用于神经形态计算的电场控制的变磁转换
Zhiyuan Duan1,2, Peixin Qin1,2, Chengyan Zhong3
1School of Materials Science and Engineering, Beihang University; Beijing 100191, China.
Journal of the American Chemical Society
|December 11, 2025
概括
研究人员使用超低功率电场控制MnTe的变磁性. 这使得磁态的高效操纵能够用于节能的神经形态计算应用.
科学领域:
- 凝聚物质物理学
- 材料科学
- 机器人
背景情况:
- 变磁器是一种新的磁相,
- 有效控制磁变状态至关重要但具有挑战性.
- 现有的方法可能涉及大量的能源消耗.
研究的目的:
- 为了证明在MnTe中超低功率的电场控制.
- 探索压力介导合用于操纵磁性状态.
- 在神经形态计算中研究变磁材料的应用.
主要方法:
- 制造MnTe/PMN-PT异构结构
- 应用电场来诱导压电应变.
- 测量磁相过渡温度和电阻调制.
- 在Hopfield神经形态网络中实现.
主要成果:
- 在电场控制过程中微不足道的焦尔加热.
- 通过应变调节尼尔温度 (310K至328K).
- 可逆转换的变磁旋转分裂.
- 在磁相转换过程中可达到9.7%的电阻调节.
- 100%的模式识别准确度在一个神经形态网络在40%的噪音.
结论:
- 电场控制是一种可行的低功率策略,
- 在MnTe异构中,压力介导的效应能够显著调节电阻.
- 变磁材料对节能神经形态计算具有前景.
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