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Highlights Two-dimensional (2D) materials are highlighted for their exceptional mechanical, electrical, optical, and chemical properties, making them ideal for fabricating high-performance wearable biodevices. The review categorizes cutting-edge wearable biodevices by their interactions with physical, electrophysiological, and biochemical signals, showcasing how 2D materials enhance these devices' functionality, mainly including self-powering and human-machine interaction. 2D materials enable multifunctional, high-performance biodevices, integrating self-powered systems, treatment platforms, and human-machine interactions, though challenges remain in practical applications. The proliferation of wearable biodevices has boosted the development of soft, innovative, and multifunctional materials for human health monitoring. The integration of wearable sensors with intelligent systems is an overwhelming tendency, providing powerful tools for remote health monitoring and personal health management. Among many candidates, two-dimensional (2D) materials stand out due to several exotic mechanical, electrical, optical, and chemical properties that can be efficiently integrated into atomic-thin films. While previous reviews on 2D materials for biodevices primarily focus on conventional configurations and materials like graphene, the rapid development of new 2D materials with exotic properties has opened up novel applications, particularly in smart interaction and integrated functionalities. This review aims to consolidate recent progress, highlight the unique advantages of 2D materials, and guide future research by discussing existing challenges and opportunities in applying 2D materials for smart wearable biodevices. We begin with an in-depth analysis of the advantages, sensing mechanisms, and potential applications of 2D materials in wearable biodevice fabrication. Following this, we systematically discuss state-of-the-art biodevices based on 2D materials for monitoring various physiological signals within the human body. Special attention is given to showcasing the integration of multi-functionality in 2D smart devices, mainly including self-power supply, integrated diagnosis/treatment, and human–machine interaction. Finally, the review concludes with a concise summary of existing challenges and prospective solutions concerning the utilization of 2D materials for advanced biodevices.

We report the observation of the controlled expansion of a two-dimensional (2D) quantum gas confined onto a curved shell-shaped surface. We start from the ellipsoidal geometry of a dressed quadrupole trap and introduce a novel gravity compensation mechanism enabling to explore the full ellipsoid. The zero-point energy of the transverse confinement manifests itself by the spontaneous emergence of an annular shape in the atomic distribution. The experimental results are compared with the solution of the three-dimensional Gross–Pitaevskii equation and with a 2D semi-analytical model. This work evidences how a hidden dimension can affect dramatically the embedded low-dimensional system by inducing a change of topology.

Quantum simulation using synthetic systems is a promising route to solve outstanding quantum many-body problems in regimes where other approaches, including numerical ones, fail 1 . Many platforms are being developed towards this goal, in particular based on trapped ions 2 – 4 , superconducting circuits 5 – 7 , neutral atoms 8 – 11 or molecules 12 , 13 . All of these platforms face two key challenges: scaling up the ensemble size while retaining high-quality control over the parameters, and validating the outputs for these large systems. Here we use programmable arrays of individual atoms trapped in optical tweezers, with interactions controlled by laser excitation to Rydberg states 11 , to implement an iconic many-body problem—the antiferromagnetic two-dimensional transverse-field Ising model. We push this platform to a regime with up to 196 atoms manipulated with high fidelity and probe the antiferromagnetic order by dynamically tuning the parameters of the Hamiltonian. We illustrate the versatility of our platform by exploring various system sizes on two qualitatively different geometries—square and triangular arrays. We obtain good agreement with numerical calculations up to a computationally feasible size (approximately 100 particles). This work demonstrates that our platform can be readily used to address open questions in many-body physics. Programmable quantum simulation of two-dimensional antiferromagnets is achieved with up to 196 neutral atoms, and the capability of the platform is demonstrated on square and triangular arrays.

Photodetectors based on two-dimensional (2D) materials have been the focus of intensive research and development over the past decade. However, a gap has long persisted between fundamental research and mature applications. One of the main reasons behind this gap has been the lack of a practical and unified approach for the characterization of their figures of merit, which should be compatible with the traditional performance evaluation system of photodetectors. This is essential to determine the degree of compatibility of laboratory prototypes with industrial technologies. Here we propose general guidelines for the characterization of the figures of merit of 2D photodetectors and analyze common situations when the specific detectivity, responsivity, dark current, and speed can be misestimated. Our guidelines should help improve the standardization and industrial compatibility of 2D photodetectors. The lack of a standardized approach for the characterization of the performance of 2D photodetectors represents an important obstacle towards their industrialization. Here, the authors propose practical guidelines to characterize their figures of merit and analyse common situations where their performance can be misestimated.

Numerical simulation of fluids plays an essential role in modeling many physical phenomena, such as weather, climate, aerodynamics, and plasma physics. Fluids are well described by the Navier–Stokes equations, but solving these equations at scale remains daunting, limited by the computational cost of resolving the smallest spatiotemporal features. This leads to unfavorable tradeoffs between accuracy and tractability. Here we use end-to-end deep learning to improve approximations inside computational fluid dynamics for modeling two-dimensional turbulent flows. For both direct numerical simulation of turbulence and large-eddy simulation, our results are as accurate as baseline solvers with 8 to 10× finer resolution in each spatial dimension, resulting in 40- to 80-fold computational speedups. Our method remains stable during long simulations and generalizes to forcing functions and Reynolds numbers outside of the flows where it is trained, in contrast to black-box machine-learning approaches. Our approach exemplifies how scientific computing can leverage machine learning and hardware accelerators to improve simulations without sacrificing accuracy or generalization.

The application of strain to semiconductors allows for controlled modification of their band structure. This principle is employed for the manufacturing of devices ranging from high-performance transistors to solid-state lasers. Traditionally, strain is typically achieved via growth on lattice-mismatched substrates. For two-dimensional (2D) semiconductors, this is not feasible as they typically do not interact epitaxially with the substrate. Here, we demonstrate controlled strain engineering of 2D semiconductors during synthesis by utilizing the thermal coefficient of expansion mismatch between the substrate and semiconductor. Using WSe 2 as a model system, we demonstrate stable built-in strains ranging from 1% tensile to 0.2% compressive on substrates with different thermal coefficient of expansion. Consequently, we observe a dramatic modulation of the band structure, manifested by a strain-driven indirect-to-direct bandgap transition and brightening of the dark exciton in bilayer and monolayer WSe 2 , respectively. The growth method developed here should enable flexibility in design of more sophisticated devices based on 2D materials. Strain engineering is an essential tool for modifying local electronic properties in silicon-based electronics. Here, Ahn et al. demonstrate control of biaxial strain in two-dimensional materials based on the growth substrate, enabling more complex low-dimensional electronics.

The three-dimensional stability of two-dimensional natural convection flows in a heated, square enclosure inclined to the horizontal is investigated numerically. First, the computational procedure is validated by comparison of base flow solutions to results reported in literature across a range of inclinations. A bi-global linear stability analysis is then conducted to investigate the stability of these two-dimensional base flows to infinitesimal three-dimensional perturbations, and the effect that buoyancy forces (defined by a buoyancy number $R_N$) and enclosure inclination $\\theta$ have on these stability characteristics. The flow is first observed to become three-dimensionally unstable at buoyancy number $R_N = 213.8$ when $\\theta$ is $180^\\circ$; this increases to $R_N = 2.54 \\times 10^4$ at inclination $\\theta =58^\\circ$. It is found that the two-dimensional base flow is more unstable to three-dimensional perturbations with the critical $R_N$ corresponding to three-dimensional instability being significantly lower than its two-dimensional counterpart across all considered inclinations except $83^\\circ \\leq \\theta \\leq 88^\\circ$, where the most unstable mode is a two-dimensional oscillatory mode that develops in the boundary layers along the conducting walls. Eight different leading three-dimensional instability modes are identified, with inclinations $58^\\circ \\leq \\theta < 88^\\circ$ transitioning through an oscillatory mode, and inclinations $88^\\circ \\leq \\theta \\leq 180^\\circ$ transitioning through a stationary mode. The characteristics of the primary instability modes corresponding to inclinations $88^\\circ \\leq \\theta \\leq 179^\\circ$ indicate the presence of a Taylor–Görtler instability.

Two-dimensional materials provide extraordinary opportunities for exploring phenomena arising in atomically thin crystals. Beginning with the first isolation of graphene, mechanical exfoliation has been a key to provide high-quality two-dimensional materials, but despite improvements it is still limited in yield, lateral size and contamination. Here we introduce a contamination-free, one-step and universal Au-assisted mechanical exfoliation method and demonstrate its effectiveness by isolating 40 types of single-crystalline monolayers, including elemental two-dimensional crystals, metal-dichalcogenides, magnets and superconductors. Most of them are of millimeter-size and high-quality, as shown by transfer-free measurements of electron microscopy, photo spectroscopies and electrical transport. Large suspended two-dimensional crystals and heterojunctions were also prepared with high-yield. Enhanced adhesion between the crystals and the substrates enables such efficient exfoliation, for which we identify a gold-assisted exfoliation method that underpins a universal route for producing large-area monolayers and thus supports studies of fundamental properties and potential application of two-dimensional materials. Here, the authors develop a one-step, contamination-free, Au-assisted mechanical exfoliation method for 2D materials, and isolate 40 types of single-crystalline monolayers, including elemental 2D crystals, metal-dichalcogenides, magnets and superconductors with millimetre size.

Metasurfaces based on resonant subwavelength photonic structures enable novel ways of wavefront control and light focusing, underpinning a new generation of flat-optics devices1. Recently emerged all-dielectric asymmetric metasurfaces, composed of arrays of metaunits with broken in-plane inversion symmetry2–7, exhibit high-quality resonances originating from the intriguing physics of bound states in the continuum. Here, we combine dielectric metasurfaces and hyperspectral imaging to develop an ultrasensitive label-free analytical platform for biosensing. Our technique can acquire spatially resolved spectra from millions of image pixels and use smart data-processing tools to extract high-throughput digital sensing information at the unprecedented level of less than three molecules per μm2. We further show spectral data retrieval from a single image without using spectrometers, enabled by our unique sensor design, paving the way for portable diagnostic applications. This combination of nanophotonics and imaging optics extends the capabilities of dielectric metasurfaces to analyse biological entities and atomic-layer-thick two-dimensional materials over large areas.Spatially resolved spectra from millions of pixels and information extraction from three molecules per μm2 is now possible using dielectric metasurfaces.

Confined microenvironments formed in heterogeneous catalysts have recently been recognized as equally important as catalytically active sites. Understanding the fundamentals of confined catalysis has become an important topic in heterogeneous catalysis. Well-defined 2D space between a catalyst surface and a 2D material overlayer provides an ideal microenvironment to explore the confined catalysis experimentally and theoretically. Using density functional theory calculations, we reveal that adsorption of atoms and molecules on a Pt(111) surface always has been weakened under monolayer graphene, which is attributed to the geometric constraint and confinement field in the 2D space between the graphene overlayer and the Pt(111) surface. A similar result has been found on Pt(110) and Pt(100) surfaces covered with graphene. The microenvironment created by coating a catalyst surface with 2D material overlayer can be used to modulate surface reactivity, which has been illustrated by optimizing oxygen reduction reaction activity on Pt(111) covered by various 2D materials. We demonstrate a concept of confined catalysis under 2D cover based on a weak van der Waals interaction between 2D material overlayers and underlying catalyst surfaces.