Papers

An analytical model is developed to investigate the interaction of quasi longitudinal (qP) waves with a perfectly bonded interface between a thermo piezoelectric half space and a functionally graded piezoelectric half space. The formulation is based on the fractional order Lord Shulman generalized thermoelasticity theory, which provides an enhanced description of coupled thermo electro mechanical wave behaviour. Rotational effects are incorporated into the constitutive relations and equations of motion for both media, while the lower half space is assumed to be subjected to initial stress. Closed form solutions for reflection and transmission coefficients are obtained, together with associated energy partition factors, allowing a comprehensive assessment of interface wave characteristics. Numerical simulations carried out using MATLAB demonstrate that the reflection and transmission responses are strongly influenced by initial stress, fractional order parameter, and thermal relaxation time. The calculated energy ratios of scattered waves satisfy the energy conservation condition, confirming the mathematical consistency of the formulation. The findings of this study are relevant to the design and analysis of smart sensors, rotating and aerospace structures, vibration control systems, and energy harvesting devices employing functionally graded thermo piezoelectric materials under fractional order effects.

Accessibility for the physically disabled is a prevalent issue on university campuses, where stairs and steep slopes make navigating campus arduous. Our work proposes a pipeline to model a college campus as a network by combining Strava and other APIs with depth-first search to derive insights into wheelchair-accessible paths. We then develop a custom Least Resistance algorithm to compute optimal paths between selected nodes and benchmark it against Dijkstra's algorithm. We highlight crucial nodes on campus using centrality measures, demonstrating that wheelchair users are significantly constrained by the lack of mobility options and accommodations. Our pipeline is designed to support future expansion in scope and accuracy, while enabling the proposal of engineering solutions to improve campus accessibility for physically disabled individuals.

Easy bikes have emerged as a popular and affordable mode of last-mile transport in Bangladesh, yet their widespread use has been accompanied by growing concerns about road safety. This study investigates the underlying factors influencing both the occurrence and severity of easy bike crashes by analyzing nationwide crash data spanning from 2016 to 2024. The findings reveal that crashes predominantly occur during daytime, on paved (pucca) roads, and in low-density peri-urban areas. Intersections and curved road segments are also identified as high-risk zones for crash occurrence. Crash severity analysis, supported by binary logit and probit models, emphasizes that the type of collision plays a crucial role in determining the likelihood of fatal outcomes. Pedestrian-involved crashes and rear-end collisions are more frequently associated with fatalities, whereas crashes involving overturns tend to result in less severe consequences. In contrast, environmental factors such as temperature, rainfall, and time of day exhibit limited impact on crash severity. The distribution of crash types also varies across vehicle categories, with motorcycles, buses, and trucks commonly involved in more dangerous collision scenarios. These findings focus on the urgent need for targeted road safety interventions focusing on specific crash types, high-risk locations such as intersections and curves, and vulnerable road users. Moreover, the study underscores the necessity for improving crash data quality, especially in underreported cases, to support informed decision-making. Based on these insights, the study also proposes a set of evidence-based and context-specific interventions aimed at reducing both the frequency and severity of easy bike crashes in Bangladesh.

Embolic stroke during cardiopulmonary bypass (CPB) is strongly influenced by cannula induced flow disturbances that govern emboli transport and aortic wall loading. This study quantifies how aortic cannula orientation affects embolic distribution and atherosclerotic plaque disruption risk across patient specific, age-dependent aortic anatomies under clinical CPB conditions. A validated computational fluid dynamics and Lagrangian particle tracking (CFD-LPT) framework was applied to four patient-specific aortic models representing pediatric, adolescent, adult, and geriatric anatomies. Two clinically relevant cannula orientations: perpendicular (90 deg) and angled (30 deg), were evaluated under varying blood viscosities (1.5 to 3.5 cP) and embolus sizes (0.5 to 2.5 mm). Aortic branch exit percentage, wall pressure, and wall shear stress (WSS) were quantified. The 30 deg angled cannula reduced embolic transport into the aortic branches by 18 to 50 percent compared with perpendicular cannulation, with the largest reduction observed in the geriatric model. Perpendicular cannulation produced concentrated jet impingement, resulting in significantly elevated posterior wall pressure (24 percent) and up to an 8 fold increase in local WSS. The pediatric anatomy exhibited the highest sensitivity, where decreasing viscosity and increasing embolus size increased branch exit by 8.4 percent and 25 to 44 percent, respectively, consistent with higher particle Stokes numbers and inertial decoupling from the core flow. Angled cannulation redistributes jet momentum along the aortic curvature, weakens jet impingement, reduces localized pressure and wall stress, and limits embolic delivery towards the cerebral circulation. These findings provide mechanistic, patient-specific evidence supporting angled cannula orientation to reduce CPB complications.

A phenomenological description of the Stern–Gerlach experiment yields a mathematical structure equivalent to that of a spin-1/2 particle, described by an irreducible unitary representation of the Poincaré group. In the corresponding irreducible two-particle representation, two-particle states have the form of an integral over product states. They describe a correlation between the particles with the structure of the electromagnetic interaction and a coupling constant that numerically equals the electromagnetic coupling constant. This coupling constant is essentially the normalisation factor of these two-particle states. The Standard Model of particle physics describes the electromagnetic interaction by a perturbation algorithm, where the experimental value of the electromagnetic coupling constant is inserted by hand. It is argued that it does not make sense to insert a normalisation factor without checking the range of integration of the corresponding integral and adjusting it if necessary. This adjustment provides the perturbation algorithm with the mathematically consistent structure of a non-local, relativistic, two-particle quantum mechanics. Similarly, multi-particle representations determine a gravitational interaction that, in the quasi-classical limit, is described by the field equations of conformal gravity. A calculated, galaxy-specific value of the gravitational constant matches the experimental value.

The electric field gradients (EFGs) at the (non-spherical) nucleus contribute to atomic and molecular hyperfine structure and govern Nuclear Electric field gradients (EFGs) at nuclei contribute to atomic hyperfine structure and govern Nuclear Quadrupole Resonance (NQR) and Mössbauer spectroscopy, providing a sensitive probe of local electronic structure and symmetry. EFGs can be obtained from electronic-structure calculations and inferred from spectroscopic measurements, linking theory and experiment. In this work, we use representative molecular and crystalline examples to examine selected factors that control calculated EFGs, with particular emphasis on multiconfigurational embedded-cluster calculations for solids. We analyze the sensitivity of EFGs to geometry and to computational choices including basis set, correlation treatment, and active-space construction. We also discuss differences in EFG tensor conventions adopted by commonly used quantum-chemistry codes and their implications for comparing computational results. Periodic calculations are used where appropriate as reference data for assessing the embedded-cluster description. Our results provide practical guidelines for the reliable computation and interpretation of EFGs as descriptors of the electronic structure and local chemical environment.

Search processes are a fundamental part of natural and artificial systems. In such settings, the number of searchers is rarely constant: new agents may be recruited while others can abandon the search. Despite the ubiquity of these dynamics, their combined influence on search efficiency remains unexplored. Here we present a general framework for stochastic search in which independent agents progressively join and leave the process, a mechanism we term dynamic redundancy and mortality (DRM). Under minimal assumptions on the underlying search dynamics, this framework yields exact first-passage time statistics. It further reveals surprising connections to stochastic resetting, including a regime in which the resetting mean first-passage time emerges as a universal lower bound for DRM, as well as regimes in which DRM search is faster. We illustrate our results through a detailed analysis of one-dimensional Brownian DRM search. Altogether, this work provides a rigorous foundation for studying first-passage processes with a fluctuating number of searchers, with direct relevance across physical, biological, and algorithmic systems.

In this invited Editorial for Software and Computing for Big Science, we describe the SMARTHEP Innovative Training Network funded via the Marie Skłodowska-Curie Actions between 2021 and 2025. SMARTHEP trained 12 PhD students to advance machine learning and real-time analysis in high-energy physics experiments and industrial applications. We present the perspective of students, supervisors, and external observers of the network, concerning the work done within the network, the added value compared to “typical” PhD positions, and the emerging themes and directions from our experiences in the past four years.

This work presents a comprehensive theoretical investigation of key isomers of C2H4N2 using state-of-the-art quantum chemical methods. The objective is to characterize their molecular structures, spectroscopic constants, and electronic energies, and to elucidate plausible formation and destruction pathways, providing data critical for astrochemical and atmospheric detection. High-accuracy ab initio methods were employed, notably CCSD(T)-F12/cc-pVTZ-F12 for optimized geometries. Additional calculations were performed at the CCSD(T)/aug-cc-pVTZ, CCSD(T)/cc-pVTZ, MP2/aug-cc-pVTZ, and CIS levels. Intrinsic reaction coordinate (IRC) calculations were performed at the B3LYP/6-31G(d,p) level to explore reaction pathways. Zero-point energy corrections were determined for all isomers considered. Six low-energy C2H4N2 isomers were identified, all within 1 eV of the global minimum. Among them, methylcyanamide (MCA) exhibits the lowest relative energy (~0.2 eV) and a significant electric dipole moment of 5.00 D, making it a strong candidate for gas-phase detection. The rotational constants for MCA, computed at the CCSD(T)-F12/cc-pVTZ-F12 level, are Ae = 34932.44 MHz, Be = 4995.31 MHz, and Ce = 4520.30 MHz. The V3 torsional barrier was found to be 631.19 cm^{-1}. Centrifugal distortion constants were computed up to sextic order for all isomers. Formation pathways for MCA, such as CH3N + HCN -> CH3NHCN and related isomers, were characterized. The combination of large dipole moments and distinct rotational signatures supports the detectability of methylcyanamide and related C2H4N2 isomers via radioastronomy, infrared, and microwave spectroscopy. Isomerization and reaction pathways involving radical-neutral and neutral-neutral processes were found to be key to their formation in gas-phase environments. These results provide a robust foundation for future observational and modeling efforts.

Thin polymer films are widely used as functional and protective coatings. However, determining the composition and processing conditions that produce a desired function is a tedious process due to the large number of factors that must be considered and the manual nature of most synthesis and characterization methods. Self-driving labs (SDLs), or robotic systems that prepare and test materials samples, are designed to overcome this bottleneck by enabling the efficient exploration of complex parameter spaces. In this paper, we report the development and testing of the polymer analysis and discovery array (PANDA)-film, a modular SDL for electrochemically synthesizing polymer films and then determining their water contact angle as a measure of surface energy. The system is designed to be highly modular and based upon a lowcost gantry platform to facilitate adoption. In addition to validating fluid handling and electrochemical tasks, we introduce two novel modular capabilities that enable PANDA-film to run sustained campaigns to study the wetting properties of films: (1) an electromagnetic capping/decapping system to mitigate fluid evaporation, and (2) a top-down optical method to determine water contact angle based upon reflectance. These capabilities are validated by depositing and characterizing a poly(allyl methacrylate) (PAMA) film using electrodeposition of polymer networks (EPoN). Comprehensive details for replicating the hardware and software of PANDA-film are included.

The largest connected component in duplication-divergence growing graphs with symmetric coupled divergence is studied. Finite-size scaling reveals a phase transition occurring at a divergence rate $\delta_c$. The $\delta_c$ found is close to the locus of zero in Euler characteristic of finite-size graphs known to reflect the proximity of the largest connected component transition. A close correspondence with the vanishing of a scaling relation exponent for moments of the vertex degree distribution is shown, with such a scaling relation that generalizes a known form for duplication-divergence model graphs. The role of non-interacting vertices in shaping this transition with their presence or absence in duplication is also considered through a particular relation which would result in the two cases being comparable. The findings have relevancy for bond percolation in these growing graph models.

We examine a new NASICON-type Na$_4$NiCr(PO$_4$)$_3$ material designed for high-voltage and multi-electron reactions for the sodium-ion batteries (SIBs). The Rietveld refinement of the X-ray diffraction pattern, using the R$\bar{3}$c space group, confirmed the stabilization of the rhombohedral NASICON framework. Furthermore, the Raman and Fourier transform infrared spectroscopy are employed to probe the structure and chemical bonding. The core-level photoemission analysis reveals the Cr$^{3+}$ and mixed Ni$^{2+}$/Ni$^{3+}$ oxidation states in the sample. Moreover, the bond valence energy landscape (BVEL) analysis, based on the refined structure, revealed a three-dimensional network of well-connected sodium sites with a migration energy barrier of 0.468 eV. The material delivered a good charge capacity at around 4.5 V, but showed no sodium-ion intercalation during discharge, resulting in negligible discharge capacity. The post-mortem analysis confirmed that the crystal structure remained intact. The calculated energy barrier values indicated a reversal in sodium site stability after cycling, though the barriers can still permit feasible ion migration. This suggests that ion transport alone cannot explain the lack of reversibility, which likely arises from intrinsically poor electronic conductivity. These findings highlight key challenges in achieving stable, reversible capacity in this system and underscore the need for doping, structural modification, and electrolyte optimization to realize its full potential as a high-voltage SIB cathode.

This study introduces novel insights into the development of procedures for identifying the most relevant scales for observing the interactions of dynamic wettability and surface complexities. The experimental procedures presented for measuring dynamic contact angle hysteresis in multiscale correlation with the geometric characteristics of anisotropic surfaces contribute to a new perspective on measurement practice. In this study, microtexturing with a pyramidal structured abrasive belt is applied for precisely forming area- and length-scale anisotropic surface complexities, and consequently, topographically dependent functional features. The significant role of anisotropic topographies in modeling dynamic wettability behavior is highlighted through multiscale measurement-based analysis. These studies verify the relationship between dynamic wettability and the finest surface microgeometry (microroughness) and also the coarsest texture components (waviness). The size of topographic features, ranging from microroughness to waviness, significantly influences droplet pinning and liquid entrapment. Furthermore, the influence of material hydrophilicity and hydrophobicity on the calculated multiscale relationships is assessed. The results indicated specific scales that best correlate with dynamic wettability, with length- and area-scale complexities of 6.9 um and 28 um2, respectively. A novel measurement-based approach to scale-dependent surface-functionality interactions offers new insights for designing dynamic wettability on anisotropic surfaces.

The distribution of ions and their impact on the structure of electrolyte interfaces plays an important role in many applications. Interestingly, recent experimental studies have suggested the preferential accumulation of $SO_4^{2-}$ ions at the $Na_2SO_{4,aq}$-graphene interface in disagreement with the generally known tendency of cations to accumulate at graphene-electrolyte interfaces. Herein, we resolve the atomistic structure of the $Na_2SO_{4,aq}$-graphene interfaces in the 0.1-2.0 M concentration range using machine learning interatomic potential-based simulations and simulated sum frequency generation (SFG) spectra to reveal the molecular origins of the conundrum. Our results show that Na+ ions accumulate between the outermost and second water layers whereas $SO_4^{2-}$ ions accumulate within the second interfacial water layer indicating cation dominated interfaces. We find that the interfacial region (within ~10 ${\AA}$ of the graphene sheet) is negatively charged due to sub-stoichiometric $Na^+$/$SO_4^{2-}$ ratio at the interface. Our simulated SFG spectra show enhancement and a red-shift of the spectra in the hydrogen bonded region as a function of $Na_2SO_4$ concentration similar to measurements due to $SO_4^{2-}$-induced changes in the orientational order of water molecules in the second interfacial layer. Our study demonstrates that ion stratification and ion-induced water reorganization are key elements of understanding the electrolyte-graphene interface.

Using a gap-free, millennial-resolution ice-core record spanning the last 130,000 years, we identify the feedback architecture between Antarctic temperature and atmospheric CO$_2$. The series are found to be cointegrated, justifying estimation with a Vector Error Correction Model (VECM). The estimated long-run relationship yields a temperature change of 13.0 K per CO$_2$ doubling. Structural identification combining Milankovitch-cycle instrumental variables with the VECM residuals yields a contemporaneous carbon response (CCR) that closely aligns with the thermodynamic bounds of Henry's Law. For the contemporaneous temperature response (CTR), the estimated confidence interval fully encompasses the theoretical Planck response. Accounting for structural lags and error correction, the cumulative temperature response within one millennium of CO$_2$ doubling reaches 11.8 K, successfully quantifying the delayed manifestation of the greenhouse effect.

Bound states in the continuum (BICs) have greatly impacted our ability to manipulate light-matter interaction at the nanoscale. However, in periodic structures, BICs are typically realized below the diffraction limit, thus leaving a broad spectral domains largely unexplored. Here, we introduce a new type of at-$\Gamma$ BICs of photonic crystal (PhC) slabs supporting higher diffraction orders, which we call hybrid BICs (h-BICs), whereby symmetry protection and parameter tuning are utilized to suppress light emission in the zeroth- and higher-diffraction orders, respectively. By tuning certain structural parameters of the PhC slab, we fully characterize the dynamics of the topological structure of these h-BICs, including the generation, merging, splitting, and annihilation of circularly polarized states. We further show that the relative amount of light radiated in the first-order diffraction channels can be effectively controlled by simply breaking the $C_{4v}$ symmetry of the PhC slab. Our findings reveal a versatile approach to realize new types of BICs above the diffraction limit, and could potentially inspire new efforts towards development of novel photonic nanodevices, such as multi vortex-beam generators, frequency converters, and lasers.

The transition from automated data collection to fully autonomous discovery requires a shared vocabulary to benchmark progress. While the automotive industry relies on the SAE J3016 standard, current taxonomies for autonomous science presuppose an owner-operator model that is incompatible with the operational rigidities of Large-Scale User Facilities. Here, we propose the Benchmarking Autonomy in Scientific Experiments (BASE) Scale, a 6-level taxonomy (Levels 0-5) specifically adapted for these unique constraints. Unlike owner-operator models, User Facilities require zero-shot deployment where agents must operate immediately without extensive training periods. We define the specific technical requirements for each tier, identifying the Inference Barrier (Level 3) as the critical latency threshold where decisions shift from scalar feedback to semantic digital twins. Fundamentally, this level extends the decision manifold from spatial exploration to temporal gating, enabling the agent to synchronise acquisition with the onset of transient physical events. By establishing these operational definitions, the BASE Scale provides facility directors, funding bodies, and beamline scientists with a standardised metric to assess risk, define liability, and quantify the intelligence of experimental workflows.

Flow structures directly responsible for local skin-friction generation in turbulent channel flows are identified using the newly developed Canonical Correlation Decomposition (CCD) method. The dominant structures take the form of streamwise streaks that are spanwise-localised around the position where the skin-friction is targeted and exhibit significantly shorter streamwise extent than those revealed using POD. The resulting CCD spectrum shows a clear low-rank behaviour; flow reconstruction using only the first 4 CCD modes recovers more than 80% of the examined skin friction, as opposed to 2% recovered by the leading 4 POD modes. When the opposition control technique is used to reduce drag, the application of CCD shows that drag reduction is achieved by lifting the original streak structures and generating smaller streaks with opposite phases underneath. These findings demonstrate that CCD isolates the causally relevant flow structures governing skin-friction generation and modification, which is expected to find use in various drag control applications in wall-bounded turbulence.

It is shown that the familiar two-stream instability is the result of spontaneous parity-time (PT)-symmetry breaking in a conservative system, and more importantly, explicit PT-symmetry breaking by viscosity can destabilize the system in certain parameter regimes that are stable when viscosity vanishes. This reveals that complex systems may possess hidden free energies protected by PT-symmetry and viscosity, albeit dissipative, can expose the systems to these freed energies by breaking PT-symmetry explicitly. Such a process is accompanied by instability and total variation growth.

Recent developments in vortex particle methods for simulating three-dimensional incompressible flows are presented. A lightweight, dynamic Large-Eddy Simulation model is tested, featuring a dynamic procedure that relies solely on Lagrangian information and requires minimal auxiliary computation to update the model constant. The method employs a high-order algebraic kernel which enables direct, analytical expressions for conservation laws, the strain-rate tensor, and quadratic velocity diagnostics. Viscous diffusion is modeled using the core-spreading technique. The particle method is assessed with respect to kinematics and the conservation of energy, helicity, and enstrophy in vortex ring and leapfrogging vortex ring scenarios, both unperturbed and perturbed. The results indicate that the kinematics and flow diagnostics are accurately captured using relatively sparse particle distributions, effectively resolving the dynamics of the unstable flow phase. However, after the onset of instabilities, the sub-grid-scale methodology becomes strongly dependent on particle regularization to stabilize the flow solution.

Robust hydrological simulation is key for sustainable development, water management strategies, and climate change adaptation. In recent years, deep learning methods have been demonstrated to outperform mechanistic models at the task of hydrological discharge simulation. Adoption of these methods has been catalysed by the proliferation of large sample hydrology datasets, consisting of the observed discharge and meteorological drivers, along with geological and topographical catchment descriptors. Deep learning methods infer rainfall-runoff characteristics that have been shown to generalise across catchments, benefitting from the data diversity in large datasets. Despite this, application to catchments in Africa has been limited. The lack of adoption of deep learning methodologies is primarily due to sparsity or lack of the spatiotemporal observational data required to enable downstream model training. We therefore investigate the application of deep learning models, including LSTMs, for hydrological discharge simulation in the transboundary Limpopo River basin, emphasising application to data scarce regions. We conduct a number of computational experiments primarily focused on assessing the impact of varying the LSTM model input data on performance. Results confirm that data constraints remain the largest obstacle to deep learning applications across African river basins. We further outline the impact of human influence on data-driven modelling which is a commonly overlooked aspect of data-driven large-sample hydrology approaches and investigate solutions for model adaptation under smaller datasets. Additionally, we include recommendations for future efforts towards seasonal hydrological discharge prediction and direct comparison or inclusion of SWAT model outputs, as well as architectural improvements.

Neural quantum states (NQS) have proven highly effective in representing quantum many-body wavefunctions, but their loss landscape remains poorly understood and debated. Here, we demonstrate that the NQS loss landscape is more benign and similar to conventional deep learning than previously thought, exhibiting mode connectivity: independently trained NQS are connected by paths in parameter space with essentially no energy barrier. To construct these paths, we develop GeoNEB, a path optimizer integrating efficient stochastic reconfiguration with the nudged elastic band method for constructing minimum energy paths. For the strongly interacting six-electron quantum dot modeled by a $1.6$M-parameter Psiformer, we find two independent minima with expected energy barrier $\sim10^{-5}$ times smaller than the system's overall energy scale and $\sim10^{-3}$ times smaller than the linear path's barrier. The path respects physical symmetry in addition to achieving low energy, with the angular momentum remaining well quantized throughout. Our work is the first to construct optimized paths between independently trained NQS, and it suggests that the NQS loss landscape may not be as pathological as once feared.

We investigate the stability of crystalline undulator radiation (CUR) peaks emitted by 530 MeV positron channelling in periodically bent C(110) crystals with varying bending amplitudes and bending periods. Relativistic molecular dynamics simulations were performed to quantify how these parameters affect the intensity and position of the CUR peak. The continuous potential approximation was used to identify isolines of constant peak energy, providing a reference for regions of spectral stability. MD results show that increasing the bending amplitude shifts the CUR peak to lower photon energies, while decreasing the period shifts it to higher energies, with both trends accompanied by enhanced dechannelling. For crystal parameters similar to recent experiments conducted at the MAinz MIkrotron (MAMI), the simulated CUR peak appears near 0.515 MeV. These results demonstrate that the CUR peak remains stable across a broad range of bending amplitudes and periods, providing quantitative estimates of the sensitivity of the emitted radiation to variations in the crystal bending parameters.

Dilatational and shear surface viscosities are highly correlated parameters, making their individual contributions difficult to disentangle in Stokes flow, linearised flow models, or two-dimensional flows. We therefore investigate the three-dimensional interfacial standing waves as a means to decouple the influence of dilatational and shear surface viscosities. Two dimensionless controlling parameters are introduced: $Bq$, the total Boussinesq number, which quantifies the the relative importance of surface viscous stresses compared with bulk viscous stresses, and $\tan \chi$, which quantifies the ratio of surface dilatational viscosity to surface shear viscosity. The growth rates and threshold accelerations are independent of $\chi$, consistent with previous theoretical predictions. Nonlinear analyses of square and hexagonal patterns reveal that Fourier decomposition of wave-patterns can effectively decouple the intricate dynamics into axial modes, where the waves are weakly dependent on $\chi$, and oblique modes, where additional damping occurs in the shear surface viscous dominant interface. These results demonstrate that Faraday wave-patterns provide a route for identifying and quantifying the distinct roles of dilatational and shear surface viscosities.

Crystalline solid solutions incorporate guest atoms by substituting host lattice sites up to a solubility limit dictated by solute host similarity. Solid solutions enable tuning various material properties, such as the optoelectronic behavior of halide perovskites. In bulk, incompatibility of Cl:I halide mixtures restricts exploration throughout the ternary halide Cl:Br:I compositional range. However, solubility is extended in nanocrystals which better accommodate a wider range of ions within their lattice. Through high throughput synthesis and spectroscopic characterization of over 3000 samples, along with density functional theory and cluster expansion models, we determine the solubility boundaries of ternary halide perovskite nanocrystals and demonstrate their extended size dependent miscibility. Smaller nanocrystals, with sufficient Br content, stabilize the Cl:Br:I solid solutions, suppress planar stacking fault defects and prevent halide segregation.

We propose a theoretical scheme for controlling the Goos-Hänchen shift (GHS) of a reflected probe field in a polariton optomechanical system. The system comprises an optical mode, a molecular vibrational mode, and $N$ excitonic modes, where excitons couple to molecular vibrations via conditional displacement interactions and to photons through electric dipole interactions. We show that the effective exciton-vibration coupling provides a powerful mechanism for coherent GHS control: in its absence, the system exhibits a pronounced GHS at resonance, while activating it strongly suppresses the shift. The effective cavity detuning and the cavity length serve as additional tunable parameters for GHS manipulation. Furthermore, increasing the collective exciton-optical coupling enhances the GHS. Our results establish a framework for probing the GHS in polariton optomechanical systems and offer new avenues for designing optical devices that exploit beam-displacement phenomena.

Understanding how evanescent modes mediate energy transfer in tapered elastic waveguides is of paramount interest, as it unlocks new strategies for wave control and manipulation. Evanescent modes play a crucial role in energy localization and in the emergence of thickness resonances. We report the first unambiguous experimental evidence of Lamb mode tunneling near turning points, revealing how energy can traverse an evanescent barrier and recover its propagative nature after a finite transit time. Focusing on waveguides with linearly varying thickness, we show that the $S_2$ mode becomes evanescent over a narrow frequency band, enabling a tunnelinglike phenomenon. Our study demonstrates that the barrier width is governed by the elastic properties of the material, particularly the Poisson's ratio, within a confined range bordering the Dirac cone. Numerical results exhibit excellent agreement with predictions from the Wentzel-Kramers-Brillouin approximation. These findings provide compelling evidence that, for a specific barrier width, evanescent modes mediate energy transfer across regions classically forbidden to propagating waves, revealing the mechanisms governing transmission, localization, and mode conversion in structured or corrugated elastic waveguides.

This paper develops a comprehensive two-dimensional generalisation of the recently introduced Friction with Bristle Dynamics (FrBD) framework for rolling contact problems. The proposed formulation extends the one-dimensional FrBD model to accommodate simultaneous longitudinal and lateral slips, spin, and arbitrary transport kinematics over a finite contact region. The derivation combines a rheological representation of the bristle element with an analytical local sliding-friction law. By relying on an application of the Implicit Function Theorem, the notion of sliding velocity is then eliminated, and a fully dynamic friction model, driven solely by the rigid relative velocity, is obtained. Building upon this local model, three distributed formulations of increasing complexity are introduced, covering standard linear rolling contact, as well as linear and semilinear rolling in the presence of large spin slips. For the linear formulations, well-posedness, stability, and passivity properties are investigated under standard assumptions. In particular, the analysis reveals that the model preserves passivity under almost any parametrisation of practical interest. Numerical simulations illustrate steady-state action surfaces, transient relaxation phenomena, and the effect of time-varying normal loads. The results provide a unified and mathematically tractable friction model applicable to a broad class of rolling contact systems.

We evaluate the performance of single-clad wavelength-shifting fibers newly developed by Luxium Solutions, BCF-92XL, BCF-9929AXL, and BCF-9995XL and compare them with the multi-clad Kuraray Y-11 fiber. The BCF-XL fibers exhibit faster decay times (92XL: $2.10\pm0.01$ ns, 9929AXL: $2.10\pm0.02$ ns, 9995XL: $2.41\pm0.03$ ns) than Y-11 ($7.44\pm0.06$ ns). The attenuation lengths are comparable to that of Y-11 within the measurement range up to 3.2 m. When coupled to an EJ-204 plastic scintillator, the BCF-XL fibers achieve superior time resolution while maintaining light yields comparable to those expected for a single-clad Y-11 fiber.

A high-efficiency power-combining method for four-way 5.8-GHz magnetrons based on the external injection-locking technique is presented in this article. The method uses a nonisolated, lossless five-port hybrid waveguide combiner for power combining. Meanwhile, the injection-locking technology has been applied to magnetrons for achieving coherent power combining. The phase fluctuation of the injection-locked magnetron, without the presence of a phase-locked loop, measured nearly 2.5 degree. In contrast, when a phase-locked loop was introduced, the phase fluctuation reduced significantly to approximately 0.5 degree. This phase accuracy can fully meet the requirements of combining experiments. Four magnetrons worked in injection-locked states without phase-locked loop. The proposed power-combining system is designed, measured, and analyzed. Measurement results show that a high-power-combining efficiency of over 95% is achieved by injection-locked magnetron without PLL, with the best efficiency reaching up to 97.7% with phase control of the injected signals. Experimental results reveal that the magnetron phase-pushing effects and the ripple in high-power dc voltage and current have a minor impact of approximately 4% on the combining efficiency.