The European Physical Journal E最新文献

This study presents an extensive graph-theoretic analysis of the thermodynamic properties of indium telluride (InTe). We analyze the significant relationship between the molecular structure of InTe and its macroscopic behavior through the application of graph entropy, a fundamental metric in information theory and statistical thermodynamics. In this framework, the chemical structure is depicted as a graph, with atoms as vertices and chemical bonds as edges. We calculate a set of topological indices for InTe, a material that is very useful in thermoelectrics, phase-change memory, and infrared optics. These indices encode the material’s structural connectivity in numbers. These indices are used to figure out a range of graph entropies, which measure how complex and information-rich the molecular lattice is. The main part of this work shows strong quantitative links between these graph entropies and important thermodynamic properties, such as heat capacity and heat of formation. We use suitable quadratic surface-fitting models that show exactly how these thermodynamic responses depend on pairs of graph entropies in a nonlinear way. All computational modeling and analysis are conducted to enhance statistical fit, guaranteeing that the chosen models deliver the most dependable predictive capability for comprehending and anticipating the material’s stability and thermal characteristics.

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This short paper is a perspective article related to the seminal paper: S. Arditty, C. P. Whitby, B. P. Binks, V. Schmitt & F. Leal-Calderon “Some general features of limited coalescence in solid-stabilized emulsions” published in 2003 (Arditty et al. in Eur. Phys. J. E 12:355, 2003). I will first briefly recall the work described in this paper and discuss some of the developments that followed its publication. This will include comparisons with different coalescence mechanisms, together with comparisons with surfactant-stabilized emulsions and with particle-stabilized foams. I will end with a few comments on the state of the field of research and on future directions.

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We studied the surface morphology (micro- plus nanostructure) of Indian carpenter bee wings. In comparison with the Stenocara beetle’s surface morphology or the lotus leaf surface morphology, the Indian carpenter bee wing shows a different type of surface morphology. It is observed that the two-tire surface morphology of the wings plays a key role in controlling wettability. The equilibrium contact angle (θ) and contact angle hysteresis (Δθ) measurement revealed that the carpenter bees’ wings behave as superhydrophobic and self-cleaning for large water drops. Small drops formed by condensation nucleate in microchannels and ridges, grow through condensation and coalescence, and eventually become larger Wenzel or Wenzel–Cassie–Baxter type drops that lose their superhydrophobicity and self-cleaning property. Growth dynamics of condensed water drops on the wing surface show two distinguishing growth laws < R >  ~ t^α, α = 0.41 ± 0.03 in the initial state and < R >  ~ t^α, α = 0.99 ± 0.03 in the self-similar (coalescence-dominated) state with maximum surface coverage ≃ 0.45.

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Fluid mechanics governs numerous physiological processes in the respiratory system, influencing airflow dynamics, particle transport and aerosol formation, airway stability, mucus transport, surfactant mechanics, and pulmonary oedema. Over the past decades, engineers, physicists, and biomedical scientists have developed a wide range of models to describe these processes across multiple spatial and temporal scales. This paper provides an integrated overview of current modelling techniques in pulmonary fluid mechanics, emphasizing the multiscale and multiphysics nature of the lung. After discussing the principal challenges in simulating the mechanics of human lungs, we review the hierarchy of modelling approaches, from first-principle continuum formulations to reduced-order and data-driven models. We then explore strategies for coupling these models and conclude with a perspective on future directions, including the need for benchmark cases and clinically robust indicators for model validation.

The cytoskeleton is an essential cell component. Many cellular processes that require changes in the cell structure depend on it. One of these processes is cell migration, which occurs through the formation of structures called protrusions that interact with other cytoskeletal components, enabling the cell to move slowly. These structures are formed by the polymerization of actin monomers, a process that requires the presence of ATP, as well as the exchange of divalent cations. In this work, we present a study on the formation of actin protrusions within DMPC giant unilamellar vesicles by varying the concentration of ATP, both in the absence and presence of MgCl₂. It was found that when the concentration of ATP in the overall protein buffer increases, these structures form and extend inside the vesicle without breaking it, even in the absence of MgCl₂. These protrusions are randomly oriented; however, when an alternating current electric field is applied, the protrusions align in the direction of the field in response to the polar nature of both lipids and actin filaments.

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The mechanical behavior of single-stranded DNA (ssDNA) controls its biological function and underpins the design of DNA-based nanodevices, yet the microscopic origin of temperature-dependent elasticity remains incompletely quantified. Here, we use the salt-aware, sequence-dependent oxDNA2 coarse-grained model to map how intra-strand stacking and temperature jointly determine ssDNA mechanics for two prototypical homopolymers, poly(dA)₅₀ and poly(dT)₅₀, across 27–100 °C at 1.0 M monovalent salt. Large ensembles of independent simulations were used to extract equilibrium observables such as persistence length ({l}_{p}), radius of gyration ({R}_{g}), end-to-end distance ({R}_{text{ee}}), and equilibrium force–extension relations. We find that poly(dA) is substantially stiffer than poly(dT) at low temperature: ({l}_{p})​ = 44.8 ± 2.0 nm at 27 °C decreases to 10.0 ± 0.7 nm at 100 °C, while poly(dT) remains comparatively flexible, varying only from 1.40 ± 0.08 nm to 1.05 ± 0.04 nm. These macroscopic changes closely track the loss of intra-strand stacking. For poly(dA), the stacking fraction decreases from 0.70 ± 0.02 to 0.20 ± 0.01, whereas poly(dT) remains weakly stacked across the full range (< 0.10). Force–extension analysis shows that the wormlike chain (WLC) model captures low-force entropic elasticity but fails at intermediate extensions in strongly stacked poly(dA), where cooperative unstacking produces excess forces of ~ 8 to 10 pN near (xapprox 0.6L). The normalized root-mean-square residual at 27 °C is 0.22 for poly(dA), compared to 0.03 for poly(dT). When ({l}_{p}) is normalized by its 27 °C value, both sequences collapse onto a single master curve as a function of stacking fraction (collapse slope ≈ 3.5 ± 0.3), indicating that fractional stacking loss serves as a unifying control parameter for thermal softening. These results quantitatively link microscopic stacking statistics to macroscopic elasticity, clarify the temperature-dependent limits of continuum polymer models, and provide a mechanistic framework for interpreting single-molecule stretching and ensemble measurements of ssDNA mechanics.

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