Articles in 2023

Technology breakthroughs at the 2023 IEEE International Electron Devices Meeting, where collaboration and CMOS technology continue to play their part.

This Review examines the development of neuromorphic hardware systems based on halide perovskites, considering how devices based on these materials can serve as synapses and neurons, and can be used in neuromorphic computing networks.

An ultrathin haptic interface can selectively activate different cutaneous receptors in the skin, providing rich haptic sensation information in virtual reality.

Riki Banerjee, vice president of research and development at Synchron, tells Nature Electronics about the company’s work on brain–computer interfaces and the future of communications.

This Review examines the development of thin-film transistors for use in displays, sensors, digital circuits and memory, as well as their potential for future application in emerging technologies such as neuromorphic computing.

For a long time, spin–orbit coupling in bismuthates has been considered to be negligible; however, giant charge-to-spin conversion has now been observed in Ba(Pb,Bi)O₃-based heterostructures. These observations provide a path toward investigating the interplay of hidden spin–orbit phenomena and superconductivity.

A polymer-free method for stacking 2D materials has been demonstrated, using a cantilevered transfer support made from metallized silicon nitride. The assembly process, which is compatible with ultrahigh-vacuum operation, results in atomically clean and uniform interfaces.

A thin elastic conductive nanocomposite that is formed by cryogenically transferring laser-induced graphene to a hydrogel film can be used to create multifunctional sensors for on-skin monitoring and cardiac patches for in vivo detection.

Brain organoids — integrated with electrophysiological recording hardware — can be used to create reservoir computing systems.

An artificial intelligence hardware approach that uses the adaptive reservoir computation of biological neural networks in a brain organoid can perform tasks such as speech recognition and nonlinear equation prediction.

The integration of high-performance n-type and p-type two-dimensional transistors — which can be fabricated on 300 mm wafers using a die-by-die transfer process — is an important step in the lab-to-fab transition of two-dimensional semiconductors.

Stochastic magnetic tunnel junctions can be used to create energy-efficient neural networks with confidence estimations.

An industry-applicable fabrication flow for complementary field-effect transistors could pave the way for future logic scaling.