Cuprate superconductors remain central to condensed matter physics due to their technological relevance and unconventional, incompletely understood electronic behavior. While the canonical phase diagram and low-energy models have been shaped largely by studies of underdoped and moderately doped cuprates, the overdoped regime has received comparatively limited this http URL, we track the evolution of the electronic structure from optimal to heavy overdoping in La2-xSrxCuO4(LSCO) using broadband optical spectroscopy across x=0.15-0.60. The measured spectral changes--including the redistribution of Zhang-Rice-related spectral weigh--are in qualitative agreement with determinant quantum Monte Carlo simulations of the three-orbital Emery model, which together indicate a pronounced reconstruction of the electronic structure beyond hole concentrations x>0.2. Guided by these observations, we propose a spontaneous checkerboard-type Zhang-Rice electronic configuration that captures the coexistence of itinerant and localized carriers characteristic of the heavily overdoped state. Our results refine the doping-dependent Zhang-Rice-based framework for cuprates, illuminate how correlations persist deep into the overdoped regime, and provide new constraints on microscopic mechanisms of high-temperature superconductivity, with broader implications for correlated transition-metal oxides.

Long-range moire patterns in twisted WSe2 enable a built-in, moire-length-scale ferroelectric polarization that can be directly harnessed in electronic devices. Such a built-in ferroic landscape offers a compelling means to enable ultralow-voltage and non-volatile electronic functionality in two-dimensional materials; however, achieving stable polarization control without charge trapping has remained a persistent challenge. Here, we demonstrate a moire-engineered ferroelectric field-effect transistor (FeFET) utilizing twisted WSe2 bilayers that leverages atomically clean van der Waals interfaces to achieve efficient polarization-channel coupling and trap-suppressed, ultralow-voltage operation (subthreshold swing of 64 mV per decade). The device exhibits a stable non-volatile memory window of 0.10 V and high mobility, exceeding the performance of previously reported two-dimensional FeFET and matching that of advanced silicon-based devices. In addition, capacitance-voltage spectroscopy, corroborated by self-consistent Landau-Ginzburg-Devonshire modeling, indicates ultrafast ferroelectric switching (~0.5 microseconds). These results establish moire-engineered ferroelectricity as a practical and scalable route toward ultraclean, low-power, and non-volatile 2D electronics, bridging atomistic lattice engineering with functional device architectures for next-generation memory and logic technologies.

Second harmonic (SH) radiation can only be generated in non-centrosymmetric bulk crystals under electric dipole approximation. Nonlinear thin films made from bulk crystals are technologically challenging because of complex and high temperature fabrication processes. In this work, heterostructures made of amorphous materials SiO$_2$ and TiO$_2$ were prepared by a CMOS-compatible technique named plasma enhanced atomic layer deposition (PEALD) with deposition temperature at 100 °C. By using the uniaxial dispersion model, we characterized the form-birefringence property, which can enable the phase matching condition in waveguides or other nonlinear optical applications. By applying a fringe-based technique, we determined the largest diagonal component of the effective second-order bulk susceptibility $\chi_{zzz}^{(2)}$ = 1.30$\pm$0.13 pm/V at a wavelength of 1032 nm. Noteworthy, we observed strong SHG signals from two-component nanolaminates which are several orders of magnitude larger than from single layers. The SHG signals from our samples only require the broken inversion symmetry at the interface. Here optical properties of nanocomposites can be precisely tuned by the promising PEALD technology.

As quantum computing processors increase in size, there is growing interest in developing cryogenic electronics to overcome significant challenges to system scaling. Single flux-quantum (SFQ) circuits offer a promising alternative to remote, bulky, and power-hungry room temperature electronics. To meet the need for digital qubit control, readout, and co-processing, SFQ circuits must be adapted to operate at millikelvin temperatures near quantum processors. SEEQC's SFQuClass digital quantum management approach proximally places energy-efficient SFQ (ERSFQ) circuits and qubits in a multi-chip module. This enables extremely low power dissipation, compatible with a typical dilution cryostat's limited cooling power, while maintaining high processing speed and low error rates. We report on systematic testing from 4 K to 10 mK of a comprehensive set of ERSFQ cells, as well as more complex circuits such as programmable counters and demultiplexers used in digital qubit control. We compare the operating margins and error rates of these circuits and find that, at millikelvin, bias margins decrease and the center of the margins (i.e., the optimal bias current value) increases by ~15%, compared to 4.2 K. The margins can be restored by thermal annealing by reducing Josephson junction (JJ) critical current Ic. To provide guidance for how circuit parameters vary from 4.2 K to millikelvin, relevant analog process control monitors (PCMs) were tested in the temperature range of interest. The measured JJ critical current (of the PCM JJ arrays) increases by ~15% when decreasing temperature from 4.2 K to millikelvin, in good agreement with both theory and the empirically measured change in the center of bias margins for the tested digital circuits.

Magnetic skyrmions, renowned for their fascinating electromagnetic properties, hold potential for next-generation topological spintronic devices. Recent advancements have unveiled a rich tapestry of 3D topological magnetism. Nevertheless, the practical application of 3D topological magnetism in the development of topological spintronic devices remains a challenge. Here, we showcase the experimental utilization of 3D topological magnetism through the exploitation of skyrmion-edge attractive interactions in 90-nm-wide confined chiral FeGe and CoZnMn magnetic nanostructures. These attractive interactions result in two degenerate equilibrium positions, which can be naturally interpreted as binary bits for a skyrmion sliding switch. Our theory and simulation reveal current-driven spiral motions of skyrmions, governed by the anisotropic gradient of the potential landscape. Our experiments validate the theory that predicts a tunable threshold current density via magnetic field and temperature modulation of the energy barrier. Our results offer an approach for implementing universal on-off switch functions in 3D topological spintronic devices.

The integration of high-refractive-index dielectrics into scalable photonic architectures is foundational to advancing integrated circuits and augmented reality (AR) displays. Van der Waals (vdW) materials offer exceptional optical properties, including high refractive indices and giant anisotropy, but their implementation is constrained by the small area and uncontrolled thickness of mechanically exfoliated flakes. Here, we demonstrate that atomic layer deposition (ALD) grown gallium sulfide (GaS) overcomes the trade-off between high optical performance and manufacturability, emerging as a large-scale vdW dielectric platform. Through rigorous optical and structural benchmarking against pristine single crystals, we establish that the optical constants (n, k) of ALD-GaS are virtually indistinguishable from single-crystal counterparts. By leveraging the retained out-of-plane anisotropy, we demonstrate that ALD-GaS enables superior suppression of crosstalk in densely integrated waveguides compared to conventional scalable high-index platforms. Our findings establish ALD-GaS as a technologically viable pathway for implementing anisotropic vdW materials in visible-spectrum photonics.

Thin, metallic magnetic films can support nonreciprocal spin waves due to the interfacial Dzyaloshinskii-Moriya interaction (iDMI). However, these films typically have high damping, making spin wave propagation distances short (less than one micrometer). In this work, we theoretically study a thin ferromagnetic strip with iDMI and excite spin waves by driving a central segment of the strip. Spin waves propagate with different amplitudes to the left versus to the right from the driving region (i.e. nonreciprocity occurs) due to the iDMI. Our calculation based on spin-wave-dispersion plus our micromagnetic simulations both show that changing the driving segment width, driving frequency and static applied field strength tunes the nonreciprocity. Our calculation based on spin-wave-dispersion, using a so-called "overlap function" will allow researchers to predict conditions of maximum nonreciprocity, without the need for computational solvers. Moreover, to circumvent the issue of short propagation distances, we propose a geometry where iDMI is only present in the driving region and low-damping materials comprise the remainder of the strip. Our calculations show significant spin wave amplitudes over several microns from the excitation region.

High-k (115), crystalline SrTiO3 (STO) thin film was transferred on GaN for potential applications in power devices (transistor and diodes) by nanomembrane transfer method and the detailed electrical properties such as leakage current, CV profiles, dielectric constant, frequency dispersion was reported from fabricated MOSCAP structures. The leakage current was negligible (under noise-level of tool) up to 6 V and 11 V for 50 nm and 200 nm STO membrane respectively A high-quality dielectric was indicated by the CV profile, which showed almost negligible frequency dispersion in the frequency range of 10 kHz to 500 kHz. The dielectric constant was 50 to 82 with the 50 nm thick STO membrane and 115 to 186 in the 200 nm thick STO membrane. Thermal annealing of the membrane in ambient conditions at 250 degrees for 2 hours led to a slight improvement in the dielectric constant (8 to 20 percent), albeit at the expense of degraded leakage current performance, as indicated by a reduction of 1 V to 3 V in the "no leakage region" of the IV curves after annealing. The possible physical mechanisms responsible for these changes were also analyzed and discussed.

Freestanding thin films, a class of low-dimensional materials capable of maintaining structural integrity without substrates, have emerged as a forefront research focus. Their unique advantages-circumventing substrate clamping, liberating intrinsic material properties, and enabling cross-platform heterogeneous integration-underpin this prominence. This review systematically summarizes core fabrication techniques, including physical delamination (e.g., laser lift-off, mechanical exfoliation) and chemical etching, alongside associated transfer strategies. It further explores the induced strain modulation mechanisms, extreme mechanical properties and interface decoupling effects enabled by these films. Representative case studies demonstrate breakthrough applications in flexible/ultrathin electronics, ultrahigh-sensitivity sensors and the exploration of novel quantum states. Critical challenges regarding scalable fabrication, precise interface control, and long-term stability are analyzed, concluding with prospects for emerging applications in bio-inspired intelligent devices, quantum precision sensing, and brain-inspired neural networks.

Quantum sensors based on electronic spins have emerged as powerful probes of microwave-frequency fields. Among other solid-state platforms, spins in molecular crystals offer a range of advantages, from high spin density to functionalization via chemical tunability. Here, we demonstrate microwave vector magnetometry using the photoexcited spin triplet of pentacene molecules, operating at zero external magnetic field and room temperature. We achieve full three-dimensional microwave field reconstruction by detecting the Rabi frequencies of anisotropic spin-triplet transitions associated with two crystallographic orientations of pentacene in deuterated naphthalene crystals. We further introduce a phase alternated protocol that extends the rotating-frame coherence time by an order of magnitude and enables sensitivities of approximately $1~\mu\mathrm{T}/\sqrt{\mathrm{Hz}}$ with sub-micrometer spatial resolution. These results establish pentacene-based molecular spins as a practical and high-performance platform for microwave quantum sensing in addition to demonstrating control techniques broadly applicable to other molecular and solid-state spin systems.

Quantum geometry is a differential geometry based on quantum mechanics. It is related to various transport and optical properties in condensed matter physics. The Zeeman quantum geometry is a generalization of quantum geometry including the spin degrees of freedom. It is related to electromagnetic cross responses. Quantum geometry is generalized to non-Hermitian systems and density matrices. Especially, the latter is quantum information geometry, where the quantum Fisher information naturally arises as quantum metric. We apply these results to the $X$-wave magnets, which include $d$-wave, $g$-wave and $i$-wave altermagnets as well as $p$-wave and $f$-wave magnets. They have universal physics for anomalous Hall conductivity, tunneling magneto-resistance and planar Hall effect. We obtain various analytic formulas based on the two-band Hamiltonian.

Accurate simulations of electric fields (E-fields) in brain stimulation depend on tissue conductivity representations that link macroscopic assumptions with underlying microscopic tissue structure. Mesoscale conductivity variations can produce meaningful changes in E-fields and neural activation thresholds but remain largely absent from standard macroscopic models. Recent microscopic models have suggested substantial local E-field perturbations and could, in principle, inform mesoscale conductivity. However, the quantitative validity of microscopic models is limited by fixation-related tissue distortion and incomplete extracellular-space reconstruction. We outline approaches that bridge macro- and microscales to derive consistent mesoscale conductivity distributions, providing a foundation for accurate multiscale models of E-fields and neural activation in brain stimulation.

We report that due to the orbital Hall effect, orbital pumping effects can occur in materials with weak spin-orbit coupling. Moreover, there is a positive correlation between the strength of the orbital Hall effect and the size of spin-pumping. During the spin-pumping, with the enhancement of the orbital Hall effect, the resonant absorption of orbital current and the damping of the ferromagnetic layer also increase. Especially, when the thickness of Ti reaches 60 nm, the orbital -mixing conductance of Ti/Co is an order of magnitude higher than spin-mixing conductance of heavy metal/Co, reaching 474.1 3 ^18 m^(-2). The results indicate that the orbital current is more easily transmitted across the interface

Core-shell electrode particles are a promising morphology control strategy for high-performance lithium-ion batteries. However, experimental observations reveal that these structures remain prone to mechanical failure, with shell fractures and core-shell debonding occurring after a single charge. In this work, we present a novel, comprehensive computational framework to predict and gain insight into the failure of core-shell morphologies and the associated degradation in battery performance. The fully coupled chemo-mechano-damage model presented captures the interplay between mechanical damage and electrochemical behaviours, enabling the quantification of particle cracking and capacity fade. Both bulk material fracture and interface debonding are captured by utilising the phase field method. We quantify the severity of particle cracking and capacity loss through case studies on a representative core-shell system (NMC811@NMC532). The results bring valuable insights into cracking patterns, underlying mechanisms, and their impact on capacity loss. Surface cracks are found to initiate when a significantly higher lithium concentration accumulates in the core compared to the shell. Interfacial debonding is shown to arise from localised hoop stresses near the core-shell interface, due to greater shell expansion. This debonding develops rapidly, impedes lithium-ion transport, and can lead to more than 10\% capacity loss after a single discharge. Furthermore, larger particles may experience crack branching driven by extensive tensile zones, potentially fragmenting the entire particle. The framework developed can not only bring new insight into the degradation mechanisms of core-shell particles but also be used to design electrode materials with improved performance and extended lifetime.

Particle-like chiral magnetic skyrmions can flow in nanotracks and behave like chiral fluids. Using interacting flows to perform logical operations is an important topic in microfluidics and nanofluidics. Here, we report a basic nanofluidic logic computing system based on chiral magnetic skyrmions flowing in parallel pipelines connected by an H-shaped junction. The flow behaviors could be manipulated by adjusting the spin polarization angle, which controls the intrinsic skyrmion Hall angle. We demonstrate that within certain range of the spin polarization angle, fully developed skyrmion flows could lead to fluidic logical operations, which significantly reduce the complexity of skyrmion logic as there is no need for deterministic creation, precise control, and detection of a single isolated skyrmion. Our results suggest that the chiral flow behaviors of magnetic quasiparticles may offer possibilities for spintronic and nanofluidic functions.

We present an uncertainty-aware, physics-informed neural network (PINN) for option pricing that solves the Black--Scholes (BS) partial differential equation (PDE) as a mesh-free, global surrogate over $(S,t)$. The model embeds the BS operator and boundary/terminal conditions in a residual-based objective and requires no labeled prices. For American options, early exercise is handled via an obstacle-style relaxation while retaining the BS residual in the continuation region. To quantify \emph{epistemic} uncertainty, we introduce an anchored-ensemble fine-tuning stage (AT--PINN) that regularizes each model toward a sampled anchor and yields prediction bands alongside point estimates. On European calls/puts, the approach attains low errors (e.g., MAE $\sim 5\times10^{-2}$, RMSE $\sim 7\times10^{-2}$, explained variance $\approx 0.999$ in representative settings) and tracks ground truth closely across strikes and maturities. For American puts, the method remains accurate (MAE/RMSE on the order of $10^{-1}$ with EV $\approx 0.999$) and does not exhibit the error accumulation associated with time-marching schemes. Against data-driven baselines (ANN, RNN) and a Kolmogorov--Arnold FINN variant (KAN), our PINN matches or outperforms on accuracy while training more stably; anchored ensembles provide uncertainty bands that align with observed error scales. We discuss design choices (loss balancing, sampling near the payoff kink), limitations, and extensions to higher-dimensional BS settings and alternative dynamics.

Surface roughness is a critical factor influencing the fatigue life of structural components. Its effect is commonly quantified using a correction coefficient known as the surface factor. In this paper, a phase field based numerical framework is proposed to estimate the surface factor while accounting for the stochastic nature of surface roughness. The model is validated against existing experimental data. Furthermore, we investigate the influence of key parameters on the fatigue life of rough surfaces, such as surface topology and failure strength. An important effect of surface roughness is observed when the average surface roughness increases and the correlation length of the surface profile decreases. This effect becomes more pronounced with higher failure strengths.

With the widespread application of composite structures in the fields of building and bridge constructions, thin-covered composite dowels are increasingly adopted in various engineering scenarios. This paper presents a design methodology for thin-covered composite dowels, supported by both experimental and theoretical investigations. In the experiment, a novel test rig and specimens are designed to facilitate tensile-shear coupling loading. The study identifies a new failure mode: Restricted Cone Failure (RCF) in thin-covered composite dowels under tensile-shear coupling load, which distinct from conventional composite dowels. This RCF mode is attributed to the thin thickness of the side concrete cover, which restricts the development of the failure cone in the thickness direction. Additionally, a parametric analysis is conducted to evaluate the effects of key factors--such as steel dowel thickness, effective embedment depth, and the tensile strength of steel fiber reinforced concrete--on the bearing capacity and ductility of thin-covered composite dowels. Based on the theoretical findings, comprehensive tensile, shear, and tensile-shear coupling capacity models along with an engineering design model are developed to aid in the practical application of thin-covered composite dowels.

We consider the novel problem of optimizing a large set of passive superconducting coils (PSCs) with currents induced by a background magnetic field rather than power supplies. In the nuclear fusion literature, such coils have been proposed to partially produce the 3D magnetic fields for stellarators and provide passive stabilization. We perform the first optimizations of PSC arrays with respect to the orientation, shape, and location of each coil, jointly minimized with the background fields. We conclude by generating passive coil array solutions for four stellarators.

Semiconductor nano-crystals, known as quantum dots (QDs), have attracted significant attention for their unique fluorescence properties. Under continuous excitation, QDs emit photons with intricate intensity fluctuation: the intensity of photon emission fluctuates during the excitation, and such a fluctuation pattern can vary across different QDs even under the same experimental conditions. What adding to the complication is that the processed intensity series are non-Gaussian and truncated due to necessary thresholding and normalization. Conventional normality-based single-dot analysis fall short of addressing these complexities. In collaboration with chemists, we develop an integrative learning approach to simultaneously analyzing intensity series from multiple QDs. Motivated by the unique data structure and the hypothesized behaviors of the QDs, our approach leverages the celebrated hidden Markov model as its structural backbone to characterize individual dot intensity fluctuations, while assuming that, in each state the normalized intensity follows a 0/1 inflated Beta distribution, the state/emission distributions are shared across the QDs, and the state transition dynamics can vary among a few QD clusters. This framework allows for a precise, collective characterization of intensity fluctuation patterns and have the potential to transform current practice in chemistry. Applying our method to experimental data from 128 QDs, we reveal three shared intensity states and capture several distinct intensity transition patterns, underscoring the effectiveness of our approach in providing deeper insights into QD behaviors and their design and application potential.