Objective. Motion management is a critical challenge in proton therapy for mobile tumours. This study aims to develop and evaluate a novel four-dimensional (4D) pencil beam delivery strategy that incorporates respiratory motion into a dynamic treatment plan to improve dose conformity and treatment efficiency. Approach. To assess this 4D pencil beam delivery strategy, a mobile phantom was used. The generated 4D treatment plans were assessed with various scanner configurations, including gantry-free and magnet-free scanner heads. For each setup, the treatment time, dose conformity, and robustness against irregular breathing patterns were quantified. The influence of scanner head design and patient-specific motion irregularities on overall plan quality was evaluated. Main Results. The 4D planning tool generated treatment plans that achieved clinically acceptable dose distributions across all configurations. In magnet-free configurations, static beam operation substantially increased treatment time and reduced dose conformity. In contrast, configurations using a single scanner magnet, without a gantry, maintained acceptable conformity within practical treatment times. Significance. The proposed 4D delivery strategy demonstrates feasibility for treating mobile targets with simplified, gantry-free and magnet-free scanner designs. Further improvements could be achieved by synchronising the patient's breathing with 4D delivery, which may enhance dose accuracy during irregular or interrupted breathing. By reducing system complexity while preserving dosimetric performance, this approach offers a pathway toward more accessible and cost-effective proton beam therapy for motion-affected tumours.

A surface geometry consisting of parallel, meandering streamwise grooves has been experimentally studied as an alternative means of passive transverse forcing of turbulent boundary-layer flow. Contrary to the original expectation, the flow does not exhibit a spanwise-uniform undulation aligned with the grooves; instead, a converging-diverging flow pattern results. This flow pattern can be attributed to the spanwise periodicity of the lateral pressure gradient. The forcing effect is found to initially increase with the groove amplitude, but it saturates when the groove slope becomes too steep. The observed induced flow, referred to as a Passive Stokes Layer (PSL), can be considered as being composed of an inertial (pressure-driven) outer solution generated by the displacement effect of the non-smooth surface geometry, and a viscous inner solution to accommodate the no-slip condition at the wall. The mechanism of transverse flow generation is elucidated by an inviscid flow model that relates the forcing to the surface geometric properties, with predictions in good agreement with the experimental results. Although a reduction in the near-wall turbulence levels over the groove surfaces is observed, no direct evidence for (mean) drag reduction is evident from the data. Instead, an estimate of the frictional drag potential is based on establishing a tentative relation to an equivalent spatial Stokes layer (SSL) induced by active wall forcing. This theoretical comparison indicates that the induced passive forcing is sufficient to act on the (active) spanwise forcing mechanism, but produces at most a few per cent of frictional drag reduction. Any potential savings are likely offset by pressure drag and other losses, so that, similar to active forcing, its potential for net drag reduction in practical applications is limited.

Optical vortices carry quantized phase information (topological charge) and are considered candidates for information processing in all-optical circuits. Accurately identifying the quantized vortex charge in a way that is most efficient is essential for data processing. Here, we demonstrate that using only intensity information machine learning algorithms are able to classify vortices into distinct phase categories using a properly trained model. Preprocessing of the original intensity data leads to an improved prediction accuracy of the trained classifier and a much shorter training time (~3 orders of magnitude faster). The learning mechanism of the algorithms is revealed by the statistical analyses based on calculation of Cohen's d. We also find that the training efficiency is associated with nonlinearity, non-Hermiticity, and the vortex shape. In some cases, the trained classifier performs well across distinct physical models. Our findings will benefit and accelerate vorticity-based binary information processing and can also be extended to other physical systems.

Integrated tunable lasers are central to coherent communications, wavelength-routed optical interconnects, spectroscopy and frequency-modulated continuous-wave LiDAR, yet chip-scale sources rarely combine broad wavelength coverage, nanosecond switching, high spectral purity and stable high-power operation. Here we demonstrate a frequency-agile hybrid external-cavity laser enabled by the Pockels effect in thin-film lead zirconate titanate (PZT). The strong linear electro-optic response of PZT provides direct, non-thermal tuning of compact microring resonators with a wavelength-tuning efficiency of 17 pm/V. In contrast to conventional anisotropic Pockels materials, the near-isotropic in-plane electro-optic behaviour of thin-film PZT relaxes crystal-axis layout constraints, allowing efficient Vernier wavelength selection in compact ring cavities. The PZT resonators also show no measurable photorefractive resonance distortion and no resolvable DC-bias drift during operation, preserving stable wavelength-selective feedback. The demonstrated laser achieves an 82 nm tuning range, a 5 mW fiber-coupled output power, a side-mode suppression ratio (SMSR) exceeding 56.7 dB, and a wavelength-switching time of 5.5 ns. These results establish thin-film PZT photonics as a powerful electro-optic platform for compact, high-power, and frequency-agile integrated laser sources.

Silicon pixel detectors are widely used in high-energy physics experiments as tracking detectors close to the primary interaction vertex. They provide excellent space-point resolution together with fast electronic readout. Many of them employ only digital (binary) readout which makes the applicability of centre-of-gravity algorithms less obvious. Charge sharing between neighboring pixels improves the resolution beyond the single-pixel limit, but in practice there is a lack of quantitative understanding of the achievable gains. This work provides a simplified analytical and numerical model with which the maximum improvement achievable through charge sharing is quantified for both one and two-dimensional pixel geometries. A phenomenological parameterisation of the resolution as a function of the average cluster size is derived and compared to experimental data from several detector technologies.

Muography is a non-invasive imaging technique that uses cosmic-ray muons, commonly divided into transmission (absorption) and scattering muography. For transmission muography, the inversion algorithm critically determines reconstruction quality. However, widely used schemes may produce smearing artifacts when measurement locations are limited and data are sparse. We develop an optimized Metropolis--Hastings (M--H) algorithm that mitigates smearing and retrieves sharper, more accurate density distributions without auxiliary data. Additionally, we implement an inverse distance weighting (IDW) approach to reconstruct the air--rock interface from muon measurements. The optimized M--H algorithm is applied in Monte Carlo simulations and applied to field data from the TianQin Tunnel experiment using the MuGrid-v2 detector. The IDW-reconstructed air--rock interface is validated against Light Detection and Ranging (LiDAR) measurements. In simulations, the optimized M--H algorithm improves high-density anomaly detection precision from $42\%$ to $100\%$ at threshold $5.1\,\mathrm{g/cm^3}$, with gains of $6\%$ to $42\%$ across other threshold and low-density scenarios, together with the TianQin Tunnel reconstructions, these results demonstrate the effectiveness of the proposed approach.

We review the definitions of 22 parameters of a multiport antenna array operating in a specified direction: 4 excitation-dependent parameters for emission, 10 excitation-independent parameters for emission, and 8 parameters for reception. We concisely set forth their main properties. As examples, we compute and discuss these parameters in the cases of two simple 6-port antenna arrays made of parallel dipole antennas. We investigate the effect of a change of variable describing the excitation during emission. This allows us to find an ``invariance under a change of excitation variable'', and to compare some of the parameters with the ones used by other authors. We study passive linear embeddings of the MAA ports, to reveal an ``invariance under an invertible lossless linear embedding''.

This manuscript describes the establishment of a local production line for 10 cm x 10 cm Gas Electron Multiplier (GEM) foils at the Forschungs- und Technologiezentrum Detektorphysik (FTD) at the university of Bonn. GEM foils are widely used in modern gaseous detectors, providing high-gain signal amplification and high-rate capability. Our fabrication process utilizes a double-mask photolithographic technique on 50 $μ$m polyimide cladded on both sides with 5 $μ$m copper. The chemical etching procedure that is required to achieve uniform hole geometries with outer hole diameters of 70 $μ$m and inner hole diameters of 50 $μ$m will be described. Quality control protocols, including semi-automated optical inspection and high-voltage leakage current tests, demonstrate that foils produced at our facility achieve uniform hole size distributions and leakage currents of less than 1 nA at 600 V in air with no discharge hotspots. These results confirm that the production chain is capable of delivering high-performance foils suitable for research and development purposes.

Three-dimensional (3D) assemblies of gold nanoparticles (AuNPs) offer a rich platform for plasmonic coupling and near-field engineering, yet their optical behavior is often complex due to structural disorder and fabrication-induced variability. Here, we present a systematic optical investigation of large-scale 3D AuNP assemblies fabricated via meniscus-guided assembly, focusing on the reproducibility and spatial uniformity. Spatially-resolved dark-field scattering measurements reveal that high-aspect-ratio AuNP pillars exhibit uniform scattering spectra along their height and across different pillars, despite variations in geometry and structure. Electromagnetic simulations suggest that this robustness arises from an ensemble-averaged plasmonic response governed by many local coupling regions within a finite plasmon delocalization length. Simulated near-field and surface charge distributions suggest that the broad ensemble response remains spatially distributed under representative structural perturbations, consistent with volumetric averaging. Building on this robust platform, we introduce compositional modulation through a core-satellite architecture by incorporating smaller AuNPs. This yields a composition-dependent spectral redistribution, including an additional long-wavelength spectral feature in the core-satellite assemblies. Wavelength-dependent surface-enhanced Raman scattering measurements reveal contrasting responses under 633 and 785 nm excitation, reflecting redistribution of local plasmonic coupling pathways. These results establish design principles for robust 3D plasmonic nanoparticle assemblies with ensemble-averaged and composition-tunable optical responses.

The ionization mechanisms of small H$_2$O/D$_2$O clusters embedded in helium nanodroplets (HNDs) irradiated with extreme ultraviolet photons of energy $hν$ = 21.6 eV are investigated using Penning ionization electron-ion coincidence spectroscopy. Both protonated (H$_2$O)$_{n-1}$H$^{+}$/(D$_2$O)$_{n-1}$D$^{+}$ ($n$ = 3-6) and unprotonated (H$_2$O)$_{n}$$^{+}$/(D$_2$O)$_{n}$$^{+}$ ($n$ = 2-5) cluster ions were observed. Penning ionization electron spectra measured in coincidence with water cluster ions emitted from water clusters doped into both large and small HNDs are analyzed and compared with photoelectron-photoion coincidence spectra measured for free water clusters at $hν$ =20.6 eV. The results reveal suppression of fragmentation inside HNDs and stabilization of intact cluster ions. Quantum chemical calculations support the coexistence of proton-transferred and hemibonded conformers under the cryogenic conditions of helium nanodroplets.

A nonlinear equation for dust drift waves is derived assuming two-dimensional propagation and ignoring the role of dust acoustic waves. Both the nonlinear dust density term and the dust vorticity term are taken into account. If vorticity term is ignored, the equation gives two dimensional solitary waves and if density nonlinearity effect is discarded, then it reduces to Hasegawa-Mima equation for dust drift waves which admits dipole vortex solutions.

We propose a reduced asymptotic model for the mutual interaction between a weakly nonlinear surface gravity wave field and a slowly evolving incompressible current in a homogeneous rotating fluid. The formulation builds on the Craik-Leibovich theory for the wave-averaged momentum equation, but the Stokes drift is not prescribed externally. Instead, it is determined by a companion amplitude equation for a narrow-band wave field concentrated near the wavenumber circle associated with a prescribed carrier frequency. The derivation combines a multiple-time-scale expansion in wave steepness with a phenomenological closure that neglects quartic wave-wave interactions while retaining the third-order Stokes correction. Importantly, no spatial-scale separation is imposed on the wave-current interaction, allowing the wave equation to represent current-induced advection, refraction, and multidirectional scattering. The resulting equations conserve wave action and admit closed energy and momentum budgets for the coupled wave-current system. The model thus provides a tractable bidirectional extension of the classical Craik-Leibovich framework for regimes in which current-induced wave evolution feeds back significantly on the mean flow.

We have demonstrated highly-sensitive photon counting in the infrared based on the two-photon absorption (2PA) in a silicon avalanche photodiode, where the required photon energy for inducing effective conductivity was provided by an intense mid-infrared (MIR) field at 3 $μ$m. The used MIR pumping scheme could not only benefit from the enhanced 2PA coefficient in the non-degenerate regime, but also eliminate the detrimental background noises due to the pump harmonic excitation of the pump. Consequently, the enhancement factor for the signal counting rate unprecedented reached to about $10^{5}$ with input infrared pulses at the femtojoule level. Additionally, the noise equivalent power was substantially improved by two orders of magnitude comparing to conventional schemes with near-infrared pumping. Therefore, the presented configuration might provide an alternative to realize sensitive infrared detection and imaging with desirable features of room-temperature operation, no phase-matching requirement, and broadband responding window, which would find a variety of applications including remote ranging, sensitive sensing, biochemical imaging, and trace spectroscopy.

We report a passive stabilization of the repetition rate for a mode-locked fiber laser by using an electro-optic modulator in a phase-biased nonlinear amplifying loop mirror. The underlying mechanism, in contrast to active feedback operations, lies in the cross-phase modulation between electrical and optical pulses within an electro-optic crystal. The resulting spectral shift can automatically compensate the cavity-length drift via the group velocity dispersion. Consequently, the artificial actuator enables to obtain a capture range up to 2.3 mm, much longer than that achieved by index changes of the modulator. A robust and tight locking for the repetition rate is then realized with a standard deviation as low as 9 $μ$Hz with a 1-s sample time over 11 hours, corresponding to a fractional instability of 4.3$\times$10$^{-13}$. Furthermore, a dynamic optical sampling by repetition-rate tuning has been manifested with a fast refresh rate at 100 kHz and a broad scanning range over 305 ps. The demonstrated passive servo action may provide a simple yet effective way to stabilize the repetition rate with high precision, large bandwidth and wide tunability.

Frequency upconversion technique, where the infrared signal is nonlinearly translated into the visible band to leverage the silicon sensors, offers a promising alternation for the mid-infrared (MIR) imaging. However, the intrinsic field of view (FOV) is typically limited by the phase-matching condition, thus imposing a remaining challenge to promote subsequent applications. Here, we demonstrate a wide-field upconversion imaging based on the aperiodic quasi-phase-matching configuration. The acceptance angle is significantly expanded to about 30$^\circ$, over tenfold larger than that with the periodical poling crystal. The extended FOV is realized in one shot without the need of parameter scanning or post-processing. Consequently, a fast snapshot allows to facilitate high-speed imaging at a frame rate up to 216 kHz. Alternatively, single-photon imaging at room temperature is permitted due to the substantially suppressed background noise by the spectro-temporal filtering. Furthermore, we have implemented high-resolution time-of-flight 3D imaging based on the picosecond optical gating. These presented MIR imaging features with wide field, fast speed, and high sensitivity might stimulate immediate applications, such as non-destructive defect inspection, in-vivo biomedical examination, and high-speed volumetric tomography.

We theoretically and numerically investigate the formation of soliton crystals in Kerr microresonators in the presence of an avoided mode crossing (AMX). Our study combines dynamical simulations based on a modified Lugiato-Lefever equation (LLE) with a stability analysis of its stationary solutions. We show that, depending on its strength and spectral position, the AMX can either stabilize otherwise unstable soliton crystals or induce Turing patterns which subsequently seeds soliton crystal formation. Both perfect and imperfect soliton crystals can form below the pump threshold for spatiotemporal chaos, and we identify the conditions required for perfect crystals. Finally, we investigate modulation instability in the presence of an AMX, showing that it modifies the parametric gain and can suppress or promote Turing pattern formation depending on its spectral position.

Multiheme cytochromes, located on the bacterial cell surface, function as long-distance (> 10 nm) electron conduits linking intracellular reactions to external surfaces. This extracellular electron transfer process, which allows microorganisms to gain energy by respiring solid redox-active minerals, also facilitates the wiring of cells to electrodes. While recent studies suggested that a chiral induced spin selectivity effect is linked to efficient electron transmission through biomolecules, this phenomenon has not been investigated in the extracellular electron conduits. Using magnetic conductive probe atomic force microscopy, Hall voltage measurements, and spin-dependent electrochemistry of the decaheme cytochromes MtrF and OmcA from the metal-reducing bacterium Shewanella oneidensis MR-1, we show that electron transport through these extracellular conduits is spin-selective. Our study has implications for understanding how spin-dependent interactions and magnetic fields may control electron transport across biotic-abiotic interfaces in both natural and biotechnological systems. Electron

The electron drift instability (EDI) is widely recognized as the leading mechanism for anomalous electron transport in Hall thrusters, but its millimeter and sub-millimeter wavelength makes conventional wave-probe analysis strongly limited by spatial aliasing. A multi-geometry spatial anti-aliasing algorithm provides a route for wave-probe diagnostics to break the spatial Nyquist limit, but its effectiveness for nonmonotonic, folded, multi-resonance EDI dispersion has not been quantified. Using the numerically solved linear kinetic EDI dispersion relation under typical Hall-thruster discharge parameters as a benchmark, this work evaluates two-dimensional maximum-likelihood spatial anti-aliasing inversion based on two-probe synthetic signals generated for 25 simulated angle-spacing configurations. For a sampling frequency fs = 100 MHz and signal-to-noise ratio SNR = 10, the method breaks the conventional Nyquist wavenumber limit of about 1 krad/m, extends the accessible range to about 22 krad/m, and recovers the dominant likelihood ridges associated with the first- to fifth-order EDI branches. Parameter scans further show that the statistical realization count L mainly determines the suppression of spurious alias peaks, whereas the frequency resolution delta f mainly determines local branch separation near folded extrema. These results provide benchmark sampling and segmentation constraints for multi-geometry wave-probe diagnosis of EDI dispersion under the present synthetic conditions and can guide future experiments.

Graph-based linear-scaling electronic-structure theory provides a scalable framework for parallel quantum-mechanical molecular dynamics (QMD) simulations by exploiting the nearsightedness of the non-local electronic connectivity in non-metallic systems. When combined with recent shadow molecular dynamics in an extended-Lagrangian formulation, it enables stable long-time simulations of large, chemically active systems. This article introduces the Scalable Ecosystem, Driver, and Analyzer for Complex Chemistry Simulations (SEDACS), which integrates all these advances within a modular, Python-based software package for large-scale QMD simulations driven by external electronic-structure codes. SEDACS provides a tunable, adaptive graph construction in which edges encode the non-local electronic overlap between atoms. This graph is then decomposed into a set of smaller, overlapping subgraphs, where the electronic structure of each of these subgraphs is solved for independently and in parallel using an external electronic-structure code. SEDACS can be coupled to a variety of external electronic-structure solvers with minimal modifications to their software, enabling rapid adoption of the graph-based QMD approach. In this way, SEDACS can greatly extend the capability of existing electronic-structure packages by enabling stable QMD simulations of systems that were previously computationally inaccessible. We demonstrate highly efficient and stable QMD simulations for chemically active systems with tens of thousands of atoms by interfacing SEDACS with an external Fortran-based electronic-structure code based on self-consistent-charge density functional tight-binding theory.

We show that maximizing the generalized entropic functional $S_{q,δ}$ subject to standard kinetic energy constraints provides generalized canonical distributions that agree perfectly with measured probability densities of velocity differences at distance $r$ in highly-turbulent Taylor-Couette flow. The end point of the turbulent cascade is described by $δ=\frac{3}{2}$, a parameter value that also plays an important role in black-hole physics. At this point the Kolmogorov length scale $r=η$ is reached and all observable eddy structures of the turbulent flow disappear, in certain analogy to what is observed for black holes at the event horizon. Our approach generalizes statistical mechanics to more general nonadditive entropic functionals $S_{q,δ}$ such that it is applicable to turbulent flows. This approach asymptotically generates stretched $q$-exponentials as generalized canonical distributions relevant for turbulent flow, with a particular dependence of the stretching exponent $δ^{-1}$ on $q$ that follows from the well-known escort formalism in nonextensive statistical mechanics. Along this particular line in the parameter space, the physics can be described by $S_q$ on its own with suitable escort constraints, leading to the prediction $δ^{-1} (r) =2-q(r)$, thus allowing for a consistent thermodynamic description since $S_q$ is both trace-form and composable. We show that the above theoretically derived relation is well satisfied by measured high-precision experimental data for Taylor-Couette flow. At the Kolmogorov length scale $r=η$, the endpoint of our scenario, one has $δ=\frac{3}{2}$ and at this point the third moment of velocity differences ceases to exist and all eddies disappear. We point out various analogies with thermodynamic entropic approaches to black hole physics.

The electromagnetic behavior of a uniformly moving medium has been traditionally described by the Minkowski's theory, based on which the electromagnetic (EM) emission from a rotating isotropic medium should be linear, which means that the frequency of the EM emission should be the same as that of the excitation source. However, we experimentally observed that the near-field EM emission from a rotating charged dielectric disk shows discrete multi-harmonics at frequencies of nf_R, with n= 1 to 6, where f_R is the rotation frequency of the disk. By reversing the rotating direction of the disk, the phase shift for the observed magnetic field is π for odd harmonics, but it is zero for the even harmonics. The experimental results may not be consistent with the Minkowski's theory, but the data can be well explained using the Maxwell's equations for a mechano-driven media system (MEs-f-MDMS). This study not only provides a solid proof to MEs-f-MDMS, but also establishes the theory for describing the near-field EM emission from accelerated medium motion, which has many engineering applications.

Microchannel flow boiling is a promising technique for micro-device thermal management, and understanding the bubble dynamics in microchannel flow boiling is important for the applications. Previous studies only focused on single, isolated bubbles, but the bubbles in microchannel flow boiling applications often exist as bubble trains, in which the bubbles interact with each other. Here, we investigate numerically vapor bubble trains in microchannel flow boiling by adopting the flow-focusing technique to form monodispersed bubbles in the upstream of the microchannel. With increasing the initial vapor-liquid volume ratio, the bubble frequency increases while the growth rate of the bubbles decreases because of the reduced bubble size. With increasing the heat flux on the wall or reducing the latent heat of the working fluid, the bubble train growth rate increases because of the increased vaporization rate. The vaporization of the fluid in the upstream causes the bubble expansion and accelerates the bubble movement in the downstream. The wall temperature and the Nusselt number fluctuate because of the periodic pass-through of bubbles.

This study proposes an RTM- and iteration-free TES (RIFTES) framework to improve both computational efficiency and retrieval accuracy of the temperature-emissivity separation (TES) algorithm for clear-sky land surface temperature (LST) retrieval. Based on physical derivations, a non-iterative TES algorithm was first developed by reformulating the original iterative procedure into a mathematically equivalent closed-form solution, thereby eliminating the need for cumbersome iterations. To further reduce error propagation risks and computational burdens, a deep residual neural network that integrates atmospheric radiative transfer physics was adopted to conduct atmospheric correction using easily accessible parameters, with a masking mechanism introduced to flexibly incorporate atmospheric constraints when available. Comprehensive validations demonstrate the effectiveness of the proposed algorithm. Simulation results show that RIFTES remains robust to input uncertainties and achieves the lowest root mean squared error (RMSE) of 1.06 K among representative existing algorithms, including split-window (SW), TES, and SW-TES hybrid methods. In-situ measurements from globally distributed sites were then used to evaluate the practical performance of RIFTES when applied to both the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) and the Advanced Baseline Imager (ABI). The new algorithm achieves RMSE values of 1.51 K and 1.97 K for ECOSTRESS and ABI, respectively, reducing retrieval uncertainties by up to 24% and 32% compared with existing methods. Furthermore, by simplifying both the iterative procedure and atmospheric correction, RIFTES reduces the overall computational time by 74.0% and 62.5% compared with the TES and hybrid algorithms, respectively.

Across the Northern Hemisphere, Indigenous hunters developed arrows capable of skipping across the water surface to strike waterfowl. Archaeological and ethnographic records reveal remarkably similar projectile designs spanning millennia and geographically distant cultures, suggesting a convergent technological solution. Despite extensive study of water-entry dynamics, the physical principles underlying this behaviour remain poorly understood. Here we show that successful water-skipping arises from a small set of coupled geometric and dynamical parameters that define a bounded operational regime separating rebound, plunging, and overshoot. Using a combination of controlled experiments, hydrodynamic modeling, and historical reconstruction, we demonstrate that reconstructed arrow designs from independent cultures consistently fall within this predicted regime. These results demonstrate that Indigenous technologies were effectively tuned to satisfy the hydrodynamic constraints governing controlled skipping, providing evidence of convergent optimization in human-engineered systems. More broadly, our results suggest that material culture encodes physical knowledge that formal science is only beginning to articulate, and that the archaeological record and Indigenous culture may be an underexplored archive of empirical discovery.

Stretchable displays are critical for emerging wearable electronics, soft sensors, and next-generation AR/VR interfaces. Although recent advances have enabled foldable, twistable, and rollable displays, intrinsically stretchable substrates often exhibit significant lateral contraction under tensile strain due to their high Poisson ratio, leading to unintended wrapping, distortion, and shrinkage. Here, we report a transparent heterogeneous-modulus elastomeric substrate designed to achieve near-zero Poisson ratio while maintaining mechanical softness and optical transparency. The substrate consists of line-patterned hard polydimethylsiloxane (PDMS) embedded within a soft PDMS matrix, producing spatially heterogeneous strain distribution during stretching. In this architecture, the soft PDMS functions as a strain-absorbing medium, while the embedded hard PDMS patterns suppress lateral deformation perpendicular to the applied strain. As a result, the structure significantly dampens transverse contraction and realizes a near-zero effective Poisson ratio. To demonstrate the utility of this platform for stretchable optoelectronics, LED arrays were integrated onto the heterogeneous substrate. The devices exhibit minimal vertical and lateral distortion during tensile deformation, enabling mechanically stable operation of stretchable light-emitting displays. This heterogeneous modulus strategy provides a simple, scalable approach to mechanically robust stretchable display platforms.

Scientific machine learning models, as versatile tools for numerical simulation and analysis, are increasingly transforming the landscape of fluid mechanics research. However, existing datasets and benchmarks are primarily limited to continuum fluids and provide limited support for non-equilibrium transport phenomena. To address this gap, we present TransportBench, a high-fidelity dataset and standardized benchmark for non-equilibrium flow transport, designed to reveal the strengths and limitations of neural network models across diverse flow regimes. Specifically, the dataset encompasses a broad physical spectrum, covering continuum and rarefied regimes, low-speed and hypersonic flows, inert and chemically reactive gases, and both translational and internal-energy non-equilibrium effects. Built upon this dataset, we systematically benchmark representative neural architectures using unified evaluation protocols to probe key challenges in learning non-equilibrium flows, including robustness to shock-dominated discontinuities and multi-scale effects, as well as generalization across geometry and physical parameters. Numerical results demonstrate that model performance exhibits a pronounced dependence upon the specific flow characteristics. No single architecture consistently performs best for all the tasks. Instead, different architectural inductive biases provide distinct advantages in capturing smooth flow fields, shock-induced discontinuities, and high-order non-equilibrium statistics. By jointly providing the non-equilibrium flow dataset and model benchmark, TransportBench offers a new testbed for the development, evaluation, and diagnosis of scientific machine learning methods for fluid transport beyond the Navier-Stokes hydrodynamics. The benchmark datasets and implementation codes are available under the MIT license.

We report the demonstration of regrown epitaxial AlN gate interlayers with ultra-wide bandgap (UWBG) AlGaN polarization-graded field effect transistors (PolFETs). The introduction of the epitaxial AlN gate interlayer enables significant improvement in breakdown strength, with average breakdown field exceeding 6.94 MV/cm, which represents state-of-the-art for lateral field effect transistors, while maintaining excellent on-state current density exceeding 1 A/mm. The integration of epitaxial AlN enables state-of-the-art power-switching figure of merit exceeding 1.87 GW/cm2 at a breakdown voltage exceeding 1.45 kV. This work shows the potential of UWBG AlGaN for next-generation high-power switching and RF applications with enhanced device performance established by a high-quality epitaxially regrown AlN gate interlayer.

In geostrophic convective turbulence, large-scale vortices (LSVs) emerge through upscale energy transfer and are commonly regulated by large-scale friction. Yet the role of friction in setting the LSV size remains poorly understood. Here we perform direct numerical simulations of rotating Rayleigh-Benard convection with a linear friction term $α\mathbf{u}$. Contrary to the classical prediction $L_α\simα^{-3/2}$ obtained from the Kraichnan-Leith-Batchelor (KLB) theory, we find that the LSV radius follows $R_{LSV}\simα^{-1/2}$. This discrepancy originates from the energy spectrum of the barotropic (2D) manifold, which exhibits $E_{2D}(k)\sim k^{-3}$ over the range of upscale energy transfer, rather than the canonical $k^{-5/3}$ scaling. To explain this behavior, we analyze the energy pathways of the barotropic manifold and show that the inverse transfer is strongly nonlocal, coupling a broad range of intermediate scales directly to the cutoff scale. We propose that this coupling leads to a balance between the local and large-scale shear strain rates, resulting in a scale-invariant coarse-grained vorticity. The resulting prediction $E_{2D}(k)\sim k^{-3}$ is supported by circulation statistics exhibiting $\langle|Γ(r)|\rangle\sim r^2$. The observed $k^{-3}$ spectrum naturally yields the scaling $R_{LSV}\simα^{-1/2}$. These results provide a physical interpretation for the widely observed $k^{-3}$ spectrum in condensation-dominated turbulence and suggest that LSV-size estimates based on the classical $k^{-5/3}$ spectrum may be significantly biased in geophysical and astrophysical flows.

The Cr(III) coordination complex serves as an archetypical 3d transition metal system for probing ultrafast excited-state dynamics with spin conversion due to its intrinsic intersystem crossing (ISC) pathway, $^{4}T_{2g} \rightarrow ^{2}E_{g}$, upon photoexcitation. Here we conduct ab initio molecular dynamics simulations in the $^{4}T_{2g}$ state of a model Cr(III) coordination complex, followed by analyses of multireference electronic structure properties. Across 50 trajectories, the compound retains a persistent Jahn-Teller distortion in the excited state, while exhibiting prominent symmetric metal-ligand bond stretching vibrations with frequencies of 219 cm$^{-1}$ and 465 cm$^{-1}$. State-averaged complete active space self-consistent field (SA-CASSCF) calculations obtain two corresponding normal modes at 225 cm$^{-1}$ and 487 cm$^{-1}$ with symmetric stretching character. The lower-frequency twisting/scissoring mode strongly modulates the $^{4}T_{2g}/^{2}E_{g}$ energy gap, periodically zeroing the energy gap, whereas spin-orbit coupling is essentially invariant to vibrational motion ($\approx$ 60-80 cm$^{-1}$). Furthermore, calculations of single-point excited-state absorption from $^{2}E_{g}$ to a higher ligand-to-metal charge-transfer (LMCT) state indicate that the coherences previously observed in transient absorption spectra arise from nuclear motion on the $^{2}E_{g}$ surface. These results provide insights into the correlation between vibrational motion and electronic transitions, which can facilitate rational molecular design of transition metal complexes with desired excited-state properties by leveraging ligand versatility.

The Fourier spectra of resonant quantities in tokamaks depend on the choice of magnetic coordinates, and an area weighting of the Fourier integrand preserves the resonant coefficients on rational surfaces. That result constrains only the resonant interior; the coordinate dependence of the external Fourier spectrum, which determines the coupling to Resonant Magnetic Perturbation (RMP) coils and error-field penetration, was left untreated. This paper shows that pairing a square-root-area weighted vacuum field perturbation with a full-area-weighted resonant field yields a coupling matrix C whose singular values are invariant under coordinate transformations and whose right singular vectors reconstruct to a consistent real-space field pattern across coordinate systems, completing the coordinate-invariance picture for the plasma-3D-field coupling paradigm. GPEC calculations confirm the analytic result and show that improperly weighted coupling matrices can produce dominant modes whose overlap with the vacuum field perturbation differs by a factor of $2--3$ between coordinate systems for strongly shaped, low aspect ratio equilibria, with the discrepancy growing with inverse aspect ratio. The same coordinate dependence afflicts alternative formulations such as the three-mode metric or zeroing the $q=2$ resonant field without proper weighting. The result applies to any tool computing Fourier spectra of resonant or external quantities on flux surfaces.