The reliable identification of magnetic ground states remains a major challenge in high-throughput materials databases, where density functional theory (DFT) workflows often converge to ferromagnetic (FM) solutions. Here, we partially address this challenge by developing machine-learning classifiers trained on experimentally validated MAGNDATA magnetic materials, leveraging a limited number of simple compositional, structural, and electronic descriptors sourced from the Materials Project Database. Our propagation-vector classifiers achieve accuracies above $92\%$, outperforming a recent equivariant-neural-network study on a differently constructed dataset in reliably distinguishing between zero and nonzero propagation-vector structures, and exposing a systematic ferromagnetic bias inherent to the Materials Project database for more than 6840 candidate materials. In parallel, LightGBM and XGBoost models trained directly on the Materials Project labels achieve accuracies of $82\%$ and $85\%$, respectively (with macro-$F_1$ average scores of $66\%$ and $63\%$), proving useful for large-scale screening for magnetic classes, when refined by MAGNDATA-trained classifiers. These results underscore the role of machine-learning techniques as corrective and exploratory tools, enabling more trustworthy databases and accelerating progress toward the identification of materials with various properties.

Anomalous Hall effect has been understood in terms of the geometric nature of Bloch bands and impurity scattering, and has been observed in a wide variety of magnetic materials, including ferromagnets and antiferromagnets. Recently, a large anomalous Hall effect was reported in the noncollinear antiferromagnetic metal $\mathrm{NbMnP}$, whose magnetic order is a mixture of even- and odd-parity magnetic components. Such a magnetic structure is expected to exhibit the anomalous Hall effect and the nonlinear Hall effect from the symmetry breaking of the antiferromagnetic ordering. Here, we theoretically investigate the intrinsic anomalous and nonlinear Hall effect in $\mathrm{NbMnP}$ induced by the quantum geometry of the Bloch band using the first-principles calculation and the Wannier interpolation method. We found that the intrinsic Hall response of $\mathrm{NbMnP}$ is predominantly governed by the strongly enhanced Berry curvature and Berry-connection-polarization dipole on a specific mirror plane. These enhanced geometric quantities originate from the spin-orbit-coupling-induced gap openings along the nodal lines. Our results indicate that $\mathrm{NbMnP}$ serves as a model system for investigating transport phenomena originating from nodal lines in parity-mixed antiferromagnets.

We present a comprehensive first-principles study on the origin of the piezomagnetic effect in the noncollinear antiferromagnet ${\mathrm{Mn}}_3\mathrm{Sn}$, a material known for exhibiting a large anomalous Hall effect. We investigate stress-induced variations of electronic and magnetic states and elucidate the mechanism of the piezomagnetic effect from both real-space and wave-number space perspectives. In real space, the emergence of piezomagnetism is understood to arise from rotations of the magnetic moments at specific Mn sites, which directly couple to the strain. Through detailed electronic structure analysis, we identify the Fermi surfaces that play a crucial role in the emergence of piezomagnetism. Our results reveal that pseudodegenerate Fermi surfaces are lifted under applied stress, which significantly contributes to the induced net magnetization. By combining these complementary real-space and $k$-space pictures, our dual-space analysis provides deep insight into the microscopic origins of stress-driven magnetization in ${\mathrm{Mn}}_3\mathrm{Sn}$.

Materials datasets are often assembled from multiple experimental and literature sources that differ substantially in quality and reliability. We present an uncertainty-aware framework for materials property prediction that accounts for such data heterogeneity. A resampling-based approach is used to quantify per-source uncertainty, and the resulting data-driven uncertainty proxies are embedded into a Kriging surrogate model, enabling adaptive weighting of data according to reliability. Applied to four ferroelectric datasets, including electrostrain, piezoelectric coefficient, recoverable energy storage density, and electrocaloric strength, the framework consistently improves predictive accuracy relative to uncertainty-agnostic baselines. Experimental validation on five newly synthesized compositions further confirms its robustness and predictive reliability. This data-efficient framework provides a practical route for integrating heterogeneous and variable-fidelity datasets in materials informatics.

As the first intrinsic antiferromagnetic topological insulator, ${\mathrm{MnBi}}_2{\mathrm{Te}}_4$ offers a platform for investigating topological phenomena driven by magnetism. Prior studies focused on bulk single crystals and exfoliated flakes, but the extreme two-dimensional (2D) limit remains underexplored, despite theoretical predictions of exotic behavior. In particular, synthesis and atomic-scale characterization of ultrathin ${\mathrm{MnBi}}_2{\mathrm{Te}}_4$ films remain challenging. Here we explore molecular beam epitaxy grown ${\mathrm{MnBi}}_2{\mathrm{Te}}_4$ thin films down to a single-layer thickness. Structural characterization via electron and x-ray diffraction, atomic force microscopy, and scanning tunneling microscopy confirms layer-by-layer growth and high crystallinity, while magnetotransport measurements show the expected magnetic signatures. Interestingly, scanning tunneling microscopy and quasiparticle interference imaging reveal Dirac-like surface states that persist even in monolayer films and monolayer islands. Our experiments provide elusive atomic-scale insights into the band structure of ${\mathrm{MnBi}}_2{\mathrm{Te}}_4$ in the 2D limit and under lateral confinement, and establish a foundation for the synthesis of heterostructures based on monolayer ${\mathrm{MnBi}}_2{\mathrm{Te}}_4$ and device applications.

Rutile ${\mathrm{Sn}}_{1-x}{\mathrm{Ge}}_x{\mathrm{O}}_2$ alloys are promising materials for high-power electronic applications due to their dopability and tunable ultrawide band gaps. We use first-principles density functional theory and statistical mechanics to investigate the crystallographic, electronic, and thermodynamic properties of rutile ${\text{Sn}}_{1-x}{\text{Ge}}_x{\text{O}}_2$ alloys. We predict that the lattice parameters follow Vegard's law, while band gaps calculated with the hybrid HSE06 functional exhibit strong bowing, consistent with experiment. We also predict that the disordered phase has a large positive mixing enthalpy and a slight tendency for Ge-Sn clustering, indicated by weakly negative short-range order parameters. This large positive mixing enthalpy produces a miscibility gap with a critical temperature above 2300 K, implying that the high Ge and Sn solubilities observed in thin-film synthesis cannot be explained by the incoherent phase diagram alone. We demonstrate that coherency strain substantially alters phase stability. Calculations of the coherent spinodal show significant suppression of the miscibility gap, reducing the critical temperature to $\approx 900\mathrm{K}$. These coherent phase boundaries could account for the experimentally observed high solubilities at typical growth temperatures. Our results indicate that coherency strain stabilizes these metastable alloys and enables band-gap engineering in this ultrawide-band-gap material system.

In this study, we demonstrate the successful fabrication of ${\mathrm{TiO}}_2/\mathrm{FeSe}/{\mathrm{SrTiO}}_3$ and ${\mathrm{TiO}}_2/\mathrm{FeSe}/{\mathrm{LaAlO}}_3$ heterostructures using PLD. When the growth rates were sufficiently low, anatase ${\mathrm{TiO}}_2$, which has been reported to induce superconductivity in FeSe, could be grown epitaxially on FeSe. For ${\mathrm{TiO}}_2/\mathrm{FeSe}/{\mathrm{SrTiO}}_3$ with FeSe layers thicker than 5 nm, the $\mathrm{FeSe}/{\mathrm{TiO}}_2$ interface was clean, as confirmed by the observation of Laue fringes around the FeSe(001) reflection. Although a thinner FeSe layer is expected to enhance $T_{\mathrm{c}}$, we could not observe such behavior because it was difficult to realize interfacial superconductivity while growing anatase ${\mathrm{TiO}}_2$. Most strikingly, superconductivity appeared when ${\mathrm{TiO}}_2$ was deposited on $\mathrm{FeSe}/{\mathrm{LaAlO}}_3$, clearly demonstrating that the interaction between the top oxide layer and underlying FeSe can induce superconductivity. This work demonstrates the feasibility of fabricating FeSe/oxide superlattices by PLD, establishing a platform for the exploration of interfacial superconductivity in iron-based superconductors.

High-entropy alloys (HEAs) possess exceptional mechanical properties and thermal stability, yet their vast compositional space and complex atomic arrangements present significant challenges for property prediction and design. To overcome this, we have trained a machine-learned interatomic potential (MLIP) for the AlTiCrMoW HEA using the message-passing atomic cluster expansion (MACE) framework. This new MLIP is trained on a series of high-accuracy density functional theory (DFT) calculations that covers the available configuration space of the HEA. The training set includes key configurations with linear-response-informed short-range ordered configurations, which are generated using a concentration wave analysis within the coherent potential approximation (CPA) and subsequently optimizedd using conventional DFT calculations. Phonon bispersion ands (PDBs) for the HEA are generated using the MACE model, and several physical properties are extracted for the HEA, such as the elastic constants and the bulk modulus. The fine-tuned model reproduces DFT structural and elastic benchmarks with high accuracy, at a significantly reduced computational cost, allowing for larger simulations to be performed, which can more accurately probe the configuration space and composition of the alloy. Here, we perform Monte Carlo based simulations to identify the ordering transition of equiatomic AlTiCrMoW, where we match the experimental value of 1273 K. Vacancy relaxation volumes are investigated for AlTiCrMoW, as an example of a property analysis, which would be computationally intractable via DFT.

This work describes topological magnon transport in zigzag ${\mathrm{CrI}}_3$ nanoribbons in the presence of edge strain. Exchange coupling terms under strain are obtained from first-principles calculations and the topological properties are introduced via second-neighbor Dzyaloshinskii-Moriya interactions (DMI). The magnon Hamiltonian is calculated using linear spin-wave theory and the Holstein-Primakoff transformation. Then, we use the nonequilibrium Green's function method to calculate the spin-wave-generated currents in ribbons with different edge strain. Our calculations show the formation of strongly localized edge topological magnons within the gap for DMI values slightly higher than the ones reported experimentally and in the presence of a tensile edge strain of the order of 3%. The magnon-mediated topological spin transport calculations show an increase of the spin current and characteristic decay length in tensile-strained ${\mathrm{CrI}}_3$ nanoribbons compared with unstrained ones. Our findings demonstrate that straintronics provides a powerful route to harness and control topological magnons in two-dimensional magnetic materials.

We characterize the magnetic ground state of the newly synthesized lanthanide intermetallic ${\mathrm{GdNiSn}}_4$ via resonant elastic x-ray scattering measurements. This compound forms distorted square nets of Gd that initially order magnetically below 23 K, followed by a lower-temperature transition at 16 K. Our scattering data identify the ground state order as a single-q incommensurate, collinear order that slides towards a commensurate wave vector above the 16 K transition. Magnetic symmetry analysis combined with azimuthal dependence resolves the ground state magnetic structure as a moment-modulated spin density wave state with Gd moments oriented parallel to the in-plane $a$-axis. We discuss connections between the observed magnetic order and electronic properties in this square-net compound.

Cerium hydride has a variety of interesting properties, including a known lattice contraction and densification with increasing hydrogen content. However, precise stoichiometric control is not experimentally straightforward and ab initio approaches are not computationally feasible for many properties such as melting and low temperature diffusion. Therefore, we develop a machine-learned interatomic potential for cerium hydride that is valid for H to Ce ratios from 2.0 to 3.0. A query-by-committee active learning approach is used to develop the training set. Leveraging classical molecular dynamics simulations, we assess a range of properties and provide fundamental mechanisms for the trends with stoichiometry. A majority of the properties follow the trend of lattice contraction, being governed by the stronger lattice binding induced by adding octahedral atoms.

Using liquid-quench reactive force field ReaxFF molecular dynamics, we revisit how changes within the method parameter space—annealing time, annealing temperature, and number of atoms—influence the nanostructure of ${sp}^2$-dominated amorphous carbon at 1 g/cm³ mass density. Initially, the degree of graphitization, measured by the fraction of ${sp}^2$ bonding, increases monotonically with annealing time and temperature. Elevating the annealing temperature above 4000 K disrupts the balance between graphitic ordering and temperature-induced disorder, resulting in detrimental variations in the ${sp}^2$-bonding fractions, ring-size distributions, pore formation, and mass-density uniformity. The widest nanopore-size distribution, extending into the mesopore range, is associated with the maximum graphitization, and is achieved through pore coarsening within the 4000 K annealing window. The system size maintains the robustness of these findings as the larger available volume promotes formation of larger nanopores. The obtained models were subsequently subjected to large uniaxial deformations, where representative 8000 atoms models display only modest residual elastic anisotropy, even in systems with both micro- and mesopores. The initial linear elastic response extends into a nonlinear elastic regime characterized by preservation of original carbon–carbon bonding and pore identity, but with pore stretching and progressive alignment of graphitic layers with the loading direction. At higher strains, heterogeneous ring-size expansion accompanied by ${sp}^2$-chain formation at layer junctions enables extended plastic deformation prior to fracture. The intrinsic pore preservation across a large strain range, high strain tolerance, and gradual failure make microporous amorphous carbon particularly attractive as a durable carbon framework for next-generation ion-based battery electrodes.

The applicability of hybrid density functional approximations (DFAs) in the solid state is still largely hindered by a high computational cost in the evaluation of the exact exchange series. We review formal and computational aspects of a direct space approach to the evaluation of exact exchange in periodic systems with local, atom-centered, Gaussian-type basis functions. We discuss an efficient prescreening strategy in terms of the localized basis to either truncate the series via overlap-based criteria or partition it into distinct regions where the integrals can be computed exactly or approximately via a bipolar expansion of the Coulomb operator. The inclusion of exact exchange in hybrid DFAs largely corrects for the self-interaction error, ensures a better description of electron localization, and thus proves crucial to the characterization of defects, strongly correlated materials, band gaps in semiconductors, as well as to an effective treatment of spin-orbit and electron-phonon couplings. Three test systems are considered, which have been selected as representative of different electronic regimes: (i) bulk hematite, $\alpha \text{−}{\mathrm{Fe}}_2{\mathrm{O}}_3$, in its insulating, antiferromagnetic configuration; (ii) semiconducting single-layer ${\mathrm{WSe}}_2$ (with inclusion of spin-orbit coupling); and (iii) bulk EuO in its metallic ferromagnetic phase at a pressure of 20 GPa. The strategy is assessed on various electronic properties (energy, band gap, spin magnetic moment, Rashba splitting) and is documented to yield calculations with hybrid DFAs with a relative cost of just 3–6 times that of standard (semi)local DFAs.

Direct orientation contrast imaging of zinc-blende III-V materials is studied using scanning electron microscopy. A quantitative approach is taken using a 3 µm thick orientation-patterned GaP grown on a GaAs sample, studying the antiphase domain contrast with respect to the electron beam energy and the tilt angle. A qualitative approach is taken for III-V grown on nonpolar materials with and without chemical mechanical polishing. Finally, a processing of the acquired image for GaP on Si reveals in-plane preferential antiphase boundaries.

Bilayer stacking provides a powerful route to engineer quantum phases in two-dimensional materials. We investigate a bilayer system constructed from monolayers of the BaF electride—a prototypical magnetrene—and find a pronounced tendency toward antiferromagnetic (AFM) ordering driven by interlayer confinement of interstitial anionic electrons. Using first-principles calculations and dynamical mean-field theory (DMFT), we show that the bilayer is dynamically stable and that our density functional theory calculations indicate an AFM-G configuration as the lowest among the collinear magnetic orders examined, with spin density highly localized between the layers. Constructing cavity-centered Wannier functions yields an effective low-energy Hamiltonian for the correlated interstitial subspace. DMFT calculations show that increasing electronic correlations triggers spectral weight transfer to Hubbard bands, leading to quasiparticle suppression and the opening of a correlation-induced gap. Long-lived local moments emerging within the interlayer subspace, signaled by the progressive flattening of $\chi \left(\tau \right)$ with $U$, naturally favor AFM ordering. Our findings establish bilayer electrides as a tunable platform for creating and controlling correlated magnetic states via confinement in a van der Waals gap.

Ionic liquid gating (ILG) technique has been demonstrated as a powerful manner to manipulate the valence-state and electronic structures of complex oxides through topotactic phase transformations. However, the dominant type of transfer ions of a particular system and the underlying mechanisms for the ion incorporation dynamics remain controversies in different systems. In this article, ILG treatments were applied to double-perovskite ${\mathrm{La}}_2{\mathrm{NiMnO}}_6$ (LNMO) system. In response to positively gated electric bias, protons (${\mathrm{H}}^{+}$) incorporate into LNMO films gradually. Based on the combined results from synchrotron-based x-ray absorption and photoelectron spectroscopies, the doped electrons not only induce the valence-state reductions of both Mn and Ni sites, but also the downshift of the valence-band maximum away from the Fermi level, which is distinct from the valence-state and electronic-state variations induced by electron doping from oxygen vacancies (${\mathrm{V}}_{\mathrm{o}}$). This peculiar valence-state reduction has been verified by first-principles calculations, which not only enlightens the roles of energy competitions between ${\mathrm{H}}^{+}$ insertion and ${\mathrm{V}}_{\mathrm{o}}$ formation, but also the electronic structures near the Fermi level in determining the electrochemical gating mechanism of complex oxides.

The crystal and magnetic structures of the nitride antiperovskite $\mathrm{M}{\mathrm{n}}_3\mathrm{GeN}$ reveals ferrimagnetic order stemming from a distorted kagome-derived lattice of the Mn atoms. Polycrystalline $\mathrm{M}{\mathrm{n}}_3\mathrm{GeN}$ was synthesized via a solid-state reaction and characterized using neutron powder diffraction, dc magnetometry, and first-principles calculations. Rietveld refinement reveals near-stoichiometric composition ($\mathrm{M}{\mathrm{n}}_3\mathrm{Ge}{\mathrm{N}}_{0.992\left(7\right)}$) adopting a tetragonal $I4/mcm$ structure at $T=500\mathrm{K}$ and below, featuring axially distorted and tilted $\left[\mathrm{NM}{\mathrm{n}}_6\right]$ octahedra that result in a buckled Mn kagome lattice. On heating, the tetragonal distortion and octahedral tilt angle decrease continuously before transitioning to the cubic $Pm\overline{3}m$ antiperovskite phase at $T\approx 527\mathrm{K}$. Neutron diffraction and magnetometry together reveal noncollinear ferrimagnetic ordering. For $30\mathrm{K}\le T\le 500\mathrm{K}$, the magnetic structure is described by magnetic space group $Ib{a}^{\prime }{m}^{\prime }$ (72.544), with inequivalent Mn1 and Mn2 sublattices that couple antiferromagnetically to yield a net moment. Density-functional theory-based calculations show that the different local moments originate from the bandwidths associated with distinct Mn–N bond lengths. Temperature-dependent refinements reveal distinct differences in the thermal disordering profiles of the Mn1 and Mn2 sublattices. These findings reveal a subtlety in the magnetic and structural behavior of $\mathrm{M}{\mathrm{n}}_3\mathrm{GeN}$, highlighting the interplay between structural distortions, magnetic ordering, and electronic structure in kagome-derived antiperovskite materials.

As a crucial information carrier in condensed matter physics and next-generation information devices, the valley degree of freedom has made the realization of its polarization modulation and effective induction of the anomalous valley Hall effect a core research direction in the field of valleytronics. However, relevant studies on achieving this effect in two-dimensional double-transition-metal MXenes antiferromagnetic systems remain scarce. Based on first-principles calculations, we systematically investigate the valley-related electronic structure and transport properties of double-transition-metal MXene ${\mathrm{HfCr}}_2{\mathrm{C}}_2{\mathrm{H}}_2$. It is found that the ${\mathrm{HfCr}}_2{\mathrm{C}}_2{\mathrm{H}}_2$ can lift the valley degeneracy at the edges of the conduction and valence bands, resulting in valley splittings of 63.3 meV and 16.1 meV, respectively. Importantly, the nonzero Berry curvature in the K and ${\mathrm{K}}^{\prime }$ valleys, together with the finite anomalous Hall conductivity in the vicinity of the band edges, provides evidence for the anomalous Hall effect in the valley in this material. Furthermore, the valley splitting can be effectively tuned by the magnetization direction and biaxial strain, while the valley polarization can be reversed through manipulation of the magnetization direction. This study provides a new material platform and theoretical basis for the design and development of magnetically controlled valleytronic devices in double-transition-metal MXenes.