Volume 7 Issue 5, May 2024

Non-volatile memory devices capable of recording and reading information at temperatures up to 600 °C can be built using aluminium scandium nitride ferroelectric diodes.

Photoresponsive perovskite light-emitting diodes can be used to build multifunctional displays that can function as touch screens, light sensors and image sensors.

A methodology — called auto tiny classifiers — is proposed to directly generate predictor circuits for the classification of tabular data, searching over the space of combinational logic using an evolutionary algorithm to maximize training prediction accuracy. Prediction performance is comparable to typical machine learning methods, but substantially fewer hardware resources and power are required.

This Review examines the development of van der Waals opto-spintronic devices, highlighting the importance of light–matter interactions in van der Waals magnetic materials and the control of their magnetization via external stimuli, as well as exploring potential opto-spintronic device architectures and applications.

A non-volatile memory device that is based on an aluminium scandium nitride (Al_0.68Sc_0.32N) ferroelectric diode can operate at temperatures of up to 600 °C.

A method for integrating polycrystalline molybdenum disulfide using processes in a 200 mm fab facility can create transistors with high robustness and performance comparable with single-crystalline devices.

Using an intrinsically stretchable nanocomposite of quantum dots, an elastomer and a hole transport polymer as an emissive layer, stretchable light-emitting diodes can be fabricated that exhibit high brightness even under 50% strain.

Photo-responsive metal halide perovskite light-emitting diodes can be used to create a multifunctional display that can function as a touch screen, ambient light sensor and image sensor.

High-density device arrays can be integrated on flexible substrates using a dip-transfer coating method that suppresses adhesive layers from forming between closely spaced devices and uses magnetically self-assembled particles to increase the anisotropic conductivity.

An integrated photonic circuit that is directly embedded on an electronic platform can generate random numbers at a rate of 2 Gbit s⁻¹.

A graph-based genetic programming method can be used to automatically generate small and energy-efficient circuits from tabular data for machine learning classification tasks.