Papers

Hopfions, associated with higher-dimensional topology through the Hopf fibration, exhibit {exotic} features like {complex knot} and improved stability compared to skyrmions, enhancing their appeal for innovative applications. In this paper, we study the nonlinear response of magnetic Hopfion to microwave fields. {We observe the emergence of higher-order harmonics of the driving microwave field as it interacts with the Hopfion}. By carefully selecting the {driving frequency, the corresponding harmonic can efficiently excite localized magnon state of a Hopfion. Our results demonstrate the promising potential of hopfions in nonlinear magnonics.

We study helicity-selective antiferromagnetic resonance in an antiferromagnetic-insulator/nonmagnetic-metal junction with sublattice-dependent damping and spin-orbit torque. By formulating the linearized Landau–Lifshitz–Gilbert equation as a 2x2 non-Hermitian eigenvalue problem, we analyze the complex resonance frequencies and the stability threshold, using MnF$_2$ parameters as a representative example of a uniaxial antiferromagnet. We show that the absorption is strongly enhanced near the stability threshold, where one helicity mode becomes weakly damped, leading to linewidth narrowing and pronounced helicity selectivity in the sub-THz regime. The selected helicity can be switched by reversing the current direction, which reverses the spin-orbit torque acting on the interfacial sublattice. These results identify stability-threshold control as a design principle for electrically tunable helicity-selective antiferromagnetic resonance in uniaxial antiferromagnets.

We present the approach needed to calculate stress within density functional theory (DFT) using a localised orbital basis, both for exact diagonalisation and linear scaling approaches, and demonstrate our implementation within the large scale DFT code Conquest. For the linear scaling approach, we test the rate of convergence of stress with density matrix range, and compare it to the convergence of energy and forces for different materials with a range of band gaps. We show that excellent convergence is found for modest cutoffs (below 0.1GPa error for range of 20a0), and show that large-scale isothermal-isobaric molecular dynamics is stable and accurate, showing negligible drift over picoseconds of dynamics.

Understanding the thermodynamic properties of disordered magnetic alloys requires a unified treatment of configurational (chemical, spin, etc.) and structural degrees of freedom, which has remained beyond the scope of existing computational frameworks. Here we present a general framework that integrates machine learning models (such as graph neural networks and machine learning interatomic potentials) and statistical sampling methods (such as Monte Carlo and molecular dynamics simulations) to study the coupled chemical, spin, and structural disorder in alloys. We demonstrate the framework on body-centered-cubic Fe-Co alloys with interstitial carbon dopants, where the Fe-Co host exhibits intrinsic chemical and spin disorder, and the interstitial carbon introduces additional structural disorder through local lattice distortions, making the system a prototypical multi-disorder magnetic alloy. The framework predicts the order-to-disorder phase transition temperature and the melting temperature of Fe-Co alloy to be 1,000 K and 1,690 K, in excellent agreement with the experimentally measured values of 1,006 K and approximately 1,700 K, respectively. It also predicts the tetragonal-to-nearly-cubic structural transitions in Fe-Co-C alloy as temperature increases. These results establish the framework as a reliable tool for studying multi-disorder alloys, with applications to complex disordered systems such as high-entropy alloys, multiferroics, and spintronic devices.

SrTiO3 thin films, 20-30nm, with high quality crystal structure and low roughness can be used as growth templates for complex oxides or as the dielectric materials for capacitor structures. In this work, stoichiometric STO thin films were grown by radio frequency magnetron sputtering on Pt (111) templates grown on rAl2O3 substrates, and the effects of growth parameters as well as the underlying Pt templates structural properties on the quality of STO films were studied. A comparison between room temp grown Pt and Pt grown at elevated temps showed that the latter lead to highly ordered Pt and STO films with quasi 2D surface roughness. Xray diffraction showed that the STO thin films had (111) and (222) crystal orientation. A rocking curve full width at half maximum value of 0.2{\deg} was achieved, indicating that the STO films are high-quality. The STO films have a roughness less than 1 nm, as measured using atomic force microscopy, comparable to the underlying Pt templates roughness.

Hyperuniform systems, defined by the anomalous suppression of large-scale density fluctuations, are a paradigm of non-equilibrium self-assembly. While mechanisms underlying the self-assembly of hyperuniform states have been widely studied, the energetics of this process remain unexplored. This raises a fundamental question: what is the energetic cost of self-assembling a hyperuniform system? Here, we address this question across several noisy particle systems drawn from soft matter and machine learning, in which hyperuniformity can be induced by tuning noise correlations. Despite their distinct microscopic dynamics, we uncover a universal behavior across all systems: hyperuniform states are maximally irreversible, as quantified by the entropy production rate. Further, we develop a path integral formulation of the entropy production rate directly from the microscopic dynamics, which explains our observations. Our work establishes a direct link between emergent long-range structure and time irreversibility and opens a new avenue of probing the energetic cost of hyperuniform self-assembly, ubiquitous across physics, biology, and materials science.

Quasi-2D Bi$_2$O$_2$Se is part of an intensive materials research effort aimed at finding new semiconductors that outperform silicon-based electronics in terms of speed and power consumption. This material exhibits exceptionally high carrier mobility at low temperatures but mediocre mobility at 300 K. Its high mobility is generally associated with its high permittivity ($\varepsilon_r$~500), which is also associated with metallicity persisting down to very low carrier concentrations. This material exhibits a counterintuitive increase in carrier mobility as the concentration increases. The connection between low both carrier concentration and mobility in Se-rich conditions, and both high carrier concentration and mobility in Se-poor conditions suggests that the increase is related to native defects. We demonstrate that these defects can alter the effective mass of charge carriers. Specifically, substitutional Se(Bi) defects, which appear under Se-rich conditions, destroy the Bi$_2$O$_2$ channel and compromise charge transport properties. These defects increase the effective mass of charge carriers transforming the original semiconductor into a semimetal and introducing holes into charge transport. Additionally, we show that single crystals are generally inhomogeneous, particularly those grown under Se-rich conditions. Unlike Se-poor conditions, Se-rich conditions induce a higher concentration of dislocations and extraneous phases. These findings suggest that the perfection of the Bi$_2$O$_2$ channel is crucial for mobility, particularly at room temperature.

A quantitative, material-specific account of spectral and transport properties remains a central challenge in the theory of strongly correlated materials. Combining density functional theory with dynamical mean-field theory (DFT+DMFT) has proven to be a powerful approach for treating electron correlation effects and material specificity on an equal footing. Here, we examine the single-particle spectra and the dc and optical conductivity of SrVO$_3$, a prototypical, moderately correlated metal, within this framework. The degenerate $t_{2g}$ active space of SrVO$_3$, together with its well-established Fermi-liquid behavior, admits an effective-mass description governed by a single quasiparticle weight, yielding a nearly universal picture of the low-frequency, low-temperature regime. Employing a computationally efficient, real-frequency multi-orbital iterative perturbation theory (MO-IPT) impurity solver, we find reasonable agreement with experimental measurements of dc resistivity and optical conductivity across the entire experimentally relevant $(\omega, T)$ range within a single, unified scheme. The agreement is shown to not depend on specific interaction parameters provided the quasiparticle weight is kept constant. These results indicate that, in SrVO$_3$, the $\mathbf{k}$-dependence of the self-energy may be weak, and vertex corrections may not dominate the dc and optical transport in this material.

High-resolution atomic force microscopy has transformed molecular imaging by revealing intramolecular structure directly in real space. A major remaining challenge is to extend this capability from largely planar molecules to non-planar molecular systems, where the most important structural information may be distributed across different heights above the surface. Here we use probe-particle-model simulations to predict the constant-force contours expected above molecules with increasing structural complexity. By extracting force isosurfaces from simulated three-dimensional force fields, we compare the molecular information retained in constant-height and constant-force images. For tilted benzene and pyrrole, constant-force images preserve the molecular framework across a range of adsorption angles and allow the molecular orientation to be recovered quantitatively. For larger non-planar and three-dimensional systems, simulations identify characteristic force-isosurface contrast associated with adsorption geometry, lower-lying molecular structure and curved molecular surfaces. These results provide target contrasts for force isosurfaces that could be extracted from three-dimensional force-mapping experiments, evaluating the molecular information retained by ideal force-isosurface imaging across progressively non-planar systems.

Root-mean-square deviation (RMSD) is the standard metric of structural comparison in molecular dynamics (MD) simulations. In its conventional form, RMSD assigns equal weight to all atoms regardless of mobility. Hence, flexible loops and disordered regions can dominate a global RMSD, while the rigid functional core contributes negligibly to the overall metric. To address this issue, we introduce the Bayes-optimal RMSD (BRMSD), which optimizes per-atom weights jointly with structural averages by maximizing a Bayesian posterior. In a trade-off between low RMSD and weight uniformity, a position-fluctuation parameter $\sigma$ controls the transition from classical RMSD ($\sigma \to \infty$) to a progressive focus on a rigid core ($\sigma \to 0$). The BRMSD framework supports analysis modules for structural alignment, focused alignment onto a user-specified domain, trajectory smoothing, soft $K$-means conformational clustering, and rigid-domain identification. These modules are implemented in the open-source Python package BRMSD (https://github.com/bio-phys/BRMSD) and benchmarked on two MD systems, the endoplasmic reticulum translocon-associated protein SND3 and the phosphotransferase adenylate kinase.

We demonstrate that the balance between polar and positional order can be systematically tuned through molecular engineering, providing direct control over the emergence of polar and modulated liquid-crystalline phases, allowing for versatile strategy for the design of functional ferroelectric soft materials. We show that polar orthogonal smectic phases (SmAF and SmAAF), promoted by the self-segregation of aromatic cores and sufficiently long terminal chains, are readily destabilized by strong longitudinal dipolar interactions that energetically penalize parallel alignment of molecular dipoles within a smectic layer. In contrast, the tilted ferroelectric SmCF phase is remarkably robust across the entire homologous series, indicating that molecular tilt efficiently relieves dipolar frustration within the smectic layers. We further demonstrate that the interplay between microsegregation and electrostatic interactions stabilizes the new modulated SmCM phase, characterized by incommensurate electron-density waves, particularly for compounds with short terminal chains. For longer homologs controlling the spatial distribution of fluorinated molecular fragments and terminal-chain length enabled the targeted formation of broken-layer-type modulated polar phases (2D or 3D).

Motivated by recent experiments showing pressure-induced suppression of magnetic order and the emergence of a dynamical ground state in the anisotropic kagome antiferromagnet Y-kapellasite Y3Cu9(OH)19Cl8, we perform ab initio density functional theory (DFT)calculations to investigate the evolution of magnetic exchange interactions under hydrostatic pressure. We show that pressure efficiently tunes the magnetic Hamiltonian by altering the CuOCu bond geometry, thereby driving the system towards a spin-liquid regime. This evolution is governed by a nonlinear dependence of the dominant exchange coupling on the CuOCu bond angle. We further examine the influence of hydrogen positions and find that both the OH bond length and the hydrogen out-of-plane angle strongly affect the magnetic interactions. Our results provide a microscopic explanation for the experimentally observed pressure-induced enhancement of frustration and highlight the key role of hydrogen geometry.

Graph neural networks have become the dominant machine-learning architecture for predicting materials properties from crystal structures. Yet the initialization of atomic node features has received comparatively little attention, and conventional approaches rely on static elemental descriptors that carry no information about the quantum-mechanical electronic environment of each atom in its crystalline host. Here we show that augmenting atomic node representations with site-projected orbital density of states (pDOS) fingerprints, computed directly from density functional theory calculations, yields systematic and substantial improvements in predictive performance.These representations are fused with Pettifor elemental embeddings at each atomic site before message passing. For the superconducting critical temperature $T_c$ and the optical dielectric constant $\epsilon_{\infty}$,the pDOS augmentation reduces prediction errors by 22.9% and 27.9%, respectively, relative to the elemental-descriptor baseline. These improvements are comparable to those achieved by doubling the training-set size. The gains are, however, contingent on training-set size. For the magnetic exchange energies of Heusler compounds, a substantially smaller dataset, the improvement is reduced,indicating that pDOS augmentation is most effective when the training data exceeds the length of the pDOS feature vector. We introduce an interpretable spectral attention-gating mechanism that reveals that the model autonomously learns to prioritize the orbital channels and energy windows most physically relevant to each target property. These results establish pDOS-augmented graph nodes as a broadly applicable strategy for infusing first-principles electronic-structure knowledge into graph networks, opening a practical route to high-accuracy property prediction in data-scarce regimes.

We experimentally investigate spin-polarized electron transport for the centrosymmetric altermagnet CrSb, which is known to reveal both altermagnetic and topological features. We demonstrate pronounced first-harmonic anomalous and second-harmonic non-linear Hall effects for a single-crystal CrSb flake with ferromagnetic nickel contacts, while both effects can not be seen for the reference samples with non-magnetic gold ones. For the anomalous Hall effect, we demonstrate bow-tie hysteresis loop in Hall voltage, which is usually ascribed to surface spin textures in magnetic materials. The slope of the Hall curve changes a sign for two orientations of the Hall-bar contact configuration for the same sample, i.e. for the same sign of the charge carriers. We interpret the observed sign inversion and bow-tie hysteresis as the joint effect of the alternating bulk spin splitting and spin-polarized topological surface states in CrSb. The pronounced non-linear Hall effect with hysteresis in magnetic field confirms finite Berry curvature dipole under injection of spin-polarized electrons, i.e. the topological features for the altermagnetic candidate CrSb.

The magnetotransport properties of the iron-based ladder compounds BaFe2S3 and BaFe2Se3 under various pressures were investigated. BaFe2S3 had a T^2 dependence in electrical resistivity and a normal magnetoresistance near an insulator-metal transition. Therefore, it had Fermi-liquid-like properties in the normal phase. However, BaFe2Se3 had a T^3/2 dependence in electrical resistivity and a negative magnetoresistance. This suggested that BaFe2Se3 had non-Fermi-liquid properties near the insulator-metal transition. For both materials, the Hall resistivities indicated a hole-dominant magnetic field dependence. During a pressure-induced insulator-metal transition, BaFe2Se3 had a rapid decrease in electrical resistivity above 15 GPa attributed to an isomorphic structural transition previously reported in X-ray diffraction experiments. This transition had a strong impact on the electronic properties.

We study a bulk-driven nonlinear variant of the Kipnis-Marchioro-Presutti model of stochastic energy diffusion in which local collisions are biased to induce a net energy flow, resembling the effect of an external field. Starting from the microscopic master equation, we derive the hydrodynamic description of the driven system via a local equilibrium approximation, obtaining explicit expressions for the energy current and the associated diffusivity and mobility transport coefficients, which are nonlinear functions of the local energy density. We test our findings in kinetic Monte Carlo simulations of the model and, as a proof of concept, we demonstrate the versatility of this driving mechanism to control nonlinear energy transport by inducing time-crystalline phases. In particular, we show that appropriately designed packing fields induce the spontaneous formation of traveling energy condensates, exhibiting robust long-range temporal order reminiscent of continuous time crystals. Our results provide a simple yet powerful framework to study bulk-driven nonlinear energy diffusion in stochastic many-body systems, offering a bridge between microscopic dynamics, macroscopic transport, and controlled spatiotemporal order.

Inverse design - specifying a desired functionality and letting a computational algorithm find the optimal structure - has emerged as a powerful paradigm for magnonic device engineering. In this article, we survey the rapidly growing field of inverse-design magnonics, organising it along two axes: the design variables (topology, material parameters, and magnetic field landscape) and the algorithmic toolbox (gradient-free, gradient-based, and neural-network-based methods) together with the differentiable micromagnetic solvers that enable them. We then identify open frontiers that we consider most promising for the next phase of the field: sensitivity analysis and robust design to bridge the gap between simulation and experiment; input shaping and transducer optimisation; the incorporation of nonlinear spin-wave effects as an explicit design resource; spatially structured amplification; self-adapting media and machine-learning-based design; and the long-term vision of a universal, reconfigurable magnonic platform. We argue that magnonics and artificial intelligence are converging from two directions - machine-learning tools for designing magnonic devices, and magnonic devices as hardware for neuromorphic computation - and propose the term AI magnonics to describe this emerging paradigm.

Based on public data, we analyze the distributions of energy and carbon emission over world countries on a scale of the last 40-50 years using their presentation via Lorenz and Pareto curves. These curves in rescaled format remain remarkably stable on this time period being characterized by high values of the Gini coefficient indicating a strong inequality of energy distribution. To explain these distributions, we introduce the ENergy Thermalization Hypothesis (ENTH) according to which these distributions result from the Rayleigh-Jeans (RJ) thermalization and condensation of agents representing different countries. We show that this hypothesis provides an excellent description of Lorenz and Pareto curves obtained from data on the above time period. It also gives natural grounds for inequality relating it to the RJ condensation at low energy states. We additionally trace parallels with the wealth inequality in the world.

We investigate the magnetotransport properties of the antiferromagnetic metal LaMnSi, in which the collinear magnetic order breaks both spatial inversion (P) and time-reversal (T) symmetry yet preserves their combined PT symmetry. High pressure is found to suppress this PT-symmetric antiferromagnetic phase, inducing a transition into a PT-broken state characterized by a large anomalous Hall effect. Based on symmetry analysis, we propose a candidate magnetic structure for the high-pressure phase. Subsequent band calculations for this structure reveal the emergence of band splitting and orbital-dependent spin polarization. Our results establish LaMnSi as an ideal platform for controlling PT symmetry breaking via external parameters.

We investigate the magnetocaloric properties of a class of centered magnetic molecules that are very similar in their magnetic properties. In particular, we study the magnetocaloric response of these molecules in the space of two exchange parameters and as function of the spin quantum numbers. Major figures of merit such as adiabatic temperature change and isothermal entropy change as well as theoretically achievable low temperatures show that overall ferromagnetic interactions are preferential as long as this does not lead to dipolar ordering.

Altermagnets, which combine antiferromagnetic-like magnetic compensation with ferromagnetic-like broken time-reversal symmetry, hold great promise for high-density and ultrafast spintronic applications. However, the detection and switching of perpendicular altermagnetic order are fundamentally constrained by magnetic symmetry, restricting both fundamental studies and practical implementation. We realize robust electrical reading and deterministic switching of perpendicular altermagnetic order by designing a Dirac semimetal/altermagnet heterostructure of PtTe2/CrSb. This engineered interface enables anomalous Hall readout via altermagnetic proximity effect and delivers efficient spin-orbit torque for manipulating the epitaxial perpendicular Neel vector in CrSb. These findings significantly broaden the functional scope of altermagnetic heterostructures and pave the way for highly scalable altermagnetic memory.

A topotactic phase transition involves the transformation of one crystalline solid to another, which may include the loss or gain of material, where the orientation of the parent crystal determines the orientation of the daughter. We set out an experimental approach, based on polyepitaxial thin film deposition, where the precise transformation mechanism in important physico-chemical processes can be revealed in brilliant detail. Here, we find a reversible topotactic transition from (001) cubic UO2 to a (130) orthorhombic U3O8 structure; a >35% expansion/contraction. This remarkable result solves a puzzle that has eluded researchers for decades, and presents a method for determining the mechanism of crystallographic transformation in many other compounds.

This study presents a multi-fidelity framework for the systematic optimization of genetic algorithm (GA) hyperparameters. The framework integrates three fidelity levels: high-fidelity Fast Fourier Transform (FFT) homogenization for validation, a medium-fidelity 3D convolutional neural network surrogate for rapid property evaluation, and a low-fidelity Gaussian process (GP) surrogate within a Bayesian optimization (BO) framework to guide the hyperparameter search. Various acquisition functions are evaluated, with logNEI achieving the best performance by effectively accounting for the noise inherent in GA evaluations. The proposed framework identifies hyperparameter configurations that enable a 25-generation GA run to achieve elastic modulus values comparable to those obtained in a full 75-generation optimization. Furthermore, introducing a penalized BO objective significantly reduces the number of required lattices with only minor decreases in absolute achieved elastic modulus, revealing a practical trade-off between performance and the number of structures that must be evaluated. High-fidelity FFT validation verifies the effectiveness of the surrogate-driven optimization strategy. The optimized hyperparameters allow for rapid convergence, eliminate the need for lattice mutation, and reduce the overall computational cost by 24% (from 225 to 171 hours) while preserving mechanical performance. These results demonstrate the potential of multi-fidelity optimization as an efficient and practical approach for GA hyperparameter tuning and future experimental lattice design studies.

Porous gallium nitride (GaN) is a mesoporous crystalline material, typically in the form of a thin film on an unlike substrate, prepared by electrochemically etching conductive GaN. The use of porous GaN in electronics and optoelectronics is rapidly expanding, but is held back significantly by a lack of structural control and understanding of the principles of pore formation from underlying electrochemical mechanisms, where high-quality characterisation of pore morphology is essential to understanding these principles. Focused ion beam (FIB) tomography is an invaluable tool for such characterisation, but is hindered greatly by the pore back effect, where unwanted contrast appears in an image due to electrons scattering out from the back wall of a pore. No major attempts to formally quantify or assess the extent of the effect for different tomography experiments has been demonstrated. In this work, we demonstrate an advanced methodology for performing FIB tomography on porous GaN thin films, where the experiment is rotated to image pores perpendicular to the surface of the sample, and introduce new voxel intensity-based formalisms for assessing the impact of the pore back effect based on voxel intensities for individual features and the whole dataset. The new approach, which requires more complex preliminary setup, is found to significantly mitigate the pore back effect in porous GaN thin films with a range of pore morphologies without increasing the total experimental duration. The pore back effect can thus be quantified and mitigated in FIB tomography of porous GaN and similar mesoporous thin films.

The deconfined quantum critical point (DQCP) in square lattice S=1/2 quantum antiferromagnets has been extensively studied with a large body of evidence pointing to a weakly first-order transition scenario. Recent studies, which focused on entanglement at this nearly continuous DQCP in square lattice J-Q models, have observed conflicting bipartite entanglement entropy (EE) scaling behavior. One bipartition choice gave scaling coefficients in remarkable agreement with predictions from the unitary CFT corresponding to the putative DQCP. While another equally natural choice gave scaling coefficients in complete violation of unitary CFT that may be attributed to lack of scale invariance at the known weakly first-order behavior of the model. This motivates the exploration of DQCP behavior via entanglement measures in lattice models with distinct crystalline symmetries. Here we study a S=1/2 honeycomb model that hosts a nearly continuous transition between Néel and valence-bond-solid ground states relevant to probing DQCP. Using large-scale quantum Monte Carlo simulations, we compute the Rényi EE for a variety of bipartitions and test the CFT based description of the DQCP on the honeycomb lattice. For smooth bipartitions, we find no evidence of logarithmic corrections, in accordance with CFT, thereby essentially ruling out contributions from Goldstone modes. For subsystems with corners, CFT predicts universal logarithmic contributions, which we extract for corners with 60 and 120 degree angles and find close agreement with an emergent SO(5) CFT. While we observe scaling consistent with a critical system in the majority of cases, we also demonstrate an intriguing counterexample of the hexagon subsystem that exhibits a subtle period three oscillation. This results in three separate finite-size series, where the sign of the logarithmic term apparently changes depending on the series.

We predict a class of bound states in the continuum (BICs) in non-subwavelength periodic metasurfaces – Rayleigh BICs – that emerge precisely at Rayleigh anomalies, where diffraction channels open. In contrast to conventional symmetry-protected and accidental BICs, which are typically engineered in the subwavelength regime with only a few radiation channels, Rayleigh BICs remain nonradiating far beyond this limit, even when multiple diffraction channels are open. Their formation originates from the interplay between collective lattice resonances, Rayleigh anomalies, and anapole states of the constituent metaatoms. We show that Rayleigh BICs are characterized by an unusual cubic scaling of the quality factor in reciprocal space, ($Q \propto 1/k^3$), an asymptotic behavior that is not characteristic of either symmetry-protected or accidental BICs. Our results establish a constructive route for engineering nonradiating states in metasurfaces beyond the subwavelength regime.

The quantum boomerang effect (QBE) is a unique dynamical signature of Anderson localization, characterized by a launched wavepacket that initially drifts but ultimately returns to its initial position due to fundamental quantum interference. In this work, we theoretically establish and quantitatively characterize the QBE in a time-crystalline structure using a periodically driven quantum particle in a one-dimensional potential well. By constructing maximally localized Floquet-Wannier states and introducing temporal disorder, we rigorously map the continuous Floquet dynamics onto a discrete disordered tight-binding lattice. By positioning a detector at a fixed spatial coordinate, we monitor the temporal evolution of the wavepacket, to extract the mean temporal center of mass of the probability density in a time-crystalline structure. This mean temporal center of mass exhibits an initial ballistic expansion, followed by a pronounced U-turn, and ultimately returns to its initial temporal position after long-time evolution. These results confirm the existence of the complete QBE in the time domain. They also demonstrate that non-trivial dynamics can be explored within time-crystalline systems, even though these structures already possess an inherent temporal periodicity.

Electromagnetic waves are intrinsically vectorial and require description via polarization, unlike scalar fields such as acoustic pressure or electronic wavefunctions. In three dimensions, the transversality constraint further prevents any globally smooth transverse-polarization frame at the $\Gamma$ point, which would apparently rule out a simple scalar band structure for three-dimensional (3D) photonic crystals. We show here that site-adapted $p$-orbitals can realize scalar-wave dispersion: the induced band representation is isomorphic to the scalar elementary band representation up to a one-dimensional character twist, so the symmetry-enforced degeneracies and compatibility relations are the same. We demonstrate this mechanism experimentally in 3D photonic meta-crystals, where the local $p$-orbital axes adapt from site to site according to symmetry. In contrast to a fixed-polarization reduction (e.g., in 2D), our construction preserves site-polarization textures while simultaneously supporting a scalar network with one amplitude per site. Thus, it offers a pathway from vectorial photonic degrees of freedom to scalar band engineering, keeping polarization as an active design knob.

Molecular passivation has become central to reducing photovoltage losses in metal-halide perovskite solar cells, but its electronic action is still often inferred from device-level metrics rather than directly resolved at the nanoscale. Here, we use amplitude-modulated Kelvin probe force microscopy to examine how [3-(2-aminoethylamino)propyl]trimethoxysilane (AEAPTMS) modifies the surface potential and photovoltage dynamics of mixed-cation, mixed-halide perovskite thin films. AEAPTMS homogenises the dark contact potential difference (CPD), narrowing its distribution from ~45.7 to ~14.6 mV without obvious morphological changes. Under illumination, passivated films show a larger steady-state surface photovoltage (SPV) and faster stabilisation, with the SPV increasing from ~345 to ~417 mV and the stabilisation time constant decreasing from ~840 to ~470 s. Wavelength-dependent SPV further indicates reduced sub-bandgap electronic disorder. By separating grain-boundary and grain-interior contributions, we show that AEAPTMS suppresses grain-boundary potential barriers, linking amino-silane passivation to a more homogeneous and stable carrier landscape.

We demonstrate microsecond-timescale electrical control of the terahertz (THz) emission phase in broadband field-free spintronic THz emitters, enabling megahertz-rate phase inversion while overcoming the kilohertz limitations of conventional mechanical and field-driven approaches. Our device integrates an H-dipole antenna with a spintronic heterostructure exhibiting uniaxial magnetic anisotropy, enabling deterministic spin-orbit torque induced in-plane magnetization switching without external magnetic fields. The corresponding THz phase inversion is directly observed in the time domain signal, by applying $1\,\mu \mathrm{s}$ electrical pulses on the bias striplines of the H-dipole. This field-free operation reduces system complexity while significantly extending modulation bandwidth. Our results establish electrically programmable spintronic THz emitters that could be used to develop a compact and scalable platform for integrated on-chip THz devices and ultrafast applications, including phase-sensitive spectroscopy and near-field imaging, where high-speed and precise control of THz waveforms is essential.