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Two-qubit operations exceeding 99% fidelity have been demonstrated by silicon devices made with standard semiconductor tooling in a 300-mm foundry environment.

The Tomonaga–Luttinger liquid framework can be used to describe 1D quantum systems, spanning fermions, bosons and anyons. In this Review, we discuss the various platforms that can host TLL states, including Josephson junctions, cold atoms and topological materials, and discuss the advances TLL theory can provide in quantum criticality, nonequilibrium dynamics and condensed-matter physics exploration.

Experiments and theory show how superlubricity can emerge in large flakes sliding on a surface when the lattices of the flake and the surface are incommensurate.

A nanoscale set–reset machine — the simplest logic circuit with a built-in memory — that operates at room temperature can be created by attaching a silicon nanoparticle to the inner pore of a protein.

The prediction of chronic toxicity is a major challenge in nanotoxicity studies. Here, the authors present an in silico framework for predicting ENM-induced lung fibrosis, displaying 85% accuracy in experimental validation and leading to identification of key events at nano-bio interfaces that allows mechanism interpretation of ENM-induced lung fibrosis.

Sampling is a key for metasurface design but causes aliasing at high numerical apertures or short wavelengths. The authors identify appropriateness of the Nyquist criterion and propose anti-aliasing strategies for metasurface design.

Physical reservoir computing allows real-time low power information processing. Here, the authors report reservoir computing with magnetic skyrmions able to detect millisecond time-scale hand gestures, matching software neural networks’ performance.

Improving signal to noise ratio of Raman spectra is vital for the application. Here, authors show a noise learning method that learns the noise feature of a spectrometer. This improves the signal to noise ratio and makes deep learning to be instrument dependent instead of sample dependent.

Calculations show that two-dimensional conductance spectra in a graphene nanoribbon placed across a fluidic nanochannel can be used to rapidly and reliably sequence DNA.

It is possible to form covalent bonds between the gold atoms in an electrode and the carbon atoms in the backbone of a conducting molecule to create highly conducting contacts.

The metal–insulator transition in vanadium dioxide can be reversibly suppressed to cryogenic temperatures by doping with atomic hydrogen.

Computer simulations show that the shape and initial orientation of nanoparticles on a lipid bilayer can affect the way they penetrate it, thus offering new insights for the design of nanocarriers for various biological applications.

The plasticity of bulk silicon is dominated by phase transformations, whereas silicon nanoparticles display dislocation-driven plasticity.

Nucleic acid catalysts can be used to build a multipurpose molecular automaton that can be programmed by example.

A spintronic device in which the input, output and internal states are all represented by spin, and that shows the five essential characteristics necessary for logic applications, is proposed.

Exploring new mechanics regime, researchers created centimeter-long, nanometer-thin resonators, achieving unmatched room temperature mechanical isolation via cutting edge nanoengineering and machine learning design; rivaling cryogenic counterparts.

Probabilistic inference hardware prevents overconfidence. Lee et al. report a Gaussian-like memory transistor using p-n junction coupled with separate floating gate, offering precise control of the Gaussian outputs, simplified circuit design, and low power consumption for inference computing.

Combinatorial optimization problems can be solved on parallel hardware called Ising machines. Most studies have focused on the use of second-order Ising machines. Compared to second-order Ising machines, the authors show that higher-order Ising machines realized with coupled-oscillator networks can be more resource-efficient and provide superior solutions for constraint satisfaction problems.

Combining a tungsten disulfide monolayer and a topologically protected bound state in the continuum formed by a one-dimensional photonic crystal, strong light–matter interaction enhancement and large exciton–polariton nonlinearities at room temperature are demonstrated.

Magnetic skyrmions, due to their strongly nonlinearity and multiscale dynamics, are promising for implementing reservoir computing. Here, the authors experimentally demonstrate skyrmion-based spatially multiplexed reservoir computing able to perform Boolean Logic operations, using thermal and current driven dynamics of spin structures.

DNA may be used to fabricate functional nanostructures with various possible geometries, but first being able to predict these structures is a challenging task. Here, the authors use coarse-grained modelling to predict the shape of artificial DNA nanostructures in solution.

While noble gases can be trapped in 3D porous structures, immobilizing them on 2D surfaces represents a formidable challenge. Here, the authors cage individual argon atoms in 2D model zeolite frameworks at room temperature, providing exciting opportunities for the fundamental study of isolated noble gas atoms using surface science methods.

Molecular motors move in response to an imbalance between concentrations of fuel and waste molecules. Here, the authors simulate such non-equilibrium conditions to characterize a model motor’s performance and mechanism of operation.

In standard computing architectures, memory and logic circuits are separated, a feature that slows matrix operations vital to deep learning algorithms. Here, the authors present an alternate in-memory architecture and demonstrate a feasible approach for analog matrix multiplication.