Papers

A In this work, an experimental approach is introduced to redistribute optical energy among the multiple concentric core rings of high-order R-TEM laser modes, differing from conventional high-order R-TEM modes that inherently exhibit non-uniform energy across their rings. By employing a diffractive optical element formed from a binary phase mask with two oppositely phased regions, the energy sharing between the rings can be tuned to achieve a variable intensity ratio in the ring pattern. The resulting modulated high-order R-TEM modes are expected to surpass standard R-TEM modes for applications requiring ring structures with nearly equal intensity, such as micro- and nanoparticle manipulation, optical lithography, and near-field optical data storage.

Spintronic terahertz emitters (STEs) generate broadband terahertz (THz) radiation, which is essential for spectroscopy, imaging, and communication. The performances and the essential physical parameters of STE devices are linked to the dielectric properties of the constituent materials. Terahertz time-domain spectroscopy (THz-TDS) is an effective tool to measure these properties, but conventional analysis struggles with thin or complex multilayered systems due to simplifying approximations or complex transfer functions. In this work, we present a practical method to extract dielectric properties of STE multilayers using the Transfer Matrix Method (TMM). By comparing the THz pulse calculated using the Transfer Matrix Method (TMM) with the experimentally measured pulse transmitted through the sample, we can extract the dielectric properties of STEs, enhancing THz-TDS analysis and facilitating STE design and optimization. This method avoids constructing complex transfer functions, accommodates diverse sample geometries, and is designed to be accessible, with a publicly available codebase, making it a useful tool for STE research.

We present MOCVD-grown, nitrogen-doped e̱ta}-Ga2O3 films as an insulating buffer layer on Fe-doped (010) e̱ta}-Ga2O3 substrates in lieu of 49% HF treatment to remove unintentional silicon at the substrate-epitaxial layer growth interface. N-doped layer thickness and NH3 flow were systematically varied to experimentally determine the lowest nitrogen concentration and thickness of the buffer layer needed to fully compensate the interfacial silicon peak. The NH3 molar flow rate was varied from 200 sccm to 1800 sccm. Results showed fully insulating N-doped layers for samples with NH3 flow rates greater than or equal to 1200 sccm and a thickness of 50 nm. This study demonstrates the efficacy of in-situ, controllably doped nitrogen buffer layers as a mitigation method for unintentional interfacial silicon at the substrate-epitaxial layer growth interface.

We investigate buoyancy-induced transitions in flow structure and the associated velocity dip in turbulent mixed convection. Numerical simulations are performed for an open Poiseuille–Rayleigh–Bénard system with a heated no-slip lower wall and a cooled free-slip upper boundary over $10^5 \leq Ra \leq 10^8$, $90 \leq Re_b \leq 5700$, $Pr=0.71$, and $0.013 \leq Ri_b \leq 17$. The flow organisation is governed primarily by the bulk Richardson number $Ri_b$. As buoyancy increases, the flow changes from a shear-dominated state to streamwise-oriented large-scale rolls and then to fragmented rolls. Roll formation coincides with a reorganisation of the velocity statistics about the channel midplane and a displacement of the maximum mean streamwise velocity from the upper boundary into the channel interior, producing a velocity dip. The mean momentum balance shows that spatially uniform streamwise forcing imposes a linear total-stress profile. Wherever the Reynolds shear stress exceeds the local total stress, the viscous stress and mean velocity gradient must be negative. A triple decomposition attributes most of the Reynolds-stress excess in the roll states to slowly varying, roll-associated motions. The roll-associated stress and dip strength vary non-monotonically with $Ri_b$. Quadrant analysis shows that ejections and sweeps sustain the net roll-associated stress, whereas roll fragmentation strengthens the cancellation between positive and negative contributions and weakens the dip. The turbulent kinetic energy (TKE) budget shows a corresponding shift from near-wall shear production to bulk buoyancy production, with shear production becoming negative above the velocity maximum. Finally, a case-specific a posteriori simplification of the core-region TKE budget yields an approximate velocity profile that captures the gradient reversal.

An ab initio approach is presented for studying the collective excitations in excitonic insulators, charge/spin density waves and superconductors. We derive the Bethe-Salpeter-Equation for the particle-hole excitations in the quasiparticle representation, from which the collective excited states are solved and the corresponding order parameter fluctuations are computed. This method is demonstrated numerically for the excitonic insulating phases of the biased WSe2-MoSe2 bilayer. It reveals the gapless phase-mode, the subgap Bardasis-Schrieffer modes and the above-gap scattering states. Our work paves the way for quantitative predictions of excited state phenomena from first-principles calculations in electronic systems with spontaneous symmetry breaking.

The accelerating digitization of economic activity has made information a dominant driver of market expectations, coordination, and systemic risk. Yet contemporary monetary systems remain anchored in architectures designed for material scarcity, institutional authority, or cryptographic constraint, leaving them increasingly misaligned with information-driven economies. This conceptual paper proposes Information-Backed Currency (IBC) as a monetary framework in which verified, high-integrity information functions as the primary source of value creation and monetary stability. Drawing on insights from econophysics, information theory, and cognitive economics, the paper advances the proposition that economic value emerges when information measurably reduces uncertainty within complex systems. Building on this premise, the study develops an architectural model in which currency issuance is linked to quantified entropy reduction achieved through multi-path information verification, reproducibility assessment, and contextual validation. An ethical governance layer, termed the Dharma Protocol, is introduced to ensure that only socially stabilizing, non-manipulative information qualifies as currency-backing input. The proposed IBC architecture comprises four interdependent layers: information ingestion, verification and validation, ethical oversight, and monetization through a Verification Value Unit tied to uncertainty reduction. While the framework is intentionally conceptual and non-empirical, it offers a coherent blueprint for re-imagining monetary governance in an era characterized by information abundance, cognitive constraints, and systemic fragility.

The PandaX-xT cryogenic distillation system for removing radon (Rn) is designed to operate at a high liquid flow rate of 856 kg/h, equal to 5 liters per minute (LPM), to meet the required Rn concentration. However, it is challenging to maintain a continuous supply of cooling power (20 kW) for the Rn-removal system. This work proposes a throttling refrigeration system to address the power supply problem for the next-generation PandaX-xT dark matter detection experiment. The system utilizes carbon tetrafluoride (R14) refrigerant to recover power based on heat pump principles. The cooling power from the liquid xenon (LXe) in the reboiler at 178 K is transferred to liquefy the gaseous xenon (GXe) in the cryostat through the phase change circulation of R14, enabling xenon (Xe) to return to the detector in the same state as when it was extracted. Consequently, a stable circulation for liquid distillation is established. Given the high cost of Xe, a research and development (R&D) experiment has been conducted to validate the feasibility of this high-cooling-recovery system by using ethanol as a substitute for Xe. Experimental results indicate that the proposed system could achieve a cooling power recovery of 25 kW, with a recovery efficiency of 99%+-0.5%. Additionally, process simulation and optimization of the throttling refrigeration cycle are performed using Aspen Hysys. The deviation between the simulation and experimental results is found to be <3.64%. These findings demonstrate that implementing Rn-removal distillation at a high flow rate is feasible, eliminating the need for liquid nitrogen or cryocoolers. This system could save approximately 3650 m3 of liquid nitrogen per year or reduce power consumption by 230 kW.

Data-driven surrogate models are increasingly adopted to accelerate vehicle design. However, open-source multi-fidelity datasets and empirical guidelines linking dataset size to model performance remain limited. This study investigates the relationship between training data size and prediction accuracy for a graph neural network (GNN) based surrogate model for aerodynamic field prediction. We release an open-source, multi-fidelity aerodynamic dataset for double-delta wings, comprising 2448 flow snapshots across 272 geometries evaluated at angles of attack from 11 (degree) to 19 (degree) at Ma=0.3 using both Vortex Lattice Method (VLM) and Reynolds-Averaged Navier-Stokes (RANS) solvers. The geometries are generated using a nested Saltelli sampling scheme to support future dataset expansion and variance-based sensitivity analysis. Using this dataset, we conduct a preliminary empirical scaling study of the MF-VortexNet surrogate by constructing six training datasets with sizes ranging from 40 to 1280 snapshots and training models with 0.1 to 2.4 million parameters under a fixed training budget. We find that the test error decreases with data size with a power-law exponent of -0.6122, indicating efficient data utilization. Based on this scaling law, we estimate that the optimal sampling density is approximately eight samples per dimension in a d-dimensional design space. The results also suggest improved data utilization efficiency for larger surrogate models, implying a potential trade-off between dataset generation cost and model training budget.

We present spectroscopic measurements of xenon luminescence in a time projection chamber operated in a dual-phase (liquid-gas) configuration. Thorium-228 $\alpha$ decays excited the liquid, resulting in the formation of singlet and triplet excimers that emit vacuum ultraviolet (VUV) scintillation. Ionisation electrons were drifted to the liquid surface and extracted into the vapour, where they produced VUV electroluminescence. A time-resolved photon-counting technique was used to obtain the scintillation spectrum in the liquid, which exhibited a peak wavelength of $177.1\pm0.1_\mathrm{stat} \pm0.1_\mathrm{sys}\,\textrm{nm}$ and a full-width at half maximum (FWHM) of $11.3\pm0.2_\mathrm{stat} \pm0.0_\mathrm{sys}\,\textrm{nm}$. The data were also used to obtain distinct singlet and triplet emission models, with the singlet emission peaking $1.8\pm0.3_{\mathrm{stat}}\pm 0.3_{\mathrm{sys}}\,\textrm{nm}$ shorter than the triplet. The gas electroluminescence spectrum was obtained simultaneously, while under conditions of thermal equilibrium. It remained consistent across vapour pressures of $1.3$-$2.2\,\textrm{bar}$, with a peak of $173.28\pm0.02_\mathrm{stat} {_{-0.1}^{+0.2}}{}_\mathrm{sys}\,\textrm{nm}$, a FWHM of $10.59\pm0.03_\mathrm{stat} {_{-0.2}^{+0.0}}{}_\mathrm{sys}\,\textrm{nm}$, and a small short-wavelength tail that constitutes $(0.6\pm0.1)$% of the total spectrum. These are the only spectroscopic measurements of liquid scintillation and gas electroluminescence acquired simultaneously to date, and the first such measurements of singlet and triplet emission in the liquid phase. They are important for precisely characterising dual-phase xenon detectors used to search for dark matter particle interactions and other rare events.

Can machine learning models identify which chemist made a molecule from structure alone? If so, models trained on literature data may exploit chemist intent rather than learning causal structure-activity relationships. We test this by linking CHEMBL assays to publication authors and training a 1,815-class classifier to predict authors from molecular fingerprints, achieving 60% top-5 accuracy under scaffold-based splitting. We then train an activity model that receives only a protein identifier and an author-probability vector derived from structure, with no direct access to molecular descriptors. This author-only model achieves predictive power comparable to a simple baseline that has access to structure. This reveals a "Clever Hans" failure mode: models can predict bioactivity largely by inferring chemist goals and favorite targets without requiring a lab-independent understanding of chemistry. We analyze the sources of this leakage, propose author-disjoint splits, and recommend dataset practices to decouple chemist intent from biological outcomes.

Quantum state readout with minimal resources is crucial for scalable quantum information processing. As a leading platform, neutral atom arrays rely on atomic fluorescence imaging for qubit readout, requiring short exposure, low photon count schemes to mitigate heating and atom loss while enabling mid-circuit feedback. However, a fundamental challenge arises in the single-photon regime where severe overlap in state distributions causes conventional threshold discrimination to fail. Here, we report an AI-accelerated Bayesian inference method for fluorescence readout in neutral atom arrays. Our approach leverages Bayesian inference to achieve reliable state detection at the single-photon level under short exposure. Specifically, we introduce a weakly anchored Bayesian scheme that requires calibration of only one state, addressing asymmetric calibration challenges common across quantum platforms. Furthermore, acceleration is achieved via a permutation-invariant neural network, which yields a 100-fold speedup by compressing iterative inference into a single forward pass. The approach achieves relative readout fidelity above 99% and 98% for histogram overlaps of 61% and 72%, respectively, enabling reliable extraction of Rabi oscillations and Ramsey interference results unattainable with conventional threshold based methods. This framework supports scalable, real-time readout of large atom arrays and paves the way toward AI-enhanced quantum technology in computation and sensing.

As superconducting circuits emerge as a leading platform for scalable quantum information processing, building comprehensive bridges from the foundational principles of macroscopic quantum phenomena to the architecture of modern quantum devices is increasingly essential for introducing new researchers to the field. This tutorial provides a self-contained, pedagogical introduction to superconducting quantum circuits at the undergraduate level. Beginning with an overview of superconductivity and the Josephson effect, the tutorial systematically develops the quantization of microwave circuits into the framework of circuit quantum electrodynamics (cQED). The transmon qubit is then introduced as a state-of-the-art application, with a detailed derivation of its Hamiltonian and its interaction with control and readout circuitry. The theoretical formalism is consolidated through a numerical simulation of vacuum Rabi oscillations in a driven transmon-resonator system, a canonical experiment that demonstrates the coherent energy exchange characteristic of the strong coupling regime. This work serves as a foundational guide and first point of contact, equipping students and researchers with the conceptual and mathematical tools necessary to understand and engineer superconducting quantum hardware.

This paper presents a rigorous mathematical analysis for symmetry-based Bound States in the Continuum (BICs) in optical waveguide arrays. Different from existing research, we consider a finite system of horizontally and equidistantly aligned waveguides and transform the wave propagation problem into Nonorthogonal Coupled-Mode Equations (NCME), rather than adopting the tight-binding approximation or orthogonal coupled-mode equations. We derive the exact expressions of the overlap integrals and coupling coefficients by utilizing the addition theorems of Bessel functions. We then generalize the discussion to an infinite waveguide array and rigorously characterize the dispersion relation and continuum with the help of theories in harmonic analysis. In the second part of the paper, we give a strict proof of the existence of BICs in the aforementioned waveguide system with two additional identical vertical waveguides aligned symmetrically above and below the horizontal waveguide array. We further numerically demonstrate the transition from a perfect BIC to a leaky mode by introducing a symmetry-breaking refractive index perturbation and quantitatively analyze the resulting radiation losses. This work gives a comprehensive study of symmetry-protected BICs and provides an efficient and precise computational model for designing such BICs devices.

Stationary take-off, without a running start or elevated descent, requires substantial aerodynamic forces to overcome weight, particularly for large birds such as geese exceeding 2 kg. However, the complex wing motion and high-Reynolds-number (Re $\approx$$10^5$) flow dynamics challenge conventional expectations of avian flight aerodynamics, rendering this mechanism elusive. Analyzing 578 stationary take-offs from seven geese (Anser cygnoides) and applying Principal Component Analysis (PCA), we reveal that the complex wing kinematics collapse onto a low-dimensional manifold dominated by two synergies: a Stroke Synergy responsible for fundamental rhythmic stroke, and a Morphing Synergy governing spanwise geometry. This modular control strategy orchestrates a stereotyped wing kinematics featuring an accelerated translational downstroke and a rapid tip-reversal upstroke. By integrating wing kinematic analysis with the mass distribution of the geese, we quantified the aerodynamic forces and found that entirely positive lift and thrust are generated throughout the motion cycle. The enhanced aerodynamic performance of geese takeoff results from three principal mechanisms. During the downstroke, significant lift generated from wing acceleration is predicted by the quasi-steady framework. Flow visualization reveals that wake capture further enhances the lift generation in downstroke by orienting the position of wake vortices. During the upstroke, the distal wing performs a rapid pitching motion and generates a substantial thrust, the vertical component of which contributes significantly to weight support.

Determining the relationship between nanoflare energies and their delays is the key for understanding the physical mechanism of the events and the plasma response. Nanoflares analyzed in this study were generated self-consistently via prescribed photospheric motions in a 3D multi-strand simulation of a subset of active region magnetic flux. Energies and durations were quantified using three distinct methods. In this study, we investigated the correlation between nanoflare energies (E) and delays ($\tau_D$) using two non-parametric, rank-based statistical tests. Across all methods, results consistently show little to no correlation. This is further supported by the distribution of the exponent $\alpha$ in the assumed relation $E \propto \tau_D^\alpha$, which peaks near zero, and by broad delay distributions within fixed energy bins. These findings are irrespective of whether delays are correlated with the energy of the preceding or subsequent event. They also hold for a subset of high-energy nanoflares. The absence of correlation suggests that nanoflare onset is not solely determined by a critical value of magnetic stress and may involve triggering by other events, perhaps related to a locally complex topology.

The magneto-Rayleigh-Taylor instability (mRTI) is a key process in inertial confinement fusion and is thought to be widespread in the interstellar medium, where it can concentrate plasma into discrete structures. We present resistive MHD simulations of the nonlinear evolution of multi-mode mRTI in both two and three dimensions, examining the effects of uniform external magnetic fields oriented either parallel or perpendicular to the initial interface. In both 2-D and 3-D, weak parallel fields enhance mixing-zone growth, whereas stronger fields suppress it. For perpendicular fields, growth is initially inhibited but becomes enhanced at later times. These behaviors arise from magnetic tension, which modifies flow anisotropy, buoyancy, drag, and vortex dynamics. The interplay of these mechanisms governs the distinct ways in which magnetic fields influence mRTI evolution.

Magnetocardiography system is a medical device that diagnoses cardiac disease by measuring magnetic fields generated from electric currents flowing through the myocardium. However, the accuracy of measurement data can be degraded if strong magnetic materials are present or magnetic field changes occur near the MCG system. With the widespread use of implants, the number of patients with metallic implants is increasing, but there is a lack of in-depth research on the potential impact of implant materials on the results of the MCG examination. This study aims to analyze the effect of implant materials on MCG measurements and establish relevant criteria. In this study, a 96-channel MCG system employing Superconducting Quantum Interference Device sensors, specifically first-order gradiometers based on the Double Relaxation Oscillation SQUID method, and a Magnetically Shielded Room were utilized. Ti6Al4V ELI was selected as the representative implant material sample. Experiments were conducted under extreme conditions, where a sample significantly larger than an actual implant was placed as close as possible to the sensors. As a result, when the implant material was at the minimum distance to the sensor, the noise increase was approximately 0.7 fT/$\sqrt{\mathrm{Hz}}$, which satisfies the sensitivity criteria for MCG. Furthermore, since these results were obtained under severely adverse conditions designed to maximize the noise impact, it is anticipated that the effect would be even more negligible in actual clinical settings. In conclusion, it was confirmed that common implant materials have little to no effect on MCG measurements. However, as the experiments were not conducted with the material inserted into the human body, unlike actual clinical environments, the generation of magnetic fields due to micromotion has not been verified, thus requiring further experimentation.

We study the response of a prototype Zero-Degree Calorimeter (ZDC) detector to irradiation equivalent to 10$^{11}$ 1-MeV $n_{\text{eq}}/\text{cm}^{2}$, which matches the expected exposure after one year of operation at full nominal luminosity at the future Electron-Ion Collider (EIC). The prototype, which consists of 563 channels and represents about 10 percent of the final ZDC design in terms of both channel count and detector volume, was irradiated at the NASA Space Radiation Laboratory (NSRL) at Brookhaven National Laboratory (BNL) with proton beams. We demonstrate that, despite significant radiation damage to the SiPMs and non-uniform degradation across the detector volume, the detector can be successfully calibrated on a channel-by-channel basis using cosmic-ray data. The damage profile, similar to what is expected in the experiment, varies by an order of magnitude or more across the detector. Even for the most heavily damaged channels, the signal-to-noise ratio for a MIP signal remains above 5. This study provides a realistic test of the system's performance under irradiation. It complements previous SiPM-specific irradiation studies and will inform the future operation of the ZDC and other detectors that use SiPM-on-tile technology.

We consider static linear elastic composite materials (CMs) with periodic structure. The core of the proposed methodology is the generation of a novel dataset using specially designed body force fields with compact support (BFCS), enabling a new RVE concept that reduces the infinite periodic medium to a finite domain without boundary artifacts. This functionally reduced RVE is used for translated averaging of direct numerical simulations (DNS) results, efficiently computed via a newly developed FFT-based solver for BFCS loading. The resulting dataset captures localized field responses and is used to train machine learning (ML) and neural networks (NN) models to learn effective nonlocal surrogate operators. These operators accurately predict macroscopic responses while reflecting microstructural features and nonlocal interactions. By accounting for field localization while simultaneously eliminating influences from finite sample size and boundary effects, it provides a physically grounded and data-driven framework for constructing accurate surrogate models for the homogenization of complex materials.

The construction of modern detectors used in high-energy physics experiments is typically guided by modeling with the Geant4 toolkit to evaluate detector performance in terms of geometrical acceptance and detection efficiency. Several hadronic models are available in Geant4 for modeling nuclear reactions induced by fast nucleons. It is shown that they result in different multiplicity and charge distributions of secondary particles and nuclear fragments. The impact of these differences on modeling the Highly-Granular Neutron Detector (HGND) prototype for the BM@N experiment at Nuclotron-based Ion Collider fAcility (NICA) is evaluated.

Wavefunction collapse is commonly associated with unavoidable physical disturbance of the measured system. Here we show that in driven-dissipative quantum systems, continuous measurement can induce strong trajectory-level collapse while leaving the ensemble-averaged steady state strictly invariant. We identify measurement-invariant steady states whose unconditional density matrix remains unchanged under continuous monitoring, despite pronounced measurement-induced localization in conditioned quantum trajectories. This separation between trajectory-level collapse and ensemble invariance defines a regime of partial collapse, in which measurement-induced localization is continuously counteracted by dissipative dynamics. We derive a necessary and sufficient condition for steady-state invariance under continuous measurement and identify Liouvillian symmetry as a concrete dynamical mechanism enforcing it. Our results clarify the distinction between conditional collapse and physical disturbance in open quantum systems and provide a framework for non-invasive continuous monitoring in driven-dissipative settings.

Understanding the intricate interplay between soot dynamics and chemical reactions within catalytic diesel particulate filters (CDPF) is crucial for enhancing both filtration efficiency and regeneration performance. In this paper, we establish a unified pore-scale multiphysics model based on the Eulerian-Lagrangian framework to comprehensively resolve the transport, deposition, and oxidation of soot. Distinguishing itself from conventional empirical correlations and stochastic-based approximations, the system models soot deposition through fundamental physical principles, integrating elastic deformation and surface adhesion mechanics at the particle-wall interface. Simultaneously, it incorporates a robust oxidation model that accounts for the competitive kinetics of both $\textrm{O}_2$ and $\textrm{NO}_2$ pathways, enabling comprehensive coverage of all CDPF operating regimes. Validated against three classical benchmark cases, the model demonstrates superior accuracy in capturing interfacial mass transfer and particle-wall interactions. Simulation under a typical CDPF low-temperature operating condition emphasizes the pivotal role of $\textrm{NO}_2$ and catalyst in promoting regeneration and reveals complex synergistic and competitive effects between distinct reaction pathways. Notably, the reaction rate of direct $\textrm{O}_2$ pathway is accelerated by a factor of 87 in the presence of the catalyst. For ultra-fine soot particles ($50~\mathrm{nm}$), the Brownian motion and thermophoretic forces directly dictate the deposition efficiency. Their strong thermal sensitivity also underscores the necessity for an integrated soot transport-deposition-oxidation framework. To support further research, the model implementation can be accessed at https://github.com/zhangyujing2001.

Many solid-state quantum platforms do not permit sharp, projective measurements but instead yield continuous voltage or field traces under weak, non-demolition readout. In such systems, standard Bell tests based on dichotomic projective measurements are not directly applicable, raising the question of how quantum nonlocality can be certified from continuous time-series data. Here we develop a general theoretical framework showing that Bell-CHSH inequality violation can be extracted from continuous, non-projective measurements without assuming any specific collapse model or phase distribution. We show that sufficiently long continuous measurements of a single entangled pair sample its internal phase-probability structure, enabling effective dichotomic observables to be constructed through phase-sensitive projections and coarse-graining. The resulting Bell correlator is governed by two experimentally accessible resources: intrinsic single-qubit phase spread and nonlocal phase locking between qubits. We benchmark the resulting estimator against conventional projective-measurement CHSH tests implemented via quantum-circuit simulations using Qiskit, finding quantitative agreement in the Bell-violating regime without parameter fitting. Classical deterministic correlations cannot violate the CHSH bound, whereas quantum phase-locked systems recover the nonlinear angular dependence characteristic of entanglement. Our results provide a practical route to demonstrating Bell nonlocality in platforms where measurements are inherently continuous and weak.

Ultrathin polymer-graphene heterostructures are promising materials for next generation optoelectronic and photovoltaic technologies, while the influence of the polymer's structural variation on interfacial charge transfer remains unclear. Here, using ab initio quantum mechanical calculations we show how different forms of Poly(3-hexylthiophene) (P3HT), a widely used organic semiconductor, interact with graphene. We analyze the effects of molecular chain length, end-group termination, periodicity, and the distinction between ordered and random P3HT arrangements. For isolated P3HT, the band gap decreases with increasing chain length and layer thickness, while structural disorder leads to slightly larger gaps due to reduced electronic coupling. When P3HT is deposited on graphene, all configurations exhibit spontaneous charge transfer, with electrons accumulating on graphene and holes remaining in the polymer. This effect is significantly enhanced in ordered and fully periodic structures and is noticeably weaker in disordered ones. Charge density analyses further show that thicker and more ordered P3HT layers improve electron hole separation across the interface. Our results reveal how molecular structure governs charge transfer in P3HT-graphene heterojunctions and provide practical guidelines for designing high efficiency polymer-graphene photovoltaic devices.

We describe combined experiments and simulations of droplet breakup during flow-driven interactions with a circular obstacle in a quasi-two-dimensional microfluidic chamber. Due to a lack of in-plane confinement, the droplets can also slip past the obstacle without breaking. Droplets are more likely to break when they have a higher flow velocity, larger size (relative to the obstacle radius R), smaller surface tension, and for head-on collisions with the obstacle. We also observe that droplet-obstacle collisions are more likely to result in breakup when the height of the sample chamber is increased. We define a nondimensional breakup number Bk ~ Ca, where Ca is the Capillary number, that accounts for changes in the likelihood of droplet break up with variations in these parameters. As Bk increases, we find in both experiments and discrete element method (DEM) simulations of the deformable particle model that the behavior changes from droplets never breaking (Bk << 1) to always breaking for Bk >> 1, with a rapid change in the probability of droplet breakup near Bk = 1. We also find that Bk ~ S^(4/3), where S characterizes the symmetry of the collision, which implies that the minimum symmetry required for breakup is controlled by a characteristic distance h ~ R.

A Quantum Computing Concept Inventory is needed for the acceleration of uptake of best practice in quantum computing education required to support the quantum computing workforce for the next two decades. Eight experts in quantum computing, quantum ommunication or quantum sensing were interviewed to determine if there is substantial non-mathematical content to warrant such an inventory and determine a preliminary list of key concepts that should be included in such an inventory. Developing such an inventory is a challenging task requiring significant international 'buy-in' and creativity to produce jargon-free valid questions which are accessible to students who are yet to study quantum mechanics.

A novel method combining the fully Lagrangian approach (FLA) and kernel regression has been developed for two-way coupled simulations of evaporating sprays. The carrier phase is incompressible viscous flow described by the Navier-Stokes equations. The admixture is considered to be a cloud of monodisperse evaporating droplets, which is treated as a continuum in the FLA. All droplet parameters are calculated along selected trajectories with the number density calculated using the Lagrangian form of the continuity equation. To enable two-way coupling, the momentum and mass phase exchange terms must be calculated in each volume element of an Eulerian mesh. This is achieved by using kernel regression in conjunction with the FLA trajectory data, which retains the detail of complex structures in droplet clouds by adaptively scaling the kernel support according to the local droplet field deformation. In this work, the mass and momentum coupling source terms obtained using the FLA are assessed against reference values calculated using a standard Lagrangian particle tracking simulation that incorporates a PSI-CELL box-counting method. It is shown that the FLA retains the same level of fidelity and smoothness as the reference PSI-CELL case, whilst also providing a computational speedup factor of around 100 times due to the decreased droplet seeding.

Radon is a naturally occurring radioactive gas that contributes significantly to human radiation exposure and must be controlled to avoid concentrations harmful to health. The paper presents an impulse-proportional ionization chamber that is suitable for the direct measurement of low radon concentrations in ambient air and achieves spectroscopic resolutions of 2-3%. This accuracy can be achieved through two novel principles. Firstly, the double-cylindrical, coaxial design of the IC allows for efficient, nearly complete detection of $\alpha$-radiation. Secondly, a customized measurement method for spectroscopic evaluation was developed to discriminate between the proportions of 222Rn, 218Po, and 214Po and extract their concentrations. Particular attention was paid to the energy resolution of the detection system by suppressing the effects of acoustic and vibration noise on the detector's operation. The high spectral resolution of the developed ionization chamber, with working volumes of 7.7l and 8.7l, enables measurements with uncertainties of less than 5% at 15-minute measurement times in ambient air with $50\,\mathrm{Bq/m^3}$ radon activity.

Quantum electrodynamics (QED) accurately describes all known forms of modern optics and photonics regarding interactions between photons and matter. While matter ranges widely from atoms, particles, to solids, photons are predominantly in a confined physical space, such as a pair of mirrors, for enhanced photon-matter interactions known as cavity QED. Since position and momentum are canonically conjugate variables governed by Heisenberg's uncertainty principle, a fundamental question arises - what if light confinement is in the not-so-intuitive momentum or reciprocal space? The realization of photonic bound states in the continuum (BICs) has made this exotic scenario possible. Here, we summarize the most recent advancements at this research frontier in optics and photonics, covering weak coupling, strong coupling, and nonlinear optics. We can designate such photon-matter interactions enabled by reciprocal light confinement through BICs with truly open systems as reciprocal QED, which holds great promise to comprehend and extend cavity QED for optics, photonics, and related fields.

We demonstrate a dual nanopore platform (DNP) containing a top 2D MoS2 pore in series with a 3 to 5 nm thick SiN pore, vertically separated by 30 nm, with diameters of 1.0 and 3.0 nm, respectively. This platform enables independent probing of analytes by each pore, thereby providing complementary information. We measure translocations of single amino acids (AA) and evaluate current blockades recorded across the two pores upon applying voltage. Small diameters ensured tight passage of individual AAs through the nanopores and provided a good signal-tonoise ratio (RMS current noise of 16 pA_RMS and SNR = 6). We focus on measurements of O-Phospho-L-tyrosine at 400 mV, demonstrating single amino acid detection and a good quantitative agreement with the calculated open pore and blocked currents. Based on these results, future device performance can benefit from slightly smaller pores, specifically the SiN pore, higher voltages and electrolyte concentration, and lower system noise.