Description of the dataset on alkoxycarbonylation catalyzed by supported palladium phosphide nanoparticles.

Left ventricular (LV) remodeling, whether occurring with somatic growth or as a chronic response to a sustained stimulus, is a primary factor underlying cardiac mechanical function. Although LV remodeling is a complex process that can be described at several levels, response variables that govern cardiac mechanics include changes in LV wall and chamber geometry, the mechanical properties of the LV myocardium, and LV structural mechanical properties such as LV chamber stiffness. We leverage two-dimensional speckle-tracking echocardiography (STE) to serially monitor key LV remodeling response variables in porcine models of LV pressure overload (LVPO), chronic exercise (CE), and the superposition of both settings (CE+LVPO), and compare changes to those occurring in age-matched referent control (RC) animals. Our findings show that over 28-days, LVPO and CE both induce hypertrophy, but passive LV myocardial stiffness increases with the former and decreases with the latter. As a net effect of geometrical and mechanical property changes, these settings induce divergent changes in LV chamber stiffness, namely, an elevation with LVPO and reduction with CE. In the CE+LVPO cohort, exercise was found to attenuate the LVPO-induced increase in LV myocardial and LV chamber stiffnesses. Data obtained were used to identify a phenomenological model of LV chamber stiffness and develop a predictive mathematical model of late changes in LV chamber stiffness based on early remodeling response variables irrespective of stimulus. Our findings support exercise in cardiac therapy and the use of STE to predict cardiac disease risk/progression.

• Determination of radiative properties of ceramic open-cell foams. • Parametric study on material and geometric properties. • Experimental validation of parameter identification. Since ceramic open-cell foams are mostly utilized in high-temperature applications, investigation of their thermophysical properties, regarding radiative heat transfer, is crucial. This study comprises a comprehensive characterization of the radiative properties of various ceramic foams, considering their specific scattering behavior. Spectroscopic measurements performed with a Fourier-transform infrared spectrometer are combined with a numerical parameter identification procedure to establish extinction coefficients and scattering albedos using appropriate scattering phase functions. Fundamental differences in the radiation behavior of the foams are demonstrated, depending on whether the struts behave as semi-transparent or opaque. A parametric study revealed the influence of several material and structural parameters on the spectral or temperature-dependent extinction coefficients. At room temperature, when all ceramics behave opaquely, extinction coefficients are affected by the surface reflectivity, but mainly by the geometric properties of the foams (porosity, pore size). In contrast to carbon-containing foams with nearly constant radiative properties, extinction coefficients of foams made of oxidic ceramics show a nearly linear increase with increasing temperature. Validation is achieved by comparing model predictions, using Rosseland diffusion approximation and identified radiative properties, with measurement results at up to 700 °C of the effective thermal conductivity obtained from the transient plane source method (Hot Disk). Deviations largely amount to ±10 % for a pure alumina, as well as differently coated foams, when considering appropriate sample thickness and anisotropic scattering. Besides confirming the reasonability of the identified radiative properties, the suitability of both measurement devices and the simplified modelling procedure for ceramic open-cell foams is thus demonstrated.

In pursuit of efficient organic light-emitting materials, we employed a rational design strategy to develop eleven cyanotriazine-based donor-π-acceptor emitters for thermally activated delayed fluorescence (TADF) applications. A comprehensive computational investigation using DFT and TD-DFT methods was carried out to evaluate their geometric and optoelectronic properties. The designed molecules are based on 4,4'-(6-phenyl-1,3,5-triazine-2,4-diyl)dibenzonitrile, where the dibenzonitrile unit acts as an acceptor and various donor units are introduced via a phenyl π-linker. Steric interactions between the donor units and π-linker induce twisted donor-acceptor geometries, which are favorable for TADF. Initial screening based on vertical excitation energies identified eight promising candidates with singlet-triplet energy gaps (ΔEST) below 0.3 eV. These systems were further analyzed in terms of spin-orbit coupling matrix elements (SOCMEs) and reorganization energies, which govern reverse intersystem crossing (RISC). Among the studied molecules, TZCN-PXZ, TZCN-PTZ, and TZCN-ICbz exhibit particularly favorable combinations of small ΔEST and enhanced SOCME values, indicating efficient TADF behavior. While nearly orthogonal geometries promote strong HOMO-LUMO separation and minimal ΔEST, moderately twisted conformations (≈70°) provide an optimal balance between ΔEST reduction and spin-orbit coupling enhancement via LE-CT orbital mixing. These findings establish clear structure-property relationships and provide useful design guidelines for developing high-performance TADF emitters.

Rhombic triacontahedron-based hexagonal discrete global grid systems (RTHDGGS) exhibit desirable geometric properties; however, their practical application is constrained by expensive cross-face computations and incongruent hierarchical subdivisions. To overcome these limitations, we propose a combined structure that merges three adjacent rhombic faces sharing one vertex and defines a triaxial integer coordinate system for unified spatial encoding. Building on this structure, we developed a multiscale model based on the aperture-4 hexagonal subdivision, including topological mapping rules for subdivision consistency and a coordinate conversion mechanism for efficient cross-scale aggregation and decomposition. Experiments show that the proposed method retains the geometric advantages of the icosahedron, improves adaptability to regions of interest, increases regional grid generation efficiency by approximately 2.3 times, and reduces hexagonal data aggregation error by 40% relative to previous methods. The proposed framework supports efficient and robust geospatial computing for large-scale Earth system applications.

This paper investigates the influence of interfaces on the performance of finite-sized mechanical metamaterial structures for vibration damping applications. The metamaterial structures are designed in a sandwich configuration in which two homogeneous plates are connected to a metamaterial array. We test four different arrays that are obtained from the same metamaterial by differently cutting the metamaterial’s unit cell at the metamaterial/plate interface. When the four unit cells are periodically repeated in space, they create the same infinitely large metamaterial with an identical mechanical response. In finite-sized structures, however, the different interfaces between the metamaterial array and the plates – called “material interfaces” – and between the metamaterial and the air – called “free interfaces” – strongly affect the specimen’s vibration transmission characteristics. Using experimental measurements and validated finite-element (FE) models, we demonstrate a significant influence of the different types of interfaces on the global responses and local displacement fields of the structures. We also demonstrate the presence of a vibroacoustic coupling in the structures which also depends on the type of metamaterial/plate interfaces. Furthermore, we explore optimization strategies for enhancing the vibration damping performance of the metamaterial structures considering not only the metamaterial array but also the adjacent structures, i.e. the homogeneous plates. A comparison with benchmark cases clearly illustrates the optimization potential that the interfaces’ design offers for the vibration damping capability of finite-sized metamaterial structures. We show that optimizing the type of targeted interfaces can shift a given metamaterial’s response from underperforming to significantly outperforming compared to classical solutions for noise and vibration damping in civil engineering. • Using a selected example of a composed metamaterial structure, we prove the influence of material interfaces and free interfaces on the behavior of the targeted metamaterial structure experimentally and in numerical simulations. • We show in detail how different types of interfaces influence the wave propagation in the metamaterial by comparing the local displacement fields of specimens which provide different boundary conditions and by assessing the resulting global dynamic behavior. • We analyze different factors that influence the behavior of the metamaterial structures: surrounding air, number of unit cells, geometric properties of connected structures. • We describe how the design of the interfaces and the aforementioned factors can be used to optimize the vibration damping performance of the metamaterial in the composed structure.

Computational and machine learning approach for nanoparticles-enhanced bio-heat transport with coupled effects of interparticle spacing and particles radius.

Anomalous topological Bloch oscillations under non-Abelian gauge fields

ABSTRACT The territorial networks that humans create are examples of cellular networks, a broad class of polygonal structures that share a consistent set of geometrical and topological properties. Hexagonal polygons predominate in cellular networks, but previous studies of territorial networks have failed to determine whether measuring polygon contact number provides useful information as to how the network evolved. Here we argue that this was due to a failure to integrate contact number measurements with an understanding of a network’s historical development. We analyse the contact number distribution of the English parish boundary network, uncovering a region of hexagonality that corresponds well to an area already known to be culturally and demographically distinctive in the early Middle Ages. Spatial variation in contact number in the English parish boundary network is shown not to be a simple function of topographical homogeneity and population density; instead, such relationships are mediated by spatial variation in tenurial and social systems. We conclude that the actual cause of hexagonality is more complex than often assumed in models of cellular network evolution, and that a holistic approach to the study of contact number can yield novel insights for landscape historians, historical geographers and spatial analysts.

Offshore jacket tubular members are continuously exposed to harsh marine environments, where corrosion significantly affects structural integrity. Therefore, accurate assessment of the residual axial resistance of corroded members is essential for ensuring safe operation and effective maintenance planning of offshore structures. This study proposes a data-driven analytical framework to examine the relationship between corrosion parameters obtained from ultrasonic thickness gauge (UTG) inspections and the residual axial resistance of offshore tubular members. Corrosion-related geometric descriptors extracted from inspection data are used as input features for several machine learning models, including Linear Regression, Random Forest, Support Vector Regression, and XGBoost. The axial resistance is calculated using the ISO 19902 based on the measured geometric properties. The results demonstrate strong predictive performance across the models (R² > 0.99) and confirm that effective thickness and geometric parameters dominate the residual load-carrying capacity. This study highlights the potential of machine learning as a complementary tool for interpreting field inspection data in the structural integrity assessment of offshore structures

The Flatland thought experiment, drawn from Abbott's 1884 novella and developed by Carl Sagan, has been increasingly applied to neurodiversity discourse and artificial intelligence ethics as a metaphor for constrained perception. The standard reading positions neurotypical cognition as the three-dimensional Sphere — the more complete, higher-dimensional observer — and neurodivergent cognition as the two-dimensional Square, generating a cross-section interpreted as disorder rather than difference. This article argues that this reading encodes the deficit model it was designed to challenge and introduces Epistemic Parallax as a novel theoretical construct to correct it. Epistemic Parallax is defined as the systematic displacement in meaning, classification, and judgment that arises when a cognitive system, institutional framework, or artificial intelligence observes neurodivergent experience from a non-parallel normative frame — producing distortions that are a geometric property of the observational relationship rather than a feature of the observed. The construct is distinguished from the Double Empathy Problem, institutional ableism, and algorithmic bias by its specification of mechanism over outcome and its applicability to non-adaptive systems that cannot self-correct through reciprocal interaction. Grounded in the Double Empathy Problem's empirical record, the full dimensional progression from point to tesseract, Intense World Theory, monotropism, and multidimensional sensory processing research, Epistemic Parallax is applied to AI in digital mental health to identify the deployment of neurotypically-trained systems as clinical arbiters of neurodivergent experience as a form of structural hermeneutical injustice in Fricker's precise sense. The Dimensional Parity Standard is proposed as the operational correction, comprising six criteria — bidirectional validation, cross-plane transparency, co-authorship of ground truth, relational deployment, dimensional humility, and a sixth principle extending the Feynman honesty framework developed in the companion article. Implications for regulatory policy, system design, and a three-priority research agenda are identified.

Starbursts are the light-intensity patterns seen when small bright sources are observed at low illumination levels, typically stars at night. Starburst patterns are formed because the eye's wave aberrations generate caustics at the retina. However, a fascinating yet unexplained fact about starbursts is that they usually exhibit p-fold symmetry. Moreover, the number of peaks, related to the symmetry perceived by the subject, is not always the same. The main aim of this study is to explain these visual optics phenomena. For this purpose, we provide a theoretical framework based on the geometric and algebraic properties of the wave aberration function expressed as a Zernike polynomial expansion. Specifically, we investigated the number and distribution of the fertile cusps of Gauss of the wave aberration function. We also established the connections between these points with the symmetries and the number of starburst peaks. We found that starbursts are likely generated by wave aberrations dominated by axially symmetric polynomials combined with a certain amount of non-axially symmetric ones. For instance, whereas a wave aberration with a dominant spherical aberration (Zernike polynomial [Formula: see text]) plus [Formula: see text] may induce a 3-peaks starburst with a 3-fold symmetry, a wave aberration combining [Formula: see text] and [Formula: see text] may induce a 4-fold symmetry starburst with four or eight peaks. In addition to providing a comprehensive explanation of starburst symmetries, our theory has other promising applications; for instance, we could infer some basic properties of an eye's wave aberration function from a measurement (subjective or objective) of the starburst pattern.

Single-Hessian Gaussian wavepacket dynamics (GWD) significantly reduces the computational burden of Heller's local harmonic GWD while maintaining comparable accuracy in approximating vibronic spectra. Here, we provide a new, symplectic derivation of the equations of motion of single-Hessian GWD and show that, unlike the local harmonic version, this method conserves the non-canonical symplectic structure on the manifold of Gaussian wavepackets and-for bounded dynamics in smooth potentials-avoids the drift of energy. Our numerical results suggest that, despite being much more efficient than the local harmonic variant, the single-Hessian GWD exhibits the same O(ℏ) asymptotic error in averages of observables. To further accelerate numerical simulations, we implement high-order time-stepping geometric integrators that are time-reversible and conserve the normand symplectic structure exactly, regardless of the time step. In addition, we present explicit expressions for the exact evolution of the width of a single-Hessian Gaussian wavepacket in a general potential, as well as for the exact evolution of the whole wavepacket in a global harmonic potential. Using on-the-fly abinitio Gaussian wavepacket dynamics on the first excited-state surface of ammonia, we numerically confirm the conservation of geometric properties by these integrators and demonstrate that high-order integrators can enhance both accuracy and computational efficiency. We also compute the photoelectron spectrum of the difluorocarbene anion and the absorption spectrum of methylamine and find that, in comparison with experiment, single-Hessian GWD outperforms global harmonic models and matches the accuracy of local harmonic GWD. Finally, we identify which spectral features are sensitive to the choice of reference Hessian.

The bulk circulation associated with convective clouds includes not only a region of updraft and cloudy air but also a region of compensating descent and cloud-free air, and horizontal motions coupling these regions. The Kinematic Representation of Non-rotating Updraft Tori (KRoNUT) model is a simple representation of this entire flow. First, the skill of the KRoNUT in representing flows from a high-resolution full-physics simulation of marine tropical convection is compared to various plume representations of convection. Then the KRoNUT is used to construct bulk descriptions of the dry dynamics of isolated and interacting convective circulations under the influence of advection and diffusion only . Cross sections of advective and diffusive tendencies show that while vertical advection of the vertical wind is the most important advective tendency in clouds, the horizontal component of the convective circulation and advection thereof plays a crucial role in the evolution of circulations in the absence of buoyancy. Strong curvature of the flow near the surface and near the updraft core results in locally strong diffusive tendencies that depend on scale. Cross sections of tendencies from the KRoNUT compare favourably to results from the simulation. Interacting circulations are shown to exhibit a wide range of dynamics, with some cases of interactions leading to unique stability of geometric properties of otherwise evolving flows and some leading to geometric clustering of circulation centres.

Abstract We study the free vibrations of two hanging strings that remain in mutual contact over a time-varying span and separated elsewhere. The contact is enforced by reversible Johnson–Kendall–Roberts (JKR) type adhesion, so the contact length is an unknown, time-dependent quantity. Using the variational approach, we derive the governing equations, boundary conditions, and a transversality condition that determines the contact length. As exact solutions are unavailable, we apply asymptotic analysis to obtain displacement fields and the motion of the contact point. Static equilibria appear above a critical adhesive strength and undergo a saddle-node bifurcation; one branch is unstable due to divergence instability, and the bifurcation point is independent of material, geometric, and adhesive properties. Two families of normal modes (NMs) emerge: one with fixed contact length (single string behavior) and one with contact-point motion. The associated eigenvalue problems (EVPs) are self-adjoint and the computed NMs satisfy orthonormality properties. Impulsive responses are examined based on the modal expansion. We have explored approximate solutions based on Ritz method which incorporates the moving contact, without invoking the transversality condition. This numerical framework validates the asymptotic predictions for equilibria, frequency spectrum, and contact point dynamics. We identify a counterintuitive threshold of the contact length for sustained oscillations and show that beyond these limits the strings separate irreversibly as t ∞ 8.

Nonconventional hydrogen bonds are attractive molecular interactions that can generate self-assembled, dynamic, yet robust, multifunctional hydrogen-bonded organic 2D and 3D frameworks (HOFs). To effectively create and manipulate such HOF structures requires detailed knowledge of their molecular geometrical ordering properties. Here, we employ scanning tunneling microscopy (STM) and X-ray crystallography to probe the differential control of C-H···O═C hydrogen bonding in the ordering of nonplanar tetraphenylethene (TPE)-based methyl ester derivatives at the solution/solid interface and in the solid state. The esters include the core structures of tetraphenylethene (Me4TPE), tetraphenylethene biphenyl (Me2TPDC), and tetraphenylethene tetrakis-phenyl (Me4ETTC), both meta- and para-substituted. At the solution/HOPG (highly ordered pyrolytic graphite) interface, the esters form surprisingly robust monolayer assemblies stabilized by a combination of multiple intermolecular C-H···O═C hydrogen bonds, π-π interactions, and molecule-substrate interactions. The proposed dominant C-H···O═C bonds involve cyclic motifs that show cooperative recognition together with bifurcated or three-centered hydrogen bonding geometries. Mostly similar conformations of C-H···O═C bonds exist in the solid state. Both molecular geometry and energetic parameters are found to complement each other in determining the extent and type of hydrogen bonding present in the tetraphenylethene-based methyl ester organizations at the solution/solid interface and in the solid state.

Sliding ferroelectricity in van der Waals materials shows great potential for designing robust memory devices. However, its thermodynamic behaviors and the coupling with certain quantum effects remain largely unexplored. Here, we demonstrate ferroelectric control over quantum nonlinear transport in a hexagonal boron nitride (hBN)-encapsulated twisted double-bilayer graphene moiré heterostructure. The ferroelectricity is attributed to the presence of rhombohedral stacking in the top hBN, confirmed by both electrical transport and optical second harmonic generation measurements. Remarkably, the polarization magnitude remains temperature-independent across 1.7-200 K, while nucleation time exhibits thermally activated behavior, decreasing with increasing temperature. Furthermore, we demonstrate a ferroelectric-switchable nonlinear Hall effect, attributed to the chiral scattering induced by Berry curvature, with outstanding fatigue-resistant and nonvolatility, demonstrating direct coupling between sliding ferroelectricity and quantum geometric properties. Our results establish sliding ferroelectrics as a platform for exploring electrically programmable Berry curvature physics.

To improve CO2 uptake in Biomass-Derived Activated Carbon (BDAC), this study develops a multiscale hybrid digital twin framework. By integrating microscopic descriptors from Density Functional Theory and Molecular Dynamics (DFT/MD) with experimental data from 63 chemically diverse biomass precursors, a Gaussian Process Regression (GPR) model was developed using the Matérn 5/2 Automatic Relevance Determination (ARD) kernel. The framework achieved high internal training accuracy (R 2 = 0.968) and Root Mean Square Error (RMSE = 0.2552), while providing a realistic generalization baseline across heterogeneous precursors with a 5-fold Cross-Validated (CV) R 2 of 0.1567 and CV RMSE of 0.283. Explainable Artificial Intelligence (XAI) identified a synergistic mechanism for pore filling, revealing the interaction between ln Brunauer-Emmett-Teller (BET) specific surface area and ln total pore volume (ln S BET × ln V total) as the primary mechanical driver (rank 1). Sensitivity analysis identified a maximum thermal window near 400 °C, with 800 °C identified as the critical sintering threshold where structural breakdown begins. Furthermore, the model validates the nonreliance theory of raw material, demonstrating that the geometric surface properties exert a more dominant influence on performance than the biomass origin. The model was effectively stabilized by Bayesian optimization at a minimum internal training loss of 0.065, providing a scalable, materials information-based scheme for using high-resolution virtual screening to accelerate the circular carbon economy.

Traditional acoustic energy-harvesting devices, constrained by their linear operating mechanisms, struggle to simultaneously achieve broadband capture of low-frequency sound waves and efficient electromechanical conversion. This study proposes a novel acoustic energy-harvesting meta-surface (AEHMS) capable of achieving acoustic energy collection through the coupling of a nonlinear Helmholtz resonator and an auxetic structure. This meta-surface exhibits subwavelength characteristics (thickness ∼ λ/12), with its core design philosophy centred on achieving physical cascading and synergy between acoustic and elastic functions: The Helmholtz resonator (HR) leverages its nonlinear acoustic response at high throat amplitudes (characterized and optimized via the Melnikov method) to broaden the acoustic energy capture bandwidth and surpass the energy input limits of linear systems; while the auxetic structure leverages its unique geometric deformation properties to convert the resonator-concentrated acoustic energy into high-density, uniformly distributed elastic strain energy, significantly enhancing the electromechanical conversion efficiency of piezoelectric materials. Experimental results demonstrate that at a centre frequency of 250 Hz and 100 dB sound pressure level, this AEHMS achieves an open-circuit voltage of 1.33 V (31 times higher than that of conventional piezoelectric beams) and an output power of 56.64 µW. This device has pioneered a novel theoretical approach for developing highly efficient, ultra-thin low-frequency acoustic energy-harvesting devices.

Three-dimensional (3D) rhombic zero-depth pores present a promising solution to the challenges associated with the requirement for ultrathin membranes in DNA sequencing. This study provides a comprehensive numerical analysis of 3D rhombic zero-depth pores formed at the intersection of triangular microchannels using finite element modeling. The model was validated with a mean absolute error of 2.75% between numerical and experimental results. We identified a critical channel length, beyond which pore conductance varies linearly with the diameter, vertex angle, and electrolyte concentration. We derived a mathematical correlation that provides a predictive framework for non-destructive pore size estimation without microscopy. As the vertex angle increases and the pore geometry approaches that of a 2D pore, its conductance converges toward the electrolyte conductivity. We also analyzed the electric field distribution, which influences signal amplitude and particle dwell time. Results showed maximum field intensity at the mid-plane origin along the Y-axis, with higher values at larger vertex angles and smaller pore diameters. Notably, the strongest electric fields occurred at the mid-points of the mid-plane sides, which we defined as critical points. We also derived equations that can determine the maximum electric field and effective length of the pore based on the applied voltage and the pore's geometrical properties. This study represents a significant advance in understanding zero-depth pores for future sensing and sequencing applications.