Mechanism of Type-II Multiferroicity in Pure and Al-Doped CuFeO_{2}.

Type-II multiferroicity, where electric polarization is induced by specific spin patterns, is crucial in fundamental physics and advanced spintronics. However, the spin model and magnetoelectric coupling mechanisms in prototypical type-II multiferroic CuFeO_{2} and Al-doped CuFeO_{2} remain unclear. Here, by considering both spin and alloy degrees of freedom, we develop a magnetic cluster expansion method, which considers all symmetry allowed interactions.

Advancing nonadiabatic molecular dynamics simulations in solids with E(3) equivariant deep neural hamiltonians.

Non-adiabatic molecular dynamics (NAMD) simulations have become an indispensable tool for investigating excited-state dynamics in solids. In this work, we propose a general framework, NAMD (Neural-Network Non-Adiabatic Molecular Dynamics), which employs an E(3)-equivariant deep neural Hamiltonian to boost the accuracy and efficiency of NAMD simulations. Distinct from conventional machine learning methods that predict key quantities in NAMD, NAMD computes these quantities directly with a deep neural Hamiltonian, ensuring excellent accuracy, efficiency, and consistency.

Symmetry Strategy for Rapid Discovery of Abundant Fractional Quantum Ferroelectrics.

Traditional ferroelectrics are limited by Neumann's principle, which confines exploration of ferroelectrics within polar point groups. Our recent work [Ji et al., Nat.

Band Gap Narrowing in Lead-Halide Perovskites by Dynamic Defect Self-Doping for Enhanced Light Absorption and Energy Upconversion.

Metal halide perovskites (MHP) have attracted great attention in the photovoltaic industry due to their high and rapidly rising power conversion efficiencies, currently over 25%. However, hybrid organic-inorganic MHPs are inherently chemically unstable, limiting their application. All-inorganic MHPs perovskites, such as CsPbI, have many merits, but their stable conversion efficiency is lower, around 18%, due to a larger band gap causing a mismatch with the solar spectrum.

Atomistic Origin of Microsecond Carrier Lifetimes at Perovskite Grain Boundaries: Machine Learning-Assisted Nonadiabatic Molecular Dynamics.

The polycrystalline nature of perovskites, stemming from their facile solution-based fabrication, leads to a high density of grain boundaries (GBs) and point defects. However, the impact of GBs on perovskite performance remains uncertain, with contradictory statements found in the literature. We developed a machine learning force field, sampled GB structures on a nanosecond time scale, and performed nonadiabatic (NA) molecular dynamics simulations of charge carrier trapping and recombination in stoichiometric and doped GBs.

Nonvolatile Magnonics in Bilayer Magnetic Insulators.

Nonvolatile control of spin order or spin excitations offers a promising avenue for advancing spintronics; however, practical implementation remains challenging. In this Letter, we propose a general framework to realize electrical control of magnons in 2D magnetic insulators. We demonstrate that in bilayer ferromagnetic insulators with strong spin-layer coupling, the electric field can effectively manipulate the spin exchange interactions between the layers, enabling nonvolatile control of the corresponding magnons.

Tunable Ultrafast Charge Transfer across Homojunction Interface.

Charge transfer at heterojunction interfaces is a fundamental process that plays a crucial role in modern electronic and photonic devices. The essence of such charge transfer lies in the band offset, making charge transfer uncommon in a homojunction. Recently, sliding ferroelectricity has been proposed and confirmed in two-dimensional van der Waals stacked materials such as bilayer boron nitride.

An approach for full space inverse materials design by combining universal machine learning potential, universal property model, and optimization algorithm.

We present a full space inverse materials design (FSIMD) approach that fully automates the materials design for target physical properties without the need to provide the atomic composition, chemical stoichiometry, and crystal structure in advance. Here, we used density functional theory reference data to train a universal machine learning potential (UPot) and transfer learning to train a universal bulk modulus model (UBmod). Both UPot and UBmod were able to cover materials systems composed of any element among 42 elements.

Accelerating the calculation of electron-phonon coupling strength with machine learning.

The calculation of electron-phonon couplings (EPCs) is essential for understanding various fundamental physical properties, including electrical transport, optical and superconducting behaviors in materials. However, obtaining EPCs through fully first-principles methods is notably challenging, particularly for large systems or when employing advanced functionals. Here we introduce a machine learning framework to accelerate EPC calculations by utilizing atomic orbital-based Hamiltonian matrices and gradients predicted by an equivariant graph neural network.

Electrosynthesis of Ammonia from Nitrate Using a Self-Activated Carbon Fiber Paper.

While electrochemically upcycling nitrate wastes to valuable ammonia is considered a very promising pathway for tackling the environmental and energy challenges underlying the nitrogen cycle, the effective catalysts involved are mainly limited to metal-based materials. Here, we report that commercial carbon fiber paper, which is a classical current collector and is typically assumed to be electrochemically inert, can be significantly activated during the reaction. As a result, it shows a high NH Faradaic efficiency of 87.

Memristive switching in the surface of a charge-density-wave topological semimetal.

Owing to the outstanding properties provided by nontrivial band topology, topological phases of matter are considered as a promising platform towards low-dissipation electronics, efficient spin-charge conversion, and topological quantum computation. Achieving ferroelectricity in topological materials enables the non-volatile control of the quantum states, which could greatly facilitate topological electronic research. However, ferroelectricity is generally incompatible with systems featuring metallicity due to the screening effect of free carriers.

Organic Ligand Engineering for Tailoring Electron-Phonon Coupling in 2D Hybrid Perovskites.

In the emerging two-dimensional organic-inorganic hybrid perovskites, the electronic structures and carrier behaviors are strongly impacted by intrinsic electron-phonon interactions, which have received inadequate attention. In this study, we report an intriguing phenomenon of negative carrier diffusion induced by electron-phonon coupling in (2T)PbI. Theoretical calculations reveal that the electron-phonon coupling drives the band alignment in (2T)PbI to alternate between type I and type II heterostructures.

Spin disorder control of topological spin texture.

Stabilization of topological spin textures in layered magnets has the potential to drive the development of advanced low-dimensional spintronics devices. However, achieving reliable and flexible manipulation of the topological spin textures beyond skyrmion in a two-dimensional magnet system remains challenging. Here, we demonstrate the introduction of magnetic iron atoms between the van der Waals gap of a layered magnet, FeGaTe, to modify local anisotropic magnetic interactions.

Atomistic Origin of Diverse Charge Density Wave States in CsV_{3}Sb_{5}.

Kagome metals AV_{3}Sb_{5} (A=K, Rb, or Cs) exhibit intriguing charge density wave (CDW) instabilities, which interplay with superconductivity and band topology. However, despite firm observations, the atomistic origins of the CDW phases, as well as hidden instabilities, remain elusive. Here, we adopt our newly developed symmetry-adapted cluster expansion method to construct a first-principles-based effective Hamiltonian of CsV_{3}Sb_{5}, which not only reproduces the established inverse star of David (ISD) phase, but also predict a series of D_{3h}-n states under mild tensile strains.

Moiré magnetic exchange interactions in twisted magnets.

In addition to moiré superlattices, twisting can also generate moiré magnetic exchange interactions (MMEIs) in van der Waals magnets. However, owing to the extreme complexity and twist-angle-dependent sensitivity, all existing models fail to fully capture MMEIs and thus cannot provide an understanding of MMEI-induced physics. Here, we develop a microscopic moiré spin Hamiltonian that enables the effective description of MMEIs via a sliding-mapping approach in twisted magnets, as demonstrated in twisted bilayer CrI.

Fractional quantum ferroelectricity.

For an ordinary ferroelectric, the magnitude of the spontaneous electric polarization is at least one order of magnitude smaller than that resulting from the ionic displacement of the lattice vectors, and the direction of the spontaneous electric polarization is determined by the point group of the ferroelectric. Here, we introduce a new class of ferroelectricity termed Fractional Quantum Ferroelectricity. Unlike ordinary ferroelectrics, the polarization of Fractional Quantum Ferroelectricity arises from substantial atomic displacements that are comparable to lattice constants.

Out-of-plane ferroelectricity and robust magnetoelectricity in quasi-two-dimensional materials.

Thin-film ferroelectrics have been pursued for capacitive and nonvolatile memory devices. They rely on polarizations that are oriented in an out-of-plane direction to facilitate integration and addressability with complementary metal-oxide semiconductor architectures. The internal depolarization field, however, formed by surface charges can suppress the out-of-plane polarization in ultrathin ferroelectric films that could otherwise exhibit lower coercive fields and operate with lower power.

Lattice Distortion and Low-Frequency Anharmonic Phonons Suppress Charge Recombination in Lead Halide Perovskites upon Pseudohalide Doping: Time-Domain Ab Initio Analysis.

Perovskite solar cells have witnessed a surge in interest as a promising technology for low-cost, high-efficiency photovoltaics with certified power conversion efficiencies beyond 25%. However, their commercial development is hindered by poor stability and nonradiative losses that restrict their approach to the theoretical efficiency limit. Using ab initio nonadiabatic molecular dynamics, we demonstrate that nonradiative charge recombination is suppressed when the iodide in formamidinium lead iodide (FAPbI) is partially replaced with pseudohalide anions (SCN, BF, and PF).

Manipulating two-dimensional magnetic states electric field and pressure.

Topological spin configurations have been an intriguing topic due to the exotic transport properties and promising applications in spintronic devices. The discovery of two-dimensional (2D) magnetic materials such as CrI provides new platforms for manipulating magnetic structures. Here, by first-principles calculations and Monte Carlo methods, we investigated the exchange interaction and magnetic states of 2D van der Waals ferromagnetic/ferroelectric heterostructure CrI/InSe.

Realistic Spin Model for Multiferroic NiI_{2}.

A realistic first-principle-based spin Hamiltonian is constructed for the type-II multiferroic NiI_{2}, using a symmetry-adapted cluster expansion method. Besides single ion anisotropy and isotropic Heisenberg terms, this model further includes the Kitaev interaction and a biquadratic term, and can well reproduce striking features of the experimental helical ground state, that are, e.g.

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.