Flexible 3D memristor array for binary storage and multi‐states neuromorphic computing applications
The demand of flexible neuromorphic computing electronics is increasing with the rapid development of wearable artificial intelligent devices. The flexible resistive random‐access memory (RRAM) is one excellent candidate of high‐density storage devices. However, due to the limitations of fabrication...
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Published in | InfoMat Vol. 3; no. 2; pp. 212 - 221 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
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Melbourne
John Wiley & Sons, Inc
01.02.2021
Wiley |
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Abstract | The demand of flexible neuromorphic computing electronics is increasing with the rapid development of wearable artificial intelligent devices. The flexible resistive random‐access memory (RRAM) is one excellent candidate of high‐density storage devices. However, due to the limitations of fabrication process, materials system and device structure, it is difficult to prepare flexible 3D high‐density network for neuromorphic computing. In this paper, a 3D flexible memristors network is developed via low‐temperature atomic layer deposition (ALD) at 130°C, with potential of extending to various flexible electronics. The typical bipolar switching characteristics are verified in RRAM units of 3D network, including first, second and third layers. Besides binary storage, the multibit storage in single unit is demonstrated and the storage density is further increased. As a connection link between binary storage and brain‐inspired neuromorphic computing, the multibit storage capability paves the way for the tunable synaptic plasticity, for example, long‐term potentiation/depression (LTP/LTD). The 3D memristors network successfully mimicked the typical neuromorphic functionality and realized ultra‐multi conductance states modulation under 600 spikes. The robust mechanical flexibility is further demonstrated via LTP/LTD emulation under bending states (radius = 10 mm). The 3D flexible memristors network shows significant potential of applications in high‐performance, high‐density and reliable wearable neuromorphic computing system.
The 3D flexible memristors array consists of three‐layer crossbar structure, where the resistive random‐access memory (RRAM) of first, second and third layers correspond to top, middle and bottom units, respectively. The single unit in every cross point is a metal‐insulator‐metal (MIM) based RRAM and the final 3D structure is formed by stacking the crossbar structure on the flexible substrate. With the compliance current of 400 μA, first, second and third‐layer units all exhibit typical bipolar resistive switching curves, indicating the high‐density storage capability of the 3D memristors array via 3D structure design. |
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AbstractList | Abstract The demand of flexible neuromorphic computing electronics is increasing with the rapid development of wearable artificial intelligent devices. The flexible resistive random‐access memory (RRAM) is one excellent candidate of high‐density storage devices. However, due to the limitations of fabrication process, materials system and device structure, it is difficult to prepare flexible 3D high‐density network for neuromorphic computing. In this paper, a 3D flexible memristors network is developed via low‐temperature atomic layer deposition (ALD) at 130°C, with potential of extending to various flexible electronics. The typical bipolar switching characteristics are verified in RRAM units of 3D network, including first, second and third layers. Besides binary storage, the multibit storage in single unit is demonstrated and the storage density is further increased. As a connection link between binary storage and brain‐inspired neuromorphic computing, the multibit storage capability paves the way for the tunable synaptic plasticity, for example, long‐term potentiation/depression (LTP/LTD). The 3D memristors network successfully mimicked the typical neuromorphic functionality and realized ultra‐multi conductance states modulation under 600 spikes. The robust mechanical flexibility is further demonstrated via LTP/LTD emulation under bending states (radius = 10 mm). The 3D flexible memristors network shows significant potential of applications in high‐performance, high‐density and reliable wearable neuromorphic computing system. The demand of flexible neuromorphic computing electronics is increasing with the rapid development of wearable artificial intelligent devices. The flexible resistive random‐access memory (RRAM) is one excellent candidate of high‐density storage devices. However, due to the limitations of fabrication process, materials system and device structure, it is difficult to prepare flexible 3D high‐density network for neuromorphic computing. In this paper, a 3D flexible memristors network is developed via low‐temperature atomic layer deposition (ALD) at 130°C, with potential of extending to various flexible electronics. The typical bipolar switching characteristics are verified in RRAM units of 3D network, including first, second and third layers. Besides binary storage, the multibit storage in single unit is demonstrated and the storage density is further increased. As a connection link between binary storage and brain‐inspired neuromorphic computing, the multibit storage capability paves the way for the tunable synaptic plasticity, for example, long‐term potentiation/depression (LTP/LTD). The 3D memristors network successfully mimicked the typical neuromorphic functionality and realized ultra‐multi conductance states modulation under 600 spikes. The robust mechanical flexibility is further demonstrated via LTP/LTD emulation under bending states (radius = 10 mm). The 3D flexible memristors network shows significant potential of applications in high‐performance, high‐density and reliable wearable neuromorphic computing system. image The demand of flexible neuromorphic computing electronics is increasing with the rapid development of wearable artificial intelligent devices. The flexible resistive random‐access memory (RRAM) is one excellent candidate of high‐density storage devices. However, due to the limitations of fabrication process, materials system and device structure, it is difficult to prepare flexible 3D high‐density network for neuromorphic computing. In this paper, a 3D flexible memristors network is developed via low‐temperature atomic layer deposition (ALD) at 130°C, with potential of extending to various flexible electronics. The typical bipolar switching characteristics are verified in RRAM units of 3D network, including first, second and third layers. Besides binary storage, the multibit storage in single unit is demonstrated and the storage density is further increased. As a connection link between binary storage and brain‐inspired neuromorphic computing, the multibit storage capability paves the way for the tunable synaptic plasticity, for example, long‐term potentiation/depression (LTP/LTD). The 3D memristors network successfully mimicked the typical neuromorphic functionality and realized ultra‐multi conductance states modulation under 600 spikes. The robust mechanical flexibility is further demonstrated via LTP/LTD emulation under bending states (radius = 10 mm). The 3D flexible memristors network shows significant potential of applications in high‐performance, high‐density and reliable wearable neuromorphic computing system. The 3D flexible memristors array consists of three‐layer crossbar structure, where the resistive random‐access memory (RRAM) of first, second and third layers correspond to top, middle and bottom units, respectively. The single unit in every cross point is a metal‐insulator‐metal (MIM) based RRAM and the final 3D structure is formed by stacking the crossbar structure on the flexible substrate. With the compliance current of 400 μA, first, second and third‐layer units all exhibit typical bipolar resistive switching curves, indicating the high‐density storage capability of the 3D memristors array via 3D structure design. |
Author | Meng, Jia‐Lin Bao, Wen‐Zhong Chen, Lin Sun, Qing‐Qing Wang, Tian‐Yu Zhang, David Wei Ding, Shi‐Jin Zhu, Hao |
Author_xml | – sequence: 1 givenname: Tian‐Yu surname: Wang fullname: Wang, Tian‐Yu organization: Fudan University – sequence: 2 givenname: Jia‐Lin surname: Meng fullname: Meng, Jia‐Lin organization: Fudan University – sequence: 3 givenname: Lin orcidid: 0000-0002-7145-7564 surname: Chen fullname: Chen, Lin email: linchen@fudan.edu.cn organization: Fudan University – sequence: 4 givenname: Hao surname: Zhu fullname: Zhu, Hao organization: Fudan University – sequence: 5 givenname: Qing‐Qing surname: Sun fullname: Sun, Qing‐Qing email: qqsun@fudan.edu.cn organization: Fudan University – sequence: 6 givenname: Shi‐Jin surname: Ding fullname: Ding, Shi‐Jin organization: Fudan University – sequence: 7 givenname: Wen‐Zhong surname: Bao fullname: Bao, Wen‐Zhong organization: Fudan University – sequence: 8 givenname: David Wei surname: Zhang fullname: Zhang, David Wei organization: Fudan University |
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Notes | Funding information National Natural Science Foundation of China, Grant/Award Numbers: 61522404, 61704030; Program of Shanghai Subject Chief Scientist, Grant/Award Number: 18XD1402800; Shanghai Rising‐Star Program, Grant/Award Number: 19QA1400600; Support Plans for the Youth Top‐Notch Talents of China Tian‐Yu Wang and Jia‐Lin Meng equally contributed to this work. |
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SubjectTerms | 3D crossbar brain‐inspired computing flexible memory low‐temperature ALD multilevel storage |
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Title | Flexible 3D memristor array for binary storage and multi‐states neuromorphic computing applications |
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