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Criticality and Neuromorphic Sensing in a Single Memristor.
Ma, Zelin; Chen, Wanjun; Cao, Xucheng; Diao, Shanqing; Liu, Zhiyu; Ge, Jun; Pan, Shusheng.
Afiliação
  • Ma Z; Research Center for Advanced Information Materials (CAIM), Huangpu Research & Graduate School of Guangzhou University, Guangzhou 510555, China.
  • Chen W; Solid State Physics & Material Research Laboratory, School of Physics and Material Science, Guangzhou University, Guangzhou 510006, China.
  • Cao X; Research Center for Advanced Information Materials (CAIM), Huangpu Research & Graduate School of Guangzhou University, Guangzhou 510555, China.
  • Diao S; Solid State Physics & Material Research Laboratory, School of Physics and Material Science, Guangzhou University, Guangzhou 510006, China.
  • Liu Z; Research Center for Advanced Information Materials (CAIM), Huangpu Research & Graduate School of Guangzhou University, Guangzhou 510555, China.
  • Ge J; Solid State Physics & Material Research Laboratory, School of Physics and Material Science, Guangzhou University, Guangzhou 510006, China.
  • Pan S; Research Center for Advanced Information Materials (CAIM), Huangpu Research & Graduate School of Guangzhou University, Guangzhou 510555, China.
Nano Lett ; 23(13): 5902-5910, 2023 Jul 12.
Article em En | MEDLINE | ID: mdl-37326403
Resistive random access memory (RRAM) is an important technology for both data storage and neuromorphic computation, where the dynamics of nanoscale conductive filaments lies at the core of the technology. Here, we analyze the current noise of various silicon-based memristors that involves the creation of a percolation path at the intermediate phase of filament growth. Remarkably, we find that these atomic switching events follow scale-free avalanche dynamics with exponents satisfying the criteria for criticality. We further prove that the switching dynamics are universal and show little dependence on device sizes or material features. Utilizing criticality in memristors, we simulate the functionality of hair cells in auditory sensory systems by observing the frequency selectivity of input stimuli with tunable characteristic frequency. We further demonstrate a single-memristor-based sensing primitive for representation of input stimuli that exceeds the theoretical limits dictated by the Nyquist-Shannon theorem.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Nano Lett Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Nano Lett Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China