Full Electrical Switching of a Freestanding Ferrimagnetic Metal for Energy-Efficient Bipolar Neuromorphic Computing
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| Format: | Preprint |
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2025
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| author | Liu, Li Qin, Peixin Wang, Xiang She, Xiaobo Zhang, Shaoxuan Wang, Xiaoning Chen, Hongyu Zhao, Guojian Duan, Zhiyuan Meng, Ziang Zhang, Qinghua Wu, Qiong Liu, Yu Liu, Zhiqi |
| author_facet | Liu, Li Qin, Peixin Wang, Xiang She, Xiaobo Zhang, Shaoxuan Wang, Xiaoning Chen, Hongyu Zhao, Guojian Duan, Zhiyuan Meng, Ziang Zhang, Qinghua Wu, Qiong Liu, Yu Liu, Zhiqi |
| contents | Flexible electronics and neuromorphic computing face key challenges in material integration and function retention. In particular, freestanding membranes suffer from slow sacrificial layer removal and interfacial strain, while neuromorphic hardware often relies on area-intensive dual-device schemes for bipolar synaptic weights. Here, we present a universal strategy based on water-soluble Sr4Al2O7 sacrificial layers, enabling the rapid release of freestanding ferrimagnetic metal membranes, which exhibit deterministic spin-orbit torque switching characteristics with well-preserved perpendicular magnetic anisotropy and are potential for next-generation ultrafast information technology. Extending this approach, we realize single-device ferrimagnetic synapses exhibiting intrinsic bipolar resistive switching. When implemented in a ResNet-18 architecture, these devices achieve 92% accuracy on CIFAR-10 - comparable to floating-point software models - while halving device counts relative to differential-pair implementations. These results establish a scalable platform linking flexible spintronics with compact, high-performance neuromorphic systems, offering foundational advances for next-generation electronics and brain-inspired hardware. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_06669 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Full Electrical Switching of a Freestanding Ferrimagnetic Metal for Energy-Efficient Bipolar Neuromorphic Computing Liu, Li Qin, Peixin Wang, Xiang She, Xiaobo Zhang, Shaoxuan Wang, Xiaoning Chen, Hongyu Zhao, Guojian Duan, Zhiyuan Meng, Ziang Zhang, Qinghua Wu, Qiong Liu, Yu Liu, Zhiqi Mesoscale and Nanoscale Physics Materials Science Applied Physics Flexible electronics and neuromorphic computing face key challenges in material integration and function retention. In particular, freestanding membranes suffer from slow sacrificial layer removal and interfacial strain, while neuromorphic hardware often relies on area-intensive dual-device schemes for bipolar synaptic weights. Here, we present a universal strategy based on water-soluble Sr4Al2O7 sacrificial layers, enabling the rapid release of freestanding ferrimagnetic metal membranes, which exhibit deterministic spin-orbit torque switching characteristics with well-preserved perpendicular magnetic anisotropy and are potential for next-generation ultrafast information technology. Extending this approach, we realize single-device ferrimagnetic synapses exhibiting intrinsic bipolar resistive switching. When implemented in a ResNet-18 architecture, these devices achieve 92% accuracy on CIFAR-10 - comparable to floating-point software models - while halving device counts relative to differential-pair implementations. These results establish a scalable platform linking flexible spintronics with compact, high-performance neuromorphic systems, offering foundational advances for next-generation electronics and brain-inspired hardware. |
| title | Full Electrical Switching of a Freestanding Ferrimagnetic Metal for Energy-Efficient Bipolar Neuromorphic Computing |
| topic | Mesoscale and Nanoscale Physics Materials Science Applied Physics |
| url | https://arxiv.org/abs/2512.06669 |