Domain wall magnetic tunnel junction-based artificial synapses and neurons for all-spin neuromorphic hardware
文献类型：期刊论文
| 作者 | Liu, Long1,2; Wang, Di1,2; Wang, Dandan3; Sun, Yan4; Lin, Huai1,2; Gong, Xiliang4; Zhang, Yifan1,2; Tang, Ruifeng1,2; Mai, Zhihong3; Hou, Zhipeng5 |
| 刊名 | NATURE COMMUNICATIONS
 |
| 出版日期 | 2024-05-28 |
| 卷号 | 15期号:1页码:12 |
| DOI | 10.1038/s41467-024-48631-4 |
| 通讯作者 | Wang, Dandan(wangdandan@jfslab.com.cn) ; Xing, Guozhong(gzxing@ime.ac.cn) ; Liu, Ming(liuming@ime.ac.cn) |
| 英文摘要 | We report a breakthrough in the hardware implementation of energy-efficient all-spin synapse and neuron devices for highly scalable integrated neuromorphic circuits. Our work demonstrates the successful execution of all-spin synapse and activation function generator using domain wall-magnetic tunnel junctions. By harnessing the synergistic effects of spin-orbit torque and interfacial Dzyaloshinskii-Moriya interaction in selectively etched spin-orbit coupling layers, we achieve a programmable multi-state synaptic device with high reliability. Our first-principles calculations confirm that the reduced atomic distance between 5d and 3d atoms enhances Dzyaloshinskii-Moriya interaction, leading to stable domain wall pinning. Our experimental results, supported by visualizing energy landscapes and theoretical simulations, validate the proposed mechanism. Furthermore, we demonstrate a spin-neuron with a sigmoidal activation function, enabling high operation frequency up to 20 MHz and low energy consumption of 508 fJ/operation. A neuron circuit design with a compact sigmoidal cell area and low power consumption is also presented, along with corroborated experimental implementation. Our findings highlight the great potential of domain wall-magnetic tunnel junctions in the development of all-spin neuromorphic computing hardware, offering exciting possibilities for energy-efficient and scalable neural network architectures. The authors demonstrate all-spin synapses and neurons using domain wall-magnetic tunnel junctions, utilizing synergistic spin-orbit torque and Dzyaloshinskii-Moriya interaction. The intrinsic linearity is required for compact and energy-efficient bio-inspired hardware for neuromorphic computing. |
| 资助项目 | National Natural Science Foundation of China (National Science Foundation of China)[2021YFB3601300] ; National Key Research and Development Program of China[92365113] ; National Natural Science Foundation of China[XDB44010000] ; Strategic Priority Research Program of the Chinese Academy of Sciences ; State Key Laboratory of Integrated Chips and Systems of Fudan University ; Information Science Laboratory Center of USTC ; Qingdao Research Institute |
| WOS研究方向 | Science & Technology - Other Topics |
| 语种 | 英语 |
| WOS记录号 | WOS:001234660500028 |
| 出版者 | NATURE PORTFOLIO |
| 资助机构 | National Natural Science Foundation of China (National Science Foundation of China) ; National Key Research and Development Program of China ; National Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences ; State Key Laboratory of Integrated Chips and Systems of Fudan University ; Information Science Laboratory Center of USTC ; Qingdao Research Institute |
| 源URL |  |
| 专题 | 金属研究所_中国科学院金属研究所 |
| 通讯作者 | Wang, Dandan; Xing, Guozhong; Liu, Ming |
| 作者单位 | 1.Chinese Acad Sci, Inst Microelect, Key Lab Fabricat Technol Integrated Circuits, Beijing 100029, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Hubei Jiufengshan Lab, Wuhan 430206, Hubei, Peoples R China 4.Chinese Acad Sci, Inst Met Res, Shenyang Natl Lab Mat Sci, Shenyang 110016, Peoples R China 5.South China Normal Univ, Inst Adv Mat, Guangzhou 510006, Peoples R China 6.ShanghaiTech Univ, Sch Informat Sci & Technol, Shanghai 201210, Peoples R China 7.Univ Sci & Technol China, Sch Microelect, Hefei 230026, Peoples R China 8.Hefei Univ Technol, Sch Phys, Lab Low Dimens Magnetism & Spintron Devices, Hefei 230009, Anhui, Peoples R China 9.Fudan Univ, Frontier Inst Chip & Syst, Zhangjiang Fudan Int Innovat Ctr, State Key Lab Integrated Chips & Syst, Shanghai 200433, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Long,Wang, Di,Wang, Dandan,et al. Domain wall magnetic tunnel junction-based artificial synapses and neurons for all-spin neuromorphic hardware[J]. NATURE COMMUNICATIONS,2024,15(1):12. |
| APA | Liu, Long.,Wang, Di.,Wang, Dandan.,Sun, Yan.,Lin, Huai.,...&Liu, Ming.(2024).Domain wall magnetic tunnel junction-based artificial synapses and neurons for all-spin neuromorphic hardware.NATURE COMMUNICATIONS,15(1),12. |
| MLA | Liu, Long,et al."Domain wall magnetic tunnel junction-based artificial synapses and neurons for all-spin neuromorphic hardware".NATURE COMMUNICATIONS 15.1(2024):12. |
入库方式： OAI收割
来源：金属研究所
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