Papers

Predicting the evolving microstructure of hydrating cement is essential for understanding and modeling its mechanical property development. Physics-based continuum approaches offer a rigorous framework for capturing the thermodynamics of dissolution and precipitation processes at the microstructural scale. In this work, we present an adapted Phase-Field (PF) model for cement hydration that resolves key physical inconsistencies in existing PF formulations by introducing a revised free-energy potential and distinct equilibrium constants for clinker dissolution and hydrate precipitation. The resulting PF framework reproduces microstructural evolution, yielding realistic porosity levels and continuous phase boundaries in close agreement with experimental observations. The predicted hydrated microstructures are subsequently used in a computational homogenization scheme to evaluate the elastic response of the material. The PF-derived mechanical properties show good agreement with experimental trends, supporting the ability of the proposed framework to consistently link hydration chemistry, microstructure formation, and the resulting mechanical response.

Recently, the size-dependence of high-order harmonic generation (HHG) in quantum dots has been investigated experimentally. In particular, for longer driving wavelengths and QDs smaller than 3\,nm, HHG was strongly suppressed, however, there is no computational model capable of describing the strong-field response of such systems. In this work, we introduce a computationally efficient three-dimensional real-space tight-binding model specifically designed for the simulation of HHG in confined systems. The model parameters are meticulously derived from density functional theory (DFT) calculations for the semiconductor bulk, followed by a process of Wannierization. Our findings demonstrate that the proposed model accurately captures the observed dependency of the HHG yield on the quantum dot size. Additionally, we simulate the HHG yield for elliptically polarized pulses for different QD-sizes and driving wavelengths up to $5\,\mu{\mathrm{m}}$. The herein proposed model fills the theoretical void in simulating HHG within medium-sized nanostructures, which cannot be described by methods applied for periodic solids or small molecules or atoms.

Interferometric Particle Imaging (IPI) is a powerful technique to characterize aerosol particles, which so far has been applied only to particles larger than about 100 wavelengths. We extend its applicability to smaller ice crystals, combining rigorous modelling of particle shapes with the Phase Field Modelling and light-scattering simulations with the Discrete Dipole Approximation (DDA). Even for particles with the largest dimension of 11.5 wavelengths (and the smallest one comparable to the wavelength), the 2D Fourier transform of the interferometric image remains linked to the 2D autocorrelation of the particle shape at various viewing angles, validating the general measurement principle. However, the sensor must necessarily have wide viewing angle, which complicates interpretation of apparent particle shape, when such particles are observed from the edge. IPI is, thus, shown to be a powerful optical technology for characterizing ice particles down to a few micrometers in the atmosphere. Meanwhile, DDA is a versatile method for such synthetic experiments and can further supply large datasets for development of various inversion methods.

Lanthanide-based emitters are attracting increasing interest for their potential in high-performance OLEDs due to their narrow emission bands, high photostability, and functional versatility. However, their low radiative rates and poor charge transport properties remain key challenges for efficient device integration. Here, we report the design, synthesis, and characterization of dual-emissive Eu3+ - Yb3+ coordination compounds that exhibit temperature-dependent luminescence intensity ratios (LIR) between the visible and near-infrared regions. These materials enable simultaneous optical thermometry and electroluminescence, with LIR values showing excellent agreement with external thermocouple measurements over a broad temperature range. OLED devices incorporating these complexes demonstrate stable operation, and their luminescence properties are further enhanced by integration with engineered plasmonic metasurfaces. This integration leads to a significant increase in emission directionality and a reduction of the excited-state lifetime via Purcell enhancement, without compromising spectral integrity. Our findings highlight the promise of lanthanide-based coordination compounds as multifunctional emitters for next-generation optoelectronic devices and suggest new pathways toward intelligent OLED architectures with integrated sensing and directional control.

A spectroscopic study of a plasma deflagration accelerator was carried out to investigate the temporal evolution of plasma density within the pinch region. A half-meter imaging monochromator, paired with a fast (10 MHz) camera operating at 1 MHz, was used to collect broadened chord-integrated spectral lines from the pinch region of a plasma deflagration device. Specifically, images of the $H_{\beta}$ and the $H_{\alpha}$ lines were taken - with the $H_{\alpha}$ used to find the background continuum. Voigt fits of the Abel inverted H$_{\beta}$ emission lines allowed for determination of the radial profile of the number density in the pinch at intervals of 1 $\mu$s. This provided insight into the formation, growth, and decay of the pinch in both the deflagration and detonation modes of the accelerator. It was found that the maximum density for the deflagration increased from $\sim 10^{20}$ m$^{-3}$ 1.4 cm away from the core of the pinch to $\sim 10^{23}$ m$^{-3}$ at the core of the deflagration pinch. In contrast, the detonation pinch featured a broader zone of relatively constant density on the order of $\sim 10^{20}$ m$^{-3}$. Furthermore, an energy balance of the plasma in the deflagration pinch and downstream, as informed by prior work, was done to get an estimate of temperatures in the core of the pinch where measurements are not currently possible revealing potential temperatures on the 550 eV in the core of the pinch suggesting departures from some of the assumptions in the analysis.

We measure the ensemble transverse relaxation time (T2*) and spin-echo coherence time (T2) of the proton spin of HD molecules trapped in solid parahydrogen. By using high-purity parahydrogen matrices, we are able to measure significantly longer T2 and T2* times than seen in prior work. We also measure the longitudinal spin relaxation time T1. We examine how these parameters scale with the matrix purity and find limits on the coherence time from the parahydrogen matrix itself.

We present a high-order conservative, positivity-preserving, and non-oscillatory scheme for solving the Vlasov equation. The scheme attains formal fifth-order accuracy through a convex combination of positive and non-oscillatory polynomials in substencils. Nonlinear weights for these polynomials are formulated that assign higher priority to substencils with larger L2 norm to enhance resolution while maintaining positivity and non-oscillatory properties. An approximate dispersion relation indicates that the spectral properties of the present scheme outperform those of an underlying fifth-order scheme and even surpass those of a seventh-order scheme in certain wavenumber ranges. We apply this scheme to the one-dimensional Vlasov-Ampere equations and the two-dimensional Vlasov-Maxwell equations, and demonstrate high-resolution simulations with improved conservation of entropy.

The Sllod equations of motion enable modeling of homogeneous flow at the atomic scale, and are commonly used to predict fluid properties such as viscosity. However, few publicly available codes support such simulations, and those that do often do not implement a reversible numerical integration scheme or have other subtle problems. Here, we demonstrate a reversible and energy-conserving integration scheme for the Sllod equations of motion with error on the order of $\delta t^3$, in line with typical operator splitting integrators used in standard molecular dynamics simulations. We discuss various implementation details, and implement the scheme in LAMMPS where we find that our changes enable more accurate simulation of transient responses, mixed flows, and steady states, especially at high rates of flow. Importantly, we show that a lack of energy conservation can manifest as a systematic error in the direct ensemble average of the pressure tensor, leading to an error in the calculated viscosity which becomes significant at high flow rates.

The representation of buoyancy-driven turbulence in Reynolds-averaged Navier–Stokes (RANS) models remains unresolved, with no widely accepted standard formulation. A key difficulty is the lack of analytical guidance for incorporating buoyant effects, particularly under unstable stratification. This study derives an analytical solution of the standard $k$–$\omega$ model for Rayleigh–Bénard convection in an infinite layer, where turbulent kinetic energy is generated solely by buoyancy. The solution provides explicit scaling relations among the Rayleigh ($Ra$), Prandtl ($Pr$), and Nusselt ($Nu$) numbers that capture the simulation trends: $Nu \sim Ra^{1/3} Pr^{1/3}$ for $Pr \ll 1$ and $Nu \sim Ra^{1/3} Pr^{-0.415}$ for $Pr \gg 1$. This framework quantifies the discrepancies in the conventional buoyancy treatment and clarifies their origin. Informed by this analysis, the buoyancy-related modeling terms are reformulated to recover the measured trends: namely $Nu \sim Pr^{1/8}$ for $Pr \ll 1$ and $Nu \sim Pr^{0}$ for $Pr \gg 1$ at moderate $Ra$. Only two dimensionless algebraic functions are introduced, which vanish in the absence of buoyancy, ensuring full compatibility with the standard closure. The corrected model is validated across a range of buoyancy-driven flows, including two-dimensional Rayleigh–Bénard convection, internally heated convection in two configurations, unstably stratified Couette flow, and vertically heated natural convection with varying aspect ratios. Across all cases, the corrected model provides significantly improved predictions of mean temperature fields and turbulent heat flux distributions.

The ability to switch and program the spectral response of quantum modes via deterministically located plasmonic nanoantennae presents opportunities for wide spectrum of applications from biosensors to quantum computing. Due to its topology, toroidal nanoantenna (TNA) focuses immense amount of three-dimensional (3D) local electric field by toroidal moment while allowing pre and post positioning around quantum emitters (QEs). Here, within local-response finite difference time domain (FDTD) simulations, we demonstrate high-contrast spectral switching of the radiative decay channel of a dipolar QE coupled to a TNA by introducing effective Lorentzian quantum objects (QOs). At optimized TNA geometries, Fano interference between the broadband plasmonic continuum and narrow quantum transitions of QOs suppresses both radiative and non-radiative decay channels near 850 nm, yielding an observable full switching that traps energy within the hybrid mode instead of re-emitting it. To show the promises of the concept, we further demonstrate systems with multiple QOs where spectral degeneracy enhances the transparency bandwidth, while detuning generates distinct minima, enabling individually addressable spectral responses. These results establish plasmonic TNAs as promising architectures for spectral detection and individual mode switching of single- or multi-QO configurations and empowers the user for the implementation of photonic processing of continuous photon sources.

We study the van der Waals-London force, which is typically associated with fluctuating electric dipoles in atoms, in a mesoscopic circuit consisting of two inductively coupled superconducting loops. We investigate the inductive van der Waals-London interaction using both semiclassical and quantum electrodynamic (QED) approaches. The semiclassical model predicts a repulsive interaction due to anticorrelated current fluctuations. In contrast, the QED framework, which incorporates virtual photon exchange, reveals a predominantly attractive force. A key contribution comes from a state-independent two-photon exchange, which is absent in the semiclassical description and undetectable by spectroscopy. Our study introduces a theoretical framework for exploring the van der Waals force between individual artificial atoms via controlled mesoscopic circuits.

Adaptive mesh refinement (AMR) reduces computational costs in CFD by concentrating resolution where needed, but efficiently embedding complex, non-aligned geometries on GPUs remains challenging. We present a GPU-native algorithm for incorporating stationary triangle-mesh geometries into block-structured forest-of-octrees grids, performing both solid voxelization and automated near-wall refinement entirely on the device. The method employs local ray casting accelerated by a hierarchy of spatial bins, leveraging efficient grid-block traversal to eliminate the need for index orderings and hash tables commonly used in CPU pipelines, and enabling coalesced memory access without CPU-GPU synchronization. A flattened lookup table of cut-link distances between fluid and solid cells is constructed to support accurate interpolated bounce-back boundary conditions for the lattice Boltzmann method (LBM). We implement this approach as an extension of the AGAL framework for GPU-based AMR and benchmark the geometry module using the Stanford Bunny (112K triangles) and XYZ RGB Dragon (7.2M triangles) models from the Stanford 3D Scanning Repository. The extended solver is validated for external flows past a circular/square cylinder (2D, $Re = 100$), and a sphere (3D, $\text{Re}\in\{10, 15, 20\}$). Results demonstrate that geometry handling and interpolation impose modest overhead while delivering accurate force predictions and stable near-wall resolution on adaptive Cartesian grids. The approach is general and applicable to other explicit solvers requiring GPU-resident geometry embedding.

We propose a time series analysis framework focused on higher-order temporal correlations in the event sequence beyond the interevent time distribution by employing the burst-tree decomposition method. Bursts are clustered events that rapidly occur within shorter time periods, and they are separated by relatively longer inactive periods. The burst-tree decomposition method exactly maps the event sequence onto a tree, called a burst tree, in which each internal node represents a merge of consecutive bursts at the timescale separating those bursts. The burst tree fully reveals the hierarchical structure of bursts, hence the higher-order temporal correlations for the entire range of timescales. Those correlations are quantified using novel and existing measures derived from the burst tree, such as the burst complexity, memory coefficient for bursts, and principal and secondary cross sections of the burst-merging kernel. We apply our framework to the heartbeat time series of healthy people and of those with heart disease to reveal distinct multiscale temporal properties in physiological time series.

Understanding efficient fish locomotion offers insights for biomechanics, fluid dynamics, and engineering. Traditional studies often miss the link between neuromuscular control and whole-body movement. To explore energy transfer in carangiform swimming, we created a bio-inspired digital trout. This model combined multibody dynamics, Hill-type muscle modeling, and a high-fidelity fluid-structure interaction algorithm, accurately replicating a real trout's form and properties. Using deep reinforcement learning, the trout's neural system achieved hierarchical spatiotemporal control of muscle activation. We systematically examined how activation strategies affect speed and energy use. Results show that axial myomere coupling-with activation spanning over 0.5 body lengths-is crucial for stable body wave propagation. Moderate muscle contraction duration ([0.1,0.3] of a tail-beat cycle) lets the body and fluid act as a passive damping system, cutting energy use. Additionally, the activation phase lag of myomeres shapes the body wave; if too large, it causes antagonistic contractions that hinder thrust. These findings advance bio-inspired locomotion understanding and aid energy-efficient underwater system design.

Terahertz (THz) wave manipulation based on laser filaments-plasma channels formed by femtosecond laser-induced air ionization-has emerged as a promising platform for free-space THz applications. However, in-situ characterization of the spatially confined THz modes within filaments faces significant challenges due to the plasma's ultra-high intensity, which not only hinders direct near-field probing but also limits reliance on indirect far-field reconstruction. Here, we introduce a non-invasive near-field modulation scheme where a metal plate approaches the filament at submillimeter distances (comparable to THz wavelengths), perturbing the dielectric environment to convert the symmetric annular THz mode into an asymmetric state. This controlled transition enables far-field detection of broadband calculus behaviors (first- and second-order differentiation/integration) on time-domain THz waveforms and characteristic spectral transfer functions with 1/f, 1/f^2, f or f^2 dependency (where f is the THz frequency), thereby diagnosing the near-field THz mode confinement. Hence, the proposed approach synergizes near-field modulation efficiency with far-field detection robustness, advancing fundamental understanding of plasma-THz interactions and enabling novel all-optical signal processing for filament-based THz technologies.

We present a new holographic approach for generating large scale, polarization resolved optical tweezer arrays. By analyzing the ideal Jones fields that realize a target pattern, we identify that the fundamental degrees of freedom are the relative phases of the individual tweezers, rather than the full spatial phase profile. Leveraging this insight, we formulate a reverse projection optimization that adjusts only a small set of phase parameters to approximate the ideal operator within the physical constraints of a metasurface. This produces significantly higher fidelity and robustness than Gerchberg_Saxton type algorithms. Experimentally, we demonstrate H, V, L, and R polarized tweezer arrays using a single layer metasurface. A key advantage of our method is its phase stability, yielding strong resistance to optical aberrations and enabling coherent global phase modulation such as forming vortex tweezer lattice, without degrading trap quality. This framework provides a conceptually clear and experimentally powerful route for scalable optical field synthesis.

The relation between gravity and quantum mechanics is investigated in this work. The link is given by the wave packet expansion process, rooted from the Uncertainty Principle. The basic idea is to express the de Broglie wavelength used by Schrodinger for a massive particle in terms of the associated Compton wavelength which is replaced by the Michell-Laplace radius $Gm/c^{2}$ of the spherical object of mass $m\geq m_{P}$, where $m_{P}$ is the Planck mass. The wave packet spreading is studying in spherical coordinates, having the width $\sigma(t)$, expressed in terms of $G$ and $c$ instead of $\hbar$. Therefore, for masses larger than the Planck mass, a faster dispersion rate of $\sigma(t)$ is obtained, compared to the standard case. The dispersion of the wave packet is observed only by a free falling observer and the process breaks down once the observer hits the surface of the object. Different freely falling observers notice different rates of expansion of the wave packet and the source of gravity is in a quantum superposition. We further confront the Mita formula for the mean energy of the wave packet with the de Broglie-Bohm quantum potential energy when the Schrodinger equation is expressed in the Madelung form.

This research tries to understand how seat capacity on routes connecting 267 African cities is distributed across airlines by analysing supply decisions between 2016 and 2022. The paper compiles an Africa-specific database on seat capacity by origin-destination pair and year, using revealed preference data for one week in November each year extracted from the Official Aviation Guide (OAG). Supplemented with socio-economic and historical data such as GDP per capita, market size, predominant language, and colonial ties, the research applies the extended Multiple Discrete-Continuous (eMDC) choice model. The model results show that African carriers are, indeed, the ones offering the best connectivity for intra-African travel, but they also show less flexibility in their route networks. As expected, there is significant preferential treatment for national carriers regarding serving their home countries. The study highlights the structural and regulatory barriers that continue to constrain intra-African air connectivity, despite policies such as the Yamoussoukro Decision, designed to liberalise the sector. The dominance of airlines in serving only their home markets suggests a lack of cross-border cooperation and competition, limiting the potential for an integrated, efficient African aviation market. This not only restricts mobility across the continent but also hampers broader economic growth. The model estimates are statistically significant at a 95% confidence level, supporting the use of these findings for informed policy and strategic decision-making. This paper represents the first application of discrete-continuous modelling using capacity-supply data within the African aviation context and offers policy-relevant insights into improving air connectivity.

This study presents an analysis of modern open-source large language models (LLMs) – including Llama, Qwen, and Gemma – to evaluate their encoded knowledge of Quantum Chromodynamics (QCD). Through reverse engineering of these models' representations, we uncover the naturally idiosyncratic patterns in how foundational QCD concepts are embedded within their parameter spaces. Our methodology combines targeted probing techniques and knowledge extraction protocols to assess the models' understanding of critical QCD principles like color confinement, asymptotic freedom, and the running coupling constant. This work provides a tool for utilizing LLMs as an assistant in physics research, while also highlighting current limitations in their representation of advanced quantum field theory concepts that future model development should address.

A recently introduced two-phase flow model by Chun Shen is studied in this work. The model is derived to describe the dynamics of immersed water bubbles in liquid water as carrier. Several assumptions are made to obtain a reduced form of the mathematical model. The established model consists of nonlinear coupled PDEs in which the unknowns are the densities of the liquid and gas phases and the velocity of the liquid phase; these depend on space and time. For numerical purposes a one-dimensional space–time coordinate system $(x,t)$ is considered. Using the Python programming framework, several Riemann-type initial value problems for the two-phase flow model are solved numerically. A comparison of three finite-difference schemes is presented in order to examine their performance: the Lax–Friedrichs scheme, the Lax–Wendroff scheme, and the FORCE scheme. The FORCE scheme is total-variation diminishing (TVD) and monotone and does not create oscillations. As expected, the numerical solution of the Riemann problems consists of combinations of smooth profiles, shock waves, and rarefaction waves.

The analogy between free-electron lasers (FELs) - laboratory devices which generate intense coherent light with tunable frequencies - and whistler wave-particle interactions in the magnetosphere has recently been extended to account for waves with spatially dependent amplitudes and a spectrum of frequencies. The whistler was found to be governed by one of the most well-studied nonlinear equations in physics, the Ginzburg-Landau equation (GLE), which can be used to predict the complex nonlinear physics of multi-mode interactions. In this study, we focus on the single-mode solutions of the GLE and investigate their propagation and stability in the context of magnetospheric chorus. As with FELs, there are two types of instabilities, the Benjamin-Feir instability, where all single modes are unstable, and the Eckhaus instability, where there is a band of stable modes, but all modes outside of the band are unstable. Both stability conditions are given by well known inequalities in the GLE literature. For whistler-mode chorus, we analytically reduce the inequalities to simple expressions and show that, to the extent that the GLE represents magnetospheric chorus, it is Benjamin-Feir stable. We also derive the width of the Eckhaus stability band. We find that the predicted bandwidth is consistent with in situ satellite observations and support our analytical calculations with numerical simulations of the GLE. Our simulations demonstrate the robustness of the stable modes, the evolution from unstable modes to stable ones, and the tendency for mode condensation, whereby a noisy spectrum of modes tends to relax to a single stable mode.

The elevation of Mount Rainier was last surveyed in 2010 by the Land Surveyors Association of Washington. More recent LiDAR data and observational reports have indicated that the historical highest point on the mountain, Columbia Crest, has lost a significant amount of elevation and may no longer be the highest point. This report documents the results of multiple ground surveys conducted in August and September 2024 to determine the current elevation of Columbia Crest and the current elevation and location of the summit of Mt Rainier. On August 28, 2024, a Promark 220 differential GPS unit was used to measure the elevation of Columbia Crest and the Southwest Rim, two recognized historical local maxima on the rim of the summit caldera. Columbia Crest is a year-round ice-capped locality, while the Southwest Rim melts to rock each summer. Measurements were corroborated with Abney level measurements and LiDAR data from 2007 and 2022. On September 21 and 22, 2024, additional ground measurements were taken with the Promark 220 of the Summit 2 USGS monument location and of the highest rock on the Southwest Rim. Additionally, the three USGS monuments lower on the mountain (Muir, McClure, and Paradise) were measured. These measurements were used to corroborate the summit measurements. Monument measurements were found to be consistent with 2010 measurements. Southwest Rim summit measurements were consistent from August and September. Columbia Crest, last measured at 14,411.0ft (NGVD29) in 1998, was measured to have lost 21.8ft of elevation. Now the ice-capped Columbia Crest is no longer the summit of Mt Rainier. The summit is now on the seasonally rocky Southwest Rim, next to the Summit 2 USGS monument location. (The physical monument was not located and has likely been stolen). The new summit elevation of Mount Rainier is 14,399.6ft +/-0.1ft NGVD29 (14,406.2ft +/-0.1ft NAVD88).

The projected rapid growth of battery cell production over the next decade demands advanced diagnostic tools for quality control, ageing prediction, and recycling. Most existing techniques lack the spatial and temporal resolution required to capture internal electrochemical processes non-invasively. Here, we present magnetic imaging of current densities in battery cells, a sensitive quantum-magnetometry method that uses optically pumped magnetometers (OPMs) to perform real-time imaging of internal dynamics in open-circuit configuration. We demonstrate this approach for monitoring relaxation processes in 6000 mA h lithium-ion cells following pulsed discharges across a range of pulse durations and currents as well as states of charge. The measurement results are benchmarked against superconducting-quantum-interference-device (SQUID) magnetometry and validated with three-dimensional finite element simulations. Equivalent circuit models are employed to interpret the relaxation profiles, revealing spatially resolved features and transient magnetic-field signatures that are inaccessible with complementary non-invasive techniques such as electrochemical impedance spectroscopy (EIS). This work establishes OPM-based magnetic imaging of battery current density as a powerful diagnostic tool with potential impact on cell development, manufacturing quality assurance, and second-life assessment.

We present a variational quantum algorithm that solves the one-dimensional diffusion problem with a space-dependent diffusion constant $D(x)$. This problem is relevant for the exchange of hydroxide ions across a two-layer membrane in an alkaline electrolyzer, where the concentration of OH$^-$ ion determines the chemical stability for longer time periods. We use $16$ to $64$ grid points across the membrane, resulting from $n=4$ to $6$ data qubits for the ideal statevector and shot-based quantum simulations implemented using Qiskit. For these qubit numbers, the depth of the parametric quantum circuit has been chosen to ensure sufficient expressibility. The state preparation requires particular attention since the diffusivity $D$ is piecewise constant in the different layers with discontinuities at the interface. Furthermore, we compare different classical optimization schemes with respect to their convergence in the VQA method. We demonstrate the applicability of the quantum algorithm to a problem with non-trivial boundary conditions and jump conditions of the diffusion constant and outline possible extensions of the proof-of-concept application case of quantum computing. Our simulations show that pronounced hydroxide ion concentration gradients, and thus chemical instabilities, can occur only when the ratio of diffusivity in both layers of the membrane exceeds approximately 50.

Woven shell structures are beneficial for applications requiring lightweight, damage resilience, and design tunability, such as in wearable devices, soft robotics, and aerospace systems. A fundamental component of woven structures is the woven column. While the mechanical properties of a woven column can be determined using sophisticated finite element (FE) simulations, these FE models are computationally expensive and do not explain the underlying mechanics behind scaling relationships. In this work, we derive purely analytical models for the buckling load and stiffness of woven columns, and discuss the criteria that lead to different buckling modes of the woven columns. The simulated results based on our models closely match experimental data across various weave design parameters. This work advances our understanding of the mechanics of woven systems and serves as a baseline for the design of next-generation hierarchical structures and materials.

The phenomenon of Entangled Two-Photon Absorption (ETPA) presents a persistent controversy in the literature, evidenced by a wide disparity in the reported values for the $\sigma_E$ cross-sections. Much of this discrepancy is attributed to the difficulty in discriminating ETPA from various background processes that can mimic its signal, such as linear absorption or scattering. Given this need to certify the presence of ETPA unequivocally, this work introduces a key strategy to isolate the ETPA contribution through its spectral signature. This involves modeling the molecule as a two-photon notch filter and inducing a controlled asymmetric overlap with the joint spectral intensity (JSI) of the incident photons. This asymmetry is used to generate a measurable distortion in the transmitted JSI, and, complementarily, as a reduction in the visibility of the Hong-Ou-Mandel (HOM) dip. To ensure the experimental feasibility of this technique, a comprehensive analysis of the experimental conditions required for its detection is presented, establishing the absorption efficiency limits that must be overcome given the constraints of entangled-photon-pair flux and detector noise. A preliminary experiment addressing the ETPA detection limits using the standard RhB dye is presented.

We report an optimized implementation of spectral-domain quantum optical coherence tomography (SD-QOCT) capable of acquiring axial scans (A-scans) of multilayer samples without in the absence of mechanical scanning, at an unprecedented speed. We demonstrate a proof-of-concept system that integrates a diffraction grating, a high-resolution intensified CCD camera, and a high-flux photon-pair source operating in the VIS-NIR region (810 nm). This configuration enables the acquisition of an entire marginal SD-QOCT interferogram in a single camera exposure, yielding a transverse A-scan with a record acquisition time of 100 ms and a penetration depth of 4 mm. The measured interferometric response shows excellent agreement with the theoretical model. These results represent a decisive step toward the practical deployment of SD-QOCT as a competitive imaging modality for biomedical applications.

There is increasing evidence that numerous membrane proteins can assemble into aggregates that modulate their function and affect many cellular processes such as signal transduction and endocytosis. Here, we present a theoretical description of the instantaneous translational diffusion coefficients of transmembrane protein aggregates on free and supported lipid membranes using Kirkwood-Riseman theory. We find that hydrodynamic interactions within protein aggregates must be accounted for, as neglecting them yields several times lower diffusion coefficients. By deriving hydrodynamic radii for free and supported lipid membranes, we identify effective length scales that accurately characterize aggregate diffusivities in the presence of hydrodynamic interactions. These findings motivate the approximation of an aggregate by its outline and a random particle distribution inside it. We show that this approach provides a practical method to accurately determine aggregate diffusion coefficients when the particle locations cannot be resolved. The results presented in this article have immediate implications for the formation and function of membrane protein aggregates.

Growing interest in decarbonization and Arctic accessibility has renewed attention on Europe-Asia shipping corridors. The Northern Sea Route (NSR) is often portrayed as a 30-40% shortcut relative to Suez, with savings propagated to time, fuel, and CO2. The effect of enforcing sea-only feasibility on these baselines, and its downstream impact on time, fuel, and CO2, remains under-examined. We compare great-circle baselines with sea-only routes computed via A-star search (A*) on a 0.5-degree grid between Northern Europe and Northeast Asia across the Suez, Cape of Good Hope, and NSR corridors under three waypoint philosophies. Distances are mapped to voyage time using corridor-typical speeds and to fuel/CO2 using main- and auxiliary-engine accounting. Sea-only routing preserves the ranking NSR < Suez < Cape but compresses NSR's advantage once realistic speeds are applied. NSR remains shortest (about 8000-10000 nm versus 11000-12000 nm for Suez), yet typical durations differ modestly and fuel/CO2 savings over Suez are small and variant-dependent. Equal-speed tests restore geometric ordering, and endpoint sensitivity shows larger NSR gains for more northern East Asian ports. The framework provides a reproducible, corridor-agnostic benchmark for later integration of sea ice, weather, regulatory overlays, and AIS data in dynamic Arctic voyage planning.

First-principles DFT calculations on the hydrides Ca2NiH6, Sr2NiH6, and Ba2NiH6 reveal key thermodynamic properties. These compounds exhibit increasing entropy and heat capacity with temperature, and are thermodynamically stable at elevated temperatures due to negative free energies. The kinetics of hydrogen storage is influenced by entropy changes during hydrogen adsorption and desorption. Optically, Ba2NiH6 shows a high refractive index at low energies. Mechanical assessments indicate Sr2NiH6 is incompressible with moderate malleability, Ca2NiH6 has the highest resistance to deformation, while Ba2NiH6 is most compressible. Formation energies and hydrogen storage capacities (4.005 wt% for Ca2NiH6, 2.548 wt% for Sr2NiH6, and 1.750 wt% for Ba2NiH6) highlight Ca2NiH6 as the most promising candidate for hydrogen storage technology.