Electric-Field-Controlled Altermagnetic Transition for Neuromorphic Computing

TL;DR

This paper demonstrates ultra-low-power electric-field control of altermagnetism in MnTe, enabling programmable resistance states for neuromorphic computing with high pattern recognition accuracy, paving the way for energy-efficient spintronic devices.

Contribution

It introduces strain-mediated electric-field control of altermagnetism in MnTe and applies it to neuromorphic computing, a novel approach for low-power magnetic state manipulation.

Findings

Electric fields modulate Néel temperature in MnTe from 310 to 328 K.

Reversible switching of altermagnetic spin splitting is achieved.

Neuromorphic network attains 100% pattern recognition accuracy at <=40% noise.

Abstract

Altermagnets represent a novel magnetic phase with transformative potential for ultrafast spintronics, yet efficient control of their magnetic states remains challenging. We demonstrate an ultra-low-power electric-field control of altermagnetism in MnTe through strain-mediated coupling in MnTe/PMN-PT heterostructures with negligible Joule heating. Application of +6 kV/cm electric fields induces piezoelectric strain in PMN-PT, modulating the N\'eel temperature from 310 to 328 K. As a result, around the magnetic phase transition, the altermagnetic spin splitting of MnTe is reversibly switched "on" and "off" by the electric fields. Meanwhile, the piezoelectric strain generates lattice distortions and magnetic structure changes in MnTe, enabling up to 9.7% resistance modulation around the magnetic phase transition temperature. Leveraging this effect, we implement programmable resistance states in a Hopfield neuromorphic network, achieving 100% pattern recognition accuracy at <=40% noise levels. This approach establishes the electric-field control as a low-power strategy for altermagnetic manipulation while demonstrating the viability of altermagnetic materials for energy-efficient neuromorphic computing beyond conventional charge-based architectures.