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Shaoxuan Zhang

Publications and source records attributed to Shaoxuan Zhang.

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Electric-Field-Controlled Altermagnetic Transition for Neuromorphic Computing

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 Néel 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.

cond-mat.mtrl-sci

Full Electrical Switching of a Freestanding Ferrimagnetic Metal for Energy-Efficient Bipolar Neuromorphic Computing

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.

cond-mat.mes-hall