Negative capacitance field-effect transistors have been proposed as a route to low-power electronics, but a lack of fundamental understanding limits progress.

The ability to estimate the uncertainty of predictions made by a neural network is essential when applying neural networks to tasks such as medical diagnosis and autonomous vehicles. The approach is of particular relevance when deploying the networks on devices with limited hardware resources, but existing competency-aware neural networks largely ignore any resource constraints. Here we examine the

Progress towards low-power electronics based on negative capacitance has been slow. For the field to develop, the gap between fundamental research on ferroelectric materials and the engineering of practical devices needs to be bridged.

A monocentric lens and a sensitive hemispherical imager can be combined to create a miniaturized camera that offers a field of view of 120°, deep depth of field and minimal optical aberration.

Accurately detecting a potential collision and triggering a timely escape response is critical in the field of robotics and autonomous vehicle safety. The lobula giant movement detector (LGMD) neuron in locusts can detect an approaching object and prevent collisions within a swarm of millions of locusts. This single neuronal cell performs nonlinear mathematical operations on visual stimuli to elicit

Electronics devices that operate in outer space and nuclear reactors require radiation-hardened transistors. However, high-energy radiation can damage the channel, gate oxide and substrate of a field-effect transistor (FET), and redesigning all vulnerable parts to make them more resistant to total ionizing dose irradiation has proved challenging. Here, we report a radiation-hardened FET that uses semiconducting

Two-dimensional materials could first find widespread commercial application in analogue electronics, rather than as a replacement for silicon in digital devices.

Spintronic devices exploit the spin, as well as the charge, of electrons and could bring new capabilities to the microelectronics industry. However, in order for spintronic devices to meet the ever-increasing demands of the industry, innovation in terms of materials, processes and circuits are required. Here, we review recent developments in spintronics that could soon have an impact on the microelectronics

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Digital electronics are ubiquitous in the modern world, but analogue electronics also play a crucial role in many devices and applications. Analogue circuits are typically manufactured using silicon as the active material. However, the desire for improved performance, new devices and flexible integration has—as for their digital counterparts—led to research into alternative materials, including the

The range of luminescent materials that can be used in electroluminescent devices is limited due to material processing challenges and band alignment issues. This impedes the development of electroluminescent devices at extreme wavelengths and hinders the use of electroluminescence spectroscopy as an analytical technique. Here, we show that a two-terminal device that uses an array of carbon nanotubes

Spin splitting in graphene is required to develop graphene-based multifunctional spintronic devices with low dissipation and long-distance spin transport. Magnetic proximity effects are a promising route to realize exchange splitting in the material, which is otherwise intrinsically non-spin-polarized. Here, we show that monolayer graphene can be magnetized by coupling to an antiferromagnetic thin

The two-dimensional semiconductor Bi2O2Se can be oxidized to create an atomically thin layer of Bi2SeO5 that can be used as the insulator in scaled field-effect transistors.

A van der Waals ferroelectric tunnel junction with asymmetric metal and graphene contacts exhibits a high resistance ratio between on and off states, and could be of value in the development of low-power computing.

Silicon-based transistors are approaching their physical limits and thus new high-mobility semiconductors are sought to replace silicon in the microelectronics industry. Both bulk materials (such as silicon-germanium and III–V semiconductors) and low-dimensional nanomaterials (such as one-dimensional carbon nanotubes and two-dimensional transition metal dichalcogenides) have been explored, but, unlike

Hydrogen-resist lithography with the tip of a scanning tunnelling microscope can be used to fabricate atomic-scale dopant devices in silicon substrates and could potentially be used to build a dopant-based quantum computer. However, all devices fabricated so far have been based on the n-type dopant precursor phosphine. Here, we show that diborane can be used as a p-type dopant precursor, allowing p-type

Integrated circuits and certain silicon-based quantum devices require the precise positioning of dopant nanostructures, and hydrogen resist lithography can be used to fabricate such structures at the atomic-scale limit. However, there is no single technique capable of measuring the three-dimensional location and electrical characteristics of these dopant nanostructures, as well as the charge dynamics

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Neuromorphic computing might be the answer to AI’s hardware problem.

Neuromorphic engineering aims to create computing hardware that mimics biological nervous systems, and it is expected to play a key role in the next era of hardware development. Carver Mead recounts how it all began.

Neuromorphic engineering attempts to create brain-like computing hardware and has helped reawaken interest in computer chip start-ups. But is the technology ready for mainstream application?

The rapid development of artificial intelligence (AI) demands the rapid development of domain-specific hardware specifically designed for AI applications. Neuro-inspired computing chips integrate a range of features inspired by neurobiological systems and could provide an energy-efficient approach to AI computing workloads. Here, we review the development of neuro-inspired computing chips, including

Monolayers of boron nitride can be used to build high-performance radio-frequency switches that can operate at the frequencies required for 5G and the communication systems beyond it.

The development of recognition and translation technology for signed language requires an interdisciplinary approach that begins with deaf contributors.

Circuits capable of reconfigurable logic and neuromorphic functions can be created by exploiting the electronic tunability of two-dimensional tungsten diselenide homojunctions.

Recent advances in materials, mechanics and design have led to the development of ultrathin, lightweight electronic devices that can conformally interface with human skin. With few exceptions, these devices rely on electrical power to support sensing, wireless communication and signal conditioning. Unfortunately, most sources of such power consist of batteries constructed using hazardous materials

A flexible processing engine that is hardwired for machine learning can be used to create a smart electronic nose for odour classification.

Flexible electronics can create lightweight, conformable components that could be integrated into smart systems for applications in healthcare, wearable devices and the Internet of Things. Such integrated smart systems will require a flexible processing engine to address their computational needs. However, the flexible processors demonstrated so far are typically fabricated using low-temperature poly-silicon

Ferroelectric tunnel junctions use a thin ferroelectric layer as a tunnelling barrier, the height of which can be modified by switching its ferroelectric polarization. The junctions can offer low power consumption, non-volatile switching and non-destructive readout, and thus are promising for the development of memory and computing applications. However, achieving a high tunnelling electroresistance

To tackle important combinatorial optimization problems, a variety of annealing-inspired computing accelerators, based on several different technology platforms, have been proposed, including quantum-, optical- and electronics-based approaches. However, to be of use in industrial applications, further improvements in speed and energy efficiency are necessary. Here, we report a memristor-based annealing

Reconfigurable logic and neuromorphic devices are crucial for the development of high-performance computing. However, creating reconfigurable devices based on conventional complementary metal–oxide–semiconductor technology is challenging due to the limited field-effect characteristics of the fundamental silicon devices. Here we show that a homojunction device made from two-dimensional tungsten diselenide

Magnetic skyrmions are topological spin textures that could be used to create magnetic memory and logic devices. Such devices typically rely on current-controlled motion of skyrmions, but using skyrmions that are fixed in space could lead to more compact and energy-efficient devices. Here we report the manipulation of fixed magnetic skyrmions using voltage-controlled magnetic anisotropy. We show that

Signed languages are not as pervasive a conversational medium as spoken languages due to the history of institutional suppression of the former and the linguistic hegemony of the latter. This has led to a communication barrier between signers and non-signers that could be mitigated by technology-mediated approaches. Here, we show that a wearable sign-to-speech translation system, assisted by machine

Driverless cars are improving, but is the public ready to accept them?

Electro-optic transmitters with high bandwidth can be created by monolithically integrating bipolar CMOS electronics with plasmonics.

Modern cars have an array of sensors that allow different objects to be recognized, including large and small animals. They thus have the potential to become a tool for monitoring biodiversity and improving driver safety. But to achieve this various challenges in computing, communications and privacy need to be addressed.

The adoption of autonomous vehicles will depend on the public’s trust in the technology. To establish such trust, it is important to understand the actions of different road users, and their reactions to the vehicles.

A fibre with liquid-metal core and soft outer shell can be woven into textiles and used to sense multiple compression and stretching events simultaneously.

Conventional wide-field-of-view cameras consist of multi-lens optics and flat image sensor arrays, which makes them bulky and heavy. As a result, they are poorly suited to advanced mobile applications such as drones and autonomous vehicles. In nature, the eyes of aquatic animals consist of a single spherical lens and a highly sensitive hemispherical retina, an approach that could be beneficial in the

The rapid growth in the amount of data being transferred within data centres, combined with the slowdown in Moore’s Law, creates challenges for the future scalability of electronically switched data-centre networks. Optical switches could offer a future-proof alternative, and photonic integration platforms have been demonstrated with nanosecond-scale optical switching times. End-to-end switching time

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Electrical control of magnetism in van der Waals ferromagnetic semiconductors is an important step in creating novel spintronic devices, capable of processing and storing information, with these materials. For practical devices, electrical control at or near room temperature is sought, but most layered ferromagnetic semiconductors exhibit Curie temperatures below 100 K. Here, we show that electrostatic

Magnetoresistance effects are used in a variety of devices including hard disk drives and magnetic random access memories. In particular, giant magnetoresistance and tunnelling magnetoresistance can be used to create spin valves and tunnel junctions in which the resistance depends on the relative magnetization orientations of two ferromagnetic conducting layers. Here, we report a magnetoresistance

Gesture recognition using machine-learning methods is valuable in the development of advanced cybernetics, robotics and healthcare systems, and typically relies on images or videos. To improve recognition accuracy, such visual data can be combined with data from other sensors, but this approach, which is termed data fusion, is limited by the quality of the sensor data and the incompatibility of the

Hyperdimensional computing is an emerging computational framework that takes inspiration from attributes of neuronal circuits including hyperdimensionality, fully distributed holographic representation and (pseudo)randomness. When employed for machine learning tasks, such as learning and classification, the framework involves manipulation and comparison of large patterns within memory. A key attribute

Mechanical sensing is a key functionality in soft electronics intended for applications in health monitoring, human–machine interactions and soft robotics. Current methods typically use intricate networks of sensors specific to one type of deformation and one point in space, which limits their sensing capabilities. An alternative approach to distributed sensing is electrical reflectometry, but it is

Carbon nanotube field-effect transistors (CNFETs) are a promising nanotechnology for the development of energy-efficient computing. Despite rapid progress, CNFETs have only been fabricated in academic or research laboratories. A critical challenge in transferring this technology to commercial manufacturing facilities is developing a suitable method for depositing nanotubes uniformly over industry-standard

To address the challenge of increasing data rates, next-generation optical communication networks will require the co-integration of electronics and photonics. Heterogeneous integration of these technologies has shown promise, but will eventually become bandwidth-limited. Faster monolithic approaches will therefore be needed, but monolithic approaches using complementary metal–oxide–semiconductor (CMOS)

Hexagonal boron nitride (hBN) has a large bandgap, high phonon energies and an atomically smooth surface absent of dangling bonds. As a result, it has been widely used as a dielectric to investigate electron physics in two-dimensional heterostructures and as a dielectric in the fabrication of two-dimensional transistors and optoelectronic devices. Here we show that hBN can be used to create analogue

Neuromorphic architectures merge learning and memory functions within a single unit cell and in a neuron-like fashion. Research in the field has been mainly focused on the plasticity of artificial synapses. However, the intrinsic plasticity of the neuronal membrane is also important in the implementation of neuromorphic information processing. Here we report a neurotransistor made from a silicon nanowire

Advanced semiconductor technologies are helping to find new ways to create components capable of one-way transmission.

Frequency multiplication is essential in wireless communication systems, where stable high-frequency oscillations are required. However, multipliers typically employ power- and area-hungry filtering and amplification circuits. Here, we show that a single ferroelectric field-effect transistor, made from ferroelectric hafnium oxide, can be used as a full-wave rectifier and frequency doubler. This is

Acoustic waves are versatile on-chip information carriers that can be used in applications such as microwave filters and transducers. Nonreciprocal devices, in which the transmission of waves is non-symmetric between two ports, are desirable for the manipulation and routing of phonons, but building acoustic non-reciprocal devices is difficult because acoustic systems typically have a linear response

An impedance measurement technique based on dielectric excitation in oxide semiconductors can provide a highly linear sensing signal over a wide range of gas concentrations.

Non-linear ferroelectric tunnel junctions could be used to create low-power in-memory computing systems.

Semiconducting metal oxides are widely used for gas sensors. The resulting chemiresistor devices, however, suffer from non-linear responses, signal fluctuations and gas cross-sensitivities, which limits their use in demanding applications of air-quality monitoring. Here, we show that conventional semiconducting metal oxide materials can provide high-performance sensors using an impedance measurement

Analogue in-memory computing using memristors could alleviate the performance constraints imposed by digital von Neumann systems in data-intensive tasks. Conventional linear memristors typically operate at high currents, potentially limiting power efficiency and scalability in practical applications. Here, we show that nonlinear ferroelectric tunnel junction memristors can perform linear computation

In general, reciprocity requires that signals travel in the same manner in both forward and reverse directions. It governs the behaviour of the majority of electronic circuits and components, imposing severe restrictions on how they operate. Components that violate reciprocity, such as gyrators, isolators and circulators, are, however, of use in many different electronic applications. Non-reciprocal

Does smartphone surveillance have a role to play in the fight against the coronavirus pandemic?