Instituto de Física La Plata

Binary stars are as common as single stars. The number of detected planets orbiting binaries is rapidly increasing thanks to the synergy between transit surveys, Gaia, and high-resolution direct-imaging campaigns. However, global planet formation models around binary stars are still underdeveloped, which limits the theoretical understanding of planets orbiting binary star systems. We introduce the PAIRS project, which aims to build a global planet formation model for planets in binaries and to produce a planet population synthesis to statistically compare theory and observations. In this first paper, we present the adaptation of the circumstellar disc to simulate the formation of S-type planets. The presence of a secondary star tidally truncates and heats the outer part of the circumprimary disc (and vice versa for the circumsecondary disc), limiting the material to form planets. We implemented and quantified this effect for a range of binary parameters by adapting the Bern Model of planet formation in its pebble-based form and for in situ planet growth. We find that disc truncation has a strong impact on reducing the pebble supply for core growth and steadily suppresses planet formation for binary separations below 160 a when all the formed planets more massive than Mars are considered. Moreover, S-type planets tend to form close to the central star with respect to the binary separation and disc truncation radius. Our newly developed model will be the basis of future S-type planet population synthesis studies.

A bstract We study spacetime four-point functions of chiral primary operators for superstrings propagating in AdS 3 × S 3 × T 4 from the worldsheet perspective, allowing for external states with arbitrary spectral flow charges. We work at small boundary cross-ratio and consider both extremal (supersymmetry-protected) and non-extremal configurations. The string correlators involve a non-trivial integration over the worldsheet moduli, and we demonstrate how the exchange of short and long strings is encoded in distinct integration regions. We interpret our results in terms of the operator product expansion in the boundary theory, and make explicit the precise matching with the available data for the relevant holographic correlators.

Bis(monoacylglycero)phosphate (BMP) possesses an atypical headgroup structure, and its naturally occurring 2,2′-isomer rapidly rearranges to the more stable 3,3′-form in aqueous buffers. Because the BMP is a major component of endosomal and lysosomal membranes, understanding its intrinsic physicochemical behavior is broadly relevant to the organization of acidic intracellular interfaces. To quantify how acidity modulates the physicochemical organization of 3,3′-BMP membranes, we characterized model bilayers across a controlled pH range by using electrophoretic mobility, fluorescence spectroscopy, optical microscopy, small-angle X-ray scattering (SAXS), dynamic light scattering (DLS), and atomistic molecular dynamics (MD) simulations. Below pH 5, BMP vesicles show a marked decrease in surface charge, a reduction in area per lipid, and diminished hydration at the polar–apolar interface. Simulations reveal that protonation enables transient flipping of the phosphate group toward the hydrophobic core, generating a pH-dependent coexistence of headgroup orientations absent in the deprotonated state. Experimentally, these changes manifest as reduced vesicle sizes and the emergence of multilamellar protrusions and locally folded membrane regions. The combined results demonstrate how small variations in the BMP charge state generate amplified structural responses at the bilayer level, establishing a molecular mechanism by which protonation governs packing, hydration, and curvature in BMP-rich membranes.

We report the optimized one-pot synthesis of gold nanoparticle/polypyrrole (AuNPs/PPy) nanocomposites via a 23 factorial design, enabling control of key optical and electrochemical properties. The nanocomposite formulation with the highest performance exhibited a maximum fluorescence intensity of (3.55 ± 0.063) × 106 CPS upon excitation at 350 nm. Nonlinear optical characterization by the Z-scan technique revealed self-defocusing behavior with a negative nonlinear refractive index of −9.6 × 10–8 cm2/W. Electrochemical impedance spectroscopy confirmed the hybrid’s capacitive and conductive characteristics, with a charge transfer resistance of approximately 81 Ω and a distinct capacitive response in the Bode phase angle. STEM analysis revealed a core–shell nanostructure with an average particle size of 66.4 ± 12.0 nm, consistent with direct measurement. Thermogravimetric analysis confirmed thermal stability, while cytotoxicity assays in four mammalian cell lines revealed no significant toxic effects up to 500 μg/mL, supporting the material’s biocompatibility. These combined features position the AuNPs/PPy nanocomposite as a promising multifunctional platform for integrated optical, electrochemical, and biosensing technologies.

The escalating frequency and severity of extreme environmental events underscores the critical need for a paradigm shift from reactive to proactive management strategies. This perspective article argues that artificial neural networks (ANNs) represent a transformative tool for environmental forecasting, capable of capturing the non-linear, high-dimensional dynamics that define complex Earth systems. While ANNs demonstrate superior predictive performance across domains such as hydrology, air quality, and ecology, their integration into decision-making workflows remains hindered by challenges related to data quality, model interpretability, and a lack of interdisciplinary collaboration. We synthesize current advancements, highlighting the pivotal role of physics-informed neural networks (PINNs) and explainable AI (XAI) in bridging the gap between data-driven insights and physical plausibility. Finally, we propose a concrete interdisciplinary roadmap, encompassing curated benchmarks, hybrid modeling, educational initiatives, and institutional co-design, to translate computational potential into trustworthy, actionable tools for building environmental resilience.

Peptide nanostructures are versatile supramolecular systemswithpotential applications in biomaterials and nanotechnology, where stabilityemerges from the cooperative action of noncovalent interactions. Inthis study, we investigated the bola-amphiphilic peptide EF4K assembled into nanomembranes, focusing on the combined effectsof temperature and multilayer organization. Molecular dynamics simulationswere conducted at 250, 270, 300, 320, and 350 K in monolayer and multilayerconfigurations, allowing direct evaluation of peptide–peptideand peptide–solvent interactions. The results demonstrate thatwhile the number of hydrogen bonds increases with temperature, theirlifetimes decrease markedly, with reductions of nearly 79%. Peptide–solventinteractions weaken significantly, with losses of up to 90%, whereasmultilayer assemblies partially compensate this destabilization byreinforcing peptide–peptide hydrogen bonds and van der Waalscontacts. Electrostatic contributions between peptides remain stableand even strengthen in multilayers, indicating supramolecular reinforcementupon stacking. Confined water within multilayers exhibits longer hydrogenbond lifetimes despite a lower number of contacts, contrasting withthe destabilization of hydration shells observed in monolayers athigher temperatures. These findings reveal that EF4K membranesundergo a redistribution of stabilizing forces under thermal stress,with multilayers achieving enhanced internal cohesion, thereby highlightingtheir potential as robust peptide-based nanomaterials.

Abstract The Young–Laplace equation relates the pressure difference across a fluid interface to its curvature and surface tension and plays a fundamental role in physical phenomena and engineering applications. This work aims to present a clear and pedagogically oriented exposition of the physical and mathematical foundations of the Young–Laplace equation. The approach combines a theoretical derivation with illustrative examples based on common physical situations. The results demonstrate how the equation quantitatively explains pressure variations in curved interfaces and clarifies the role of curvature in determining equilibrium configurations. These examples highlight the consistency between the mathematical formulation and observable phenomena. By systematically linking theory, derivation, and application, the work provides an accessible and comprehensive reference that supports the teaching and learning at undergraduate and graduate levels.

Abstract Typicality is a well-established and very general property of quantum many-body systems, referring to the phenomenon that the expectation values of any given observable are practically indistinguishable for the overwhelming majority of all pure states (normalized vectors) in a sufficiently high-dimensional Hilbert (sub-)space. Here, we provide very simple and general arguments that analogous typicality properties of pure states (phase space points) in classical many-body systems are still expected to hold true for macroscopic observables, but not any more for microscopic (few-body) observables.