We investigate how many-electron excited states emerge in twisted MoSe_{2} homobilayers when the lattice reconstructions evolve. Notably, we identify a new trion resonance that arises in the transition regime of lattice reconstruction, where gradual changes in atomic alignment between the layers occur. Magnetic field-dependent measurements, supported by first-principles calculations, indicate that the exciton forms at the K valley while the doped hole resides in the Γ valley. First-principles calculations further indicate that two nearly degenerate exciton resonances can arise, localized at different sites within the moiré supercell. We propose that the new trion resonance is a "charge-transfer" trion, in which the electron-hole pair is spatially separated from the doped hole. The emergence of these complex excited states stems from the distinct moiré potentials acting on holes and excitons, resulting in their different spatial distribution within the superlattice.

Colloidal quantum well light-emitting diodes (CQW-LEDs) hold tremendous potential for next-generation display and lighting applications, owing to their high color purity, excellent efficiency, and low fabrication cost. However, efficiency roll-off at high current density makes it challenging to achieve high brightness and long lifetime. Here, we designed CdSe/ZnSe/ZnS core/shell/shell CQWs with near-unity photoluminescence quantum yield. The graded heterostructure promotes carrier injection, and the bottom-emission device based on CdSe/ZnSe/ZnS CQWs exhibits remarkably suppressed efficiency roll-off with a record-high J90 (current density for EQE to decrease to 90%) of 485 mA/cm2 and a long operational lifetime (T95 @ 100 cd/m2) over 47000 h. In addition, the top-emission device also shows low efficiency roll-off and high current efficiency of 36.5 cd/A. This study provides a compositionally graded approach to suppress efficiency roll-off in CQW-LEDs, demonstrating the strong potential of the newly developed CQWs for next-generation ultrabright and highly efficient optoelectronic devices.

Integrating essential physical priors into deep-learning first-principles methods is a critical fundamental problem. Here we demonstrate that the deep learning density functional theory Hamiltonian (DeepH) method can be substantially improved by changing the learning objective to a rotation-invariant and basis-free quantity-the real-space Kohn-Sham potential (named DeepH-R). Benefiting from the enhanced physical priors, DeepH-R achieves substantially improved prediction accuracy and generalization ability compared to previous DeepH approaches. Moreover, DeepH-R provides a more accurate and straightforward route to deep-learning density functional perturbation theory, and enables the training of foundation models of electronic structure with sub-meV accuracy, opening new opportunities for AI-driven materials discovery.

In computational physics and materials science, first-principles methods, particularly density functional theory, have become central tools for electronic structure prediction and materials design. Recently, rapid advances in artificial intelligence (AI) have begun to reshape the research landscape, giving rise to the emerging field of deep-learning electronic structure calculations. Despite numerous pioneering studies, the field remains in its early stages; existing software implementations are often fragmented, lacking unified frameworks and standardized interfaces required for broad community adoption. Here we present DeepH-pack, a comprehensive and unified software package that integrates first-principles calculations with deep learning. By incorporating fundamental physical principles into neural-network design, such as the nearsightedness principle and the equivariance principle, DeepH-pack achieves robust cross-scale and cross-material generalizability. This allows models trained on small-scale structures to generalize to large-scale and previously unseen materials. The toolkit preserves first-principles accuracy while accelerating electronic structure calculations by several orders of magnitude, establishing an efficient and intelligent computational paradigm for large-scale materials simulation, high-throughput materials database construction, and AI-driven materials discovery.

Triferroic compounds, characterized by the coexistence and coupling of more than two ferroic orders, have attracted considerable attention as a novel class of multiferroic materials. Compared with conventional multiferroics dominated by pairwise coupling, the involvement of a third ferroic order enables more complex and tunable functional responses, facilitating deterministic multistate control. Although triferroicity has so far been observed only in 3D systems, extending it to 2D materials is particularly appealing, as 2D systems offer advantages such as high storage density, low energy consumption, and mechanical flexibility. In this review, we provide a comprehensive overview of recent progress in 2D triferroic materials, with a particular focus on the origin and interplay of the three ferroic orders at the structural and electronic levels. In addition, we highlight potential applications of 2D triferroics, including multistate storage and spintronic devices. Finally, we outline several promising directions for future research and development in the field of 2D triferroics.

Two-dimensional transition metal dichalcogenides have emerged as promising candidates for optoelectronic applications because of their rich excitonic landscape featuring distinct spin-valley configurations. High-quality plasmonic nanocavities can dramatically enhance exciton-plasmon coupling through extreme optical field confinement. However, it has remained elusive to develop a robust nanocavity system for the manipulation of different excitons toward room-temperature excitonic devices. Herein we present a type of hierarchical plasmonic nanocavity constructed on a pyramid array for probing diverse excitons in WSe2 monolayer and multilayer at room temperature. Different excitons, including dark A, localized, and interlayer excitons, can be simultaneously detected and modulated within the plasmonic nanocavities. This hierarchical nanocavity platform utilizes sharp pyramid tips to introduce strain confinement and out-of-plane field enhancement for visualizing both localized and dark A excitons, whose emissions can be selectively modified by controlling the cavity dimensions. Different from classical bright A excitons, the valley-polarized emission enhancement of dark A excitons shows the opposite handedness to the excitation state. Our results offer an interesting cavity platform for the investigation of different excitonic systems and the development of quantum emitters.

Moiré superlattices provide a powerful platform for flat bands and correlated topological phases, yet most established examples rely on valley-contrasting Berry curvature in hexagonal lattices. Here, we propose a different route to achieve topological moiré minibands based on noncollinear spin-orbit coupling (SOC) in centrosymmetric type-II SOC bilayers. Interlayer hybridization opens local pseudogaps and produces sharply localized Berry curvature, which twisting reconstructs into isolated topological minibands without requiring valley degrees of freedom or hexagonal symmetry. We demonstrate this mechanism in tetragonal Dresselhaus-SOC HgI2, where a Lieb-like moiré potential yields topological flat bands. To improve miniband isolation, we develop a physics-informed machine-learning surrogate that identifies stronger SOC as a key design principle and guides the replacement of Hg by Pb. The resulting PbI2 minibands are narrower and better isolated, supporting correlation-driven magnetism and tunable quantum spin Hall and Chern insulating phases, thereby providing an optimized material realization for experimental exploration.

The computational discovery of phonon-mediated superconductors is hindered by the prohibitive cost of density functional perturbation theory (DFPT). Here, guided by the metallized σ-bonding picture, we introduce the σ-bonding density of states (σDOS) as an efficient physical descriptor to identify high-transition-temperature (T_c) superconductors from density functional theory (DFT)-level electronic structure without explicit DFPT calculations. The evaluation of σDOS can be further accelerated by a deep-learning DFT Hamiltonian method, enabling efficient large-scale screening for superconductors. Screening 2 million materials, we identify B_13Se as an ambient-pressure superconductor candidate with predicted T_c > 40 K, together with a family of high-T_c B_13X candidates, supporting the effectiveness of this discovery strategy. By bridging physics priors with AI acceleration, this study delivers an efficient and generalizable route for computational materials discovery in the AI era.

Metallic environments are generally expected to suppress excitons through strong dielectric screening, yet their influence can differ in composite systems where metallic and insulating regions coexist. Here, we investigate excitonic states in PdxCu1-xCrO2 thin films across a percolation-driven metal-insulator transition. Optical spectroscopy and many-body GW calculations show that CuCrO2 hosts strongly bound excitons with a binding energy of about 489 meV. With increasing Pd substitution, the system approaches an insulator-to-metal transition near x = 0.5, consistent with the site-percolation threshold of a triangular lattice. In the pre-percolation regime, the excitonic resonance redshifts by 241 meV while the Tanguy continuum onset remains nearly unchanged, consistent with a substantial increase in exciton binding energy before metallization. An image-charge-based excitonic hydrogen model shows that isolated metallic regions can enhance electron-hole binding through image-charge interactions, whereas conventional screening is recovered once a continuous metallic network forms. Although this model provides a possible interpretation of the observed excitonic evolution, an alternative scenario in which metallic and excitonic responses originate from electronically distinct states and evolve independently cannot be excluded. These results reveal unusual metallic-excitonic coexistence near a percolation-driven metal-insulator transition and suggest nanoscale metallic proximity as a possible route for modifying excitonic interactions.

Using a self-consistent Hartree-Fock theory, we show that the recently observed ferromagnetism in twisted bilayer WSe2 [Nat. Commun. 16, 1959 (2025)] can be understood as a Stoner-like instability of interactionrenormalized moir & eacute; bands. We quantitatively reproduce the observed Lifshitz transition as function of hole filling and applied electric field that marks the boundary between layer-hybridized and layer-polarized regimes. The former supports a ferromagnetic valley-polarized ground state below half-filling, developing a topological charge gap at half-filling for smaller twist angles. At larger twist angles, the system hosts a gapped triangular N & eacute;el antiferromagnet. On the other hand, the layer-polarized regime supports a stripe antiferromagnet below half-filling and a wing-shaped multiferroic ground state above half-filling. We map the evolution of these states as a function of filling factor, electric field, twist angle, and interaction strength. Our results demonstrate that long-range exchange in a symmetry-unbroken parent state with strongly renormalized moir & eacute; bands provides a broadly applicable framework to understand itinerant magnetism in moir & eacute; TMDs.

We predict a so-called axial Hall effect, a Berry-curvature-driven anomalous Hall response, in Lieb-lattice altermagnets. Using a tight-binding model, we reveal a hidden topological degree of freedom: the axial pseudospin. Breaking the double degeneracy of axial symmetry exposes this pseudospin, generating a substantial Berry curvature and pronounced intrinsic anomalous Hall conductivity. Subsequent first-principles calculations confirm the emergence of this effect in the family of strained ternary transition-metal dichalcogenides. Focusing on Mn2WS4, we demonstrate that the axial Hall effect essentially arises from the interplay between Dresselhaus spin-orbit coupling and the piezomagnetic response, resulting in highly localized and enhanced Berry curvature. Remarkably, the magnitude of this effect is significant and remains constant under varying strain, underscoring the topological nature of the axial degree of freedom. Beyond monolayers, this effect manifests as a distinctive thickness-dependent modulation of both anomalous and spin Hall responses in multilayer structures. These findings emphasize the critical role of spin-orbit coupling and noncollinear spin textures in altermagnets, an area that has received limited attention, and open new pathways for exploring and tuning intrinsic Hall phenomena and spintronic applications in topological altermagnets.

Predicting charge transport in strongly anharmonic materials, particularly ultralow thermal conductors, remains a major challenge for first-principles methods. In such systems, perturbative treatments of electron-phonon interactions and the harmonic phonon picture often break down, necessitating non-perturbative approaches. The ab initio Kubo-Greenwood(aiKG) formalism provides a rigorous framework for evaluating temperature-dependent carrier transport beyond the harmonic approximation. Nevertheless, its practical application is computationally demanding because it requires large supercells, extensive statistical sampling, and extrapolation to the zero-frequency limit. In this work, we introduce an artificial-intelligence(AI)-assisted aiKG framework that incorporates the deep-learning Hamiltonian model. By predicting the Kohn-Sham Hamiltonian with sub-meV accuracy for supercells of up to 250 atoms, the model bypasses the costly iterative self-consistent field calculations while retaining first-principles reliability within the scope of effects captured by the training data. Using a strongly anharmonic thermal insulator, potassium iodide(KI) as a benchmark system, we demonstrate that the proposed approach enables efficient simulations of electronic structure and transport properties from a large supercell. The framework reproduces temperature-dependent carrier mobilities, spectral functions, and effective masses in close agreement with the underlying density functional theory while reducing computational cost to 10

Two-dimensional Janus structures have garnered growing attention across multidisciplinary fields. Despite extensive theoretical and experimental efforts, a fundamental design principle for intrinsic Janus materials remains elusive. Here, we introduce a first-principles alloy theory based on cluster expansion, incorporating strong cation-mediated anion-pair repulsion and refined short-range cluster-cluster interactions, to elucidate the formation mechanism of intrinsic Janus structures with a distorted 1T phase amid competing phases. Our approach explains why intrinsic Janus structures are observed in RhSeCl and BiTeI—composed of elements from different groups—and predicts a broad range of 1T-like intrinsic Janus candidates ready for synthesis. Notably, in RhSeCl, we reveal that intrinsic Janus materials can exhibit anomalous second-harmonic generation (SHG) driven by a distinct quantum geometric effect stemming from lattice and chemical-potential mirror asymmetry. Furthermore, an unconventional skin effect emerges in finite-thickness RhSeCl, featuring a hidden bulk SHG response. Our theory paves the way for ab initio design of intrinsic Janus materials, accelerating progress in Janus science.

Altermagnets have recently been recognized as a distinct class of magnetic materials characterized by alternative spin-split electronic structures without net magnetization. Despite intensive studies on their single-particle spintronic and valleytronic properties, many-electron interactions and optical responses of altermagnets remain less explored. In this work, we employ many-body perturbation theory to investigate excited states and their strain tunability. Using monolayer Mn2WS4 as a representative candidate, we uncover a novel spin-valley-dependent excitonic selection rule in two-dimensional altermagnetic Lieb-lattices. In addition to strongly bound excitons, we find that linearly polarized light selectively excites valley-spin-polarized excitons. Importantly, these lowestenergy excitons are optically bright, making them experimentally accessible. Moreover, due to the interplay between altermagnetic spin symmetry and electronic orbital character, we predict that applying uniaxial strain can lift valley degeneracy and enable the selective excitation of spin-polarized excitons-an effect not achievable in previously studied transition-metal dichalcogenides. These generalized spin-valley-locked excitonic states and their strain tunability can offer a robust mechanism for fourfold symmetric altermagnets to encode, store, and read valley and spin information.

Ferroelectric HfO2 is a promising candidate for next-generation memory devices due to its CMOS compatibility and ability to retain polarization at nanometer scales. However, the polar orthorhombic phase (Pca2_1) responsible for ferroelectricity is metastable and requires extrinsic stabilization, which makes it challenging for integration with silicon. We predict that bilayer 1T-HfO2 can exhibit robust and switchable out-of-plane (OOP) polarization arising from stacking-induced symmetry breaking. Using first-principles density functional theory, we predict that monolayer 1T-HfO2 can be cleaved from the (111) surface of cubic hafnia, and the monolayer is dynamically stable. When two aligned monolayers are twisted to form a moiré superlattice, it breaks the interlayer symmetry and allows the emergence of bistable OOP polarization. At a twist angle of 7.34o, the system exhibits a net polarization of 16 μC/cm2. This sizeable polarization is due to the large polar displacements concentrated in AB stacking domains. Importantly, this polarization can be reversibly switched via interlayer sliding with a low energy barrier ( 8 meV/formula unit) and comparable low coercive field ( 0.2 V/nm), offering electric-field tunability. These findings establish twisted bilayer 1T-HfO2 as a scalable and robust 2D ferroelectric platform, enabling new pathways for integrating ferroelectric functionality into atomically thin memory and logic devices.

Using density-functional theory combined with the many-body perturbation approach, we have studied the evolution of quasiparticle electronic structure, electron-hole excitations, and optical properties in blue phosphorene nanoribbons. In these low-dimensional systems, the unique dielectric screening results in a significant self-energy correction, which remains impactful even in nanoribbons of large width. Density-functional theory calculations show that armchair and zigzag blue phosphorene nanoribbons exhibit distinct scaling law with width due to their substantially anisotropic effective masses. The quasiparticle band gap evolves as 1/omega with ribbon width omega and is insensitive to structural chirality, contrasting with that predicted by density functional theory. In the meantime, the optical properties are dominated by exciton effects. The exciton energy and exciton binding energy evolve as 1/omega(1.5) and 1/omega(0.8), respectively. The polarizability, evolving as 1/omega(0.4), underscores the enhanced electron-electron and electron-hole interaction in these one-dimensional systems. Our findings not only provide deep insight into the many-body effects in the electronic and optical properties of low-dimensional materials, but they also show the tunable band gap over a wide range in blue phosphorene nanoribbons, which could find potential applications in optoelectronics.

Non-magnetic FeNb_3Se_10 has been demonstrated to be an insulator at ambient pressure through both theoretical calculations and experimental measurements and it does not host topological surface states. Here we show that on the application of pressure, FeNb_3Se_10 transitions to a metallic state at around 3.0 GPa. With a further increase in pressure, its resistivity becomes independent of both temperature and pressure. Its crystal structure is maintained to at least 4.4 GPa.

First-principles electronic structure calculations have profoundly advanced research in physics, chemistry and materials science, yet their further development remains constrained by the accuracy-efficiency dilemma. Here we highlight recent breakthroughs in deep-learning methodologies that address this challenge, including the deep-learning quantum Monte Carlo method for the accurate study of correlated electrons and deep-learning density functional theory for efficient large-scale material simulations. These advances extend the reach of first-principles calculations to unprecedented scales and complexity, enhancing the impact of quantum mechanics in scientific discovery.