Volume 6 Issue 10, October 2023

External-magnetic-field-free switching of the perpendicular magnetic anisotropy in magnetic layers is a prerequisite for the wide adoption of spintronic devices. This challenge could be met by the Weyl semimetal TaIrTe₄, which is now shown to generate an out-of-plane polarized spin current at room temperature.

Machine-learning-driven atomistic simulations are shown to describe phase-change materials on the length scale of real devices. This demonstration suggests that the atomic-scale design of phase-change architectures, programming conditions and full devices could be within reach.

A network of coupled electronic oscillators can be engineered to find ground states of Ising Hamiltonians and solve various combinatorial optimization problems.

An adhesive bioelectronic patch that can conform to irregular curvilinear surfaces can be used in vivo to stimulate the heart and record electrocardiograms of freely moving rats.

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.

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 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.

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 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.

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 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.