New integration method could enable high-performance oxide-based spintronic devices on silicon substrates

Researchers from the Ningbo Institute of Materials Technology and Engineering (NIMTE) of the Chinese Academy of Sciences (CAS) and South China Normal University have proposed a hybrid transfer and epitaxy strategy, enabling the heterogeneous integration of single-crystal oxide spin Hall materials on silicon substrates for high-performance oxide-based spintronic devices.

Heterogeneous integration of single-crystal SrRuO3 films on silicon for spin-orbit torque devices with low-power consumption. Credit: NIMTE

Single-crystal oxide spin Hall materials are known for their exceptional charge-spin conversion efficiency, making them promising candidates for low-power spintronic devices, particularly spin-orbit torque (SOT) devices. However, integrating these materials with silicon substrates poses significant challenges. To address these challenges, the researchers developed a method that combines transfer technology with epitaxial deposition, successfully integrating oxide spin Hall materials onto silicon substrates. Using this approach, they were able to create single-crystal SrRuO3 (SRO) films on silicon substrates and prepare corresponding SOT devices.

 

The SRO film demonstrated a high spin Hall conductivity of 6.1×104 ħ/2e S·m-1, enabling magnetization switching with a low critical current density of 1.3×1010 A·m-2 in the SOT devices.

Furthermore, multi-state magnetization switching characteristics were observed, allowing these devices to simulate biological synaptic and neuronal functions. An artificial neural network utilizing these devices achieved an impressive accuracy rate of 88% in image recognition tasks.

This study details a new integration method for silicon-based oxide electronics, showcasing the broad applicability of the hybrid transfer and epitaxy strategy across various oxide material systems. It could advance the development of high-performance silicon-based spintronic devices and hold great potential for low-power electronics and neuromorphic computing applications.

Posted: Apr 25,2025 by Roni Peleg