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 inInfoMat Vol. 3; no. 2; pp. 212 - 221
Main Authors Wang, Tian‐Yu, Meng, Jia‐Lin, Chen, Lin, Zhu, Hao, Sun, Qing‐Qing, Ding, Shi‐Jin, Bao, Wen‐Zhong, Zhang, David Wei
Format Journal Article
LanguageEnglish
Published Melbourne John Wiley & Sons, Inc 01.02.2021
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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.
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
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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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Snippet The demand of flexible neuromorphic computing electronics is increasing with the rapid development of wearable artificial intelligent devices. The flexible...
Abstract The demand of flexible neuromorphic computing electronics is increasing with the rapid development of wearable artificial intelligent devices. The...
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wiley
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StartPage 212
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
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Finf2.12158
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