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Industry compatible solid-state doping of regions between the channel and contacts in carbon nanotube transistors can be used to control device polarity and improve device performance.
Dual-gated van der Waals heterojunction transistors can provide Gaussian, sigmoid and mixed-kernel functions for use in low-power machine learning classification operations.
Out-of-plane polarized spin current generated by the Weyl semimetal tantalum iridium telluride can be used to achieve the field-free switching of the perpendicular magnetic anisotropy ferromagnet cobalt iron boron at room temperature.
A reconfigurable field-effect transistor based on a hexagonal boron nitride/rhenium diselenide/hexagonal boron nitride heterostructure can offer nonvolatile control of its channel conductivity via photoinduced trapping of electrons or holes at the bottom dielectric interface.
A low-power radio-frequency multiplexing cryo-electronics system, which is based on complementary metal–oxide–semiconductor technology, can operate below 15 mK and provide the control and interfacing of superconducting qubits with minimal cross-coupling.
A machine-learning-based model can be used to perform atomistic simulations of phase changes along the germanium–antimony–tellurium composition line, up to a full-size memory device model that contains half a million atoms.
Acoustically driven spin control of silicon monovacancies can be used to measure the resonant properties and dynamical strain distribution in lateral overtone bulk acoustic resonators.
A neuromorphic biosensor that consists of a sensor input layer, an array of organic neuromorphic devices (forming a hardware neural network) and an output classification layer can be trained on the chip to classify a model disease and then retrained on the chip by switching the sensor input signals.
A bioelectronic patch that is composed of three layers—an ionically conductive tissue adhesive, a viscoelastic networked film and a fatigue-resistant conducting composite—is capable of instantaneous and conformable tissue adhesion on a heart for precise cardiac monitoring and feedback stimulation.
Arbitrary problem graphs with up to 48 nodes can be efficiently and quickly solved by directly mapping onto a fully connected Ising chip that uses complementary-metal–oxide–semiconductor-based oscillators.
A wireless communication approach for neural implants that is based on electro-quasistatic signalling can offer end-to-end channel losses of only around 60 dB at a distance of around 55 mm.
A platform that integrates a ferroelectric gate and two-dimensional heterostructure of tungsten diselenide and tin diselenide can operate in various gating modes, demonstrating typical transistor, steep-slope transistor and synaptic behaviours.
A clock and optical frequency synchronization technique, enabled by frequency comb and signal processing techniques, can provide users with guaranteed bandwidth and low latency for time-critical applications.
High-performance lead-free perovskite thin-film transistors that have low-defect channel–dielectric interfaces can be fabricated using a cation substitution method.
It is shown that 1,024 organic light-emitting diodes can be densely integrated with silicon complementary metal–oxide–semiconductor control circuitry to create neural probes that can selectively activate neurons with millisecond-level timing.
Individual graphene nanoribbons synthesized by an on-surface approach can be contacted with carbon nanotubes—with diameters as small as 1 nm—and used to make multigate devices that exhibit quantum transport effects such as Coulomb blockade and single-electron tunnelling.
Organic semiconductor and colloidal quantum-dot-based thin-film image sensors show reduced noise, dark current and image lag when a pinned photodiode pixel structure, similar to those in silicon-based image sensors, is used.
An integrated artificial synapse array and light-responsive motion sensor can be conformably attached to a finger and used to track finger motion in three-dimensional space.
A multicore analogue in-memory computing chip that is designed and fabricated in 14 nm complementary metal–oxide–semiconductor technology with backend-integrated phase-change memory can be used for deep neural network inference.
Magnetic fluctuations and random telegraph noise in vertical tunnelling heterostructure devices composed of vanadium-doped tungsten diselenide sandwiched between graphene layers can be tuned using an electric bias.