Papers

We identify a two-dimensional time-reversal-invariant topological metallic phase on a bilayer Lieb lattice, characterized by a quantized layer–resolved pseudo-spin Chern number. Without the orbital-angular-momentum-dependent (OAM-dependent) coupling, the system gives rise to a time-reversal-invariant topological semimetal with a zero indirect gap and quantized pseudo-spin Chern number. Opposite-sign intralayer OAM-dependent coupling immediately converts the zero-indirect-gap semimetal into a metal, in which the global spectrum is metallic while the layer–resolved pseudo-spin Chern number remains well defined as long as the direct gap at each crystal momentum and the pseudo-spin gap remain open. The model also exhibits asymmetric boundary states: in the semimetallic regime, one edge hosts perfectly flat bands, whereas the opposite edge supports gapless counter-propagating modes forming a one-dimensional Dirac cone. An edge-localized interlayer coupling gaps only the counter-propagating edge states, leaving the flat-band edge essentially intact, while intralayer OAM-dependent coupling bends the exact flat band into a dispersive boundary mode without affecting the gapped Dirac edge. These results open a route toward the controlled engineering of layer–resolved topological gapless phases in synthetic and quantum materials.

Microscopic theories predict that the critical temperature of a superconducting layer can be strongly modified in proximity to a ferroelectric; however, experimental evidence is lacking. We report on BaTiO3 (BTO)/YBa2Cu3O7-{\delta} (YBCO) heterostructures grown on SrTiO3 (001) substrates using pulsed laser deposition (PLD), with precise control of growth conditions and oxygen stoichiometry. Piezoresponse force microscopy confirms ferroelectric switching within both single-layer and heterostructured films. Neutron reflectometry measurements show low roughness parameters for the buried interfaces, which is critical for mediating the interfacial coupling between superconductivity and ferroelectric polarization. The superconducting transition temperature ($T_{\mathrm{C}}^{R}$) measured from the $R(T)$ curve of the single-layer YBCO was approximately 86 K, and a transition temperature ($T_{\mathrm{C}}^{M}$) of approximately 80-85 K was observed from the $M(T)$ curve. For the heterostructure film (YBCO/BTO/YBCO) grown under the same conditions, both resistivity and magnetization measurements indicate lower transition temperatures of approximately 75 K and approximately 55 K, respectively, as well as a lower overall susceptibility. These findings highlight the need to combine multiple techniques to characterize BTO/YBCO heterostructures and identify subtle features of the ferroelectric–superconducting coupling. This establishes BTO/YBCO heterostructures as promising systems for tunable oxide electronics and reconfigurable superconducting devices.

The magneto-optical Kerr effect (MOKE) occurs when polarized light reflects from a magnetized surface, causing a small change in the polarization angle and state. Measurement of the rotation in the angle (Kerr rotation) is well established and typically performed close to the null configuration in a polarizer-analyzer geometry. However, accurate measurement always remains a challenge and as the effect depends intricately on several optical parameters. Here we performed a series of longitudinal magneto-optical Kerr effect (MOKE) measurements on $p$ and $s$ polarized laser light at various polarizer angles on a Cobalt thin film and measured the orthogonal components of the reflected polarized light using a Wollaston prism. Analytical expressions for the orthogonal light components were fitted to the average intensity and the MOKE signal measured at different polarizer angles to obtain the Kerr roations. Our analysis yielded a $p (s)$-Kerr rotation of 0.46 (0.65) milliradians for a 633~nm laser at 45$^\circ$ angle of incidence, which agrees very well with our estimated value for Co using available literature data. Apart from being very accurate, the advantage of the process is that it eliminates the inherent uncertainties in single-point measurements of the Kerr rotation.

We investigate localization transitions and spectral topology in a one-dimensional non-Hermitian generalization of the Aubry-André model in which both the nearest-neighbor and the next-nearest-neighbor hopping amplitudes are nonreciprocal. By extending the Fermi-surface point-matching method to nonreciprocal hopping, we derive a closed-form expression for the energy-dependent mobility edge in which the two nonreciprocity parameters are absorbed into exponentially renormalized effective hopping amplitudes. The mobility edge forms a single parabola in the energy–potential plane: nearest-neighbor nonreciprocity rigidly shifts the localization boundary toward stronger potentials, whereas next-nearest-neighbor nonreciprocity reduces the curvature of the boundary and thereby broadens the energy window in which extended and localized states coexist. Exact diagonalization confirms the analytical boundary for purely nearest-neighbor, purely next-nearest-neighbor, and combined nonreciprocity, and recovers the known Hermitian mobility edge in the reciprocal limit. We further analyze the spectral topology under periodic boundary conditions and show that the spectral winding numbers evaluated at base energies near the two band edges directly bracket the mixed phase: the winding number at the lower band edge drops when the mobility edge enters the spectrum and the first localized states appear, while the winding number at the upper band edge drops when the last extended states localize, delineating the full potential-strength window over which extended and localized states coexist. These results provide a compact analytical framework that connects energy-dependent localization, spectral topology, and nonreciprocity in quasiperiodic lattices, and they are directly testable in photonic, atomic, and electrical-circuit platforms.

Understanding friction at single-asperity contacts is essential for bridging the gap between nanoscale structural superlubricity and realistic tribological systems dominated by Hertzian contact geometry. In this work, we combine atomistic simulations and a modified continuum model to investigate the onset of sliding at crystalline SiO$_2$/SiO$_2$ interfaces. Interfacial sliding potential energy surfaces (ISPES) are computed to determine the load-dependent shear strength and minimal-scale sliding (MSS) friction. Both quantities exhibit linear dependence on normal pressure below 3 GPa, and have non-zero values at zero pressure. Incorporating these parameters, we extend the classical Mindlin model by including adhesion and nanoscale load effects, allowing us to describe the stick to slip transition under realistic Hertzian stress distributions. The model shows that nonuniform pressure distributions substantially lower the effective static friction, and oscillatory-shear experiments on graphene-passivated contacts reproduce both the predicted stiffness-collapse signature and, in the passivated limit, the adhesion-limited shear strength obtained from simulation, supporting the model's relevance to real micro-asperity tribology.

Understanding fracture behavior is critical for assessing the structural integrity and longevity. Highly time-consuming physics-based fracture simulations motivate the development of machine-learning-based fracture evolution prediction with surrogate models. However, most existing machine-learning models for fracture prediction operate as black boxes and require large training datasets to generalize reliably. In this work, Thermodynamically Consistent Latent Dynamics Identification (tLaSDI) for parametric systems is introduced to predict fracture patterns and evolution in heterogeneous materials. The model learns the thermodynamic state variable in a lower-dimensional latent space using parametric GENERIC Formalism-Informed Neural Networks (pGFINNs) that enforce key thermodynamic principles, such as total energy conservation and entropy generation. This model embeds physics into the neural network architecture using a hard-constraint method that inherently complies with the underlying thermodynamic principles. The proposed tLaSDI-pGFINNs is further enhanced by a Geometry-Conditioned Autoencoder in learning the geometry configuration for effective geometry-guided learning. The energy and entropy evolution histories demonstrate that the model preserves the thermodynamic constraints on unseen testing samples. The results further show that tLaSDI-pGFINNs can more accurately capture both fracture patterns and the subsequent fracture evolution than the purely data-driven Autoencoder Long Short-Term Memory (AE-LSTM) model.

This work studies the inverse problem of recovering the relative magnitudes of the tension, bending, and bearing loads acting on a crack from its stress-intensity-factor profile along the crack front, using the public SIFBench finite-element data. The central claim is not forensic load recovery on field cases, but a rigorous characterization of when the combined load is identifiable at all, together with an estimator that returns calibrated uncertainty precisely in the regimes where it is not. For a known geometry the forward map from loads to profile is exactly linear, and identifiability reduces to a single geometric question: whether the three elementary load profiles are linearly independent as functions along the front. When they are nearly dependent, many different load combinations produce almost the same profile and the inverse problem is illposed; the analysis shows that the degree of ill-posedness is controlled by an intrinsic stability margin, not by the conditioning number alone. A single crack-front operator serves both as a structured forward surrogate and as the differentiable map required by a simplex-constrained, set-valued inverse estimator. On the SIFBench corner-crack scenario the empirical behaviour matches the theory: the typical geometry is well posed while a sizable minority is genuinely ill-posed, so a point estimate is reliable on the majority and provably uninformative on the rest. Validation is on controlled synthetic noise; no real fracture cases are used or claimed.

Reactive flocking models usually map current local observations directly to motion, leaving limited room for internal perceptual state to shape recovery after disruption. Building on a non-Markovian collective-motion model based on self-regulated perceptual dynamics, we ask whether the Bloch-type slow-fast architecture can support self-healing coordination in cognitive swarm agents. Each agent carries a bounded Bloch-type perceptual register coupled to a slow regulatory state. The slow state is not treated as a standalone memory store; here, perceptual memory is used operationally to denote history-dependent cue resolution within the closed slow-fast loop. The Bloch update is a positivity-preserving effective dynamics for internal perceptual alternatives, not a microscopic quantum claim. We evaluate the architecture in a non-periodic, obstacle-rich drone migration task with finite speed, bounded turning, collision avoidance, altitude regulation, and a fixed migratory drive. Multi-seed ablations compare the full slow-fast architecture with memoryless and partial-feedback baselines using recovery time, largest-cluster restoration, polar order, local coherence, collision risk, and path efficiency. Results show that the main functional impact is on self-healing: after obstacle-induced fragmentation, the closed slow-fast loop accelerates restoration of spatial connectedness, whereas an uncoupled slow trace behaves like a memoryless controller.

Weyl semimetals host topologically protected Fermi arcs on their surfaces, originating from the Chern number of the bulk Weyl nodes. In trigonal PtBi$_2$, superconducting signatures have been associated with the Fermi arcs. Theoretical descriptions of this surface superconductivity have so far relied on effective models that are not directly tied to the microscopic electronic structure of the material. In this work we develop a minimal description of the low-energy bands guided by density functional theory calculations and fully constrained by the relevant crystalline and time-reversal symmetries. The model captures the evolution of the Weyl nodes with spin-orbit coupling, including node annihilations, and is able to describe the spin-momentum locking of the surface Fermi arcs. It reproduces the orbital content and the band topology of PtBi$_2$ and provides a starting point for further studies.

Experimental observations of rare-earth ions doped into an antiferromagnetic crystal show an enriched optical spectrum. In this paper we present a cluster-based model to describe erbium ions doped into a gadolinium vanadate (Er:GdVO$_4$) host crystal, wherein the erbium ion couples directly to its four nearest neighbour gadolinium ions, which in turn couple to the mean field of the rest of the crystal. Compared to previous models in the literature, the parameters used to fit this model are fewer in number, with clearer physical origins. Agreement with the experimentally observed optical spectrum of Er:GdVO$_4$ suggests that our model succeeds in capturing the most important interactions of the system, suggesting that it may be useful for predicting microwave-to-optical transduction in future experiments.

Krylov complexity is a powerful diagnostic of quantum dynamics, with clear connections to other measures of quantum chaos and operator growth. One such measure is the Loschmidt amplitude, defined as the overlap of initially identical states evolved under two slightly different Hamiltonians. Its decay in certain systems is controlled by the classical Lyapunov exponent. Using the algebraic properties of the Krylov complexity operator, we express Krylov complexity as the derivative of a Loschmidt amplitude whose perturbation is parameterized by an angular variable $\phi$. This formulation allows us to define a spectral propagator that encodes the entire complexity distribution, which we characterize for specific types of systems. We study the two-dimensional quantum geometry spanned by time and $\phi$ where the original and deformed trajectories reside, demonstrating that Krylov complexity is upper-bounded by its volume. We also express the time derivative of Krylov complexity in terms of a distinct Loschmidt amplitude. Depending on the growth of the Lanczos coefficients, the perturbation term in this amplitude can be truncated. We propose that the strength of this perturbation provides a classification scheme for Krylov complexity dynamics and relate it to the $\phi$-derivative of the spectral propagator. Using this analytical framework, we derive general relations between the time-dependence of the survival amplitude and Krylov space measures.

Membrane-deformation mediated interactions play an important role in the spatial organization of proteins on the cell membrane. Although interactions between isotropic membrane deformations have been extensively investigated, the role of anisotropic deformations remains largely unexplored despite their prevalence in biological systems. Here, we experimentally investigate the assembly of anisotropic colloidal objects that deform a lipid membrane while being confined underneath it, without direct attachment. Combining experiments and numerical calculations, we analyze how a wide range of shapes, including ellipsoids, dumbbells, cubes, scalene triangles, tetrahedra, and bent rods, interact with each other through the membrane deformations they induce. We find that membrane-deforming objects initially attract through regions of highest curvature and subsequently reorient into close packed arrangements with an approximately spherical circumference. This is achieved through the alignment of flat faces - if possible in register - and locally optimized geometric packing, with regions of high curvature imposing energy barriers that influence the assembly pathway. Our work reveals general principles how anisotropic membrane deformations govern the assembly pathways and final particle arrangements, providing new insights into the behavior of membrane-deforming proteins and other inclusions.

In this work, high-quality Ge-doped (-201) $\beta$-Ga$_2$O$_3$ thin films were heteroepitaxially grown on c-plane sapphire substrates with offcut angles of 0 deg, 2 deg, 6 deg, and 8 deg using low-pressure chemical vapor deposition (LPCVD). Increasing sapphire offcut promoted step-flow growth, resulting in improved terrace alignment, reduced surface roughness, and enhanced crystalline quality. Phase-pure monoclinic $\beta$-Ga$_2$O$_3$ with strong (-201) preferential orientation was confirmed by X-ray diffraction and Raman spectroscopy, while X-ray photoelectron spectroscopy revealed near-stoichiometric composition with an O/Ga ratio of 1.48. Electrical transport properties exhibited a strong dependence on substrate offcut angle, with room-temperature Hall mobility increasing from 15 to 117 cm$^2$/V s as the offcut angle increased from 0 deg to 6 deg, across carrier concentrations spanning $1.43 \times 10^{17}$ to $2.75 \times 10^{18}$ cm$^{-3}$. The 6 deg offcut sample achieved a room-temperature mobility of 117 cm$^2$/V s at a carrier concentration of $1.43 \times 10^{17}$ cm$^{-3}$ and a peak low-temperature mobility of 337 cm$^2$/V s at 128 K with a carrier concentration of $8.96 \times 10^{16}$ cm$^{-3}$, representing the highest reported room-temperature and low-temperature mobilities for Ge-doped $\beta$-Ga$_2$O$_3$ films grown on sapphire substrates. Carrier concentration and mobility data were analyzed using charge-neutrality and Boltzmann transport models incorporating donor activation together with polar optical phonon, ionized impurity, neutral impurity, acoustic deformation potential, and dislocation scattering mechanisms. The fitting revealed shallow donor activation energies of 12.5-19 meV, a deeper donor level at 80 meV, low acceptor compensation ($< 5 \times 10^{15}$ cm$^{-3}$), and threading dislocation densities on the order of $10^9$ cm$^{-2}$.

In this work, Ge-doped $\beta$-Ga$_2$O$_3$ homoepitaxial films were grown on native (010) $\beta$-Ga$_2$O$_3$ substrates using low-pressure chemical vapor deposition (LPCVD). Controlled $n$-type doping was achieved with room-temperature carrier concentrations ranging from $7.4\times10^{17}$ to $2.57\times10^{18}\ \mathrm{cm}^{-3}$ and corresponding electron mobilities of 105-62 cm$^2$/V$\cdot$s. The films exhibited smooth surface morphology with RMS roughness values of 2.94-3.97 nm, while X-ray diffraction, Raman spectroscopy, and X-ray photoelectron spectroscopy confirmed phase-pure $\beta$-Ga$_2$O$_3$ with excellent crystalline quality and near-stoichiometric composition. Temperature-dependent Hall measurements on the film with a room-temperature carrier concentration of $7.4\times10^{17}\ \mathrm{cm}^{-3}$ and mobility of 105 cm$^2$/V$\cdot$s yielded a peak electron mobility of 234 cm$^2$/V$\cdot$s at 116 K, while charge-neutrality and transport modeling revealed a dominant shallow donor level with an activation energy of 14 meV, confirming efficient electrical activation of Ge donors. Vertical Ni/$\beta$-Ga$_2$O$_3$ Schottky barrier diodes fabricated using the Ge-doped drift layer exhibited good rectifying behavior with a turn-on voltage of 0.74 V, an ideality factor of 1.32, a Schottky barrier height of 1.02 eV, and a specific on-resistance of 2.49 m$\Omega\cdot$cm$^2$. Capacitance-voltage measurements yielded a net donor concentration of $7.7\times10^{17}\ \mathrm{cm}^{-3}$ and a Schottky barrier height of 1.13 eV, in good agreement with Hall and current-voltage measurements. These results demonstrate that LPCVD enables controllable Ge doping while maintaining high structural and electronic quality, establishing LPCVD-grown Ge-doped $\beta$-Ga$_2$O$_3$ as a promising platform for future high-voltage power electronic devices.

Quantum advantage in real-time spin dynamics should be assessed against the strongest relevant classical substitutes, not merely against the qubit nature of the microscopic system. We develop a physics-based diagnostic for this boundary by reducing a qubit spin model to a spin-Landau–Lifshitz (LL) classical sector and organizing the residual quantum sector as controlled corrections. The control parameter is graph coordination: we study a spin star with \(d\) leaves and \(O(1/d)\) hub–leaf couplings. In its homogeneous form the star benchmarks the transition from LL-substitutable dynamics to genuinely quantum, discrete-sector interference; in its fully driven form, with time-dependent fields and bilinear couplings, it is the basic message-passing primitive for tree and loopy spin structures. For coherent-state return amplitudes we prove exact leaf elimination and derive a continuous-time \(1/d\) hierarchy. L0 is a driven one-spin weak-mean-field theory, while G1 is a Gaussian nonlocal-in-time influence correction coupling leaf two-time kernels to the hub weak two-point function. On bounded finite-time windows away from zeros of the boundary amplitudes, the hierarchy gives \(\log\mathcal A-\log\mathcal A_{\rm L0}=O(1/d)\) and \(\log\mathcal A-\log\mathcal A_{\rm L0}-\Delta_{\rm G1}=O(1/d^2)\); numerical tests on fully driven anisotropic ensembles give slopes \(-1.05\) and \(-2.03\). Static, inhomogeneous, aligned, and fully driven stars provide validation rungs, and comparison with a temporal matrix-product influence-matrix baseline delineates complementary regimes. Unlike rank compression on a Trotter grid, the hierarchy is ordered by a physical parameter, formulated in continuous time, and each truncation level is itself a physical theory, with the LL sector as the high-coordination limit.

The sequence of magnetization plateaus at 1/8, 2/15, 1/6, 1/4, 1/3, 2/5, and 1/2 of the saturation observed in SrCu$_2$(BO$_3$)$_2$ remained a puzzle until tensor-networks-based numerical simulations suggested that the low-magnetization plateaus are stabilized as Wigner crystals of spin-2 bound states, and not as one of the standard configurations (semiclassical up-down, or crystals of triplets). We report on $^{63,65}$Cu nuclear magnetic resonance spectra up to 41.9 T: Based on constraints deduced from the 1/3 plateau, we show that the spectra in the 1/8 and 2/15 plateaus indeed agree with the prediction for the spin-2 bound states, while being incompatible with a crystal of triplets. This adds the formation of Wigner crystals of bound states as an alternative fundamental paradigm in the theory of magnetization plateaus.

Quantum point contacts (QPCs) are essential tools for transport experiments in solid-state systems, enabling the detection of fractional charges and anyonic braiding statistics. Realizing analogous transport setups in isolated quantum-simulation platforms, such as ultracold atoms, remains challenging, since it typically requires coupling to external reservoirs. Here we show that the scattering properties of chiral edge states at a QPC can instead be extracted directly from the stationary edge currents of an isolated, reservoir-free lattice system. Exploiting the sensitivity of this scattering to Aharonov-Bohm-type phases, we propose an equilibrium protocol to detect local magnetic fluxes from ground-state edge currents. We further introduce a dynamical scheme, robust against finite temperature and particle-number fluctuations, based on the post-quench evolution following a sudden potential-bias removal. Since anyonic excitations are themselves associated with a local, quantized magnetic flux, our approach should extend to probing anyonic statistical phases in quantum-engineered platforms.

We develop a two-axis interpolation framework for the O$(n)$ universality family, treating the spatial dimension $D$ and the spin-component number $n$ as independent continuous parameters connecting exact limiting solutions. On the spatial axis, anchoring between the Onsager solution at $D=2$ and mean-field theory at $D\to\infty$ yields a closed-form prediction for the 3D Ising critical coupling that agrees well with Monte Carlo benchmarks $K_c = 0.2204$ (benchmark: $0.22165$) with no adjustable parameters. Wilson–Fisher-constrained polynomial interpolation gives $\nu=2/3$, $\beta=31/96$, and $\eta=35/864$ at $D=3$ (benchmarks: $0.6299$, $0.3265$, $0.0362$), and reproduces conformal-bootstrap results across $3 \le D < 4$. On the spin axis, we establish a necessary compatibility criterion: two-anchor interpolation succeeds only for observables that vary monotonically between the anchor values. The critical coupling $K_c(n)$ violates this criterion because the Heisenberg value falls below the spherical limit, whereas the correlation-length exponent $\nu(n)$ satisfies it. A perturbative $1/n^2$ expansion yields $\nu(3) = 0.7493$ (benchmark: $0.7112$), and propagation through exact scaling relations gives $\beta(3) = 0.3797$ (benchmark: $0.3689$) and $\gamma(3) = 1.489$ (benchmark: $1.396$), without introducing additional parameters. The framework naturally extends to non-integer spin, producing the prediction $\nu(2.5) = 0.7143$ for the O$(2.5)$ universality class. These results establish dimensional and spin interpolation as a unified and predictive approach to critical phenomena, while clarifying the structural conditions under which interpolation succeeds.

Conventional altermagnetism, characterized by compensated collinear spin alignment and spin splitting, exhibits identical spin states at opposite momenta. In this work, we employ a non-spatial global symmetry $S$, the spinless time-reversal symmetry, which effectively replaces inversion symmetry in preserving the spin-state equivalence; hence, we systematically extend the classification of altermagnetism to all possible non-centrosymmetric crystals. By analyzing the necessary symmetry conditions, we provide a complete catalog of altermagnetic orders for all 2D magnetic wallpaper groups and all 3D magnetic space groups, identifying 17 altermagnetic wallpaper groups (12 centrosymmetric and 5 non-centrosymmetric) and 422 altermagnetic space groups (160 centrosymmetric and 262 non-centrosymmetric). This catalog assigns each altermagnetic wallpaper and space group to one of the six altermagnetic wave types established in the literature and presents its distinct spin distribution in the Brillouin zone (BZ); notably, the low-energy wave-type description does not necessarily extend throughout the full BZ, since the spin-degenerate nodal lines and planes can be unpinned from the high-symmetry planes. Beyond the catalog, nonsymmorphic symmetries further bring new patterns of the altermagnetic BZs through the emergence of hourglass dispersions, which arise from the compatibility relations between two symmetry-protected degenerate manifolds: same-spin and opposite-spin degeneracies. In both the non-centrosymmetric altermagnetism and the emergence of the hourglass dispersion, the spinless time-reversal symmetry plays the key role. Our work extends the symmetry catalog of altermagnetism and reveals that nonsymmorphic symmetries are essential for realizing altermagnetic band structures beyond the six established wave types, such as an $i$-wave-like spin winding in a tetragonal BZ.

Motivated by recent developments in van der Waals heterostructures, we revisit the acoustic plasmon mechanism of superconductivity in bilayer systems composed of a light layer (LL) and heavy layer (HL) by employing Eliashberg theory. The exchange of virtual plasmons in the HL can lead to a retarded in time attractive interaction between electrons of LL that we model through the screened interaction in the bilayer system within the random phase approximation. We explore the evolution from acoustic plasmon mediated superconductivity to phonon mediated superconductivity by studying the evolution of $T_c$ as the HL mass is increased by a few orders of magnitude compared with the electronic mass in LL. The lower HL mass corresponds to the bilayer acoustic plasmon, while the latter regime is closer to the Born-Oppenheimer regime of acoustic phonon mediated strongly retarded pairing. The heavy HL mass limit is known to obey Migdal's theorem by virtue of the small ratio of the two individual layer masses. We study the nonadiabatic effects for the arbitrary mass ratio with no small parameter systematically by using a frequency cut off in the Eliashberg theory, providing $T_c$ as a function of this cut off.

Spinel ferrites have shown wide range of applications in various fields, including supercapacitors, Li-ion batteries, water splitting, chemical sensors, catalytic activity, high-frequency magnetic devices, and biomedical, hyperthermia, drug delivery applications., etc. This review focuses on the latest progress and trends on design of spinel ferrites (MFe2O4; M = Divalent transition metal ion) based materials for electrochemical applications. Spinel ferrites exhibit good chemical stability, high surface area and excellent electrochemical behaviour with their multiple oxidation states, making them suitable for the detection of a wide range of gaseous analytes including volatile organic compounds, heavy metal ions, biomolecules, and environmental pollutants. It also makes spinel ferrites a great choice for efficient energy storage and utility in supercapacitors. The electrochemical performance of spinel ferrite-based electrode materials can be effectively tuned via morphology control, incorporation of carbon-based materials, compositional substitution, doping and forming composition systems, especially in nanostructured form. This review will serve as a comprehensive resource for researchers interested in the synthesis and various enhancement techniques for electrode material composition of electrochemical device applications specifically, gas sensors and supercapacitors, which are two of the highest emerging functional applications for the new sustainability directed world, utilizing these advanced materials.

We formulate feature learning as a geometric critical phenomenon of the lifted tensor-product learning metric. The central object is not a scalar overlap, but the target-active geometry of \[ \mathcal N_{0,L}=\frac1N\sum_{r=1}^{L}\Sigma_{r\to L}\otimes T_{0\to r-1}, \] which entangles forward pullback survival with backward push-forward visibility. The neutral phase is target-isotropic: after restriction to endpoint target-active states and trace normalization, the lifted metric is proportional to the identity. Learning corresponds to an instability of this target-isotropic fixed point and to the emergence of traceless target-aligned eigentensors. We derive discrete Dyson expansions for local anisotropic insertions and their continuous Callan–Symanzik flow. Crucially, before constructing the full temporal mean-field theory, we identify the local spatial source of the $\beta$-functions directly from microscopic kinematics: asynchronous gradient updates generate synchronous metric strains, whose target-active symmetric traceless components act as curvature-like defects. The Wilsonian depth RG flow is then governed by the transport, balance, and coarse-grained irrelevance of these defects. Heavy-tailed spectra arise, under a scale-free counting hypothesis, as the spectrum of the target-active lifted geometry, with exponent addition in the matched pullback–push-forward sector. Finally, we relate this depth RG picture to temporal stochastic training dynamics and to the kinematic imprint of the learned channel on empirical weight Gram matrices.

The Lee-Yang theorem and its quantum extensions state that, for a broad class of Hamiltonians on any graph, the partition function's zeros in the complex magnetic field plane lie only on the imaginary axis. For these Hamiltonians, we prove that under a uniform Z-field of any strength h, the ground state has a spectral gap of at least h/4, independent of the system size and of the coupling strengths. The proof uses the zero-freeness of the partition function as given by Asano and Suzuki-Fisher to show exponential decay of the imaginary-time correlations for any product of Z-operators. Our result gives a polynomial-time quantum algorithm for computing the ground state energy of any Lee-Yang Hamiltonian.

Unconventional odd-parity magnets, characterized by an odd-parity momentum-dependent spin splitting, offer a fundamentally distinct paradigm for non-collinear spintronics. Here, we theoretically investigate the Ruderman-Kittel-Kasuya-Yosida indirect exchange in two-dimensional odd-parity magnets subjected to Rashba spin-orbit coupling. Using an analytical real-space Green's function formalism, we uncover a parity-driven spatial decoupling in the magnetic response. Because of the odd-parity exchange field, the out-of-plane Ising interaction is structurally insulated from the macroscopic magnetic modulation, oscillating isotropically at the shifted Fermi wavevector. Conversely, the in-plane Heisenberg components exhibit pronounced, directionally tunable spatial beating. Beyond collinear exchange, the hybridized bands generate a highly tunable, three-component Dzyaloshinskii-Moriya interaction alongside symmetric off-diagonal anisotropies. We reveal that the out-of-plane chiral twisting is driven by the massive, nonrelativistic momentum shift, while the in-plane chiral components are relativistic. Furthermore, the competition between the nodal geometry and the Rashba gap drives an anomalous, dimension-reducing crossover, in which the in-plane chiral components follow a 1D-like $1/R$ spatial decay along the nodal lines over an extended intermediate-distance window before ultimately recovering the conventional 2D $1/R^2$ asymptote. We demonstrate that these findings hold universally across the odd-parity class by explicitly generalizing our framework to $f$-wave magnets. Finally, numerical tight-binding calculations verify the striking robustness of this parity-driven decoupling against both scalar and random magnetic exchange disorder. These findings establish odd-parity magnets as promising platforms for engineering robust, directionally tunable non-collinear spin textures.

Simultaneous detection of the spectral and polarization properties of light is highly desirable for integrated imaging and photonic technologies but typically requires complex multi-component architectures. Here, we demonstrate that the intrinsic dielectric anisotropy of layered insulating CrCl3 enables ultrabroadband polarization-resolved photodetection spanning wavelengths from 300 to 1700 nm. The photoresponse is governed by long-lived ligand-field excitons, whose microsecond-scale lifetime produces a photoconductive gain exceeding 4.5 x 10^4. By combining wavelength-, polarization-, and angle-resolved optoelectronic measurements, we reveal that distinct ligand-field and higher-energy excitonic transitions possess different optical dipole orientations, leading to excitation-energy-dependent rotation of the in-plane polarization axis. Furthermore, oblique illumination activates out-of-plane optical dipoles, while competing excitonic transitions with distinct dipole orientations drive wavelength-dependent rotation and reversal of the polarization anisotropy. Together, these effects produce a highly tunable degree of polarization ranging from -90% to +75%, establishing intrinsic three-dimensional vectorial light-matter interactions in a layered magnetic van der Waals insulator. These findings establish dielectric anisotropy and excitonic dipole engineering as powerful design principles for compact ultrabroadband polarization-sensitive photodetectors and multifunctional van der Waals photonic systems.

Soil harbors much of Earth's bacterial life. The activity of these bacteria governs plant growth, carbon and nitrogen cycling, and the response of land to a changing climate. Understanding this activity is difficult, however: soil is structurally and chemically heterogeneous and optically opaque, and its bacteria not only respond to their surroundings but continually reshape them, a two-way feedback that most idealized experiments and theories overlook. Here we review how this dynamic feedback governs the physics of bacterial motility, growth, and sensing in soil across three scales – the single pore, the mesoscale of many pores, and the broader landscape.

We have implemented soft point-contact Andreev reflection spectroscopy (PCARS) in a palm-type cubic anvil pressure cell by combining a substrate anchoring strategy with an external wire-splitting technique. This design enables the stable formation of multiple point contact junctions under hydrostatic pressures up to 15 GPa. Benchmark measurements on the elemental superconductor Nb demonstrate high reproducibility and yield a zero-temperature superconducting gap with a gap ratio of 3.3. We further apply this technique to the Kagome metal superconductor CsCr3Sb5 and the bilayer nickelate superconductor La2PrNi2O7. Pronounced zero-bias conductance peaks are observed, and their evolution with temperature, magnetic field and applied pressure is investigated, together with the superconducting gap magnitude and possible pairing symmetries. These measurements provide spectroscopic evidence consistent with unconventional superconductivity in these materials. Our work establishes a robust experimental platform that bridges macroscopic electrical transport and microscopic spectroscopic probes, opening a new avenue for investigating pairing symmetry in a wide range of pressure-induced unconventional superconductors.

Deploying AI-based visual inspection in manufacturing is hard because requirements change often, new defect types appear, and large labeled datasets are rarely available. We propose answer-conditioned chain-of-thought (CoT) distillation for rapidly adapting small vision-language models (VLMs) to new industrial tasks using minimal labeled data. A frontier VLM receives each training image along with its correct label and generates a justified visual explanation. A 3B-parameter model is then fine-tuned on these reasoning-augmented examples via LoRA. By conditioning on correct answers, we ensure all training reasoning is directed toward the correct conclusion, which is critical because frontier models score as low as 24.1% on our hardest task. We validate on four industrial classification tasks spanning three image modalities using only 18 to 30 labeled images per task. Across 4 seeds per task (32 training runs), our method outperforms direct fine-tuning on all 16 seed-task combinations, with mean improvements of +1.7 to +4.4 percentage points. A controlled equal-budget experiment confirms the improvement comes from reasoning quality, not additional training steps. An unconditioned baseline demonstrates that with out answer-conditioning, wrong reasoning degrades performance by 17.8 percentage points. On weld radiograph classification, the fine-tuned 3B model outperforms GPT-4.1 by 10.0pp using just 24 training images.

Transport in devices with multiple proximitized sectors depends heavily on the complex phases of the pairing gaps of those sectors. We investigate magnetic topological insulator nanoribbons in two- and three-terminal setups with proximitized sectors and asymptotic normal leads. Our focus is on the regime of single chiral Majoranas. The characteristic electric and thermal interferometries of chiral Majoranas can be controlled by the complex phases of the pairing. We predict an AC Majorana effect, in which phase dynamics induced by a voltage bias generate measurable time-dependent conductance oscillations. A three-terminal junction with superconducting islands can be used as a Majorana router when the relative complex phases are configured.

In this paper, we provide a systematic investigation of SO(2) theory to machine learning interatomic potentials (MLIPs) and identify the limitations of conventional SO(2) Linear architectures relative to SO(3) Clebsch-Gordan Tensor Products (CGTP). Building on these insights, we propose direct Cartesian construction and recursive Clebsch-Gordan construction of Wigner D-matrices and introduce two novel interaction building blocks. First, we propose the Edge Complex Product Basis based on Generalized Asymmetric Contraction, a new formulation for many-body expansion that directly constructs higher-order interactions on edges through complex-valued equivariant multiplications. Second, we introduce Radial Rotary Complex Attention(RRA), which enhances extrapolation performance and surpasses existing attention vector formulations. We also introduce several improvements to the Atomic Cluster Expansion module. Building on these advances, we train our models on OMat24, sAlex, and MPTrj, and introduce TECE-OAM-RRA-1.0, which achieve state-of-the-art (SOTA) performance on the Matbench Discovery.