Papers

Collective dynamics in proliferating anisotropic particle systems arise from an interplay between growth, division, and mechanical interactions, often mediated by particle shape. In classical models of prolate, rod-like growth, flow-induced alignment and division geometry reinforce one another, leading to robust nematic order under confinement. Here we introduce a complementary regime by considering smooth convex particles whose geometry can be oblate for part or all of their growth cycle, creating a tunable competition between these two alignment mechanisms. Using agent-based simulations of elliptical and rounded-rectangular particles in both channel and open-domain geometries, we systematically vary the division aspect ratio to span regimes of cooperation and competition between ordering cues. We find that oblate growth can reverse classical flow-alignment, destabilize microdomain formation in intermediate regimes, and open up new regimes with modified microdomain dynamics in free expansion and sustained orientation dynamics in channel geometry. These findings are explained by an order- and shape-dependent mechanical relaxation interpretation that is supported by explicit measurements. This sheds new light on the available relaxation pathways and therefore provides key ingredients for effective descriptions of collective anisotropic proliferation dynamics.

The ability to measure the stochastic degrees of freedom of a thermal system enables the extraction of energy from an equilibrium heat bath. This is the underlying principle of Maxwell's demon and subsequent information engines. Here, we experimentally realize a microscopic information engine configured as a compressible piston containing a thermalized colloidal suspension. The particle positions are recorded to identify when a predefined region near the wall is empty, allowing the piston to compress the colloidal suspension without applying work on the system. We find that the stored compression energy is universally set by the probability of a positive measurement outcome, which in turn is controlled by parameters such as density and compression step size. We further demonstrate that mechanical work can be extracted during the decompression of the piston, thereby closing the engine's operating cycle.

A common approach to quantify excess dissipation in slowly driven thermodynamic processes is through the use of a Riemannian metric on the space of control parameters, where optimal driving protocols follow geodesics. Near phase transitions, this geometric picture breaks down as the metric diverges and geodesics may cease to exist. Using Widom scaling, we analyze this framework for several universality classes and show that in some cases the thermodynamic length across the phase transition remains finite. We then demonstrate a numerical approach for computing minimal paths in such systems. We show that, in some regimes, the shortest path crosses the phase transition - even when alternative paths confined to a single phase exist.

Complex concentrated alloys with intrinsic chemical heterogeneity are promising candidates for nuclear applications, where local chemical order can strongly influence defect evolution under irradiation. Grain boundaries also contribute to radiation damage mitigation by serving as defect sinks, yet this interaction can alter interfacial structure, typically leading to destabilization and grain growth. This study investigates how chemical ordering influences grain boundary migration and stability during successive radiation events in CrCoNi. Using atomistic simulations, bicrystals were equilibrated to induce segregation-enhanced chemical order, followed by prolonged irradiation at 1100 K. Our results show that grain boundaries in random CrCoNi begin to migrate after only a few collision cascades, whereas those in the ordered alloy remain immobile until the chemical order is sufficiently disrupted. Single-cascade simulations reveal key mechanistic differences, where cascades near chemically ordered interfaces produce smaller damage volumes and reduced atomic displacement due to enhanced Frenkel pair combination within the cascade core. This limits both the residual defect population and the energetic driving force for interfacial rearrangement. Subsequent simulations of irradiated interfaces show that interstitial absorption induces a structural transition that modifies the segregation morphology at and near the grain boundary, demonstrating a dynamic coupling between ordering stability and defect evolution. These findings offer new insights into the role of local chemical order on defect-interface interactions under extreme conditions and highlight pathways for designing radiation-tolerant materials for next-generation nuclear systems.

Ising superconductors have attracted significant attention recently due to their resilience against magnetic fields far beyond the Pauli-paramagnetic limit as well as their broader role as a platform for exploring the interplay of spin-orbit coupling, valley degrees of freedom and superconducting pairing in two-dimensional materials. Their protection against external magnetic field relies on strong Ising spin-orbit coupling, which originates from in-plane inversion symmetry breaking. Due to the heavy atom nature of Ising SCs, a smaller but sizable Rashba SOC can arise from gating or interfacial effects. Here, we study Rashba spin-orbit coupling within a two-valley model of Ising superconductors with an attractive $s$-wave interaction. We show that Rashba SOC induces a first order quantum phase transition in Ising superconductors. At low temperatures, this means the superconducting order parameter vanishes abruptly in the vicinity of the quantum critical point. This effect, however, disappears at high temperatures. Our findings demonstrate that the low- and high temperature physics of Ising SCs are quantitatively and qualitatively different in the two-valley model.

Boron aluminum nitride (B$_x$Al$_{1-x}$N) is a promising material for next-generation electronic and optoelectronic devices due to its ultra-wide bandgap, high thermal stability, and compatibility with other III-nitride semiconductors. Despite its potential, the band alignments of B$_x$Al$_{1-x}$N remain largely unexplored, although this information is essential for device design. In this study, we compute the valence and conduction band alignments of nonpolar ($a$-plane) and polar ($c$-plane) B$_x$Al$_{1-x}$N, and compare them with those of AlN and GaN. Using density functional theory, many-body perturbation theory, $GW_0$ method, and a novel passivation scheme, we find that they have near-zero valence band alignments for low-$x$ B$_x$Al$_{1-x}$N/AlN, while higher compositions ($x > $0.333) exhibit type I or II band alignments. The band alignments also show a notable dependence on surface polarity and the tetrahedral distortion of the B$_x$Al$_{1-x}$N structures. Our computed offsets are in good agreement with available experimental data. Due to their low valence band alignments and higher conduction band alignments, the B$_x$Al$_{1-x}$N/AlN heterostructures could be well suited for high-electron-mobility transistors and ultraviolet light-emitting diodes. The band alignments of B$_x$Al$_{1-x}$N determined in this study provide essential design guidelines for integrating these ultra-wide bandgap alloys into advanced semiconductor technologies.

Active turbulence in overdamped chiral systems presents a complex challenge, namely the frequent exhibition of non-universal spectral scaling, creating large-scale coherent structuring that seemingly defies standard inertial fluid descriptions. In this study, we investigate the hydrodynamic limit of a two-dimensional polar chiral active fluid modeled as an ensemble of locally coupled, motile Kuramoto-Sakaguchi oscillators. By introducing a Renormalised Fluid Element (RFE) operator, we coarse-grain microscopic phase singularities, and in so doing, we isolate the macroscopic transport dynamics. We demonstrate that while the raw particle distributions consistently exhibit steep, dissipative energy spectra, associated with enstrophy injection at the microscale, the RFE-filtered field reveals a dual behaviour characterized by an inverse energy cascade. When the intrinsic frequency dispersion, drawn from a scale-free power-law distribution, is broad enough to seed fluctuations at all resolved scales, this hidden cascade acts akin to a topological heat pump, driving the system toward a state of macroscopic vortex clustering, structurally analogous to supersonic shallow water dynamics. Conversely, a narrow frequency dispersion results in kinetic arrest, forming an active vortex glass. These results suggest that overdamped phase-slaved active matter can sustain effective inertial cascades, providing a mathematical framework for understanding scale-dependent energy transport in driven chiral systems.

Spontaneous parametric downconversion (SPDC) and four-wave mixing in $\chi^{(2)}$ and $\chi^{(3)}$ media underpin most entangled-photon sources, but direct generation of higher-order entangled multiphoton states by $n$-th order parametric downconversion remains extremely challenging because conventional materials exhibit tiny high-order nonlinearities. Here we show that single-layer Nb$_3$Cl$_8$, an excitonic Mott insulator on a breathing Kagome lattice, supports exceptionally large nonlinear susceptibilities up to seventh order. Many-body GW–Bethe–Salpeter and time-dependent BSE / Kadanoff–Baym simulations yield resonant $\chi^{(2)}$–$\chi^{(7)}$ for monolayer Nb$_3$Cl$_8$, with $|\chi^{(4)}|$ and $|\chi^{(5)}|$ surpassing values in prototypical transition metal dichalcogenides by 5–9 orders of magnitude. We trace this enhancement to flat bands and strongly bound Frenkel excitons with ferroelectrically aligned out-of-plane dipoles. Building on experimentally demonstrated 1$\times N$ integrated beam splitters with arbitrary power ratios, we propose an on-chip architecture where each output arm hosts an Nb$_3$Cl$_8$ patch, optionally gated by graphene to tune the complex $n$-photon amplitudes. Using the ab-initio $\chi^{(3)}$ and $\chi^{(4)}$ values, we predict that three-photon GHZ$_3$ and four-photon cluster-state sources in this platform can achieve $n$-photon generation rates up to $\sim 10^8$ and $\sim 10^6$ times larger, respectively, than silica-fiber- and MoS$_2$-based implementations with comparable geometry. We derive the quantum Hamiltonian and explicit $n$-photon generation rates for this platform, and show how suitable interferometric networks enable electrically and spectrally tunable GHZ, $W$, and cluster states based on genuine high-order nonlinear processes in a 2D excitonic Mott insulator.

We develop an interpretable, data-driven framework to quantify how single-particle band geometry governs the stability of fractional Chern insulators (FCIs). Using large-scale exact diagonalization, we evaluate an FCI metric that yields a continuous spectral measure of FCI stability across parameter space. We then train Kolmogorov-Arnold networks (KANs) – a recently developed interpretable neural architecture – to regress this metric from two band-geometric descriptors: the trace violation $T$ and the Berry curvature fluctuations $\sigma_B$. Applied to spinless fermions at filling $\nu=1/3$ in models on the checkerboard and kagome lattices, our approach yields compact analytical formulas that predict FCI stability with over $>80 \%$ accuracy in both regression and classification tasks, and remain reliable even in data-scarce regimes. The learned relations reveal model-dependent trends, clarifying the limits of Landau-level-mimicking heuristics. Our framework provides a general method for extracting simple, phenomenological "laws" that connect many-body phase stability to chosen physical descriptors, enabling rapid hypothesis formation and targeted design of quantum phases.

We study whether a transformer network can learn the deterministic sequence of trees generated by the iterated prime factorization of the natural numbers. Each integer is mapped into a rooted planar tree and the resulting sequence $\mathbb{N}\mathscr{T}$ defines an arithmetic text with measurable statistical structure. A transformer network (the GPT-2 architecture) is trained from scratch on the first $10^{11}$ elements and evaluated on next-token prediction and masked-token prediction tasks, with a Hidden Markov Model as baseline and a scaling analysis over context window, dataset size, vocabulary size and model size. The model reaches a word accuracy of about $0.4$, well above the baseline, and its performance remains stable on test blocks located at $10^{13}$-$10^{15}$, far beyond the training interval. Moreover, the likelihood assigned by the trained model separates the arithmetic text from two controls: synthetic token sequences that preserve the marginal token frequencies but not their order, with a separation that widens with the context, and sequences containing more than three consecutive square-free integers, a configuration that arithmetic forbids. These results indicate that the transformer captures regularities of the arithmetic text that go beyond its frequency profile.

The antiferromagnetic Heisenberg spin chain remains a central framework for exploring exactly solvable models within quantum integrable systems. For the isotropic XXX chain, the ground-state energy per site of the spin-1/2 system is famously given by ln2. Extending the classic formulations to arbitrary spin-s, Takhtajan and Babujian derived two separate finite-series expressions for integer and half-integer spin representations. Current work introduces a unified analytical expression for the ground-state energy density in terms of the digamma function. This compact formulation reproduces both Takhtajan Babujian series.

Ionic fluids under conductive confinement are central to technologies such as batteries, supercapacitors, and fuel cells. Their interfacial behavior governs energy storage and electrochemical processes. Despite their importance, the thermodynamics of even simple models – such as the charged Lennard-Jones fluid – remain underexplored in this regime. We present an extended Wang-Landau sampling approach to efficiently compute the density of states of charged mixtures with respect to the particle number. The method supports simulations in both bulk and confined geometries. Combined with the Constant Potential Method, it also enables to study effects due to confining electrodes. We employ this approach to study symmetric, binary mixtures of charged Lennard-Jones particles – the modified Restricted Primitive Model – in bulk, in inert confinement, and in conductive confinement at the potential of zero charge. Our results show that confinement shifts the vapor-liquid critical point to lower temperatures and higher densities compared to bulk, in line with the classical concept of capillary condensation. Importantly, conductive boundaries significantly lower the chemical potential of coexistence relative to inert confinement. These findings offer deeper insight into the phase behavior of ionic fluids in energy-relevant porous environments.

Topologically ordered states are among the most interesting quantum phases of matter that host emergent quasi-particles having fractional charge and obeying fractional quantum statistics. Theoretical study of such states is however challenging owing to their strong-coupling nature that prevents conventional mean-field treatment. Here, we demonstrate that an attention-based deep neural network provides an expressive variational wavefunction that discovers fractional Chern insulator ground states purely through energy minimization without prior knowledge and achieves remarkable accuracy. We introduce an efficient method to extract ground state topological degeneracy – a hallmark of topological order – from a single optimized real-space wavefunction in translation-invariant systems by decomposing it into different many-body momentum sectors. Our results establish neural network variational Monte Carlo as a versatile tool for discovering strongly correlated topological phases.

A central challenge in machine learning is to distinguish genuine structure from chance correlations in high-dimensional data. In this work, we address this issue for the perceptron, a foundational model of neural computation. Specifically, we investigate the relationship between the pattern load $\alpha$ and the variable selection ratio $\rho$ for which a simple perceptron can perfectly classify $P = \alpha N$ random patterns by optimally selecting $M = \rho N$ variables out of $N$ variables. While the Cover–Gardner theory establishes that a random subset of $\rho N$ dimensions can separate $\alpha N$ random patterns if and only if $\alpha < 2\rho$, we demonstrate that optimal variable selection can surpass this bound by developing a method, based on the replica method from statistical mechanics, for enumerating the combinations of variables that enable perfect pattern classification. This not only provides a quantitative criterion for distinguishing true structure in the data from spurious regularities, but also yields the storage capacity of associative memory models with sparse asymmetric couplings.

We consider coherently-coupled bosonic mixtures scattering at low energies in the presence of an external confinement along either one or two directions. We exactly solve the two-body scattering problem, showing that for large Rabi coupling the confinement-induced resonance can be displaced towards scattering lengths values much smaller than the oscillator length. Our results make the observation of confinement-induced resonances more tunable and accessible, offering yet another handle for the efficient control of strong interactions in ultracold quantum gases.

Increasing integration scale of superconductor electronics (SCE) requires employing kinetic inductors and self-shunted Josephson junctions (JJs) for miniaturizing inductors and JJs. We have been developing a ten-superconductor-layer planarized fabrication process with NbN kinetic inductors and searching for suitable self-shunted JJs to potentially replace high Josephson critical current density, Jc, Nb/Al-AlOx/Nb junctions. We report on the fabrication and electrical properties of NbN/NbNx/NbN junctions produced by reactive sputtering in Ar+N2 mixture on 200-mm wafers at 200 oC and incorporated into a planarized process with two Nb ground planes and Nb wiring layer. Here NbN is a stoichiometric nitride with superconducting critical temperature Tc =15 K and NbNx is a high resistivity, nonsuperconducting nitride deposited using a higher nitrogen partial pressure than for the NbN electrodes. For comparison, we co-fabricated Nb/NbNx/Nb JJs using the same NbNx barriers deposited at 20 oC. We varied the NbNx barrier thickness from 5 nm to 20 nm, resulting in the range of Jc from about 1 mA/um^2 down to ~10 uA/um^2, and extracted coherence length of 3 nm and 4 nm in NbNx deposited, respectively at 20 oC and 200 oC. Both types of JJs are well described by resistively and capacitively shunted junction model without any excess current. We found the Jc of NbN/NbNx/NbN JJs to be somewhat lower than of Nb/NbNx/Nb JJs with the same barrier thickness, despite a much higher Tc and energy gap of NbN than of Nb electrodes. IcRn products up to ~ 0.5 mV were obtained for JJs with Jc~ 0.6 mA/um^2. Jc(T) dependences have been measured.

The problem of a mobile hole doped into an antiferromagnet Mott insulator is believed to underly the rich physics of several paradigmatic strongly correlated electron systems, ranging from heavy fermions to high-Tc superconductivity. Arguably the simplest incarnation of this problem corresponds to a doped Ising antiferromagnet, a problem widely considered essentially solved since almost 60 years by a popular yet approximate mapping to a single-particle problem on the Bethe lattice. Here we show that, despite its deceptive simplicity, the local spectrum of a single hole in a classical Ising-Néel state contains a series of anomalous, long-lived states that go beyond the well-known ladder-like spectrum with excited energies spaced as $J^{2/3} t^{1/3}$. The anomalous states we find through exact diagonalization and within the self-avoiding path approximation have excitation energies scaling approximately linear with $J$ and lead to a series of avoided crossings with the more pronounced ladder spectrum. By also computing different local, rotational spectra we explain the origin of the anomalous states as rooted in an approximate emergent local $C_3$ symmetry of the problem. From their direct spectral signatures we further conclude that these states lead to anomalously slow thermalization behavior – hence representing a new type of quantum many-body scar state, potentially related to many-body scars predicted in lattice gauge theories.

The prospect of merging the paradigms of geometric frustration on a triangular lattice and bond anisotropies in the strong spin-orbit coupling limit holds tremendous promise in the ongoing hunt for exotic quantum materials. Here we identify a new candidate system to realize such physics, the organic quantum antiferromagnet (CD$_3$ND$_3$)$_2$NaRuCl$_6$. We report a combination of thermodynamic, magneto-elastic and neutron scattering experiments on single-crystals to determine the phase diagram in axial magnetic fields $\mathbf{H \parallel c}$ and propose a minimal model Hamiltonian. (CD$_3$ND$_3$)$_2$NaRuCl$_6$ displays an ideal triangular arrangement of Ru$^{3+}$ ions adopting the spin-orbital entangled $j_{\rm eff} = 1/2$ state. It hosts residual magnetic order below $T_{\rm N} = 0.23$ K and a highly unusual $H-T$ phase diagram including three different incommensurate states. Spin-waves in the high-field polarized regime are well described by a Heisenberg-like triangular lattice Hamiltonian with a potential sub-leading bond dependent anisotropy term $J_{\pm\pm}$. We discuss possible candidate magnetic structures in the various observed phases and propose two mechanisms that could explain the field-dependent incommensurability, requiring either a small ferromagnetic Kitaev term or a tiny magneto-elastic $J-J'$ isosceles distortion driven by pseudospin-lattice coupling. We argue that the multi-$\mathbf{q}$ ground state in zero magnetic field is a prime candidate for hosting the $\mathbb{Z}_2$ vortex crystal proposed on the triangular Heisenberg-Kitaev model. (CD$_3$ND$_3$)$_2$NaRuCl$_6$ is the first member in an extended family of quantum triangular lattice magnets, providing a new playground to study the interplay of geometric frustration and spin-orbit effects.

We explore, both analytically and numerically, the quantum dynamics of a many-body free-fermion system subjected to local density measurements. We begin by extending the mapping to the nonlinear sigma-model (NLSM) field theory for the case of finite evolution time $T$ and different classes of initial states, which lead to different NLSM boundary conditions. The analytical formalism is then used to study how quantum correlations gradually develop, with increasing $T$, from those determined by the initial state towards their steady-state form. The analytical results are confirmed by numerical simulations for several types of initial states. We further consider the long-time limit, when the system in $d+1$ space-time dimensions becomes quasi-one-dimensional, and analyze the scaling of the “localization” time (which is simultaneously the purification time and the charge-sharpening time for this class of problems). The analytical predictions for scaling properties are fully confirmed by numerical simulations in a $d=2$ model around the measurement-induced phase transition. We use this dynamical approach to determine numerically the measurement-induced transition point and the associated correlation-length critical exponent.

The non Hermitian skin effect, where bulk states accumulate at system boundaries, challenges the conventional bulk boundary correspondence. Here we propose a scheme to realize hybrid skin topological states in exciton polariton honeycomb lattices by introducing sublattice dependent gain and loss. This non Hermiticity couples with the intrinsic topological edge modes, leading to relocalization of edge states. We show two distinct regimes: hybrid skin Chern states with switchable localization controlled by TE TM splitting , and hybrid skin antichiral states which preserves the spin polarized property. Our results bridge polariton spin physics and non-Hermitian topology, opening routes toward controllable non reciprocal and spin polarized transport.

We study tribological granite-granite contacts as a model for tectonic faulting, combining experiments, theory, and molecular dynamics simulations. The high friction in this system is not dominated by particulate wear or plowing, as frequently assumed, but by cold welding within plastically deformed asperity junctions. We base this conclusion on the observation that wear is repeatedly high after cleaning contacts but decreases as gouge accumulates, while friction shows the opposite trend. Moreover, adding water reduces wear by a factor of ten but barely decreases friction. Thermal and rate-dependent effects-central to most earthquake models-are negligible: friction remains unchanged between -40{\deg}C and 20{\deg}C, across abrupt velocity steps, and after hours of stationary contact. The absence of rate-state effects in our macroscopic samples is rationalized by the scale-dependence of pre-slip. The evolution of surface topography shows that quartz grains become locally smooth, with height spectra isotropic for wavelength below 10 microns but anisotropic at longer wavelengths, similar to natural faults. The resulting gouge particles have the usual characteristic sizes near 100 nm. Molecular dynamics simulations of a rigid, amorphous silica tip sliding on {\alpha}-quartz reproduce not only similar friction coefficients near unity but also other experimentally observed features, including stress-introduced transitions to phases observed in post-mortem faults, as well as theoretical estimates of local flash temperatures. Additionally, they reveal a marked decrease of interfacial shear strength above 600{\deg}C.

Mofasa is an all-atom latent diffusion model with state-of-the-art performance for generating Metal-Organic Frameworks (MOFs). These are highly porous crystalline materials used to harvest water from desert air, capture carbon dioxide, store toxic gases and catalyse chemical reactions. In recognition of their value, the development of MOFs recently received a Nobel Prize in Chemistry. In many ways, MOFs are well-suited for exploiting generative models in chemistry: they are rationally-designable materials with a large combinatorial design space and strong structure-property couplings. And yet, to date, a high performance generative model has been lacking. To fill this gap, we introduce Mofasa, a general-purpose latent diffusion model that jointly samples positions, atom-types and lattice vectors for systems as large as 500 atoms. Mofasa avoids handcrafted assembly algorithms common in the literature, unlocking the simultaneous discovery of metal nodes, linkers and topologies. To help the scientific community build on our work, we release MofasaDB, an annotated library of hundreds of thousands of sampled MOF structures, along with a user-friendly web interface for search and discovery: https://mofux.ai/ .

Measuring the electron neutrino mass is a long-standing objective and requires a high energy resolution of certain $\beta$-decay experiments, as well as a visible cosmic neutrino background (C$\nu$B) spectrum. Many quantum mechanical and chemical effects could potentially impair the required resolution/visibility, e.g., the Coulomb interactions between the electrons in the $\beta$-decaying impurity and in the solid-state environment. We analyze the effect when hybridization is suppressed completely using a dielectric spacer, and also when hybridization is present up to the lowest nontrivial order in perturbation theory.

Transition metal dichalcogenides (TMDs) have emerged as a promising class of materials for spintronics, with the aim of promoting efficient spin-charge conversion (SCC) in TMD/ferromagnet (FM)-based devices. The MoTe$_2$ semimetal with distorted orthorhombic crystal structure in the 1T$'$ phase has gathered particular attention due to its high spin-orbit coupling and reconfigurability as a type-II Weyl semimetal close to room temperature. Here, we report on the role of chemically grown 1T$'$-MoTe$_2$ thin films in inducing SCC in 1T$'$-MoTe$_2$/FM heterostructures as measured at room temperature. Ferromagnetic resonance (FMR) and electrically detected spin-pumping FMR measurements performed on 1T$'$-MoTe$_2$/Co/Au and 1T$'$-MoTe$_2$/Au/Co/Au heterostructures reveal a spin-mixing conductance value of up to $\sim1.6 \times 10^{20}~\mathrm{m^{-2}}$ and a spin Hall angle of $1.7\%$. These findings position MoTe$_2$ thin films as a competitive spin-charge conversion option compared to other functional materials (e.g., heavy metals, topological insulators), highlighting their potential for future applications in spintronic devices.

We report in-situ synthesis of iron oxide particles inside silicon nitride nanopores via a chemical reaction, monitored by current readout. Nanopores were formed by electroporation on glass chips (diameters from 1.7 to 11.3 nm), transmission electron microscopy (TEM) drilling (diameters from 6.5 to 64.6 nm), or hydrofluoric acid (HF) etching (diameters from 12.6 to 36.2 nm) in 5 to 20 nm thick membranes. Nanopores seal on timescales from ~1 ms to ~3.6 s, across a range of sizes and concentrations. We show single and ~5-pore arrays, as fabricated, after sealing, and after cleaning and pore recovery. These results are independent of fabrication method. Energy dispersive X-ray spectroscopy (EDS), aberration-corrected scanning TEM (AC-STEM), and powder X-ray diffraction (XRD) verify the synthesis of mixed magnetite and maghemite iron oxide. This work advances nanoparticle-nanopore chips for applications in biosensing, plasmonics and photonics when position and size control is required.

Recent results show remarkable interfacial–Dzyaloshinskii–Moriya interaction (i-DMI) in magnetic heterostructures composed of relatively thick Fe thin films ($\gg 1$ nm). To investigate its origin, we present a thorough magnetic characterization of the SiO$_2$/${}^{57}\mathrm{Fe}$($t$)/Au and SiO$_2$/Pt/${}^{57}\mathrm{Fe}$($t$)/Au heterostructures ($t = 1.6$ - $2.2$ nm). An i-DMI constant of $D_s^{\mathrm{Pt}} = 0.43\,\mathrm{mJ\,m^{-2}}$ is extracted for the Pt/Fe/Au system, as probed by wavevector-resolved Brillouin light scattering spectroscopy. Ferromagnetic resonance and conversion electron Mössbauer spectroscopy indicate that significant surface anisotropy is present in Pt/Fe/Au, and that an interfacial Fe fraction ($\sim18$) exhibits tilted magnetization ($\sim25^\circ$ out of plane) and an enhanced hyperfine field, correlating with the stronger i-DMI.

The interpretation of high-harmonic generation (HHG) in solids typically relies on phenomenological dephasing times far shorter than what is expected from microscopic scattering processes. Here we show that zero-point fluctuations associated with optical phonons naturally suppress long-range electronic coherences and generate clean harmonic spectra without introducing ad-hoc decoherence parameters. Using a 1D semiconductor composed of two distinct sites per unit cell and realistic phonon amplitudes, we demonstrate that random per-site optical-phonon jitter reproduces the spectral sharpening typically attributed to ultrafast $T_2$ dephasing. In contrast, acoustic phonons and local strain, whose distortions are correlated over nanometer scales, produce negligible spectral cleaning. We further show that such long-range site coherence leads to carrier-envelope-phase-dependent effects in the HHG spectrum driven by long pulses, but these effects collapse once optical-phonon-induced decoherence is included. Our results (i) identify optical zero-point motion as a key mechanism governing coherence in solid-state HHG, (ii) demonstrate that it can be qualitatively modeled in periodic solids through site-distance-dependent dephasing, and (iii) suggest that CEP-resolved measurements can probe electronic coherence lengths and atomic fluctuations in crystalline materials.

Using high-resolution scanning tunneling microscopy, we reveal two distinct types of superconducting (SC) gap modulations in bulk superconductor FeTe$_{0.55}$Se$_{0.45}$. By analyzing the phase relation between modulations at positive and negative bias, we identify in-phase (particle-hole asymmetric) and anti-phase (particle-hole symmetric) oscillations, corresponding to sign-reversing and sign-preserving scattering processes, respectively. The observed features are consistent with predictions from pair-breaking scattering interference (PBSI) theory and are distinguishable from other alternative mechanisms such as pair density waves. Our results provide compelling evidence that PBSI is the dominant mechanism behind the SC gap modulations in FeTe$_{0.55}$Se$_{0.45}$, offering new insights into the role of impurity scattering in iron-based superconductors.

The formation of permanent laser-induced periodic surface structures (LIPSS) on solid surfaces under impulsive laser irradiation above the damage threshold has been subject of extensive research. We demonstrate the formation of transient surface displacement patterns under femtosecond laser irradiation at fluences well below this threshold. Time-resolved extreme ultraviolet scattering measurements reveal distinct reciprocal-space features similar to those observed for permanent LIPSS but dissipating on the hundreds-of-picoseconds time scale. We show that the transient surface displacement patterns responsible for these features are produced via thermal expansion by the spatial modulation of absorbed laser intensity caused by scattering of the laser radiation by surface roughness and present a model accounting for the experimental observations. We suggest that our experiment revealed a universal phenomenon that will be observed on any strongly absorbing material under ultrafast laser irradiation.

Metal-organic framework (MOF) databases have grown rapidly through experimental deposition and large-scale literature extraction, but recent analyses show that nearly half of their entries contain substantial structural errors. These inaccuracies propagate through high-throughput screening and machine-learning workflows, limiting the reliability of data-driven MOF discovery. Correcting such errors is exceptionally difficult because true repairs require integrating crystallographic files, synthesis descriptions, and contextual evidence scattered across the literature. Here we introduce LitMOF, a large language model-driven multi-agent framework that validates crystallographic information directly from the original literature and cross-validates it with database entries to repair structural errors. Applying LitMOF to the experimental MOF database (the CSD MOF Subset), we constructed LitMOF-DB, a curated set of 189,567 computation-ready structures, including the successful repair of 9,227 invalid entries, which accounts for 69.1% of the CSD-derived not-computation-ready MOFs in the latest CoRE MOF DB. Additionally, the system uncovered 8,771 experimentally reported MOFs absent from existing resources, substantially expanding the known experimental design space. Using direct air capture screening as a case study, we demonstrate that structural errors severely distort predicted adsorption energies and CO2/H2O selectivity, leading to systematic misranking of materials, false positives, and the omission of high-performance candidates. This work establishes a scalable pathway toward self-correcting scientific databases and a generalizable approach for LLM-driven curation in materials science.