We study a two-orbital Hubbard-Kanamori model, which has been originally proposed for iron-based superconductors, using variational Monte Carlo. We span the nonmagnetic sector at both hole-doping and electron-doping, with respect to the half-filled case $n=2$. We report the presence of a superconductive region with a $s^{\pm}$ symmetry only when the half-filled system is in a Mott state, while orbital selectivity is absent. These results are qualitatively different from what was reported in the three-orbital Hubbard-Kanamori model, where a more extended superconductive region was observed with a concomitant development of orbital selectivity, and they are to some extent more reminiscent of the single-band Hubbard model.

We present a systematic analysis of the behavior of thin films of Cd$_3$As$_2$ under different strain profiles and in magnetic fields. In each case, we construct effective $k \cdot p$ models by considering the reduction of symmetry and all constraints imposed by the remaining symmetries. Our analysis naturally describes both in-plane biaxial and uniaxial strain. Biaxial strain is expected to preserve in-plane $C_4$ rotational symmetry while breaking inversion, allowing for a description in terms of the $4mm$ point group. Uniaxial strain, on the other hand, breaks $C_4$ symmetry. For this case, we consider two scenarios: one preserving inversion, described by the $mmm$ group, and one breaking it, leading to $2mm$ symmetry. After deriving the models, we examine the effects of out-of-plane magnetic fields, identifying two possible microscopic mechanisms that can account for the experimental results reported in Ahadi et al. (2025). Importantly, our analysis proposes a new method for differentiating between them. By incorporating the effects of multiple subbands along the confinement direction, we show that the opening of a gap in the lowest Landau level requires either reducing the symmetry down to $2mm$, breaking both inversion and $C_4$ rotations, or a topological transition of the band structure due to strain-induced band renormalization. Furthermore, we demonstrate that a two-dimensional Dirac semimetal phase can be induced by sufficiently large in-plane magnetic fields. This phase is highly sensitive to different strain profiles, with band touchings occurring when the field is applied perpendicular to preserved mirror planes, serving as a powerful probe of the material's strain profile.

Quantum mechanically, an electron moving in a uniform magnetic field forms Landau levels. A curious feature is that for states with a negative angular quantum number, the total probability current vanishes, which appears to contradict the classical picture of cyclotron motion. While a geometric interpretation based on classical orbits exists, alternative interpretations remain of interest. In this paper, we examine the probability current density and identify a critical radius that naturally partitions the plane into an inner clockwise-flow region and an outer counterclockwise-flow region. We show that the vanishing total current results from an exact cancellation between these two regions. Furthermore, by defining a partitioned kinetic angular momentum with respect to the critical radius, we reveal an intrinsic competitive structure: the electron simultaneously carries two opposing rotational components. The negative quantum number manifests in the strength of the inner counter-rotation, while the net kinetic angular momentum remains positive. This bidirectional flow picture also provides a dynamical interpretation of the infinite degeneracy of Landau levels.

We investigate frustration-induced instabilities in a trimerized quantum spin chain motivated by recent experimental findings for the compound Na$_2$Cu$_3$Ge$_4$O$_{12}$. Employing a cluster mean-field approach combined with Lanczos exact diagonalization, we analyze the ground-state and quantum-information properties of a Heisenberg model with competing interactions in a magnetic field. In the weakly frustrated regime, the system exhibits a robust $1/3$ magnetization plateau associated with a collective ferrimagnetic-like trimer state. Increasing the next-nearest-neighbor intratrimer coupling drives a pronounced reorganization of spin correlations, leading to a crossover toward a doublon-like correlation regime and providing a static ground-state picture consistent with the composite excitations observed dynamically in trimerized chains. The resulting low-energy behavior can be interpreted in terms of weakly interacting emergent spins, offering a microscopic explanation for the extended stability of the magnetization plateau. Furthermore, through finite-size scaling analyses of the energy gap, von Neumann entanglement entropy, and fidelity susceptibility, we characterize the zero-field criticality of the model. Ultimately, our results suggest that frustration gives rise to qualitatively distinct quantum states and provide a microscopic framework for understanding the emergence of fractionalized excitations in trimerized quantum spin systems.

The Kitaev spin liquid provides a rare example of exactly solvable quantum spin liquid states. Intensive research over the past two decades has identified a variety of its candidate materials. In real materials, however, the Kitaev interaction is inevitably accompanied by additional magnetic interactions such as the Heisenberg and $\Gamma$ interactions. These interactions often induce magnetic ordering at low temperatures, making it essential to clarify their effects in the search for and design of Kitaev spin liquid candidate materials. In this study, we revisit the ground-state phase diagram of the Kitaev-Heisenberg-$\Gamma$ model from both classical and quantum perspectives, using state-of-the-art numerical techniques. In the classical case, we reveal a $zoo$ $of$ $noncollinear$ $orders$, where a variety of noncollinear multiple-$Q$ magnetic orders with and without incommensurate modulations emerge. In the quantum case, we unravel that quantum fluctuations suppress many of the competing orders found in the classical case, resulting in a reduced number of dominant incommensurate orders. We further identify $highly$ $frustrated$ regions, where spiral spin liquid states as well as new magnetically ordered states are potentially stabilized by other additional magnetic interactions. Our results provide a comprehensive perspective on the Kitaev-Heisenberg-$\Gamma$ model for both classical and quantum spins and offer a valuable guide not only for interpreting experimental results on candidate materials, but also for searching and designing new materials to realize the Kitaev spin liquid.

The parent compound FeTe hosts a complex magnetic landscape that is highly susceptible to lattice distortions. Although theoretical models have predicted a bicollinear to dimer antiferromagnetic (AFM) phase transition under tensile strain, its experimental realization and deterministic control has remained elusive owing to severe magnetic frustration. Here, combining high-resolution scanning tunneling microscopy (STM) and density functional theory (DFT) calculations, we demonstrate the selective stabilization of bicollinear and dimer AFM orders in few-layer FeTe films via local uniaxial strain engineering. By mapping the strain fields near dislocation areas in FeTe films and FeTe/FeSe heterostructures, we establish a direct correspondence between specific strain components and the resulting magnetic ground states. We find that uniaxial compression along the Fe-Fe next-nearest-neighbor direction stabilizes the bicollinear AFM order, with the stripe orientation aligning parallel to the compression axis. Crucially, we report the experimental realization of the long-range dimer AFM order, which emerges under anisotropic strain along the Fe-Fe nearest-neighbor direction. This phase manifests as a distinct $\sqrt{2} \times \sqrt{2}$ electronic reconstruction and shares a common Neel temperature with the bicollinear phase. Our findings reveal that anisotropic strain effectively lifts the magnetic degeneracy among competing states. This work provides a robust strategy for the manipulation of elusive magnetic orders and offers insights into the interplay between lattice, spin, and electronic degrees of freedom in iron-based superconductors.

Two-dimensional ferroic materials exhibit rich and intriguing physical phenomena, but their response properties generally depend sensitively on thickness, requiring precise layer-number control and thereby limiting practical applications. Here, we propose a general strategy for realizing thickness-independent quantum geometric responses through symmetry engineering induced by interlayer antiferroic coupling. Using spatial-dependent symmetry analysis, we show that thickness-independent behavior emerges when the symmetry breaking required for a given response is generated by interlayer antiferromagnetic (AFM) or antiferroelectric (AFE) coupling, without invoking topological mechanisms. Our first-principles calculations predict that multilayer MnS in the G-type AFM configuration exhibits a surface-dominated anomalous Hall effect, whose thickness-independent behavior can be significantly influenced by the stacking order. We further propose design principles for achieving thickness-independent anomalous and nonlinear Hall effects driven by interlayer AFE coupling, and suggest potential applications in distinguishing magnetic structures. Our findings open a new route towards robust functional devices based on antiferroic materials.

Directional solidification of bubbly liquids plays a critical role in shaping the microstructure and properties of many materials, yet the fluid dynamics governing bubble behavior during solidification remain poorly understood. Using cryo-confocal microscopy and particle image velocimetry, we quantify fluid flows around bubbles during solidification of water containing surfactants and tracers. Our results reveal that volumetric expansion dominates fluid motion, with velocities scaling linearly with the solidification rate (1-20$~\mu m/s$), while Marangoni flows-hypothesized to play a key role-are negligible ($< 5~\mu m/s$) under our experimental conditions. Diffusiophoresis and thermophoresis also contribute minimally. These findings challenge existing theoretical models and provide a framework for controlling bubble distribution in solidified materials

We experimentally investigate the magnetic gyrotropic mode in a system of vortex ferromagnetic (FM) nanooscillator exchange coupled to an antiferromagnetic (AFM) layer. The micron-sized disks formed from the Ni80Fe20(12 nm) / Ir80Mn20 (5 nm) FM/AFM heterostructure are prepared so that the vortex magnetic state is imprinted into the AFM layer. We apply a magnetic resonance force microscopy (MRFM) method to locally study magnetic oscillations in single FM/AFM disks. We show that the gyrotropic mode frequency is significantly (approximately 4 times) shifted to the high frequency compared to similar structure consisting of a single ferromagnetic disk. Upon applying an in-plane magnetic field, we observe a strong peak at a double frequency which was previously predicted in theory. This is governed by the fact that vortex dynamics is strongly nonlinear in a noncentrosymmetric system under investigation.

Intrinsically chiral metal surfaces, where handedness arises from the asymmetric step-kink-terrace topology of high-Miller-index planes, are model systems for enantiospecific catalysis, sensing, and spintronics. Yet, no consistent method exists to classify their handedness directly from experimental observables. We report a dual-domain machine learning framework that decodes crystallographic surface chirality from two independent image representations: atomic structure models in real space and simulated momentum-resolved photoemission maps of the Fermi surface projections in reciprocal space. ResNet18, a deep convolutional neural network, fine-tuned on a database of labeled images achieves ~73% classification accuracy on atomic models and ~99% on Fermi surface projections. We show that the latter transfers directly to synchrotron-acquired experimental images after fine-tuning on just two labeled frames. We identify a working correspondence between the two representations: just as the kink site geometry fixes the orientation of crystallographic planes in real space, the surface normal position in a momentum-resolved photoemission map anchors the orientation of the Fermi surface polygons in reciprocal space. It is precisely this relative orientation that encodes handedness into the map topology with high accuracy. The pronounced difference in accuracy shows that handedness is more readily recovered from the momentum-space electronic pattern than from the local atomic geometry of the kinked surface. This finding has direct implications for the disorder resilience of geometric chiral-induced spin selectivity (CISS) at realistic metal surfaces.

We present a simplified formalism for predicting infrared optical constants from first-principles calculations. Addressing limitations of the widely used four-parameter semi-quantum Lorentz model, the proposed approach bridges the gap between the harmonic three-parameter model and full self-energy-based methods. By incorporating essential anharmonic effects including four-phonon scattering and phonon renormalisation, the model provides an efficient and accurate alternative while maintaining low computational cost. The frequency-dependent refractive indices of MgO and rutile TiO$_2$ are computed and compared with experimental data, demonstrating good quantitative agreement. The framework offers a practical approach for predicting optical properties of materials across a wide range of materials.

Machine learning and computational inference, coupled with experimental data, promise to significantly accelerate our rate of learning in most scientific disciplines. In this study, we develop tools that connect microscopic observations to macroscopic device behaviour, a capability that is essential for accelerating the design of durable energy materials. To this end, we introduce a novel approach that integrates photoluminescence imaging with drift diffusion simulations to understand operation and degradation in fully fabricated perovskite solar cells. By employing Bayesian inference, we generate "inferred maps" of parameters that govern recombination processes present in devices. We track these parameter maps while the devices are aged (70 °C, full spectrum sunlight) to analyse their temporal evolution during degradation. Notably, our approach allows us to distinguish between degradation occurring at the hole or electron transporting layer interface, or within the bulk. Our analysis reveals pronounced spatially non-uniform degradation, with significant macroscopic heterogeneity observed in the optoelectronic parameter maps. We pinpoint the greatest degradation observed in specific regions to stem from the perovskite/transport layer interfaces. Finally, we demonstrate that an amino-silane molecular passivation treatment suppresses this degradation, highlighting its specific role in enhancing device stability. Our approach offers valuable insights for future device fabrication and is a clear exemplification of how advanced Bayesian inference can significantly increase the value of experimental data.

We develop a data-induced geometric framework for temperature trajectories in optical-polarization data and apply it to temperature-dependent birefringence imaging of stress-induced ferroelectric SrTiO$_3$. By treating the measured response as an observable projection of local material states, the optical-polarization response at each pixel is cast as a trajectory along the temperature axis. Singular value decomposition separates trajectory-induced geometric objects associated with optical-polarization-direction structure and temperature-evolution modes. Holonomies are then defined by transporting these objects around closed loops in real space. The resulting maps reveal spatially localized connection mismatches correlated with an enhanced ferroelectric transition temperature and stress-related optical anisotropy. Local order parameters and angular-gradient analyses confirm that these loop-level signals are distinct from orientational disorder and simple spatial variation. The signed holonomy of the temperature-evolution modes further resolves positive and negative connection structures under a fixed frame convention. These results demonstrate that the data-induced connection geometry of temperature trajectories provides an experimentally accessible diagnostic of electromechanical inhomogeneity in SrTiO$_3$ under stress, without explicitly reconstructing hidden strain or electric-polarization fields.

Dense granular flows made of elongated particles exhibit a strong inhibition of particle rotation compared to spherical grains, but the mechanisms responsible for this effect remain unclear. Using three-dimensional discrete element simulations, we investigate the angular dynamics of elongated particles in dense, confined shear flows. We systematically vary particle aspect ratio, interparticle friction, and boundary conditions to elucidate their respective roles. We show that the reduction of the average angular velocity cannot be attributed to particle shape, friction, or solid fraction alone. Instead, it is controlled by the degree of collective alignment developed under shear, quantified by a nematic order parameter. Based on this observation, we propose a simple scaling law linking the average angular velocity to the local shear rate through a hampering parameter that depends solely on the orientational order via the nematic order parameter. This scaling successfully collapses data obtained for different particle properties (shape, friction), different flow patterns, and, remarkably, remains valid for two additional flow configurations.

We introduce a theoretical framework for analyzing federated learning in a generative setting through a teacher-multiple interacting students scenario, in which each student receives a distinct realization of the data, either through a different noise corruption or by accessing a different subset, possibly of varying size. Using theoretical tools in equilibrium disordered system, we analytically show that interactions among students systematically enhance learning performance: highly noisy students require fewer samples to recover the underlying pattern, while low-noise students achieve a larger overlap with the ground-truth signal. We derive the optimal Bayesian conditions for teacher recovery as functions of the sample complexity, noise level, and interaction strength, and validate these predictions through numerical simulations. The resulting dynamics can be mapped onto equilibrium sampling in a Restricted Boltzmann Machine with a structured hidden layer, providing a principled theoretical understanding of how interactions improve distributed generative modeling.

Twisted van der Waals bilayers provide a versatile platform for engineering moiré electronic states, yet a general design principle for time-reversal-invariant topological moiré bands remains elusive. Here, we establish a geometry-driven principle for triangular-lattice bilayers: symmetry-related minima of the stacking-energy landscape are promoted by twist and relaxation into the two sublattices of an emergent honeycomb moiré lattice. First-principles calculations for BiTeBr reveal robust $\Gamma$-valley moiré valence bands with a nontrivial $\mathbb{Z}_2$ index over a range of twist angles. A four-band Wannier Hamiltonian in the emergent honeycomb basis quantitatively maps these bands onto an extended Kane--Mele model. An out-of-plane electric field drives a transition to a trivial phase by enhancing the Rashba coupling $\lambda_R$ relative to the intrinsic Kane--Mele coupling $\lambda_{\rm SO}$. The same honeycomb reconstruction and Kane--Mele mechanism are verified in representative additional triangular-lattice bilayers, establishing stacking reconstruction as a general, geometry-controlled route to electrically tunable moiré quantum spin Hall materials.

Angular-momentum transport provides a pathway for controlling energy flow in solids beyond conventional charge-based mechanisms. While spin currents are known to mediate spin-caloritronic phenomena such as the spin Peltier effect (SPE), the role of orbital angular momentum in heat transport remains largely unexplored. Here we demonstrate orbital-angular-momentum-driven temperature modulation via the SPE in yttrium iron garnet/Pt/CuOx heterostructures. Using wedge-shaped CuOx layers combined with spatially resolved active thermal measurement techniques, we map the continuous thickness dependence and quantitatively disentangle the spin- and orbital-current-mediated contributions within a single device. The orbital-mediated component exhibits a pronounced maximum at an intermediate thickness, revealing a characteristic length scale for interfacial orbital-angular-momentum generation and propagation at the Cu/CuOx interface. These results provide direct experimental evidence that charge-current-driven orbital angular momentum can drive SPE-induced temperature modulation, establishing interfacial orbital processes as an additional channel for heat transport and providing a pathway toward spin-orbit caloritronics.

Most conventional micromagnetic frameworks in spin caloritronics rely on a unidirectional coupling approximation, wherein thermal fluctuations drive magnetization dynamics while the feedback of magnetic dissipation onto the thermal reservoir is neglected. Here, we establish a rigorously self-consistent bidirectional magneto-thermal coupling model by integrating the stochastic Landau-Lifshitz-Gilbert (sLLG) equation with a generalized heat transfer equation. In this closed-loop framework, the local temperature acts as a dynamical variable, and the damping-induced dissipation alongside stochastic work dynamically feeds back into the thermal bath as localized heat sources. Utilizing Ito stochastic calculus, we analytically prove that this coupled system strictly obeys the first law of thermodynamics and spontaneously recovers the correct Boltzmann statistics at equilibrium. Spatially resolved micromagnetic simulations further validate the energy exchange mechanism, capturing the finite-bath temperature reduction induced by spatial variation of magnetic moments and the modified density of states under exchange interactions. This bidirectional framework provides a robust microscopic foundation for investigating complex nonequilibrium magneto-thermal dynamics, such as the unidirectional spin-wave heat conveyer effect, paving the way for advanced spin-caloritronic applications.

The development of batteries with high energy density, short charging times and use of sustainable materials is critical for decarbonization. Magnesium (Mg)-based anodes for lithium (Li) metal batteries promote homogeneous Li plating, thereby avoiding the formation of Li dendrites that cause short circuits and battery failure. However, microstructural modifications induced by Li-alloying and their influence on battery operation remain elusive. Here, we unveil the previously unknown formation of an ordered B2 phase, which creates a conditional spinodal decomposition with the \b{eta}-body-centered cubic phase. Chemical fluctuations characteristic of spinodal decomposition give rise to uniformly dispersed Li-rich \b{eta}-BCC and Li-poor B2 continuous interconnected phases, with the former providing a fast diffusion pathway for Li diffusion towards the anode, hence decreasing the propensity for dendrite formation at elevated current density. This is achieved using Earth-abundant and inexpensive Mg.

We design the first neural quantum state for continuum particles that, for any chosen allowed momentum $\mathbf{k}$, is by construction an exact eigenstate of total momentum with eigenvalue $\mathbf{k}$. Our architecture, EVE, enables off-the-shelf VMC to solve for momentum-sector ground states. We test EVE on 2D bosons with mutual $1/r$ interactions, finding that a single unified ansatz is capable of describing four qualitatively different states: superfluid, roton, crystal, and phonon. At different densities, we extract the underlying phase of matter from the dispersion's shape. At $r_s = 20.0$, we see the roton minimum at finite $k$ expected of a superfluid. At $r_s = 100.0$, we see striking zone folding indicative of crystalline order, with periodically spaced minima representing floating crystals connected by phonon arcs in between. Using density-density correlation functions, we confirm the phase diagnoses and probe the excitations' correlation structures. Finally, we analyze the roton's phase texture and find unexpected multi-particle phase strings, formed when several vortex dipoles merge, leaving two vortices connected by a phase slip.

Using the Keldysh non-equilibrium Green's function approach, we investigate charge pumping through a single-stranded helical structure described by a tight-binding model that includes either short-range hopping (SRH) or long-range hopping (LRH). While quantum pumping has been studied in various low-dimensional systems, the detailed behavior of the spectral current and the pumped dc current in helical geometries in the presence of higher-order electron hopping (beyond nearest neighbors) has not yet been systematically explored. Here, we focus on the interplay between helicity and extended hopping ranges, analyzing how they jointly control the energy-resolved and dc pumped currents under time-periodic end potentials. For LRH, the pumped dc current exhibits pronounced plateau-like regions as a function of chemical potential when energy levels are sparsely spaced -- consistent with adiabatic transport -- whereas SRH yields more parameter-sensitive currents without clear plateaus. The plateau stability is controlled by the drive frequency: at higher frequencies, Floquet side-band mixing destroys the plateaus, leading to oscillatory currents. The phase dependence remains nearly sinusoidal, and the current vanishes at zero phase lag, confirming the necessity of out-of-phase potentials. Crucially, in helical systems, the decay exponent $(\ell_c)$ acts as an effective structural parameter that can tune both the magnitude and sign of the pumped current, offering a geometric knob for controlling quantum pumping. Our findings not only fill a gap in the understanding of spectral and pumped currents in helical systems with extended hopping but also provide tools that can be applied to analyze similar phenomena in other chiral or quasi-one-dimensional systems.

Cermets combining metastable ceramics and ductile metals promise superior toughness and strength. However, retaining metastability often requires high-temperature sintering that coarsens microstructures and relaxes matrix constraint. Here we introduce an ultrafast high-temperature sintering (UHS) strategy to overcome this trade-off in zirconia-copper cermets. By applying Joule heating at around 100 degrees C per second to 900 degrees C with only a 20 second hold, we obtained cermets containing up to 50 weight percent of metastable austenite in zirconia at room temperature within a fine-grained and homogeneous microstructure. The rapid sintering kinetically favors semi-thermal austenite formation while suppressing copper grain growth and matrix relaxation, thereby stabilizing the high-temperature phase and simultaneously preserving microstructural refinement. This approach offers significant potential for copper-based composites in applications such as transformation toughening, self-healing, and crack detection.

Machine-learning interatomic potentials (MLIPs) have become powerful tools for material simulations. Many MLIPs are trained based on density functional theory (DFT) datasets generated with the Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional. Using a PBE-based MLIP for HfO2, we identify a previously unreported low-energy I41/amd structure, which is predicted to be more stable than the well-known ground-state structure, the monoclinic P21/c structure. Since experiments show clearly that HfO2 takes the P21/c structure as the ground state, this is obviously a wrong prediction. Unfortunately, the same prediction is also made by widely used PBE-based foundation models such as NequIP-OAM-L and MatterSim-v1-5M. Comparisons among different DFT functionals show that this error originates from the PBE functional, which overstabilizes low-density structures containing sixfold Hf-O octahedral units, such as the I41/amd and Pbcn phases. The error also affects the calculated energy landscapes and barrier heights along ferroelectric HfO2 polarization switching paths when there are large lattice relaxations. Fortunately, the error can be largely suppressed by other functionals such as PBEsol and local density approximation. Our study serves as a warning about the impact of errors in exchange-correlation functional approximations on the reliability of MLIP simulations of crystal structures and phase transitions.

Proofreading is generally thought to improve accuracy at the expense of speed. We show that this trade-off can be reversed in stochastic processes with long-lived stalled states. Using a non-Markovian renewal framework, we derive exact expressions for the error rate and completion time under proofreading for arbitrary stall-time distributions. Our analysis reveals that fluctuations in stall durations, rather than their mean alone, determine whether proofreading can simultaneously increase speed and accuracy. In the limit of strong stalling, this regime emerges when the coefficient of variation of the stall time exceeds a threshold set by the intrinsic error rate. These results provide a general criterion for proofreading in systems ranging from self-assembly and polymer replication to immune recognition and other nonequilibrium information-processing systems.

Accurate surface thermochemistry requires balanced error cancellation between extended slabs and molecular reference states. This balance can fail whenever the electronic-structure error is not transferable across the chemically distinct species entering a thermodynamic cycle. Here we examine this problem in single-determinant fixed-node diffusion Monte Carlo (SD-FNDMC) for oxygenated ORR intermediates on Pt(111). Gas-phase thermochemistry is used to diagnose the reference-state imbalance, and a hybrid cycle is introduced to separate slab-adsorbate binding from molecular formation. The hybrid cycle keeps the surface binding term at the SD-FNDMC level, where cancellation is expected to be most favorable, and replaces the molecular formation contribution with a benchmark coupled cluster reference. For Pt(111), the resulting correction is small for O and OH but larger for OOH, while the geometry-matched refinement gives only a secondary correction. Applying the same cycle to HCO and COH on Cu(111) gives corrections of opposite sign, showing that the bias is controlled primarily by the electronic structure of the molecular reference rather than by adsorbate geometry alone. This decomposition identifies molecular reference imbalance as a separable source of error in SD-FNDMC surface thermochemistry and reduces the corresponding bias without modifying the SD-FNDMC slab-binding contribution.

Thermal conductivity in a conductor changes by the application of an external magnetic field, which functions as a magneto-thermal switch. For superconductors, a large magneto-thermal switching can occur through a superconducting-to-normal conducting phase transition due to the change in the electron contribution in thermal conductivity. Arima et al. recently reported a nonvolatile nature of the magneto-thermal switching for superconducting solders, which consist of phase-separated Sn and Pb domains. Although they clarified that magnetic flux trapping is required to induce the nonvolatile magneto-thermal switching, a rule for such material design is still unclear. Here, we investigate the microstructure dependence of magneto-thermal switching in superconducting Sn/Pb multilayered composites, which are created by an accumulative roll bonding method. The thickness of each layer, that is the scale of microstructure, can be systematically controlled by the repetition number of roll bonding while the whole sample size and average composition are unchanged. We find that, as the formation of micro-scaled Sn domains proceeds by increasing the repetition number, a nonvolatility in the magneto-thermal conductivity gradually appears in correlation with the remanent magnetization. This study directly confirms that the inclusions with a size comparable to or less than the magnetic vortex in superconducting matrix is essential for magnetic flux trapping, enabling the nonvolatile magneto-thermal switching in superconducting composites.

Direct links between electronic structure and intrinsic ductility remain elusive for metals. A framework is proposed that reduces the complexities of valence charge distribution, band filling, and shear strain effects into structure-property relationships describing the intrinsic ductility of metals and alloys. Rather than relying on crystal cleavage and dislocation nucleation at preexisting crack tips, we show that a lower energy fracture criterion, i.e., the activation energy density for amorphization, enables accurate predictions of both intrinsic ductility and ductile-to-brittle transition temperatures. From analytical expressions and tabulated ab-initio stiffness constants, lattice parameters, and binary interaction energies, we present a unified theory that reconciles ductile flow in pure metals and solid-solution alloys. Phase diagrams generated for the Nb-Ta-V-Ti system simultaneously explain its high strength and room-temperature tensile ductility, validating this framework as a practical one for rapid design of structural multi-principal-element alloys.

Global water stress has emerged as a critical challenge, driving the search for advanced membrane materials that enable efficient, selective water filtration and transport. In this context, two-dimensional nanoporous membranes provide an ideal platform to elucidate how atomic-scale structure and electronic polarization govern water flow under extreme confinement. In this study, we employ multiscale simulations to investigate the effect of water flow through nanopores in graphene and hexagonal boron nitride (hBN) membranes. Our results reveal significantly higher water flow in hBN membranes than in graphene. This enhanced flow is attributed to the asymmetry of the hBN pores, which induces an electric dipole moment, as confirmed by quantum-mechanical (QM) calculations. Classical molecular dynamics simulations further demonstrate that water molecules exhibit a random distribution with no preferential orientation near the graphene pores, whereas hBN induces strong structuring. Furthermore, hybrid quantum mechanics/molecular mechanics (QM/MM) simulations indicate that the dipole moment of the hBN pore increases in the presence of water, as evidenced by the average charge distribution. Conversely, the symmetric nature of graphene pores results in non-polar characteristics, as verified by both QM/MM and QM calculations. These findings provide valuable insights into the distinct water-transport properties when flowing through graphene and hBN nanopores, with potential implications for designing advanced nanofiltration membranes.

Thermal transport in long polymer molecules is commonly attributed to ballistic propagation of long-wavelength acoustic phonons, which act as Goldstone modes arising from translational symmetry, while the transport of other phonons is suppressed by Anderson localization. This mechanism leads to thermal conductivity that increases with molecular length. Consistent with this picture, strongly aligned polymers exhibit exceptionally high thermal conductivity, whereas poorly aligned polymers are orders of magnitude less conductive and function as thermal insulators. Here we show that this strong sensitivity to molecular alignment originates from phonon scattering by molecular kinks. Even in the long-wavelength limit, the kink scattering remains strong because kinks break translational symmetry both for longitudinal and transverse phonons. As a result, randomly oriented kinks cause a rapid decrease in thermal conductivity with increasing molecular length. These findings identify alignment control by means of kink engineering as a route for tuning thermal transport in polymers.

We report measurements of the thermopower of atomic-size gold contacts realized by the mechanically controllable break junction (MCBJ) technique over a temperature range from 18 K to 295 K. A thermometer included in the lithographic structure close to the constriction provides a direct measurement of the temperature increase generated by heating one side of the contact with a focused laser beam. While the conductance histograms confirm the quantum nature of the transport, we observe a nonmonotonic temperature dependence of the ensemble-averaged thermopower with a minimum of $-2\,\mu$VK$^{-1}$ at about 150 K. The values for the thermopower obtained at the lowest and the high temperature are compatible with values reported in the literature, but the nonmonotonic behavior in between disagrees with the expected linear dependence for quantum coherent conductors described by the Landauer formula. We develop a theoretical model based on an energy dependent transmission function that qualitatively reproduces the nonmonotonic behavior, but fails quantitatively. We therefore interpret our data as a result of phonon contributions to the thermopower beyond the Landauer model and with opposite sign than the classical phonon drag known from bulk systems. Our findings show that, firstly, the thermopower gives important insight into the transport properties of atomic-size structures and second that the linear approximation of the Landauer model has to be used with caution when studying more complex transport properties even for atomic contacts from free-electron metals.