Volume 4 Issue 1, January 2021

The potential of digital contact tracing to slow the spread of a virus had been quietly explored for over a decade before the COVID-19 pandemic thrust the technology into the spotlight. But can it actually be effective in the hard-to-model complexity of real-world social networks?

The coronavirus pandemic has forced students and educators across all levels of education to rapidly adapt to online learning. The impact of this — and the developments required to make it work — could permanently change how education is delivered.

The COVID-19 pandemic has brought an infodemic of misleading and unreliable information. In response, social media platforms have taken unprecedented steps to moderate content and promote official sources of information, which, combined with new policies and appropriate communication, could help tackle misinformation.

The increasingly prominent — and inescapable — role of digital technologies during the coronavirus pandemic has been accompanied by concerning trends in privacy and digital ethics. But more robust protection of our rights in the digital realm is possible in the future.

Wearable electronic devices, which allow physiological signals to be continuously monitored, can be used in the early detection of asymptomatic and pre-symptomatic cases of COVID-19.

A flexible biosensing system with in-sensor machine-learning functionality can recognize up to 21 hand gestures in real time based on surface electromyography patterns from a forearm.

This Review examines the three established approaches for creating stretchable transistors—buckling engineering, stiffness engineering and intrinsic-stretchability engineering—and explores the current and future capabilities of stretchable transistors and circuits in human-integrated electronics.

Electrical and short optical pulses can be used to deterministically induce and reverse a nano-fragmented domain state in antiferromagnetic CuMnAs, in a process that can be probed via changes in the resistance of the system.

Few-layer molybdenum ditelluride and tungsten diselenide field-effect transistors can be reversibly doped with different carrier types and concentrations using pulses of ultraviolet and visible light, allowing reconfigurable complementary metal–oxide–semiconductor circuits to be created.

Transistors that use two-dimensional black phosphorus as the active material can dynamically switch between p-type and n-type operation, and can be used to create security primitive circuits with polymorphic NAND/NOR obfuscation functionality.

A surface electromyography biosensing system that is based on a screen-printed, conformal electrode array and has in-sensor adaptive learning capabilities can classify human gestures in real time and with high accuracy.

A platform based on complementary metal–oxide–semiconductor (CMOS) technology operating with qubits close to 100 mK can generate static and dynamic signals for the control of many qubits.

A networked system of eight computing chips, each with its own on-chip memory, can be used to efficiently implement a range of neural network models and sizes.

Commercial complementary metal–oxide–semiconductor and resistive random-access memory technologies can be used to create multibit compute-in-memory circuits capable of fast and energy-efficient inference for use in small artificial intelligence edge devices.