Volume 5 Issue 10, October 2022

A hybrid superconducting optoelectronic circuit could be used to develop spiking neuromorphic networks that operate at the single-quantum level.

With the help of two different kinds of memristor, a low-power, fully analogue reservoir computing system can be created for use in high-accuracy arrhythmia detection and dynamic gesture recognition.

Wearable sweat-sensing devices that use self-powered sensors, electrochromic displays and thin-film batteries can operate free from any connections to bulky external electronics.

A monocrystalline native oxide dielectric, β-Bi₂SeO₅, with a high dielectric constant has been synthesized by oxidizing a two-dimensional (2D) semiconductor, Bi₂O₂Se. In 2D transistors, the ultrathin β-Bi₂SeO₅ dielectric demonstrates sub-0.5-nm equivalent oxide thickness and leakage current below the low-power limit, meeting the requirements of the International Roadmap for Devices and Systems.

Building blocks that consist of capacitors, inductors and resistors can be used to create circuit designs that can implement the spin–orbit interaction, topological Chern state and non-Abelian Aharonov–Bohm effect.

The ultraviolet-assisted intercalative oxidation of high-mobility two-dimensional semiconductor Bi₂O₂Se can be used to create a single-crystalline native oxide dielectric—β-Bi₂SeO₅—that can yield top-gated transistors with an equivalent oxide thickness of 0.41 nm.

Monolithically integrated superconducting single-photon detectors and Josephson junctions can be used to create superconducting optoelectronic synapses with analogue weighting and temporal leaky integration of single-photon presynaptic signals

An artificial synaptic transistor that uses a stretchable bilayer semiconductor as the channel and an encapsulating elastomer as the dielectric can exhibit both excitatory and inhibitory synaptic behaviour, even when under 50% strain.

Dynamic and non-volatile memristors can be used to create hardware-based reservoir and readout layers in artificial neural networks, providing a fully analogue signal processing chain for efficient data classification.

An interactive mouthguard that uses mechanoluminescent phosphors, distributed-optical-fibre sensors and machine learning algorithms can translate different biting patterns into inputs that can control other devices.

A wearable epidermal sweat sensing platform that contains a printed low-power electrochromic display and a stretchable Ag₂O–Zn battery can collect, analyse and present electrochemical data in real time without the need to connect to external devices.