Papers

The speed of optically driven magnetization dynamics is fundamentally determined by how efficiently angular momentum can be transferred between electronic, spin and lattice degrees of freedom. In rare-earth magnets, this process is typically slow because optical excitation primarily addresses itinerant electrons, whereas the magnetic moment resides in localized 4f states. Here we show that selective optical excitation of localized magnetic states can overcome this limitation. Using femtosecond pump-probe magneto-optical spectroscopy of ferrimagnetic gadolinium iron garnet, we resonantly excite an intra-4f transition of Gd3+ at 4.65 eV and resolve the ensuing dynamics of the antiferromagnetically coupled Gd and Fe sublattices. Direct excitation of the 4f manifold induces an ultrafast demagnetization of the Gd sublattice with a characteristic time of 38 fs, more than two orders of magnitude faster than in elemental gadolinium and even faster than the response of the Fe sublattice in the same material. By contrast, off-resonant excitation strongly suppresses the acceleration of the Gd dynamics while leaving the Fe response largely unchanged. These results demonstrate that the ultrafast magnetic response of rare-earth systems is governed not only by intrinsic material properties but also by the optical excitation pathway. Selective access to localized magnetic states therefore provides a powerful photonic handle for engineering angular-momentum flow and controlling magnetism far from equilibrium.

A semi-empirical kinetic framework is formulated for predicting phase selection in multicomponent concentrated alloys under rapid solidification. The approach is based on the critical cooling rate required to suppress competing crystalline pathways and combines topology-dependent ranking of BCC-, FCC-, and HCP-like crystallization pathways with a correction for glass-forming ability. The formulation includes a topology-dependent viscosity correction with a smoothed BCC multiplier and a continuous correction factor for glass-forming ability based on mixing enthalpy, excess entropy, and atomic-size dispersion. Comparison with experimental and computational data shows that the kinetic criterion captures changes in the lattice type expected from the valence electron concentration criterion, describes kinetic suppression of phase separation, and identifies competitive multiphase crystallization. The model also distinguishes alloys with high and low glass-forming ability. The proposed framework provides a practical approach for preliminary evaluation of kinetic phase competition in rapidly solidified multicomponent melts.

Semiempirical electronic structure methods such as Density-Functional Tight-Binding (DFTB) offer a computationally efficient approach to molecular and materials simulations, bridging the gap between first-principles accuracy and classical force field speed while retaining full access to electronic properties. However, DFTB calculations based on self-consistent charge (SCC) schemes can still suffer from slow convergence, particularly for complex molecular and materials systems, making the iterative procedure a significant bottleneck in large-scale simulations and high-throughput workflows. We present a machine learning approach that accelerates DFTB simulations by predicting optimal initial atomic charges. Using element-specific models based on the Smooth Overlap of Atomic Positions descriptor and kernel ridge regression, we train charge models on reference calculations and demonstrate that ML-predicted initial charges consistently and significantly improve SCC convergence across diverse chemical systems including organic molecules, biomolecules, water clusters, transition metal oxides and solid electrolytes.

Aqueous corrosion of metals involves multiple interconnected processes. Thus, computer simulation of corrosion as a whole needs to be able to describe the individual processes and how they influence each other. Atomistic simulations are designed to obtain detailed information for small regions of space over short times. Thus there are limits to the understanding that can be obtained by atomistic simulations alone. Here is presented a method that uses generalised rate equations to extend the length and time scales that can be accessed. It is shown to reduce to either the phase field or cellular automata methods in certain limits. The generalised kinetic equations can reproduce the behaviour described by both the Nernst-Planck and Butler-Volmer equations, which are frequently used to describe corrosion. In addition, the method can describe local rearrangements of atoms such as chemical reactions. Example results are shown for illustrative 1D and 2D problems, with good agreement being found with other methods.

We study terahertz field-driven second-order nonlinear electron transport phenomena, including the nonlinear Hall effect (NLHE), in two-dimensional tellurene flakes. The dc current excited by linearly polarized terahertz (THz) radiation in Hall bar samples is investigated in directions both along and perpendicular to the $c$-axis of tellurene. As expected for second-order transport phenomena, the current scales as the square of the in-plane electric field of the radiation $\bf E$, and depends on its orientation. The current results from a combination of three contributions, including the NLHE, the Nonlinear Longitudinal (NLL) and Nonlinear Diagonal (NLD) currents. We established the equivalence between NLH, NLL, and NLD transport currents and Linear photogalvanic effect (LPGE) contributions induced by the absorption of linearly polarized and unpolarized THz radiation. All contributions can be controlled by a gate voltage and have opposite signs for electron and hole conductivity. The magnitude of the current increases drastically when the samples are cooled from room temperature to 4.2 K. It also increases with decreasing radiation frequency. These results are well described by the developed phenomenological and microscopic theories. We show that the THz radiation-induced electric current originates from microscopic mechanisms such as skew scattering, side jump, and the Berry curvature dipole.

Large language model (LLM) agents are increasingly expected to play a central role in AI-driven scientific discovery. Equipped with broad knowledge, flexible reasoning, and tool use, they have the potential to autonomously explore and solve scientific problems by repeatedly proposing hypotheses, testing them, and revising their beliefs in the light of the evidence. In current agents, however, these hypotheses, tests, and belief updates are buried in unstructured logs, and no mechanism lets the agent or the human researcher audit that process. Here we propose the Hypothesis Evolution Protocol (HEP), an agent harness that provides hypothesis generation, evaluation, and evolution as explicit, auditable operations. On materials-science research tasks, a HEP-equipped agent operates the hypothesis–test–evidence–belief cycle that planning-style agents lack, generalizes across research questions, and exploits the protocol more fully as the base LLM becomes more capable. These results mark a step toward auditable AI scientists, whose scientific reasoning can be inspected, verified, and built upon.

We derive a low-energy $\mathbf{k}\cdot\mathbf{p}$ effective Hamiltonian for monolayer osmium carbide (OsC) and ruthenium carbide (RuC) in a planar hexagonal configuration. First-principles calculations indicate that both monolayers are dynamically stable and exhibit features of a two-dimensional quantum spin Hall (QSH) phase, characterized by a nontrivial $\mathbb{Z}_2$ topological invariant. Using symmetry analysis at the $\Gamma$ point, we construct a multiband $\mathbf{k}\cdot\mathbf{p}$ Hamiltonian including spin-orbit coupling and reduce it to a four-band low-energy model through Löwdin partitioning. The effective Hamiltonian has a block-diagonal form, with two blocks related by time-reversal symmetry, analogous to the Bernevig–Hughes–Zhang (BHZ) model. In contrast to the standard BHZ form, the symmetry-allowed off-diagonal coupling contains quadratic momentum-dependent terms, which modify the low-energy dispersion near the $\Gamma$ point. The fitted parameters reproduce the ab initio band structures in the low-energy region, yielding a compact model for analyzing the electronic and topological properties of monolayer OsC and RuC.

Materials characterized by competing interactions often exhibit a large number of nearly degenerate periodic states. Here we show that layered UAgBi$_2$ hosts a cascade of field- and temperature-induced magnetic transitions. Based on specific heat, thermal expansion, and neutron diffraction, we construct a phase diagram that reveals at least seven nearly degenerate magnetic states in UAgBi$_2$. The observed multi-step magnetization process can be understood by square-wave structures with distinct propagation vectors $\mathbf{k}$=(0, 0, k) in the presence of strong easy-axis anisotropy that confines the moments along the c axis. Our findings are consistent with a magnetic devil's staircase described by the axial next-nearest neighbor Ising (ANNNI) model and place UAgBi$_2$ as a rare realization of the devil's staircase in a 5f-electron system.

Artificial intelligence (AI) is transforming scientific discovery, but its effectiveness is fundamentally limited by the availability of structured scientific knowledge. Although existing databases have accelerated data-driven materials research, much of the knowledge needed for predictive modeling and inverse design remains embedded in unstructured scientific literature. We present an Autonomous Scientific Knowledge Generation Framework that transforms scientific publications into a Unified AI-Ready Scientific Knowledge Base. The framework integrates ontology-guided literature acquisition, hybrid scientific knowledge extraction, semantic harmonization, knowledge fusion, and validation within a unified workflow. Rather than treating literature retrieval, information extraction, and database construction as separate tasks, the framework progressively converts scientific publications into structured, semantically consistent, and provenance-preserving knowledge suitable for AI-driven reasoning. As a proof of concept, the framework was applied to electro-optic materials. Autonomous literature acquisition retrieved and validated about 1,000 publications from multiple scholarly repositories. A representative subset of eight publications was processed through the complete workflow, generating 29 structured scientific records that were harmonized into 7 canonical scientific records. The results demonstrate the complete transformation from scientific literature to an AI-ready scientific knowledge base while preserving quantitative measurements, operating conditions, provenance, and scientific context. The proposed framework provides a scalable, domain-independent foundation for predictive AI, generative AI, and closed-loop AI-driven scientific discovery.

For a weakly interacting Bose gas trapped by an imperfect one-dimensional artificial crystal, we study the effect of its punctual defects, i.e. vacancies, on the ground state properties of the system. In the framework of the mean field approximation, we numerically solve the corresponding Gross-Pitaevskii equation using the “Gradient Flow with Discrete Normalization” method, also known as the imaginary time method. The crystal is artificially produced by applying an external Dirac comb potential to the Bose gas where vacancies are created by randomly removing a predetermined number of deltas. We observe that as the number of randomly removed deltas increases, the ground state energy decreases exponentially from its value for the perfect crystal case until it reaches its value when the Bose gas is free. The ground state energy is reported for different magnitudes of the interaction between bosons and several system sizes which we extrapolate to infinity for the crystal with only one vacancy. Also, we observe the presence of an energy gap between the ground state energies of the perfect system and that with a vacancy, which is more noticeable for values of the particle interaction magnitude $ g \leq 0.1$, when the delta strength $P_0 = 10$. In addition, we report the boson distributions within the crystal, %inside a box with periodic boundary conditions, i.e. the probability density functions which show localization features around vacancies which disappear as $g$ increases. From the ground state energy, the chemical potential is obtained immediately.

We present an ab initio calculation of the band-to-band internal-conversion rate of the $\hbar\omega_{\rm nuc} \approx 8.35$ eV isomeric transition in $^{229}$ThO$_2$. Because the nuclear transition energy exceeds the electronic band gap of ThO$_2$, the isomer can decay nonradiatively by resonantly promoting a valence electron into the conduction band. We formulate this process as a Brillouin-zone sum over vertical interband transitions weighted by local Th-centered hyperfine matrix elements, which are evaluated directly from all-electron full-potential linearized augmented-plane-wave Bloch spinors. A finite nuclear magnetization model is included to regularize the short-range hyperfine interaction and to account for the Bohr-Weisskopf effect. After applying scissor shifts to span the experimentally reported ThO$_2$ band gaps, we find calculated internal-conversion lifetimes in the range of $1-16~\mu{\rm s}$. The lifetime increases strongly as the band gap approaches $\omega_{\rm nuc}$ because the resonant interband phase space at the nuclear transition energy is reduced. For the larger reported ThO$_2$ gaps, the calculated lifetime is comparable to the measured conversion-electron Mössbauer lifetime [Nature 648, 300 (2025)]. Our analysis implies that choosing solid-state hosts with band-gap values slightly lower than $\omega_{\rm nuc}$ can optimize solid-state nuclear clock performance with internal-conversion electron readout.

The choice of crystalline orientation and offcut angle is non-trivial for low-symmetry $\beta\text{-Ga}_2\text{O}_3$, where anisotropy impacts bulk and thin film synthesis, material properties, and power device fabrication and performance. Scalable (100)-oriented $\beta\text{-Ga}_2\text{O}_3$ wafers are desirable for electronic devices but are not typically used due to 10-30x slower growth rates compared to other orientations. Here we report molecular beam epitaxy (MBE) growth rates equal to the fast growth direction by using (100) $Ga_2O_3$ wafers with large grown-in offcuts. The offcuts (up to 13.4{\deg}) are directly grown by Edge-defined Film-fed Growth (EFG) of 2D ribbons with rotated seed crystals, avoiding material loss from crystal boule offcut methods while maintaining high crystalline quality. Chemical-mechanical polishing produces epitaxy-ready substrates, and step flow growth is observed across all offcut angles. We measure an unintentional n-type doping density of $2{\times}10^{15} cm^{-3}$, one of the lowest values reported for MBE-grown films. Planar Schottky barrier diodes on these epilayers without edge termination have an on/off ratio ~10$^5$ and an average breakdown field of 1.56 MV/cm, comparable to or exceeding similar devices fabricated on other orientations. Overall, these results illustrate the importance of both crystal face and offcut angle and validate the use of the scalable (100)-oriented $\beta\text{-Ga}_2\text{O}_3$ wafers.

Two-dimensional van der Waals heterobilayers provide an attractive platform for the development of next-generation spintronic devices. Here, first-principles calculations are performed to investigate the structural, electronic and magnetic properties of MSe2/WTe2 (M = V, Cr, Mn, Fe, and Co) van der Waals heterobilayers. The pristine WSe2/WTe2 heterobilayer in AA'-configuration is found to be energetically favorable and exhibits type-II band alignment with a band gap of 0.70 eV, and this provides an ideal platform for controlling carrier transport. Substituting W with 3d transition metal atoms, induces long-range magnetic ordering and reconstructs the spin-resolved electronic band structure. The formation of the heterointerface generates pronounced charge redistribution and an intrinsic built-in electric field, leading to interface-induced electronic reconstruction. MnSe2/WTe2 heterobilayer exhibits half-metallicity, whereas FeSe2/WTe2 heterobilayer simultaneously exhibits half-metallicity and spin-resolved type-II band alignment. Interfacial electronic reconstruction further produces a substantial perpendicular magnetic anisotropy, driving MnSe2 from an in-plane easy axis with MAE value of 1.10 meV in the isolated monolayer to a robust out-of-plane easy axis with MAE value of 20.8 meV in the heterobilayer. Among all the structures, CoSe2/WTe2 heterobilayer exhibits maximum Curie temperature (273.87 K). The combined results establish that interface engineering makes MSe2/WTe2 heterobilayers as a promising candidates for next-generation low-dimensional spintronic applications.

X-ray diffraction (XRD) is fundamental to structural materials characterization, yet transforming a raw powder pattern into a refined crystal structure still demands considerable domain expertise. We present AGAPI-XRD, a hybrid framework integrating DiffractGPT generative structure prediction, database pattern matching against JARVIS-DFT and COD, and automated Rietveld refinement and ALIGNN-FF relaxation through a unified API at https://atomgpt.org/xrd. First, we used the AGAPI-XRD pipeline to evaluate the crystal structure of a variety of minerals in the RRUFF database that were experimentally characterized using powder x-ray diffraction. Next, we benchmarked the lattice parameter prediction fidelity of the AGAPI-XRD pipeline using a subset of the Alexandria PBE-hull dataset and the subset of RRUFF minerals that have known lattice parameters. AGAPI-XRD returns valid lattice parameters for 79.7% of the RRUFF benchmark minerals and for 94.8–98.1% of the Alexandria subset, while identifying a candidate structure for 93.8% of RRUFF minerals. For this benchmark, pattern matching delivers the highest accuracy for known phases, while DiffractGPT extends structure generation to complex materials absent from existing databases. Together, AGAPI-XRD advances accessible, end-to-end automated crystal structure determination from powder XRD data.

Vapor-deposited glass mixtures of organic semiconductors commonly serve as active layers in organic electronic devices, whose lifetime and performance are strongly influenced by the stability and structure of these mixed glasses. Here, we study the stability and anisotropic molecular packing of six co-deposited organic semiconductor glass mixtures with 50:50 weight ratio, by differential scanning calorimetry and spectroscopic ellipsometry. We find that all six binary systems exhibit high kinetic stability and significantly reduced enthalpy relative to the corresponding liquid-cooled glassy mixtures (ultrastable behavior), even for systems where the glass transition temperatures of the components differ by more than 90 K. Furthermore, we demonstrate that the birefringence of a co-deposited glass mixture, a measure of its anisotropic packing, can be predicted from the birefringence of glasses of the two pure components. These results for stability and structure are expected to be applicable to other co-deposited organic semiconductor glass mixtures, so long as the two components mix well in the glass and individually can form ultrastable glasses. Therefore, our findings are significant for designing novel electronic devices with enhanced device lifetime and increased operational efficiency.

Physical Vapor Deposition (PVD) is widely utilized for the production of organic semiconductor devices due to its ability to form thin layers with exceptional properties. Although the layers in the device usually consist of two or more components, there is limited understanding about the fundamental characteristics of such multi-component vapor-deposited glasses. Here, spectroscopic ellipsometry was employed to characterize the densities, thermal stabilities and optical properties of co-vapor deposited NPD and TPD glasses across the entire range of composition. We find that co-deposited NPD and TPD form high density glasses with enhanced thermal stability. The dependences of density and stability upon substrate temperature are correlated, and the birefringence of the co-deposited glasses is determined by the reduced substrate temperature of mixtures. Additionally, we observe that the transformation of a highly stable and dense two component glass into its supercooled liquid initiates from the free surface and propagates into the bulk at constant velocity, like single component PVD glasses. All these features are consistent with the surface equilibration mechanism.

The graphite-to-diamond transition exhibits striking variability under high-pressure, high-temperature (HPHT) conditions, producing diamond, graphitic phases, or metastable, mixed diamond-graphite nanocomposites despite similar synthesis conditions. Existing atomistic models, largely based on idealised single-crystal graphite, do not explain the persistence of partially transformed intermediate states under HPHT conditions. Here, using large-scale molecular dynamics simulations, we show that precursor grain structure governs graphite-to-diamond transformation pathways by decoupling diamond nucleation from cooperative transformation propagation. Grain boundaries first facilitate local sp$^3$ nucleation, after which diamond growth propagates within individual grains but becomes arrested at crystallographically mismatched grain boundaries. As a result, structurally heterogeneous graphite stabilizes kinetically arrested mixed sp$^2$-sp$^3$ states, whereas large or single-crystalline domains favour cooperative bulk transformation into diamond. Our findings identify structural heterogeneity as a missing control parameter alongside pressure and temperature, reframing metastable transformation products as kinetically trapped states arising from precursor microstructure rather than thermodynamic intermediates. Precursor crystallinity therefore emerges as a practical control parameter governing graphite-to-diamond transformation pathways.

We investigate the role of the CaCl2-type (Pnnm) phase in the high-pressure transformation of rutile TiO2, whose experimental signature has remained elusive. While analogies with other rutile-type oxides suggest such an intermediate, TiO2 typically exhibits a direct transformation to higher-coordination phases such as baddeleyite. Using an all-electron density functional framework combined with density functional perturbation theory, we show that rutile TiO2 undergoes a ferroelastic instability characterized by the development of an orthorhombic strain and a double-well energy landscape at 13.5 GPa. This instability is associated with the softening of the C11 - C12 elastic combination and the condensation of a B1g phonon mode, involving coordinated rotations of TiO6 octahedra that lower the symmetry to the Pnnm structure. Despite this clear elastic and dynamical pathway, enthalpy calculations show that the CaCl2-type phase is only weakly stabilized relative to rutile and remains energetically unfavorable compared to competing columbite and baddeleyite phases. Consequently, the Pnnm phase does not emerge as a stable high-pressure polymorph but instead exists as a transient or weakly metastable intermediate. These results demonstrate that the CaCl2-type phase represents the intrinsic ferroelastic response of rutile TiO2, yet is suppressed by thermodynamic competition, providing a consistent and unified explanation for its elusive experimental observation.

Integrating epitaxial thin films of ferroelectric PbTiO3 and paraelectric SrTiO3 into artificially layered periodic superlattices provides a unique platform for tuning strain, depolarization, and interfacial/surface energies, thereby accessing a rich phase diagram of topological polar structures (skyrmions, vortices, merons, or sinusoidal waves) and superstructures (polar supercrystals). Here we show that the 3D arrangement of polar vortices in a supercrystal suppresses thermal conductivity (k) of PTO/STO superlattices (SLs). The temperature dependence of k reflects the evolution of the polar superstructure, as determined by X-ray diffraction and transmission electron microscopy. The comparison with other SLs suggests that the 3D arrangement is crucial for controlling thermal conductivity beyond the usual interfacial scattering. Moreover, we observed an unexpected reduction in thermal conductivity with increasing superlattice thickness, a phenomenon reminiscent of phonon-wave Anderson localization. Our results show that complex polar superstructures can be useful active elements for modulating heat transport in technologies where control over heat dissipation is critical.

We use whispering-gallery-mode analysis to characterise the microwave dielectric properties of single-crystal TeO$_2$ at cryogenic temperatures and compare its loss performance with other low-loss dielectric materials. Finite-element modelling is combined with measurements at room temperature, 4 K, and 20 mK to develop accurate cryogenic simulations and extract the anisotropic dielectric permittivities, giving $\varepsilon_\parallel=25.75\pm0.08$ and $\varepsilon_\perp=20.90\pm0.07$. Loss measurements reveal quality factors as high as $9\times10^6$ and minimum loss tangents approaching $3\times10^{-8}$, placing TeO$_2$ among promising low-loss dielectrics for cryogenic microwave applications. Electron-spin-resonance spectroscopy further indicates a clean spin environment, while identifying distinct spin systems consistent with the known properties of the crystal.

Ternary and quaternary amorphous oxide semiconductors have many properties that make them promising candidates for use in electronic applications like display, memory, and back end of line logic. However, finding the right material for a given application and optimizing its properties, deposition, and integration, requires a thorough understanding of the physics and chemistry at play. When properly carried out, first principles computations can play a crucial role in enhancing this understanding. In this work, we highlight several pitfalls often observed in research applying these computations, with the Zn-Sn-O system as an example. We show that a proper understanding of the fundamental differences between the physics of the crystalline and amorphous or disordered phases is crucial, as is a proper statistical sampling of structural models. For the Zn-Sn-O system we conclude that from a performance point of view, mobility and initial threshold voltage, it is a promising material class. However, our computed results show that a similar sensitivity to hydrogen induced doping may be present as in IGZO.

All glasses, including organic semiconductor glasses, are non-equilibrium materials whose properties will change with time. This physical aging process is poorly understood for organic semiconductors, hindering the rational design of highly durable devices. In this study, we investigated the volume and enthalpy recovery processes in both thin films and bulk glasses of N,N'-Bis(3-methylphenyl)-N,N'-diphenylbenzidine (TPD). Our results revealed that volume recovery kinetics exhibit negligible dependence on film thickness for liquid-cooled TPD films between 400 nm and 100 nm. Additionally, the volume recovery process in TPD films was strongly coupled to the enthalpy recovery observed in bulk TPD glasses during annealing near the glass transition temperature. Remarkably, TPD films prepared by physical vapor deposition at room temperature demonstrated exceptional resistance to physical aging, with an aging rate approximately one order of magnitude lower than that of their liquid-cooled counterparts. These results not only enhance our understanding of the non-equilibrium dynamics in amorphous systems but also offer valuable insights for the design of next-generation organic devices with significantly improved stability and durability.

The identification of molecules that combine long spin coherence times and efficient spin-optical interfaces, ideally at room temperature, is pivotal towards the development of molecular quantum technology. By means of advanced first-principles methods, we here unravel the electronic structure for triangulene (1), its aza-cation derivative (2), and the crystal of 2,6,10-tri-tert-butyl-4,8,12-trimesityl-triangulene (3), and show that these organic diradicals possess a triplet ground state well separated from the first singlet excited state approaching 0.5 eV, closely resembling solid-state defects like nitrogen vacancy centers. In addition, we compute spin decoherence times due to the interaction with phonons and surrounding nuclear spins, showing that a deuterated molecule of 3 in a nuclear spin-free environment would support $T_2 = 0.21$ ms at 10 K. Importantly, we show that the engineering of specific low-energy vibrations could significantly improve $T_2$ toward the limit imposed by the molecular core spin relaxation, here estimated to be as long as $T_1=27$ ms at 300 K for 2. Finally, we compute two-phonon contributions to inter-system crossing at 300 K for2 as a luminescent prototype, and find that it is highly spin-selective, supporting the possibility to engineer optical read out and spin initialization. These results advance a unified first-principles theoretical foundation of spin decoherence and spin-selective excited-state processes and point to novel chemical design strategies for optically addressable, highly coherent molecular qubits.

2D van der Waals (vdW) magnets provide new opportunities for spin-orbit torque magnetoresistive random-access memory (SOT-MRAM) due to their unique properties. Electrically manipulating the magnetization of vdW magnets is key to realizing 2D SOT-MRAM, whereas conventional spin Hall materials such as heavy metals and topological insulators suffer from limitations in torque efficiency and energy consumption. Although recent studies show that the orbital Hall conductivity in light metals greatly exceeds the spin Hall conductivity, direct experimental demonstrations that the orbital Hall effect (OHE) can induce more energy-efficient SOT switching than the spin Hall effect in vdW magnets remain scarce. Here, we utilize Cr as the orbital current source to efficiently manipulate the magnetization of the vdW ferromagnet Fe3GaTe2 at room temperature. In the Fe3GaTe2/Pt (1.5 nm)/Cr (4.5 nm) trilayer structure, the orbital current originating from Cr is converted into the spin current via Pt, which then exerts a torque on Fe3GaTe2. Compared with control samples using 6 nm Pt as the spin current source, the switching current density in OHE-based devices is reduced by 3.9 times, resulting in a 52% reduction in power consumption. This work presents the promising potential of harnessing orbital currents to realize energy-efficient 2D SOT-MRAM.

Amorphous indium oxide (a-In$_2$O$_3$) is a high-electron-mobility semiconductor of central importance in thin-film transistors and a promising photoanode for solar-driven water oxidation. Despite sustained experimental and computational investigations, the structural motifs underlying its unusual transport properties and the existence of O-O peroxide-like bonds within its network have remained unresolved. Here we develop a MACE-based machine-learned interatomic potential trained on first-principles molecular dynamics trajectories and use it to generate and analyze amorphous structures containing up to 5120 atoms, two orders of magnitude larger than those adopted in typical ab initio studies. We find X-ray structure factors in excellent quantitative agreement with experiment and we confirm that In$_2$O$_3$ is a poor glass former, with the likely presence of quasi-crystalline regions in amorphous samples. Our large-scale structural analysis reveals extended chains of edge-sharing InO$_k$ polyhedra providing a concrete structural basis for the high electron mobility of a-In$_2$O$_3$. Our results strongly support the formation of O-O peroxide-like bonds in the amorphous network, with a mean length of 1.5 Å. We show that these bonds introduce localized in-gap states near the conduction band minimum, acting as a source of intrinsic n-type self-doping and enhancing sub-gap optical absorption. These effects are detectable via a distinct Raman feature near 850 cm$^{-1}$ that is absent in the IR spectrum. Overall, our results establish a comprehensive structure-property picture of a-In$_2$O$_3$, provide directly testable experimental predictions, and suggest that controlled amorphization is a viable strategy for improving the photoelectrochemical activity of a-In$_2$O$_3$.

Self-attention neural networks provide powerful variational wavefunctions that surpass the expressivity of traditional variational ansatze. This expressivity, however, comes with increased computational complexity, raising a pressing question about scalability – can such wavefunctions retain their accuracy at large system sizes? We apply self-attention wavefunctions to the two-dimensional homogeneous electron gas for up to N=169 particles, obtaining energies systematically lower than state-of-the-art DMC. Direct access to the ground state wavefunction further lets us recover the full collective-mode dispersion of the liquid phase, from the small-q plasmon branch to a roton-like minimum near q=2k_F. Observables at N=91 and N=169 are in near-perfect agreement, indicating convergence to the thermodynamic limit.

Accurate evaluation of Gibbs free energies is essential for constructing pressure-temperature phase diagrams. Conventional methods based on the quasi-harmonic approximation (QHA) require phonon spectra at many volume points and are therefore expensive in general. Here we develop an efficient method based on the interpolation of a few ab initio data points for Gibbs free energy evaluation under volume compression. Phonon spectra are calculated only at selected volumes. An effective Gruneisen parameter derived from the zero-point energy (ZPE) reconstructs the static-ZPE branch, while piecewise mode-resolved Gruneisen slopes reconstruct the finite-temperature vibrational branches on the target volume grids. The method is validated against QHA benchmarks for diamond (C), Al, Si, Ge, rutile TiO2, beta-PtO2, and Ta2O5 polymorphs. For simple benchmark systems (C, Al, Si, Ge, rutile TiO2, and beta-PtO2), the Gibbs free energy mean absolute errors (MAEs) relative to the QHA benchmarks remain below 0.53 meV/atom, with a six-system average of 0.148 meV/atom, while the number of explicit phonon volume points is reduced from about 20-21 to 3 in the lowest-cost implementation. For the more complex Ta2O5 polymorphs, the reconstructed free energies reproduce the main phase-stability topology despite larger phase-dependent errors. With reference to the QHA workflows, the interpolation method in this work achieves speedups of 5.911-9.023 times and remains reliable for moderate compression ranges where phonon frequencies vary smoothly with volume.

We investigate the space-time evolution of the magnetization induced in a 2D ferromagnetic island by a short pulse of a rotating electric field. The field generates elastic twists that act on the magnetization via the Barnett effect: magnetization by rotation. Analytical studies are conducted within classical electrodynamics of continuous media and continuous elastic theory, while numerical studies are performed using discretized Landau-Lifshitz spin dynamics on the atomic lattice. The effect is studied for typical parameters of magnetic oxides at various field frequencies and amplitudes, and for various strengths of magnetic anisotropy, exchange, and damping. The possibility of reversing the island magnetization with an electric-field pulse is demonstrated.

Despite enormous expenditures in the research field, the electron-doped side of nickelate superconductors remains uncharted territory. Substituting the trivalent rare-earth cations by a tetravalent one hitherto failed. Here, we demonstrate by first-principles calculations a disorder-free route to electron dope Ruddlesden-Popper nickelates. When intercalating wide-band-gap insulating layers such as La$X$O$_3$ ($X$=Al, Ga, Sc) into La$_2$NiO$_4$, the extra (LaO)$^+$ layers act as electron donors, releasing carriers into the Ni-3$d$ orbitals. This electron doping puts La$_2$NiO$_4$:La$_2$AlO$_4$ naturally in the optimal region for $d_{x^2-y^2}$-wave superconductivity with T$_c$ exceeding 50 K. The same concept also allows us to electron dope La$_3$Ni$_2$O$_7$, the superconductor in the limelight.

Nanofluids, which are composed of insoluble, stable, and well-dispersed solid particles of nanoscale and/or subnanometer sizes suspended in a base liquid, are the next generation of liquids of today. The purpose of this paper is to investigate the one dimensional and three dimensional angle dependent radial distribution functions RDF and ARDF of polymeric nanofluids made up of nonrigid (soft) nanoparticles and a polymer melt (base fluid) using the molecular dynamics simulation approach and to search the shape stabilities by using these results. For this purpose, we use the nanoparticles of three different sizes: 28, 42, and 56 particles. We research them both within the base fluid and without this polymeric medium for instability analysis. We found that the nanoparticles with 28 atoms show the shape instability inside the base fluid when we increase the system temperature from T=1.2 to T=1.8 and hence, the structure of two concentric spherical shell of the nanoparticle breaks down and as a result the empty vacuum between these inner and the outer shells disappears. In contrast to this findings, the nanoparticles with 42 and 56 atoms show the shape stability inside the base fluid by preserving their concentric shell structures when we rise the system temperature and decrease the affinity between the nanoparticles and the base liquid medium.