Room-Temperature Ferroelectricity in Ultra-Thin p-Type BiCuSeO Films.

Atomically thin 2D layered ferroelectric semiconductors, where polarization switching transpires within the channel material itself, are pivotal to advancing the next generation of high-performance electronics. Nevertheless, the challenge remains in either the controllable synthesis of films or the manipulation of associated ferroelectricity. Here, 2D p-type BiCuSeO (BCSO) films with a thickness down to ≈3 nm are successfully synthesized using molecular beam epitaxy.

General framework for E(3)-equivariant neural network representation of density functional theory Hamiltonian.

The combination of deep learning and ab initio calculation has shown great promise in revolutionizing future scientific research, but how to design neural network models incorporating a priori knowledge and symmetry requirements is a key challenging subject. Here we propose an E(3)-equivariant deep-learning framework to represent density functional theory (DFT) Hamiltonian as a function of material structure, which can naturally preserve the Euclidean symmetry even in the presence of spin-orbit coupling. Our DeepH-E3 method enables efficient electronic structure calculation at ab initio accuracy by learning from DFT data of small-sized structures, making the routine study of large-scale supercells (>10 atoms) feasible.

Controlled Growth of Wafer-Scale Transition Metal Dichalcogenides with a Vertical Composition Gradient for Artificial Synapses with High Linearity.

Artificial synapses are promising for dealing with large amounts of data computing. Great progress has been made recently in terms of improving the on/off current ratio, the number of states, and the energy efficiency of synapse devices. However, the nonlinear weight update behavior of a synapse caused by the uncertain direction of the conductive filament leads to complex weight modulation, which degrades the delivery accuracy of information.

Deep-learning density functional theory Hamiltonian for efficient ab initio electronic-structure calculation.

The marriage of density functional theory (DFT) and deep-learning methods has the potential to revolutionize modern computational materials science. Here we develop a deep neural network approach to represent the DFT Hamiltonian (DeepH) of crystalline materials, aiming to bypass the computationally demanding self-consistent field iterations of DFT and substantially improve the efficiency of ab initio electronic-structure calculations. A general framework is proposed to deal with the large dimensionality and gauge (or rotation) covariance of the DFT Hamiltonian matrix by virtue of locality, and this is realized by a message-passing neural network for deep learning.

Nanoscale Control of One-Dimensional Confined States in Strongly Correlated Homojunctions.

Construction of lateral junctions is essential to generate one-dimensional (1D) confined potentials that can effectively trap quasiparticles. A series of remarkable electronic phases in one dimension, such as Wigner crystallization, are expected to be realized in such junctions. Here, we demonstrate that we can precisely tune the 1D-confined potential with an in situ manipulation technique, thus providing a dynamic way to modify the correlated electronic states at the junctions.

Two-dimensional magnetic materials: structures, properties and external controls.

Since the discovery of intrinsic ferromagnetism in atomically thin Cr2Gr2Te6 and CrI3 in 2017, research on two-dimensional (2D) magnetic materials has become a highlighted topic. Based on 2D magnetic materials and their heterostructures, exotic physical phenomena at the atomically thin limit have been discovered, such as the quantum anomalous Hall effect, magneto-electric multiferroics, and magnon valleytronics. Furthermore, magnetism in these ultrathin magnets can be effectively controlled by external perturbations, such as electric field, strain, doping, chemical functionalization, and stacking engineering.

Pressure-Dependent Intermediate Magnetic Phase in Thin FeGeTe Flakes.

We investigated the evolution of ferromagnetism in layered FeGeTe flakes under different pressures and temperatures using in situ magnetic circular dichroism (MCD) spectroscopy. We found that the rectangular shape of the hysteresis loop under an out-of-plane magnetic field sweep can be sustained below 7 GPa. Above that pressure, an intermediate state appears in the low-temperature region signaled by an 8-shaped skewed hysteresis loop.

Electric Field-Modulated Magnetic Phase Transition in van der Waals CrI Bilayers.

Two-dimensional van der Waals (vdW) magnetic materials are well-recognized milestones toward nanostructured spintronics. An interesting example is CrI; its magnetic states can be modulated electrically, allowing spintronics applications that are highly compatible with electronics technologies. Here, we report the electric field alone induces the interlayer antiferromagnetic-to-ferromagnetic (AFM-to-FM) phase transition in CrI bilayers with critical field as low as 0.

Chemical Vapor Deposition Grown Large-Scale Atomically Thin Platinum Diselenide with Semimetal-Semiconductor Transition.

Among two-dimensional (2D) transition-metal dichalcogenides (TMDCs), platinum diselenide (PtSe) stands in a distinct place due to its fancy transition from type-II Dirac semimetal to semiconductor with a thickness variation from bulk to monolayer (1 ML) and the related versatile applications especially in mid-infrared detectors. However, achieving atomically thin PtSe is still a challenging issue. Herein, we have designed a facile chemical vapor deposition (CVD) method to achieve the synthesis of atomically thin 1T-PtSe on an electrode material of Au foil.

Simultaneous Production and Functionalization of Boron Nitride Nanosheets by Sugar-Assisted Mechanochemical Exfoliation.

Due to their extraordinary properties, boron nitride nanosheets (BNNSs) have great promise for many applications. However, the difficulty of their efficient preparation and their poor dispersibility in liquids are the current factors that limit this. A simple yet efficient sugar-assisted mechanochemical exfoliation (SAMCE) method is developed here to simultaneously achieve their exfoliation and functionalization.

Biotemplating Growth of Nepenthes-like N-Doped Graphene as a Bifunctional Polysulfide Scavenger for Li-S Batteries.

The practical application of lithium-sulfur (Li-S) batteries is hindered by their poor cycling stabilities that primarily stem from the "shuttle" of dissolved lithium polysulfides. Here, we develop a nepenthes-like N-doped hierarchical graphene (NHG)-based separator to realize an efficient polysulfide scavenger for Li-S batteries. The 3D textural porous NHG architectures are realized by our designed biotemplating chemical vapor deposition (CVD) approach via the employment of naturally abundant diatomite as the growth substrate.

Vertical 1T-TaS Synthesis on Nanoporous Gold for High-Performance Electrocatalytic Applications.

2D metallic TaS is acting as an ideal platform for exploring fundamental physical issues (superconductivity, charge-density wave, etc.) and for engineering novel applications in energy-related fields. The batch synthesis of high-quality TaS nanosheets with a specific phase is crucial for such issues.

Half-Metallicity in Co-Doped WSe Nanoribbons.

The recent development of two-dimensional transition-metal dichalcogenides in electronics and optoelelectronics has triggered the exploration in spintronics, with high demand in search for half-metallicity in these systems. Here, through density functional theory (DFT) calculations, we predict robust half-metallic behaviors in Co-edge-doped WSe nanoribbons (NRs). With electrons partially occupying the antibonding state consisting of Co 3d and Se 4p orbitals, the system becomes spin-polarized due to the defect-state-induced Stoner effect and the strong exchange splitting eventually gives rise to the half-metallicity.