Papers

The article presents the results of corrosion-fatigue tests of industrial Al-Mg alloys were conducted in air and in a 3% NaCl aqueous solution. Fatigue curves can be characterized using the Basquin equation and the plastic deformation model at the crack tip. It has been demonstrated that the primary contributions to corrosion-fatigue failure in the Al-Mg alloys at low stresses are made by the process of pitting and intergranular corrosion, and by the plastic deformation at high stresses.

The effect of sintering regimes on the density, microstructure parameters, and mechanical properties of Al2O3 and Al2O3 + 0.25%MgO ceramics has been investigated. The ceramics were sintered in three regimes: Regime I - heating at a constant rate (2.5, 5, 10, 20 C/min) up to the temperature T=1650C; Regime II - heating with a varied heating rate up to 1565C with the duration corresponding to sintering at the heating rate of 10 C/min in Regime I followed by a three-fold decrease in the shrinkage rate; Regime III - two-stage sintering: heating according to Regime II up to the temperature T1+1550C, then lowering the temperature down to T2 = 1300-1500C and holding for 3 h at the T2. The sintering regimes were chosen so that the ceramics had the relative density of 97-99% and a bimodal distribution of the microstructure parameters. The Al2O3 and Al2O3 + 0.25%MgO ceramics obtained in Regimes I-III had a microstructure with abnormally large grains in a fine-grained matrix. The sizes and volume fractions of the large grains depended on the sintering regime. Most abnormally large grains had elongated shapes that leads to deviations in the crack propagation trajectories from the straight line. The optimal parameters of the bimodal microstructure parameters distribution providing enhanced mechanical properties of the ceramics (hardness, indentation fracture toughness, ultimate strength) have been determined.

Bayesian Optimization with multi-objective acquisition functions such as q-Expected Hypervolume Improvement (qEHVI) requires efficient candidate optimization to maximize acquisition function values. Traditional approaches rely on continuous optimization methods like Sequential Least Squares Programming (SLSQP) for candidate selection. However, these gradient-based methods can become trapped in local optima, particularly in complex or high-dimensional objective landscapes. This paper presents a simulated annealing-based approach for candidate optimization in batch acquisition functions as an alternative to conventional continuous optimization methods. We evaluate our simulated annealing approach against SLSQP across four benchmark multi-objective optimization problems: ZDT1 (30D, 2 objectives), DTLZ2 (7D, 3 objectives), Kursawe (3D, 2 objectives), and Latent-Aware (4D, 2 objectives). Our results demonstrate that simulated annealing consistently achieves superior hypervolume performance compared to SLSQP in most test functions. The improvement is particularly pronounced for DTLZ2 and Latent-Aware problems, where simulated annealing reaches significantly higher hypervolume values and maintains better convergence characteristics. The histogram analysis of objective space coverage further reveals that simulated annealing explores more diverse and optimal regions of the Pareto front. These findings suggest that metaheuristic optimization approaches like simulated annealing can provide more robust and effective candidate optimization for multi-objective Bayesian optimization, offering a promising alternative to traditional gradient-based methods for batch acquisition function optimization.

We investigate the interplay between charge density wave (CDW) instabilities and ferromagnetism in SmNiC$_2$ using diffuse and inelastic x-ray scattering together with Raman spectroscopy. We identify a soft acoustic phonon driving the incommensurate CDW (I-CDW) and uncover a second Kohn anomaly at the wave vector of the commensurate CDW (C-CDW) stabilized in other $R$NiC$_2$ members ($R=$ rare earth). The marked softening of both phonons and their contrasting evolution with temperature reveal a competition between the two ordering tendencies. Alongside pronounced anomalies in the temperature dependence of the zone center and soft phonons, we observe the collective amplitude mode of the CDW, which collapses abruptly as ferromagnetism sets in. Surprisingly, the Kohn anomalies persist in the ferromagnetic state despite the degradation of Fermi-surface nesting conditions. Our experimental findings, supported by ab initio calculations, highlight the central role of the electron-phonon interaction in driving the CDW formation and tuning the balance between competing charge and magnetic orders.

The unidirectional Hatano-Nelson chain serves as the fundamental non-Hermitian building block of the Su-Schrieffer-Heeger (SSH) model. We investigate its Anderson localization properties under diagonal binary disorder. For weak disorder, the complex eigenvalue spectrum forms a single closed loop, which bifurcates into two distinct loops at a critical disorder threshold. Correspondingly, the spectral winding number {\nu} undergoes a transition from {\nu} = 1 in the weak-disorder regime, through {\nu} = 1/2 at the critical point, to {\nu} = 0 in the strong-disorder limit. We show that the eigenstates are subexponentially localized, with a localization length that varies analytically as a function of the momentum-like quantum number q. Notably, at weak and critical disorder, the spectrum hosts two completely delocalized states with diverging localization lengths. This divergence is directly correlated with the non-trivial spectral winding number. These findings remain robust under various boundary conditions, with the exception of strictly open boundaries.

We derive and analyze the amplitude equation for the roll patterns in case of generalized Active Model B+ (AMB+) in the presence of chemical reactions. The generalized AMB+ differs from the original AMB+ introduced by Tjhung et al. [E. Tjhung et al., Phys. Rev. X 8, 031080 (2018)] by the addition of a quadratic term, $g\phi^2$, in the expression for the equilibrium part of the current. Also, the model includes a rotation-free active current of strength $\lambda$ and a rotational current of strength $\xi$. The inclusion of a chemical reaction with rate $\Gamma$ removes the conservation constraint and introduces a preferred wavenumber that governs the pattern formation below a critical reaction rate $\Gamma_c$. We argue for the analytical form of the amplitude equation based on symmetry considerations and explicitly derived it using multiscale analysis. By taking different limits of $g$, $\lambda$, and $\xi$, we recover amplitude equations for several well-known physical models as special cases and determine the nature transitions close to the onset of instability. We find that for $g = 0$, the transition is always supercritical, whereas for $g \ne 0$, the transition between the supercritical and subcritical regimes depends sensitively on the model parameters. Further, we derive the condition for the Eckhaus instability from the stability analysis of the amplitude equation as well as from the phase diffusion equation, and find that it is independent of $g$.

The design of quantum states at heterointerfaces has enabled a variety of emergent phenomena. Among them, molecular intercalation superlattices have attracted attention as tunable hybrid materials, formed by inserting organic molecules into van der Waals crystals, where molecular structure and chemistry provide new degrees of freedom. Traditionally, the intercalated molecules have been regarded as inactive spacers, while possible molecular ordering and its impact on the host lattice have remained largely unexplored. Here, we report the discovery of a cooperative superstructure (CSS) phase in molecule intercalated NbSe2, where ordering of the guest molecules induce a concomitant superstructure in the NbSe2 host lattice, characterized by a moiré structure due to incommensurability between the molecular layer and the inorganic lattice. Synchrotron X-ray diffraction reveals the emergence of CSS phase, accompanied by crystal symmetry lowering. Complementary resistivity and thermal-quench measurements show that the transition is governed by unusually slow order-disorder kinetics, so that the CSS phase can be selectively accessed under standard laboratory cooling rates. This kinetic behavior arises from slow molecular dynamics coupled to the host lattice, contrasting with fast charge or magnetic ordering in inorganic solids. Our findings establish molecular ordering as a route for engineering heterointerfaces, enabling thermally programmable superstructures.

Defect related disorder during InN growth is a major challenge for making high performance electronic and optoelectronic devices. This is partly because film quality is often described using reactor specific settings instead of general physical variables. In this study, we show that plasma assisted MOCVD growth of InN can be described using a single thermodynamic driving force coordinate. This coordinate brings together growth kinetics, defect sensitive Raman response and structural coherence across different process conditions. When we use this coordinate, the incorporation rate follows a universal activated trend with a kinetic scale of about 0.08 eV. Raman measurements show a clear crossover between a defect sparse and a defect rich regime, a disorder activated Raman metric increases quickly after the crossover, while an A1-LO control metric stays mostly the same. This suggests that short range lattice disorder, not long range polar coupling, dominates the defect activation process. X-ray diffraction shows that the out of plane coherence length stays the same for samples with the same driving force, even if reactor settings are very different. This supports the idea that structural coherence is organized by thermodynamics in this growth window. Finally, a simple kinetic Monte Carlo model using driving force biased incorporation and defect activation events matches the observed exponential trends and the two regimes, supporting the driving force approach. These results show that a transferable driving force coordinate can be used for plasma assisted InN growth and offer a quantitative way to achieve defect sparse growth conditions.

Quantum thermometry aims to measure temperature in nanoscale quantum systems, paralleling classical thermometry. However, temperature is not a quantum observable, and most theoretical studies have therefore concentrated on analyzing fundamental precision limits set by the quantum Fisher information through the quantum Cramer-Rao bound. In contrast, whether a direct temperature readout can be achieved in quantum thermometry remains largely unexplored, particularly under the nonequilibrium conditions prevalent in real-world applications. To address this, we develop a direct temperature readout scheme based on a thermodynamic inference strategy. The scheme integrates two conceptual developments: (i) By applying the maximum entropy principle with the thermometer's mean energy as a constraint, we assign a reference temperature to the nonequilibrium thermometer. We demonstrate that this reference temperature outperforms a commonly used effective temperature defined through equilibrium analogy. (ii) We obtain positive semi-definite error functions that lower-bound the deviation of the reference temperature from the true temperature-in analogy to the quantum Cramer-Rao bound for the mean squared error-and vanish upon thermalization with the sample. Combining the reference temperature with these error functions, we introduce a notion of corrected dynamical temperature which furnishes a postprocessed temperature readout under nonequilibrium conditions. This corrected dynamical temperature can be evaluated adaptively without prior knowledge of the actual temperature. We validate the corrected dynamical temperature in a qubit-based thermometer under a range of nonequilibrium initial states, confirming its capability to estimate the true temperature. Importantly, we find that increasing quantum coherence can enhance the precision of this readout.

Scanning diamond nitrogen-vacancy probe microscopy (SNVM) is an important tool for studying nanoscale condensed-matter phenomena. Ga$^+$-ion-focused-ion-beam (FIB) milling has been introduced as a method for fabricating SNVM, while the probe diameter is limited to a few micrometers due to Ga$^+$-induced damage. We report a method for improving the quality of FIB-fabricated SNVM probes by polyvinyl alcohol and Pt/Pd capping, followed by post-fabrication UV/ozone exposure. The effectiveness of the method is confirmed by the fabrication of an 800 nm-diameter probe with shallow NV centers, demonstrating an imaging of maze-like magnetic domain structure with a resolution of a few hundred nanometers and an improved sensitivity of 6.7 $\mu$T/Hz${1/2}$, while preserving spin coherence properties.

The Fortuin-Kasteleyn-Ginibre (FKG) inequality is an invaluable tool in monotone spin systems satisfying the FKG lattice condition, which provides positive correlations for all coordinate-wise increasing functions of spins. This inequality has numerous applications and plays an integral role in the proof of various central limit theorems (CLTs), including recent work on ferromagnetic exponential random graph models (ERGMs) wherein a Hamiltonian tilt promotes the presence of small subgraphs like triangles. However, the FKG lattice condition fails to hold when confining a spin system to a particular phase in the low-temperature regime of parameters. Thus it is not a priori clear if each phase internally has positive correlations for increasing functions, or if the positive correlations in the overall model (which is a mixture of phases) arise primarily from the global choice of phase. In this article, we show that the individual phases in ERGMs do indeed satisfy an approximate form of the FKG inequality internally. We use this to finish the proof of various CLTs within each individual phase in the phase-coexistence regime, answering a question posed by Bianchi, Collet, and Magnanini. We present the FKG inequality for ERGMs as a consequence of a more general result which holds under certain inputs related to metastable mixing; we expect this general result to be widely applicable, and we devote a section to spelling out the details of its application to a class of generalized higher-order ferromagnetic Curie-Weiss models where the necessary inputs are relatively transparent.

Motivated by recent advances in the study of altermagnetism, or unconventional magnetism, and in the realization and manipulation of two-impurity Kondo physics in real materials, we propose a phase-sensitive method to explore unconventional magnetic symmetries. Our method can be implemented with spin-resolved scanning tunneling microscopy to study two-impurity Kondo phenomena on altermagnetic metals by varying the distance and orientation between magnetic impurities. Using quantum Monte Carlo simulations, we analyze the spin splitting of the Kondo resonance, whose spatial distribution sensitively captures the symmetry of the underlying altermagnetic order. Furthermore, the impurity spin correlations reflects the anisotropy of the RKKY interaction due to the altermagnetic Fermi surface splitting. This work provides a framework for studying the competition between the Kondo effect, the RKKY interaction and altermagnetism, in the simplest possible system.

Half-metals, featuring ideal 100% spin polarization, are widely regarded as key materials for spintronic and quantum technologies; however, the half-metallic state is intrinsically fragile, as it relies on a delicate balance of exchange splitting and band filling and is therefore highly susceptible to disorder, external perturbations, and thermal effects. Here we introduce the concept of hidden half-metallicity, whereby the global electronic structure of a symmetry-enforced net-zero-magnetization magnet is non-half-metallic, while each of its two symmetry-related sectors is individually half-metallic, enabling robust 100% spin polarization through a layer degree of freedom. Crucially, the vanishing net magnetization of the entire system suppresses stray fields and magnetic instabilities, rendering the half-metallic functionality inherently more robust than in conventional ferromagnetic half-metals. Using first-principles calculations, we demonstrate this mechanism in a $PT$-symmetric bilayer $\mathrm{CrS_2}$, and further show that an external electric field drives the system into a seemingly forbidden fully compensated ferrimagnetic metal in which hidden half-metallicity persists. Finally, we briefly confirm the realization of hidden half-metallicity in altermagnets, establishing a general paradigm for stabilizing half-metallic behavior by embedding it in symmetry-protected hidden sectors and opening a new route toward the design and discovery of unprecedented half-metallic phases.

The anomalous Hall effect (AHE) in magnetic nanofilms is highly sensitive to the microstructural and magnetic homogeneity. However, the evolution of the microstructure and morphology near the percolation threshold, and its connection to the resulting magnetic and magnetotransport behavior in low-dimensional magnetic heterostructures, remain poorly understood. In this study, we present a comprehensive analysis of the evolution of the structural, microstructural, and magnetotransport properties of Si/Fe bilayers by varying the Fe layer thickness. X-ray diffraction (XRD), high-resolution transmission electron microscopy (HRTEM) and magnetisation data reveal a percolation-driven transition from a continuous metallic film to percolative network structure of grains when tFe decreases below 30 Angstrom. Transport measurements involving longitudinal resistivity (rho), and the anomalous Hall resistivity (rho_A,h,s) show clear divergence near the percolation threshold. The purely electronic conduction channels (rho) evolve more gradually as compared to the combined electronic and magnetic ones rho_A,h,s. The percolative analysis of the structural, magnetic, and magnetotransport data yields a critical exponent in the range of 0.78 to 1.16, consistent with that of 2D-disordered systems. The AHE scaling relation between the rho_A,h,s and rho reveals a crossover of the AHE mechanism from a mixed intrinsic/side-jump contribution with a minor skew scattering component (n ~ 1.42) in the thick, low-resistive samples (tFe > 30 Angstrom) to a skew-scattering-dominant mechanism (n = 0.62) in the high-resistive films (tFe <= 30 Angstrom). This crossover coincides with the onset of structural and magnetic connectivity between the grains. Furthermore, these findings underscore the interlink between microstructure, morphology, magnetism, and Hall transport under a percolation framework.

An analytical model is developed to investigate the interaction of quasi longitudinal (qP) waves with a perfectly bonded interface between a thermo piezoelectric half space and a functionally graded piezoelectric half space. The formulation is based on the fractional order Lord Shulman generalized thermoelasticity theory, which provides an enhanced description of coupled thermo electro mechanical wave behaviour. Rotational effects are incorporated into the constitutive relations and equations of motion for both media, while the lower half space is assumed to be subjected to initial stress. Closed form solutions for reflection and transmission coefficients are obtained, together with associated energy partition factors, allowing a comprehensive assessment of interface wave characteristics. Numerical simulations carried out using MATLAB demonstrate that the reflection and transmission responses are strongly influenced by initial stress, fractional order parameter, and thermal relaxation time. The calculated energy ratios of scattered waves satisfy the energy conservation condition, confirming the mathematical consistency of the formulation. The findings of this study are relevant to the design and analysis of smart sensors, rotating and aerospace structures, vibration control systems, and energy harvesting devices employing functionally graded thermo piezoelectric materials under fractional order effects.

Search processes are a fundamental part of natural and artificial systems. In such settings, the number of searchers is rarely constant: new agents may be recruited while others can abandon the search. Despite the ubiquity of these dynamics, their combined influence on search efficiency remains unexplored. Here we present a general framework for stochastic search in which independent agents progressively join and leave the process, a mechanism we term dynamic redundancy and mortality (DRM). Under minimal assumptions on the underlying search dynamics, this framework yields exact first-passage time statistics. It further reveals surprising connections to stochastic resetting, including a regime in which the resetting mean first-passage time emerges as a universal lower bound for DRM, as well as regimes in which DRM search is faster. We illustrate our results through a detailed analysis of one-dimensional Brownian DRM search. Altogether, this work provides a rigorous foundation for studying first-passage processes with a fluctuating number of searchers, with direct relevance across physical, biological, and algorithmic systems.

Engineering sublattice imbalance within the unit cell of bottom-up synthesized graphene nanoribbons (GNRs) represents a versatile tool for realizing custom-tailored quantum nanomaterials. The interaction between low-energy zero-modes (ZMs) not only contributes to frontier bands but can form the basis for magnetically ordered phases. Here, we present the bottom-up synthesis of a non-centrosymmetric GNR that places all ZMs on the majority sublattice sites. Scanning tunneling microscopy and spectroscopy reveal that strong electron-electron correlations, leading to the Stoner magnetic instability, drive the system into a ferromagnetically ordered insulat-ing ground state featuring a sizeable band gap of Eg ~ 1.2 eV. At higher temperatures, a chemical transformation induces an insulator-to-metal transition that quenches the ferromagnetic order. Tight-binding (TB), density functional theory, and GW calculations corroborate our experimental observations. This work showcases how control over molecular symmetry, sublattice polarization, and ZM hybridiza-tion in bottom-up synthesized nanographenes can open a path to the exploration of many-body physics in rationally designed quantum materials.

The largest connected component in duplication-divergence growing graphs with symmetric coupled divergence is studied. Finite-size scaling reveals a phase transition occurring at a divergence rate $\delta_c$. The $\delta_c$ found is close to the locus of zero in Euler characteristic of finite-size graphs known to reflect the proximity of the largest connected component transition. A close correspondence with the vanishing of a scaling relation exponent for moments of the vertex degree distribution is shown, with such a scaling relation that generalizes a known form for duplication-divergence model graphs. The role of non-interacting vertices in shaping this transition with their presence or absence in duplication is also considered through a particular relation which would result in the two cases being comparable. The findings have relevancy for bond percolation in these growing graph models.

Van der Waals (vdW) superconductors - atomically thin crystalline materials that can be stacked into more complex heterostructures - have opened a promising avenue for superconducting electronics thanks to their properties that are otherwise difficult to obtain in other superconducting materials. These include strong resilience to high in-plane fields, electrostatic tuneability, and non-reciprocal transport rooted in inversion-symmetry breaking and strong spin-orbit coupling. In addition to highlighting the importance of these properties for superconducting electronics, this review gives an overview over the physical mechanisms that govern and influence superconductivity in vdW materials including Ising pairing, band inversion, and proximity effects at superconductor/ferromagnet interfaces that do not have an equivalent in thin-film systems. This overview then sets the basis to survey the wide range of functionalities enabled by superconducting vdW devices including gate-controlled devices, superconducting diodes, and circuit elements for readout and control of quantum bits. The review concludes with a forward look at wafer-scale growth and deterministic assembly of vdW devices, highlighting concrete pathways that can enable the transition from vdW device prototypes to deployable components for cryogenic electronics and quantum technologies.

We examine a new NASICON-type Na$_4$NiCr(PO$_4$)$_3$ material designed for high-voltage and multi-electron reactions for the sodium-ion batteries (SIBs). The Rietveld refinement of the X-ray diffraction pattern, using the R$\bar{3}$c space group, confirmed the stabilization of the rhombohedral NASICON framework. Furthermore, the Raman and Fourier transform infrared spectroscopy are employed to probe the structure and chemical bonding. The core-level photoemission analysis reveals the Cr$^{3+}$ and mixed Ni$^{2+}$/Ni$^{3+}$ oxidation states in the sample. Moreover, the bond valence energy landscape (BVEL) analysis, based on the refined structure, revealed a three-dimensional network of well-connected sodium sites with a migration energy barrier of 0.468 eV. The material delivered a good charge capacity at around 4.5 V, but showed no sodium-ion intercalation during discharge, resulting in negligible discharge capacity. The post-mortem analysis confirmed that the crystal structure remained intact. The calculated energy barrier values indicated a reversal in sodium site stability after cycling, though the barriers can still permit feasible ion migration. This suggests that ion transport alone cannot explain the lack of reversibility, which likely arises from intrinsically poor electronic conductivity. These findings highlight key challenges in achieving stable, reversible capacity in this system and underscore the need for doping, structural modification, and electrolyte optimization to realize its full potential as a high-voltage SIB cathode.

Achieving full control of a Bose-Einstein condensate can have valuable applications in metrology, quantum information processing, and quantum condensed matter physics. We propose protocols to simultaneously control the internal (related to its pseudospin-1/2) and motional (position-related) states of a spin-orbit-coupled Bose-Einstein condensate confined in a Morse potential. In the presence of synthetic spin-orbit coupling, the state transition of a noninteracting condensate can be implemented by Raman coupling and detuning terms designed by invariant-based inverse engineering. The state transfer may also be driven by tuning the direction of the spin-orbit-coupling field and modulating the magnitude of the effective synthetic magnetic field. The results can be generalized for interacting condensates by changing the time-dependent detuning to compensate for the interaction. We find that a two-level algorithm for the inverse engineering remains numerically accurate even if the entire set of possible states is considered. The proposed approach is robust against the laser-field noise and systematic device-dependent errors.

The distribution of ions and their impact on the structure of electrolyte interfaces plays an important role in many applications. Interestingly, recent experimental studies have suggested the preferential accumulation of $SO_4^{2-}$ ions at the $Na_2SO_{4,aq}$-graphene interface in disagreement with the generally known tendency of cations to accumulate at graphene-electrolyte interfaces. Herein, we resolve the atomistic structure of the $Na_2SO_{4,aq}$-graphene interfaces in the 0.1-2.0 M concentration range using machine learning interatomic potential-based simulations and simulated sum frequency generation (SFG) spectra to reveal the molecular origins of the conundrum. Our results show that Na+ ions accumulate between the outermost and second water layers whereas $SO_4^{2-}$ ions accumulate within the second interfacial water layer indicating cation dominated interfaces. We find that the interfacial region (within ~10 ${\AA}$ of the graphene sheet) is negatively charged due to sub-stoichiometric $Na^+$/$SO_4^{2-}$ ratio at the interface. Our simulated SFG spectra show enhancement and a red-shift of the spectra in the hydrogen bonded region as a function of $Na_2SO_4$ concentration similar to measurements due to $SO_4^{2-}$-induced changes in the orientational order of water molecules in the second interfacial layer. Our study demonstrates that ion stratification and ion-induced water reorganization are key elements of understanding the electrolyte-graphene interface.

After a quantum quench, the integrable system is expected to relax to a non-thermal equilibrium state (NTES) whose local properties are believed to be governed by a generalized Gibbs ensemble (GGE). Combining quench action and the form factor approach, we compute the field-field correlation in the NTES produced by an interaction quench of the Lieb-Liniger model. The spectral distribution is shown to be qualitatively different from that of a thermal equilibrium state (TES): a new dispersion branch appears whose microscopic mechanism can be traced to the algebraic decaying tail for the root density distribution function, and indicates the existence of a broader family of NTES featuring similar spectral property.

As a fundamental measure of stability in nonequilibrium thermodynamics, fluctuations provide critical insight into the performance and reliability of heat engines. In this work, we establish universal fluctuation-dissipation bounds that directly link energy-current fluctuations to both the entropy production rate and steady-state transport currents. Our results are applicable to arbitrary temperature and chemical potential gradients and hold for all steady states within the framework of quantum scattering theory. These bounds remain robust even in regimes where quantum effects break classical thermodynamic uncertainty relations. We demonstrate their validity by using boxcar transmission functions and further derive constraints on the power output from the perspective of fluctuations and dissipation, offering a unified thermodynamic guideline for the design and evaluation of nanoscale and quantum thermal devices.

The transition from automated data collection to fully autonomous discovery requires a shared vocabulary to benchmark progress. While the automotive industry relies on the SAE J3016 standard, current taxonomies for autonomous science presuppose an owner-operator model that is incompatible with the operational rigidities of Large-Scale User Facilities. Here, we propose the Benchmarking Autonomy in Scientific Experiments (BASE) Scale, a 6-level taxonomy (Levels 0-5) specifically adapted for these unique constraints. Unlike owner-operator models, User Facilities require zero-shot deployment where agents must operate immediately without extensive training periods. We define the specific technical requirements for each tier, identifying the Inference Barrier (Level 3) as the critical latency threshold where decisions shift from scalar feedback to semantic digital twins. Fundamentally, this level extends the decision manifold from spatial exploration to temporal gating, enabling the agent to synchronise acquisition with the onset of transient physical events. By establishing these operational definitions, the BASE Scale provides facility directors, funding bodies, and beamline scientists with a standardised metric to assess risk, define liability, and quantify the intelligence of experimental workflows.

Materials discovery is a cornerstone of modern technological advancement, yet it remains constrained by traditional trial-and-error paradigms and the inherent bias of human intuition. Artificial intelligence (AI) has emerged as a transformative tool in materials science by effectively modeling structure-property relationships. Despite substantial efforts to enhance model expressiveness, data efficiency remains an equally critical challenge, given the limited availability of experimental and computational resources. Active learning (AL), as a data-driven machine learning paradigm, has shown great promise for discovering novel materials and enabling the efficient navigation of vast materials spaces. In this review, we follow the evolution of sampling strategy design techniques in AL, from Bayesian optimization to advanced deep learning-based strategies. We then highlight how AL enhances data efficiency across various data regimes, ranging from task-specific settings with limited data to the development of general-purpose datasets and large-scale models. We further provide a systematic overview of AL applications throughout the materials research pipeline, including computational simulation, composition and structural design, process optimization, and self-driving laboratory systems. Finally, we pinpoint key challenges and future perspectives of AL in materials discovery.

Type-II hyperbolic lattices constitute a new class of hyperbolic structures that are projected onto the Poincaré ring and possess both an inner and an outer boundary. In this work, we reveal the higher-order topological phases in type-II hyperbolic lattices, characterized by the generalized quadrupole moment. Unlike the type-I hyperbolic lattices where zero-energy cornerlike states exist on a single boundary, the higher-order topological phases in type-II hyperbolic lattices possess zero-energy cornerlike states localized on both the inner and outer boundaries. These findings are verified within both the modified Bernevig-Hughes-Zhang model and the Benalcazar-Bernevig-Hughes model. Furthermore, we demonstrate that the higher-order topological phase remains robust against weak disorder in type-II hyperbolic lattices. Our work provides a route for realizing and controlling higher-order topological states in type-II hyperbolic lattices.

A recently proposed generalised continuum theory of curved dislocations describes the spatial and temporal evolution of statistically stored and geometrically necessary dislocation densities as well as the curvature. The dynamics follow from a scalar plastic potential that constrains the allowed velocity fields and leads to a phase field like formulation with a nontrivial mobility function. Although conceptually related to strain gradient plasticity, the theory differs by introducing an intrinsic, evolving length scale given by the dislocation spacing. In this paper, we determine three key material independent parameters of this continuum theory by quantitatively comparing its predictions with discrete dislocation dynamics (DDD) simulations. To achieve this, we impose a narrow impenetrable wall inside the simulation volume, which blocks dislocation motion and generates characteristic spatial variations of the dislocation density fields under external loading. We show that for this geometry, the continuum equations reduce to a form that can be solved efficiently via direct numerical integration. The resulting stationary distributions of total and geometrically necessary dislocation densities are then compared to extensive 2D and 3D DDD simulations. This comparison allows us to extract the parameters that govern the back stress, the density gradient coupling, and the flow stress relation. Our results demonstrate that the continuum theory quantitatively captures the DDD observed structure of the dislocation pile up near the wall and therefore provides a reliable mesoscale description. The wall loading setup further serves as a benchmark problem to validate numerical implementations of the continuum theory in more general geometries.

Neural quantum states (NQS) have proven highly effective in representing quantum many-body wavefunctions, but their loss landscape remains poorly understood and debated. Here, we demonstrate that the NQS loss landscape is more benign and similar to conventional deep learning than previously thought, exhibiting mode connectivity: independently trained NQS are connected by paths in parameter space with essentially no energy barrier. To construct these paths, we develop GeoNEB, a path optimizer integrating efficient stochastic reconfiguration with the nudged elastic band method for constructing minimum energy paths. For the strongly interacting six-electron quantum dot modeled by a $1.6$M-parameter Psiformer, we find two independent minima with expected energy barrier $\sim10^{-5}$ times smaller than the system's overall energy scale and $\sim10^{-3}$ times smaller than the linear path's barrier. The path respects physical symmetry in addition to achieving low energy, with the angular momentum remaining well quantized throughout. Our work is the first to construct optimized paths between independently trained NQS, and it suggests that the NQS loss landscape may not be as pathological as once feared.

We present a unified geometric approach for spin-1 systems that connects seemingly distinct geometric representations such as the nematic director, the Cartesian representation and the Majorana stellar representation. Starting from a product state of two distinguishable spin-1/2 particles, we provide a direct way to capture crucial geometric information. This perspective reveals the fundamental interplay between subspace projection and geometric constraints. This approach effectively maps magnetic solitons onto a kink model, allowing us to derive their equations of motion, a task not readily achieved with traditional methods. This simplified dynamical description reveals that the novel transition of these solitons in a harmonic trap corresponds to a fundamental transformation between kink and dip structures in the underlying geometry.