Bulk orthorhombic boron (o-B14) is an intriguing, recently predicted, three-dimensional (3D) boron allotrope. Its structure is characterized by edge-sharing pentagonal bipyramids, with diverse bond lengths. These structural motifs facilitate the formation of unusual seven-center-two-electron $\pi$ bonds, predicted for the first time in 3D boron allotropes. The presence of these bonds highlights the complexity and versatility of boron chemistry under ambient conditions. Moreover, this material is predicted to be a superconductor with a critical temperature $T_c$ of 29.1 K [Phys. Chem. Chem. Phys. 25, 15400 (2023)]. In the present work, we explore the electronic and optical properties of bulk o-B14 and its monolayer and bilayer forms, including hydrogen termination, using first-principles calculations. These two-dimensional structures are predicted to be dynamically stable and to exhibit a remarkable variety of electronic behavior including semiconductivity with a band gap of 0.67 eV (bilayer), superconductivity with a $T_c$ of 24.3 K (H-terminated bilayer), and magnetism (monolayer). The plasmonic and optical responses exhibit anisotropic behavior driven by the directional bonding network, as well as absorption in the visible region of the spectrum, which suggest promising opportunities for applications in advanced optoelectronic, plasmonic, and quantum devices.

We report on the photoconductive properties of thin layers of ${\mathrm{MoS}}_2$ flakes (with layer thicknesses ranging between 25–50 nm) beyond room temperatures. Photoconductivity measurements at multiple temperatures, between 290 and 425 K were performed using a laser source of $\lambda$ = 640 nm. The variation of photocurrent with temperature at effective laser intensities, $P_{\mathrm{eff}}$ (0.1 $\mu \mathrm{W}<P_{\mathrm{eff}}<$ 0.8 $\mu \mathrm{W}$) as well as the variation of fall times of the devices as a function of increasing laser intensities was thoroughly examined and analyzed with a well established theoretical model [A. Rose, Phys. Rev. 97, 322 (1955)]. Our results indicate the possibility of achieving stable ${\mathrm{MoS}}_2$ based detectors with high photoresponsivities ($R$) $\sim {10}^2\mathrm{A}/\mathrm{W}$ and shot noise limited detectivities ($D$) $\sim {10}^{11}$ Jones, under ambient conditions and beyond room temperatures.

Controlling magnetic anisotropy (MA) in two-dimensional (2D) ferromagnetic metals is crucial for the development of spintronic devices, yet simultaneously stabilizing strong magnetism and well-defined anisotropy in the monolayer limit remains a major challenge. Previous studies have shown that tuning the STO layer thickness in ${\mathrm{SrRuO}}_3/{\mathrm{SrTiO}}_3$ (SRO/STO) superlattices can induce eightfold MA, but it remains unclear whether this behavior originates from the intrinsic properties of the isolated monolayer or relies on periodic interlayer coupling. In this work, we address this issue by synthesizing ${\mathrm{SRO}}_1/{\mathrm{STO}}_N$ superlattices and STO-capped monolayer SRO films. Our experiments reveal that changing the STO layer thickness can systematically tune the MA in the superlattices; more importantly, the STO-capped isolated monolayer simultaneously exhibits metallic transport, robust ferromagnetism, and pronounced eightfold MA with easy axes along the ${\langle 111\rangle }_{\mathrm{pc}}$ directions. These results demonstrate that single-layer SRO can stabilize a 2D correlated ferromagnetic metal and maintain eightfold MA in the fully decoupled limit, indicating that this symmetry does not rely on superlattices periodicity. Our study thus reveals an intrinsic property of single-layer SRO and provides key experimental evidence for understanding correlation-driven MA in ultrathin itinerant ferromagnets.

Ferroelectric materials are a class of dielectrics that exhibit spontaneous polarization which can be reversed under an external electric field. The emergence of ferroelectric order in incipient ferroelectrics is a topic of considerable interest from both fundamental and applied perspectives. Despite evidence from first-principles calculations that strain triggers ferroelectricity in ${\mathrm{KTaO}}_3$, conventional methods cannot reliably characterize the soft-mode dynamics that govern its ferroelectric behavior. In this study, we investigate the impact of in-plane uniaxial and biaxial strain, ranging from 0 to 1%, on pristine ${\mathrm{KTaO}}_3$ to explore its potential for ferroelectricity induction via inversion symmetry breaking. By integrating density-functional theory calculations with the stochastic self-consistent harmonic approximation assisted by on-the-fly machine learned force fields, we obtain accurate structural information and dynamical properties under varying strain conditions while incorporating higher-order anharmonic effects. Employing the Berry-phase method, we obtained the ferroelectric polarization of the strained structures over the entire temperature range up to 300 K. Our findings provide valuable insights into the role of strain in stabilizing ferroelectricity in ${\mathrm{KTaO}}_3$, offering guidance for future experimental and theoretical studies on strain-engineered ferroelectric materials.

Anomalous relaxation is one of the hallmarks of disordered systems. Following perturbation by an external source, many glassy, jammed, and amorphous systems relax as a stretched or compressed exponential as a function of time. However, despite their ubiquity, the origins of and the connection between these phenomenological relaxation functions remain to be understood. Here, we observe a tunable crossover from stretched- to compressed-exponential relaxation by photoexciting single crystal ${\mathrm{Ca}}_3{\mathrm{Ru}}_2{\mathrm{O}}_7$ across a structural phase transition. We present a simple lattice model that shows how spatial inhomogeneity and local, strain-mediated interactions cooperate to produce the dynamical crossover. Our work reveals anomalous relaxation dynamics in an idealized single crystal material and establishes photoexcited solids as promising platforms for probing the mechanisms underlying anomalous relaxation.

Electrical switching of antiferromagnets (AFM) is critical for AFM spintronics. However, electrical pulse-induced Néel vector reorientation in AFM insulators, while predicted to occur at much faster timescales than ferromagnetic switching, has only been demonstrated in the quasi-DC regime. Here we report reliable current-induced AFM switching in $\mathrm{Pt}/\alpha \text{-F}{\mathrm{e}}_2{\mathrm{O}}_3$ bilayers using electrical pulses with various durations spanning three orders of magnitude down to 0.3 ns. Together with COMSOL simulations of temperature distributions in our samples for various pulse widths, our results suggest that thermally assisted spin-orbit torque likely play an important role for sub-ns pulses. This work demonstrates the viability of electrical switching of AFM spins using sub-ns pulses.

Topological properties and topological superconductivity in real materials have attracted intensive experimental and theoretical attentions recently. The topological electronic properties of pressure-induced superconductors ${\mathrm{BiH}}_2$ have been studied based on first-principles electronic structure calculations. Recent experiments have revealed that ${\mathrm{BiH}}_2$ exhibits five distinct phases under high pressure, our studies show that $Cmcm\text{−}{\mathrm{BiH}}_2, Pnma\text{−}{\mathrm{BiH}}_2, Pnnm\text{−}{\mathrm{BiH}}_2$, and $P{2}_1/m\text{−}{\mathrm{BiH}}_2$ are all topological metals defined on curved Fermi levels, while the $P{2}_1{2}_1{2}_1\text{−}{\mathrm{BiH}}_2$ holds Weyl points near the Fermi level. The topological surface states (TSSs) and Fermi arcs of ${\mathrm{BiH}}_2$ right cross the Fermi level and hold helical spin textures. Considering the fact that the ${\mathrm{BiH}}_2$ exhibit high superconducting transition temperatures ($T_c$) of $\sim 70$ K under pressure confirmed by recent experiments, the superconducting bulks will induce superconductivity in the TSSs via the proximity effect. Thus, the hydride superconductors ${\mathrm{BiH}}_2$ may provide a promising platform for exploring topological superconductivity and Majorana zero modes.

$\text{G}{\text{a}}_2{\text{O}}_3$/GaAs heterojunctions are emerging as promising candidates for next-generation power electronics, photonics, and energy devices, leveraging the high breakdown voltage and thermal stability of $\text{G}{\text{a}}_2{\text{O}}_3$ alongside the mature technology, high hole mobility, and high refractive index of GaAs. The efficiency of these devices depends strongly on the band alignment between the two materials, however both type-I and type-II alignment have been reported in the literature for these heterostructures. To address this ambiguity, we use hybrid density functional theory to systematically investigate the band alignment at GaAs/$\text{G}{\text{a}}_2{\text{O}}_3$ interfaces, focusing on the role of interface chemistry. By considering Ga-O-, As-, and As-O-rich interfaces both in amorphous and crystalline $\text{G}{\text{a}}_2{\text{O}}_3$ phases, we demonstrate that interface stoichiometry determines the alignment type: Ga-O-rich interfaces exhibit type-II alignment with large valence band offsets (∼3.1 eV), while As-rich and As-O-rich interfaces favor type-I alignment with reduced offsets (∼2.3–2.6 eV). These trends are attributed to interface dipole formation driven by bonding configuration. Our findings provide insight into the relationship between chemistry and band alignment in GaAs/$\text{G}{\text{a}}_2{\text{O}}_3$ heterostructures, enabling targeted optimization for specific device applications.

The recently investigated nitrogen (N) incorporation into TiNbMoTaW high entropy alloy films leads to a domelike superconducting transition temperature $T_C$ vs nitrogen concentration $x$ (with $x=\text{N}/M$ representing the ratio between atomic fractions of nitrogen and metal atoms, $M=\mathrm{Ti}+\mathrm{Nb}+\mathrm{Mo}+\mathrm{Ta}+\mathrm{W}$) in the respective high entropy nitride ${\left(\mathrm{TiNbMoTaW}\right)}_{1.0}{\mathrm{N}}_x$, with a large $T_C$ enhancement. In this study, we report on the effect of N insertion into NbTaHfTiZr films, which show a lower valence electron concentration and a lower configuration entropy than those of TiNbMoTaW. The $T_C$ vs $x$ dependence in ${\left(\mathrm{NbTaHfTiZr}\right)}_{1.0}{\mathrm{N}}_x$ exhibits a different course, in which $T_C$ first decreases from $\sim 6.5\mathrm{K}$ at $x=0$ to $T_C\approx 1\mathrm{K}$ at $x=0.25$ and $x=0.42$, and then starts to increase and reaches a maximum of $\sim 8.6\mathrm{K}$ at $x=0.81$ followed by a decline to $\sim 6.7\mathrm{K}$ when $x$ approaches the stoichiometric value 1. In this case, the transition of the initial high entropy alloy bcc structure to the fcc structure of high entropy nitrides proceeds slowly and leads to a wide $x$ range in which $T_C$ is suppressed. The analysis shows that the $T_C$ vs $x$ course and the $T_C$ enhancement in high entropy nitrides depend on the valence electron concentration of the initial high entropy alloy, as higher values accelerate the tendency to form a fcc structure and are less sensitive to the localization of otherwise mobile electrons in metallic high entropy alloys due to their bonding to N atoms. However, other parameters, such as the atomic size difference of the metallic constituents and their affinity towards nitrogen, also have to be considered.

Superionic materials have attracted considerable interest due to their unique electronic and thermal transporting properties, with far-reaching implications for solid-state electrolyte batteries and planetary science. Despite extensive studies, the physicochemical origin of superionic behavior remains insufficiently understood. In this work, we develop a generalized machine-learning descriptor for superionic materials by combining structural, elemental, and density-functional theory primary features with the Sure Independence Screening and Sparsifying Operator (sisso) framework. We identify four key factors to recognize superionic materials: electronegativity, chemical hardness, density, and bond strength. The developed machine-learning descriptor applies well beyond conventional lithium- and sodium-based superionic systems and can be extended to high-pressure conditions. Based on our machine-learning descriptor, we conducted a high-throughput screening of 13 019 materials from the materials project database, and 353 potential superionic candidates were identified. This study not only sheds light on the underlying physical origin of the superionic state but also provides guidance and insights for the design and experimental synthesis of future superionic materials.

FeS is a key end-member iron alloy relevant to the cores of telluric planets. Here, we present a comprehensive study of the FeS phase diagram up to 150 GPa and 3000 K, using in situ x-ray diffraction measurements in laser-heated diamond anvil cells. Our results extend the determination of the FeS melting curve up to 100 GPa. We have investigated the subsolidus phase relations of FeS, observing transitions between FeS-VI (MnP-type structure) and FeS-IV (distorded NiAs-type structure). We find that this transition is second-order, with the stability range of FeS-IV narrowing with increasing pressure. Additionally, we identify a novel phase, designated FeS-IX, which is formed at high temperatures above the stability field of FeS-IV, and persists up to the melting point of the alloy. By integrating our data with ambient-temperature literature results, we establish a thermal equation of state for FeS over the investigated pressure and temperature range. These findings carry significant implications for understanding the thermal state and structure of planetary cores, with specific relevance to those of Mercury and Mars.

Molecular dynamics simulations are applied to study the shock response of the hard and soft phases of nanostructured polyureas. Shocks are modeled using both a nonequilibrium explicit impact method and a quasistatic Hugoniostat method. These methods subject systems to different strain rate histories, resulting in dissimilarities in the transient evolution of the thermodynamic state of the material during shock loading. Once materials are compressed into glassy states, both Hugoniostat and impact simulations display similar Eyring-like relaxation of the residual shear stress corresponding to a logarithmic slowdown in plastic deformation post-shock. The slowly relaxing shear stress makes the prediction of post-shock densities and shock speeds sensitive to total simulation time. While Hugoniostats can efficiently resolve the steady-state limiting Hugoniot, our results indicate that this is unlikely to be realized in experiments over the timescales during which shocks transit real microstructures. Instead, real shocks will travel at transient shock speeds governed by the dynamic stress relaxation of the relevant phases, which can be predicted by explicit impact simulations.

${\mathrm{ThCr}}_2{\mathrm{Si}}_2$-type intermetallics are layered conductors in which crystallographic anisotropy and multiband electronic states often give rise to characteristic magnetotransport phenomena. Here we report the molecular-beam epitaxy growth of ${\mathrm{LaAg}}_2{\mathrm{Ge}}_2$ thin films on MgO(001) and their magnetotransport properties. Hall measurements are well described by an effective two-carrier model with a high-mobility minority electron coexisting with a low-mobility majority hole. The observed positive magnetoresistance of 22.5% at 9 T exceeds the prediction of the isotropic two-band Drude model by more than an order of magnitude, indicating an anisotropic multisheet Fermi-surface origin. Consistently, angle-dependent magnetoresistance exhibits a dominant twofold anisotropy and additional reproducible dip/peak features at characteristic tilt angles that are nearly independent of field and temperature. These results extend our understanding of the anisotropic electronic transport in thin-film germanides within the ${\mathrm{ThCr}}_2{\mathrm{Si}}_2$ family.

Magnesium (Mg) is a lightweight structural metal with high specific strength, but its limited room-temperature ductility—stemming from its hcp crystal structure—remains a major barrier to its broader engineering applications. Enhancing the plastic deformability of Mg through alloying has emerged as a promising strategy, yet the atomistic mechanisms underlying these improvements remain poorly understood. In the present work, we develop a machine learning potential (MLP) to accurately model Mg-Bi alloys and elemental Mg with quantum-level fidelity and computational efficiency. Using this MLP, we perform large-scale molecular dynamics (MD) simulations to investigate the mechanical behavior of pure Mg and Mg-5%Bi nanopillars under uniaxial compression and tension along the [0001] direction. The simulation results reveal that Bi addition (5 at %) significantly enhances Mg's plasticity by promoting the nucleation and glide of $1/2\langle \mathrm{c}+\mathrm{a}\rangle$ dislocations. This leads to a transition in the dominant deformation mechanism—from transformation-assisted plasticity in pure Mg to dislocation-dominated plasticity in Mg-5%Bi. Moreover, our simulations quantitatively reproduce the experimentally observed asymmetry in yield strength, where compressive strength exceeds tensile strength along the $c$ axis. This work not only elucidates the atomic-scale origin of ductility enhancement via Bi addition, but also reveals the importance of atomistic modeling using MLP for predicting the mechanical behaviors of complex alloy systems.

The new non-collinear magnetic order, in an Al-doped lithium ferrite (Al-LFO), $\left({\mathrm{Li}}_{0.5}{\mathrm{Al}}_{0.5}\right){\left({\mathrm{Fe}}_{0.75}{\mathrm{Li}}_{0.25}\right)}_2{\mathrm{Fe}}_3{\mathrm{O}}_8$ (denoted as Li50Al50), could be determined in the magnetic space group $\mathit{P}{4}_3{2^{\prime }}_1{2}^{\prime }$ using high-resolution neutron powder diffraction (HRNPD) at 3 and 50 K. The largest spin-canting angle of the non-collinear octahedral B-sublattice determined from the structural analysis using 3K-HRNPD approaches the Yafet-Kittel angle 21° at 0 K, extrapolated from saturation magnetization. The spin-canting textures shown at 3 and 50 K are thermally averaged at elevated temperatures to reveal collinear spin alignments along [001] at 300 K under zero external fields. The non-collinearity of magnetic spins in Al-LFOs arises from multiple spin-reorientation (SR) processes without magnetic phase transitions below $T_c$ (e.g., 788 K in Li50Al50). The SRs are activated above 100 K, showing Arrhenius behavior, but blocked at 5 K without altering the spontaneous magnetic polarization, as indicated by ac magnetic susceptibility data. The dilute effect of $\mathrm{L}{\mathrm{i}}^{+}$ replacing $\mathrm{F}{\mathrm{e}}^{3+}$ ($20\%$ in Li60Al40 or $25\%$ in Li50Al50) because of the respective $\mathrm{A}{\mathrm{l}}^{3+}$-substitution for $40\%$ and $50\%$ $\mathrm{L}{\mathrm{i}}^{+}$ in the geometrically frustrated B-sublattice (the hyperkagome lattice) enhances not only the lattice-distortion-induced electric polarization, but also the intrinsic spin dynamics. All SR-related features in both Al-LFOs are effectively quenched above 0.5 kOe, where all magnetic spins of $\mathrm{F}{\mathrm{e}}^{3+}$ are collinearly aligned parallel to the external magnetic fields, independent of frequency and temperature. These findings could be applied to further develop LFO-type multiferroics, e.g., for photovoltaic applications.

In this work, we construct a database containing approximately 30 000 entries for the frequency-dependent dielectric function within the independent-particle approximation, covering a wide range of semiconductors. Calculations are performed using the PBE and TASK approximations to the exchange-correlation potential. Building on these results, we evaluate various approaches to dimensionality reduction of the spectra, including convolutional autoencoders, which achieve effective compression to a latent space around 50 times smaller. These models are comparatively inexpensive to train and help reduce the computational cost associated with training large, off-the-shelf neural network models. The resulting models are subsequently employed to screen for wide-bandgap, high-refractive-index materials.