Probing switching mechanism of memristor for neuromorphic computing
In recent, neuromorphic computing has been proposed to simulate the human brain system to overcome bottlenecks of the von Neumann architecture. Memristors, considered emerging memory devices, can be used to simulate synapses and neurons, which are the key components of neuromorphic computing systems...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2023-01-01
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| Series: | Nano Express |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/2632-959X/acd70c |
| _version_ | 1797813375883804672 |
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| author | Zhe Yang Zirui Zhang Ce Li Dongliang Yang Fei Hui Linfeng Sun |
| author_facet | Zhe Yang Zirui Zhang Ce Li Dongliang Yang Fei Hui Linfeng Sun |
| author_sort | Zhe Yang |
| collection | DOAJ |
| description | In recent, neuromorphic computing has been proposed to simulate the human brain system to overcome bottlenecks of the von Neumann architecture. Memristors, considered emerging memory devices, can be used to simulate synapses and neurons, which are the key components of neuromorphic computing systems. To observe the resistive switching (RS) behavior microscopically and probe the local conductive filaments (CFs) of the memristors, conductive atomic force microscopy (CAFM) with the ultra-high resolution has been investigated, which could be helpful to understand the dynamic processes of synaptic plasticity and the firing of neurons. This review presents the basic working principle of CAFM and discusses the observation methods using CAFM. Based on this, CAFM reveals the internal mechanism of memristors, which is used to observe the switching behavior of memristors. We then summarize the synaptic and neuronal functions assisted by CAFM for neuromorphic computing. Finally, we provide insights into discussing the challenges of CAFM used in the neuromorphic computing system, benefiting the expansion of CAFM in studying neuromorphic computing-based devices. |
| first_indexed | 2024-03-13T07:52:04Z |
| format | Article |
| id | doaj.art-638140e527ee4f978a9b3e6eba7112aa |
| institution | Directory Open Access Journal |
| issn | 2632-959X |
| language | English |
| last_indexed | 2024-03-13T07:52:04Z |
| publishDate | 2023-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Nano Express |
| spelling | doaj.art-638140e527ee4f978a9b3e6eba7112aa2023-06-02T12:26:04ZengIOP PublishingNano Express2632-959X2023-01-014202200110.1088/2632-959X/acd70cProbing switching mechanism of memristor for neuromorphic computingZhe Yang0Zirui Zhang1Ce Li2Dongliang Yang3Fei Hui4Linfeng Sun5https://orcid.org/0000-0001-5851-8206Centre for Quantum Physics, Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurement (MOE), School of Physics, Beijing Institute of Technology , Beijing 100081, People’s Republic of ChinaCentre for Quantum Physics, Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurement (MOE), School of Physics, Beijing Institute of Technology , Beijing 100081, People’s Republic of ChinaCentre for Quantum Physics, Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurement (MOE), School of Physics, Beijing Institute of Technology , Beijing 100081, People’s Republic of ChinaCentre for Quantum Physics, Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurement (MOE), School of Physics, Beijing Institute of Technology , Beijing 100081, People’s Republic of ChinaSchool of Material Science and Engineering, Zhengzhou University , Zhengzhou 450001, People’s Republic of ChinaCentre for Quantum Physics, Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurement (MOE), School of Physics, Beijing Institute of Technology , Beijing 100081, People’s Republic of China; Yangtze Delta Region Academy of Beijing Institute of Technology , Jiaxing 314019, People’s Republic of ChinaIn recent, neuromorphic computing has been proposed to simulate the human brain system to overcome bottlenecks of the von Neumann architecture. Memristors, considered emerging memory devices, can be used to simulate synapses and neurons, which are the key components of neuromorphic computing systems. To observe the resistive switching (RS) behavior microscopically and probe the local conductive filaments (CFs) of the memristors, conductive atomic force microscopy (CAFM) with the ultra-high resolution has been investigated, which could be helpful to understand the dynamic processes of synaptic plasticity and the firing of neurons. This review presents the basic working principle of CAFM and discusses the observation methods using CAFM. Based on this, CAFM reveals the internal mechanism of memristors, which is used to observe the switching behavior of memristors. We then summarize the synaptic and neuronal functions assisted by CAFM for neuromorphic computing. Finally, we provide insights into discussing the challenges of CAFM used in the neuromorphic computing system, benefiting the expansion of CAFM in studying neuromorphic computing-based devices.https://doi.org/10.1088/2632-959X/acd70cneuromorphic computing systemmemristorRSCAFMsynaptic plasticity |
| spellingShingle | Zhe Yang Zirui Zhang Ce Li Dongliang Yang Fei Hui Linfeng Sun Probing switching mechanism of memristor for neuromorphic computing Nano Express neuromorphic computing system memristor RS CAFM synaptic plasticity |
| title | Probing switching mechanism of memristor for neuromorphic computing |
| title_full | Probing switching mechanism of memristor for neuromorphic computing |
| title_fullStr | Probing switching mechanism of memristor for neuromorphic computing |
| title_full_unstemmed | Probing switching mechanism of memristor for neuromorphic computing |
| title_short | Probing switching mechanism of memristor for neuromorphic computing |
| title_sort | probing switching mechanism of memristor for neuromorphic computing |
| topic | neuromorphic computing system memristor RS CAFM synaptic plasticity |
| url | https://doi.org/10.1088/2632-959X/acd70c |
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