are integrated with the flexible plastic substrates,by using the water-soluble Sr_(3)Al_(2)O_(6)(SAO)as the sacrificial layer and the following transfer.The transferred freestanding BFO thin film exhibits excellent ferroelectric properties.Moreover,the memristive properties and the brain-like synaptic learning performance of the flexible FTJs are investigated.The results show that multilevel resistance states were maintained well of the flexible artificial synapse,together with their stable synaptic learning properties.Our work indicates the promising opportunity of ferroelectric thin film based flexible synapse used in the future neuromorphic computing system.
基金supported by the National Natural Science Foundation of China(81201147,91232713)the XieJialin Foundation of IHEP(3546370U2)foundation of IHEP(Y2515580U1)
文摘Diffusion tensor imaging(DTI)provides a unique method to reveal the integrity of white matter microstructure noninvasively.Voxel-based analysis(VBA),which is a highly reproducible and user-independent technique,has been used to analyze DTI data in a number of studies.Fractional anisotropy(FA),which is derived from DTI,is the most frequently used parameter.The parameter setting during the DTI data preprocessing might affect the FA analysis results.However,there is no reliable evidence on how the parameters affect the results of FA analysis.This study sought to quantitatively investigate the factors that might affect the voxel-based analysis of FA;these include the interpolation during spatial normalization,smoothing kernel and statistical threshold.Because it is difficult to obtain the true information of the lesion in the patients,we simulated lesions on the healthy FA maps.The DTI data were obtained from 20 healthy subjects.The FA maps were calculated using DTIStudio.We randomly divided these FA maps into two groups.One was used as a model patient group,and the other was used as a normal control group.Simulated lesions were added to the model patient group by decreasing the FA intensities in a specified region by 5%–50%.The model patient group and the normal control group were compared by two-sample t test statistic analysis voxelby-voxel to detect the simulated lesions.We evaluated these factors by comparing the difference between the detected lesion through VBA and the simulated lesion.The result showed that the space normalization of FA image should use the trilinear interpolation,and the smoothing kernel should be 2–3 times the voxel size of spatially normalized FA image.For lesions with small intensity change,FWE correction must be cautiously used.This study provided an important reference to the analysis of FA with VBA method.
