Multiferroic neuromorphic computation devices

被引:1
|
作者
Lu, Guangming [1 ]
Salje, Ekhard K. H. [2 ]
机构
[1] Yantai Univ, Sch Environm & Mat Engn, Yantai 264005, Peoples R China
[2] Univ Cambridge, Dept Earth Sci, Cambridge CB2 3EQ, England
来源
APL MATERIALS | 2024年 / 12卷 / 06期
基金
中国国家自然科学基金; 英国工程与自然科学研究理事会;
关键词
FERROELASTIC MATERIALS; DOMAIN BOUNDARIES; PHASE-TRANSITION; TWIN WALLS; X-RAY; FLEXOELECTRICITY; VORTICES; POLARITY;
D O I
10.1063/5.0216849
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
Neuromorphic computation is based on memristors, which function equivalently to neurons in brain structures. These memristors can be made more efficient and tailored to neuromorphic devices by using ferroelastic domain boundaries as fast diffusion paths for ionic conduction, such as of oxygen, sodium, or lithium. In this paper, we show that the local memristor generates a second, unexpected feature, namely, weak magnetic fields that emerge from moving ferroelastic needle domains and vortices. The vortices appear near ferroelastic "junctions" that are common when the external stimulus is a combination of electric fields and structural phase transitions. Many ferroelastic materials show such phase transitions near room temperatures so that device applications display a "multiferroic" scenario where the memristor is driven electrically and read magnetically. Our computer simulation study of an elastic spring model suggests magnetic fields in the order of 10(-7) T, which opens the way for a fundamentally new way of running neuromorphic devices. The magnetism in such devices emerges entirely from intrinsic displacement currents and not from any intrinsic magnetism of the material.
引用
收藏
页数:6
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