A General Tensor Prediction Framework Based on Graph Neural Networks.

Graph neural networks (GNNs) have been shown to be extremely flexible and accurate in predicting the physical properties of molecules and crystals. However, traditional invariant GNNs are not compatible with directional properties, which currently limits their usage to the prediction of only invariant scalar properties. To address this issue, here we propose a general framework, i.

Strong Electron-Phonon Coupling Mediates Carrier Transport in BiFeO.

The electron-phonon interaction is known as one of the major mechanisms determining electrical and thermal properties. In particular, it alters the carrier transport behaviors and sets fundamental limits to carrier mobility. Establishing how electrons interact with phonons and the resulting impact on the carrier transport property is significant for the development of high-efficiency electronic devices.

General Theory for Bilayer Stacking Ferroelectricity.

Two-dimensional (2D) ferroelectrics, which are rare in nature, enable high-density nonvolatile memory with low energy consumption. Here, we propose a theory of bilayer stacking ferroelectricity (BSF), in which two stacked layers of the same 2D material, with different rotation and translation, exhibit ferroelectricity. By performing systematic group theory analysis, we find all the possible BSF in all 80 layer groups (LGs) and discover the rules about the creation and annihilation of symmetries in the bilayer.

Theoretical study on the magnetic properties of cathode materials in the lithium-ion battery.

The layered LiMO (M = Co, Ni, and Mn) materials are commonly used as the cathode materials in the lithium-ion battery due to the distinctive layer structure for lithium extraction and insertion. Although their electrochemical properties have been extensively studied, the structural and magnetic properties of LiNiO are still under considerable debate, and the magnetic properties of monoclinic LiMnO are seldom reported. In this work, a detailed study of LiNiO, LiMnO, and a half-doped material LiNiMnO is performed via both first-principles calculations and Monte Carlo simulations based on the effective spin Hamiltonian model.

Control of Charge Carrier Relaxation at the Au/WSe Interface by Ti and TiO Adhesion Layers: Ab Initio Quantum Dynamics.

Phonon-mediated charge relaxation plays a vital role in controlling thermal transport across an interface for efficient functioning of two-dimensional (2D) nanostructured devices. Using a combination of nonadiabatic molecular dynamics with real-time time-dependent density functional theory, we demonstrate a strong influence of adhesion layers at the Au/WSe interface on nonequilibrium charge relaxation, rationalizing recent ultrafast time-resolved experiments. Ti oxide layers (TiO) create a barrier to the interaction between Au and WSe and extend hot carrier lifetimes, creating benefits for photovoltaic and photocatalytic applications.

Fluctuations at Metal Halide Perovskite Grain Boundaries Create Transient Trap States: Machine Learning Assisted Ab Initio Analysis.

All-inorganic perovskites are promising candidates for solar energy and optoelectronic applications, despite their polycrystalline nature with a large density of grain boundaries (GBs) due to facile solution-processed fabrication. GBs exhibit complex atomistic structures undergoing slow rearrangements. By studying evolution of the Σ5(210) CsPbBr GB on a nanosecond time scale, comparable to charge carrier lifetimes, we demonstrate that GB deformations appear every ∼100 ps and increase significantly the probability of deep charge traps.

Electronically phase separated nano-network in antiferromagnetic insulating LaMnO/PrMnO/CaMnO tricolor superlattice.

Strongly correlated materials often exhibit an electronic phase separation (EPS) phenomena whose domain pattern is random in nature. The ability to control the spatial arrangement of the electronic phases at microscopic scales is highly desirable for tailoring their macroscopic properties and/or designing novel electronic devices. Here we report the formation of EPS nanoscale network in a mono-atomically stacked LaMnO/CaMnO/PrMnO superlattice grown on SrTiO (STO) (001) substrate, which is known to have an antiferromagnetic (AFM) insulating ground state.

Two-Dimensional Organic-Inorganic Room-Temperature Multiferroics.

Organic-inorganic multiferroics are promising for the next generation of electronic devices. To date, dozens of organic-inorganic multiferroics have been reported; however, most of them show a magnetic Curie temperature much lower than room temperature, which drastically hampers their application. Here, by performing first-principles calculations and building effective model Hamiltonians, we reveal a molecular orbital-mediated magnetic coupling mechanism in two-dimensional Cr(pyz) (pyz = pyrazine) and the role that the valence state of the molecule plays in determining the magnetic coupling type between metal ions.

Effective lifetime of non-equilibrium carriers in semiconductors from non-adiabatic molecular dynamics simulations.

The lifetimes of non-equilibrium charge carriers in semiconductors calculated using non-adiabatic molecular dynamics often differ from experimental results by orders of magnitude. By revisiting the definition of carrier lifetime, we report a systematic procedure for calculating the effective carrier lifetime in semiconductor crystals under realistic conditions. The consideration of all recombination mechanisms and the use of appropriate carrier and defect densities are crucial to bridging the gap between modeling and measurements.

Two Dimensional MOene: From Superconductors to Direct Semiconductors and Weyl Fermions.

The number of semiconducting MXenes with direct band gaps is extremely low; thus, it is highly desirable to broaden the MXene family beyond carbides and nitrides to expand the palette of desired chemical and physical properties. Here, we theoretically report the existence of the single-layer (SL) dititanium oxide 2H-TiO MOene (MXene-like 2D transition oxides), showing an Ising superconducting feature. Moreover, SL halogenated 2H- and 1T-TiO monolayers display tunable semiconducting features and strong light-harvesting ability.

High Photoreactivity on a Reconstructed Anatase TiO(001) Surface Predicted by Nonadiabatic Molecular Dynamics.

Anatase TiO(001) surface with (4 × 1) reconstruction is proposed to be a highly active catalytic surface. In this work, using time-domain nonadiabatic molecular dynamics, we reveal that the ridge structure formed by anatase(001) surface reconstruction is the photoreactive site for hole migration and trapping. Moreover, the ridge structure is destroyed by low-coverage CHOH adsorption, leading to the suppression of its high photoreactivity.

Ultrafast charge transfer coupled to quantum proton motion at molecule/metal oxide interface.

Understanding how the nuclear quantum effects (NQEs) in the hydrogen bond (H-bond) network influence the photoexcited charge transfer at semiconductor/molecule interface is a challenging problem. By combining two kinds of emerging molecular dynamics methods at the ab initio level, the path integral-based molecular dynamics and time-dependent nonadiabatic molecular dynamics, and choosing CHOH/TiO as a prototypical system to study, we find that the quantum proton motion in the H-bond network is strongly coupled with the ultrafast photoexcited charge dynamics at the interface. The hole trapping ability of the adsorbed methanol molecule is notably enhanced by the NQEs, and thus, it behaves as a hole scavenger on titanium dioxide.

Control of Polaronic Behavior and Carrier Lifetimes via Metal and Anion Alloying in Chalcogenide Perovskites.

Transition-metal perovskite chalcogenides (TMPCs) have emerged as lead-free alternatives to lead-halide perovskites and have been currently of increasing interest for optoelectronic applications because of their suitable band gaps, high carrier mobility, strong light absorption, and high stability. Here, we systematically report a study on the effects of Ti- and Se-alloying strategies on polaron behavior and carrier lifetimes in nonradiative recombination. Although such alloying can effectively tune the band gap of BaZrS, we observe localized small polaron formation upon Ti alloying and large polarons generating in Se alloying.

Crystal structure prediction by combining graph network and optimization algorithm.

Crystal structure prediction is a long-standing challenge in condensed matter and chemical science. Here we report a machine-learning approach for crystal structure prediction, in which a graph network (GN) is employed to establish a correlation model between the crystal structure and formation enthalpies at the given database, and an optimization algorithm (OA) is used to accelerate the search for crystal structure with lowest formation enthalpy. The framework of the utilized approach (a database + a GN model + an optimization algorithm) is flexible.

Assembling Diverse Skyrmionic Phases in Fe GeTe Monolayers.

Skyrmionic magnetic states are promising in advanced spintronics. This topic is experiencing recent progress in 2D magnets, with, for example, a near 300 K Curie temperature observed in Fe GeTe . However, despite previous studies reporting skyrmions in Fe GeTe , such a system remains elusive, since it has been reported to host either Néel-type or Bloch-type textures, while a net Dzyaloshinskii-Moriya interaction (DMI) cannot occur in this compound for symmetry reasons.

Giant Biquadratic Exchange in 2D Magnets and Its Role in Stabilizing Ferromagnetism of NiCl_{2} Monolayers.

Two-dimensional (2D) van der Waals (vdW) magnets provide an ideal platform for exploring, on the fundamental side, new microscopic mechanisms and for developing, on the technological side, ultracompact spintronic applications. So far, bilinear spin Hamiltonians have been commonly adopted to investigate the magnetic properties of 2D magnets, neglecting higher order magnetic interactions. However, we here provide quantitative evidence of giant biquadratic exchange interactions in monolayer NiX_{2} (X=Cl, Br and I), by combining first-principles calculations and the newly developed machine learning method for constructing Hamiltonian.