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Post-modified ionic metal-organic frameworks regulating the electronic states of Pd NPs to improve nitroaromatic selective catalysis 认领 引用
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作者 Xinyu Gao Qi Wu +7 位作者 Shaobo Jia Yifei Wang Linxia Wang Anyang Li Guoping Yang Chuan Zuo Wenyan Zhang ao-Yu Wang 《Nano Research》 SCIE EI CSCD 2026年第3期159-168,共10页
The selective hydrogenation of nitroaromatics faces challenges such as low selectivity and rapid deactivation of noble metal catalysts.In this study,2-4 nm palladium nanoparticles(Pd NPs)were uniformly loaded into an ... The selective hydrogenation of nitroaromatics faces challenges such as low selectivity and rapid deactivation of noble metal catalysts.In this study,2-4 nm palladium nanoparticles(Pd NPs)were uniformly loaded into an amino-functionalized ionic metalorganic framework(IMOF)via an ion-exchange method,followed by post-modification with electron-withdrawing fluorine atoms.The introduced fluorine atoms effectively modulated the electronic states of Pd NPs and optimized the adsorption of polar functional groups on the catalyst surface,thereby significantly suppressing overhydrogenation side reactions.The optimized Pd@IMOF-F catalyst achieved 99%conversion and>99%selectivity in the hydrogenation of 4-nitrostyrene,with stable performance maintained over seven catalytic cycles.This work provides a novel strategy for precisely regulating the electronic states and local environments of catalytic active centers,offering significant theoretical and practical insights for the design of green chemistry and sustainable catalytic systems. 展开更多
关键词 ionic metal-organic framework selective hydrogenation nitroaromatic electronic modulation
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Neural morphology perception system based on antiferroelectric AgNbO3neurons 认领 引用 被引量：4
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作者 Jianhui Zhao Jiacheng Wang +11 位作者 Jiameng Sun Yiduo Shao Yibo Fan Yifei Pei Zhenyu Zhou Linxia Wang Zhongrong Wang Yong Sun Shukai Zheng Jianxin Guo Lei Zhao Xiaobing Yan 《InfoMat》 SCIE CSCD 2025年第3期86-101,共16页
Biologically inspired neuromorphic perceptual systems have great potential for efficient processing of multisensory signals from the physical world.Recently,artificial neurons constructed by memristor have been develo... Biologically inspired neuromorphic perceptual systems have great potential for efficient processing of multisensory signals from the physical world.Recently,artificial neurons constructed by memristor have been developed with good biological plausibility and density,but the filament-type memristor is limited by undesirable temporal and spatial variations,high electroforming voltage and limited reproducibility and the Mott insulator type memristor suffer from large driving current.Here,we propose a novel antiferroelectric artificial neu-ron(AFEAN)based on the intrinsic polarization and depolarization of AgNbO3(ANO)antiferroelectric(AFE)films to address these challenges.The antiferroelectric memristor exhibits low power consumption(8.99 nW),excel-lent durability(-105)and high stability.Using such an AFEAN,a spike-based antiferroelectric neuromorphic perception system(AFENPS)has been designed,which can encode light level and temperature signals into spikes,and further construct a spiking neural network(SNN)(784×196×10)for optical image classification and thermal imaging classification,achieving 95.34%and 95.76%recognition accuracy on the MNIST dataset,respectively.This work paves the way for the simulation of spiking neurons using antiferro-electric materials and promising a promising method for the development of highly efficient hardware for neuromorphic perception systems. 展开更多
关键词 antiferroelectric memristor antiferroelectric neuron neuromorphic perception system spiking neural networks
HfAlO-based ferroelectric memristors for artificial synaptic plasticity 认领 引用 被引量：3
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作者 Jie Yang Zixuan Jian +11 位作者 Zhongrong Wang Jianhui Zhao Zhenyu Zhou Yong Sun Mengmeng Hao Linxia Wang Pan Liu Jingjuan Wang Yifei Pei Zhen Zhao Wei Wang Xiaobing Yan 《Frontiers of physics》 SCIE CSCD 2023年第6期163-171,共9页
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
关键词 memristor ferroelectric domain polarization resistance regulation artificial synapse
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