Articles publicats en revistes (Física de la Matèria Condensada)

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Virtual magnetic hills to unlock the inner phases of hexagonal colloidal ice
(Royal Society of Chemistry, 2026-02-04) Baillou, Renaud.; Terkel, Matthew.; Tierno, Pietro
We study the low energy states in a hexagonal colloidal ice realized by using repulsive paramagnetic colloids confined by gravity within a honeycomb lattice of traps. In contrast to similar systems featuring optical or topographic double wells, here we introduce field tunable “virtual” magnetic hills. These hills are created by placing pairs of fixed paramagnetic particles close to the semi-cylindrical traps that contain the interacting, mobile colloids. With this strategy, a single magnetic field can be used to simultaneously tune the particle pair-interactions and the hill elevation, without losing the trap bistability at any field strength. We use numerical simulations to explore the rich low energy states of the system. By varying both the relative distance and the magnetic content of the fixed particles, not only the effects of the first but also of the second nearest neighbors can be accessed, allowing the inner charge-ordered ice-II phase to be reached. Our strategy of controlling the vertex energetics via fixed, field tunable interstitial units may be extended to other geometrically frustrated systems on different length scales, including nanoscale spin ice and macroscopic magnetic metamaterials.
Confinement-driven emergence of hyperuniform fluids
(American Physical Society, 2025-12-15) Leoni, Fabio; Franzese, Giancarlo; Oguz, Erdal C.; Martelli, Fausto
Controlling emergent structural order in spatially constrained systems is a fundamental challenge. Using large-scale simulations of a model fluid at equilibrium conditions, we show that geometric confinement alone can stabilize fluid and hyperuniform labyrinthine phases. Moreover, confinement can induce self-assembly into distinct regimes—ranging from nonhyperuniform to antihyperuniform configurations—providing a robust mechanism for tuning spatial order. Our results identify confinement as a minimal design principle for engineering systems with target structural properties, including (anti)hyperuniformity, without relying on genetic or chemical specificity, and with broad applications in multiple disciplines and technologies.
Efficient parallel algorithms for free-energy calculation of millions of water molecules in the fluid phases
(Frontiers Media, 2025-09-16) Coronas, Luis Enrique; Vilanova, Oriol; Franzese, Giancarlo
Simulating water droplets made up of millions of molecules and on timescales as needed in biological and technological applications is challenging due to the difficulty of balancing accuracy with computational capabilities. Most detailed descriptions, such as ab initio, polarizable, or rigid models, are typically constrained to a few hundred (for ab initio) or thousands of molecules (for rigid models). Recent machine learning approaches allow for the simulation of up to 4 million molecules with ab initio accuracy but only for tens of nanoseconds, even if parallelized across hundreds of GPUs. In contrast, coarse-grained models permit simulations on a larger scale but at the expense of accuracy or transferability. Here, we consider the CVF molecular model of fluid water, which bridges the gap between accuracy and efficiency for free-energy and thermodynamic quantities due to i) a detailed calculation of the hydrogen bond contributions at the molecular level, including cooperative effects, and ii) coarse-graining of the translational and rotational degrees of freedom of the molecules. The CVF model can reproduce the experimental equation of state and fluctuations of fluid water across a temperature range of 60$\,^{\circ}$ around ambient temperature and from 0 to 50 MPa. In this work, we describe efficient parallel Monte Carlo algorithms executed on GPUs using CUDA, tailored explicitly for the CVF model. We benchmark accessible sizes of 17 million molecules with the Metropolis and 2 million with the Swendsen-Wang Monte Carlo algorithm.
Adsorption of wastewater pollutants on amorphous TiO2: an atomistic simulation study
(Royal Society of Chemistry, 2026-02-23) von Einem, Maria; Balzaretti, Filippo; Romero, Manuela; Colombi Ciacchi, Lucio; Franzese, Giancarlo; Köppen-Hannemann, Susan
The increasing presence of polluting chemicals in man-made wastewater poses significant environmental and health risks. Advanced oxidation processes, particularly those involving photocatalytic materials like titanium dioxide (TiO2), offer a promising solution for degrading these pollutants. This study employs force field molecular dynamics simulations to investigate the interactions between pollutants, the TiO2 surface, water and ions, aiming to elucidate their role in the adsorption process. The results reveal that the protonation state of pollutants significantly influences their contact with the TiO2 surface, with negatively charged species showing a higher affinity for the surface’s active sites, especially those containing carboxylate groups. The formation of hydrogen bond networks affects the stability of these contacts positively, while the tendency of some pollutants to aggregate hinders surface contacts. Furthermore, we observe cations (Na+) to alter the surface-near environment in a typical electrical double-layer manner, as well as to participate in pollutant adsorption and aggregation. These findings provide insights into the adsorption features triggering the initial pollutant degradation on amorphous TiO2, which could enhance the design of more efficient wastewater treatment technologies .
Unveiling the entropic role of hydration water in SOD1 partitioning within FUS condensate
(American Institute of Physics (AIP), 2026-03-07) Coronas, Luis Enrique; Timr, Stepan; Sterpone, Fabio; Franzese, Giancarlo
Biological processes such as the sequestration of Superoxide Dismutase 1 (SOD1) into biomolecular condensates, including FUS and stress granules, are vital for understanding disease mechanisms, including amyotrophic lateral sclerosis (ALS). Moreover, protein-crowder interactions within these condensates are recognized as fundamental to cellular phase separation and disease-related processes. However, the specific role of the hydration environment in governing SOD1’s behavior and transition dynamics within these condensates remains poorly understood, limiting our ability to accurately model these critical biological systems. Therefore, we incorporate explicit water into an implicit solvent model (OPEP) to investigate how water influences SOD1’s behavior, residence times, and transition rates among associative states. We employ the advanced CVF water model, which accurately captures hydrogen- bond networks at the molecular level. While the OPEP model indicates that Bovine Serum Albumin (BSA) crowders reduce SOD1’s partition coefficient (PC) primarily through nonspecific interactions, our explicit-water approach points to hydration entropy in BSA as a key contributor to the observed PC reduction. This result offers a new perspective on the system’s free-energy landscape, complementing those obtained from OPEP alone. Our research supports the notion that explicitly modeling water can enhance our understanding of protein-crowder interactions and their biological implications, further emphasizing the potential role of water in cellular phase separation and disease-related processes.
Small-angle X-ray scattering unveils the internal structure of lipid nanoparticles.
(Elsevier, 2024-02-12) Spinozzi, Francesco; Moretti, Paolo; Romano Perinelli, Diego; Corucci, Giacomo; Piergiovanni, Paolo; Amenitsch, Heinz; Alfredo Sancin, Giulio; Franzese, Giancarlo; Blasi, Paolo
Lipid nanoparticles own a remarkable potential in nanomedicine, only partially disclosed. While the clinical use of liposomes and cationic lipid-nucleic acid complexes is well-established, liquid lipid nanoparticles (nanoemulsions), solid lipid nanoparticles, and nanostructured lipid carriers have even greater possibilities. However, they face obstacles in being used in clinics due to a lack of understanding about the molecular mechanisms controlling their drug loading and release, interactions with the biological environment (such as the protein corona), and shelf-life stability. To create effective drug delivery carriers and successfully translate bench research to clinical settings, it is crucial to have a thorough understanding of the internal structure of lipid nanoparticles. Through synchrotron small-angle X-ray scattering experiments, we determined the spatial distribution and internal structure of the nanoparticles’ lipid, surfactant, and the bound water in them. The nanoparticles themselves have a barrel-like shape that consists of coplanar lipid platelets (specifically cetyl palmitate) that are covered by loosely spaced polysorbate 80 surfactant molecules, whose polar heads retain a large amount of bound water. To reduce the interface cost of bound water with unbound water without stacking, the platelets collapse onto each other. This internal structure challenges the classical core-shell model typically used to describe solid lipid nanoparticles and could play a significant role in drug loading and release, biological fluid interaction, and nanoparticle stability, making our findings valuable for the rational design of lipid-based nanoparticles.
Non-linear inhibitory responses enhance performance in collective decision-making
(Springer Nature, 2025-03-27) March-Pons, David; Pastor Satorras, Romualdo; Miguel López, María del Carmen
The precise modulation of activity through inhibitory signals ensures that both insect colonies and neural circuits operate efficiently and adaptively, highlighting the fundamental importance of inhibition in biological systems. Modulatory signals are produced in various contexts and are known for subtly shifting the probability of receiver behaviors based on response thresholds. Here we propose a non-linear function to introduce inhibitory responsiveness in collective decision-making inspired by honeybee house-hunting. We show that, compared with usual linear functions, non-linear responses enhance final consensus and reduce deliberation time. This improvement comes at the cost of reduced accuracy in identifying the best option. Nonetheless, for value-based tasks, the benefits of faster consensus and enhanced decision-making might outweigh this drawback.
Decoding the Conformation of Polylactic Acid in Block Copolymer Micelles
(American Chemical Society, 2026-01-28) Muñoz López, José María; Tuveri, Gian Marco; Barbieri, Valentino; Basile, Marco; Cosenza, V.; Lorenz, Christian D.; Ruiz-Perez, Lorena; Battaglia, Giuseppe
Understanding how molecular features dictate the self-assembly of amphiphilic block copolymers into well-defined nanostructures is essential for the rational design of advanced soft materials. However, the large number of interdependent parameters involved, such as particle size, aggregation number, interfacial curvature, and molecular weight, makes it challenging to establish general design principles. Here we establish a scaling-based framework for PEG-b-PLA micelles with a fixed hydrophilic–hydrophobic ratio. Systematic variation of molecular weights enables precise control of micelle size and aggregation number, quantified by DLS, cryo-TEM, and MALS.
Activity-driven emulsification of phase-separating binary mixture
(American Physical Society, 2025-03-07) Diaz, Javier; Pagonabarraga Mora, Ignacio
Active particles self-assemble into emergent structures that respond sensitively to external constraints. Consequently, their behavior under confinement is complex, especially in soft confined media, leading to diverse emergent morphologies. Through computer simulations, we investigate the dynamical interplay between active Brownian particles and a binary mixture. Our results show that active particles stabilize nonequilibrium morphologies, arresting coarsening by exerting active pressure that competes with surface tension. For moderate activities, particles stabilize an active emulsion with a well-defined droplet size. At higher activities, when particles can cross the liquid domains, a dynamic emulsion with large droplet dispersion is sustained. Furthermore, active particles drive phase-separated mixtures away from equilibrium configurations, demonstrating a rich coassembly behavior due to competing energy scales in the system.
Non-Reciprocal interactions reshape topological defect annihilation
(American Physical Society, 2025-04-23) Rouzaire, Ylann; Pearce, Daniel J. G.; Pagonabarraga Mora, Ignacio; Levis, Demian
We show how nonreciprocal ferromagnetic interactions between neighboring planar spins in two dimensions, affect the behavior of topological defects. Nonreciprocity is introduced by weighting the coupling strength of the two-dimensional XY model by an anisotropic kernel. As a consequence, in addition to the topological charge, the actual shape of the defects becomes crucial to faithfully describe their dynamics. Nonreciprocal coupling twists the spin field, selecting specific defect shapes, dramatically altering the pair annihilation process. Defect annihilation can either be enhanced or hindered, depending on the shape of the defects concerned and the degree of nonreciprocity in the system. We introduce a continuous description—for which the phenomenological coefficients can be explicitly written in terms of the microscopic ones—that captures the behavior of the lattice model.
Activity leads to topological phase transition in 2D populations of heterogeneous oscillators
(American Physical Society, 2025-05-06) Rouzaire, Ylann; Rahmani, Parisa; Pagonabarraga Mora, Ignacio; Peruani, Fernando; Levis, Demian
Populations of heterogeneous, noisy oscillators on a two-dimensional lattice display short-range order. Here, we show that if the oscillators are allowed to actively move in space, the system undergoes instead a Berezenskii-Kosterlitz-Thouless transition and exhibits quasi-long-range order. This fundamental result connects two paradigmatic models—the XY and Kuramoto models—and provides insight into the emergence of order in active systems.
Resolving the different bulk moduli within individual soft nanogels using small-angle neutron scattering
(American Association for the Advancement of Science, 2022-01-01) Houston, Judith; Fruhner, Lisa Sarah; Cotte, Alexis de la; Rojo-González, Javier; Petrunin, Alexander V.; Gasser, Urs; Schweins, Ralf; Allgaier, Jürgen; Richtering, Walter; Fernández-Nieves, Alberto; Scotti, Andrea
The bulk modulus, K, quantifies the elastic response of an object to an isotropic compression. For soft compressible colloids, knowing K is essential to accurately predict the suspension response to crowding. Most colloids have complex architectures characterized by different softness, which additionally depends on compression. Here, we determine the different values of K for the various morphological parts of individual nanogels and probe the changes of K with compression. Our method uses a partially deuterated polymer, which exerts the required isotropic stress, and small-angle neutron scattering with contrast matching to determine the form factor of the particles without any scattering contribution from the polymer. We show a clear difference in softness, compressibility, and evolution of K between the shell of the nanogel and the rest of the particle, depending on the amount of cross-linker used in their synthesis.
Editorial: Nonequilibrium multiphase and reactive flows in porous and granular materials
(Frontiers Media, 2023-12-01) Holtzman, Ran; Sandnes, Bjornar; Moura, Marcel; Icardi, Matteo; Planet Latorre, Ramon
Porous systems that involve the flow of multiple fluids, particles, or solutes, capable of undergoing reactions with each other or with the solid porous matrix, often exist in an out-of-equilibrium state. These systems are driven away from equilibrium by various underlying mechanisms. These mechanisms include interfacial instabilities caused by capillary or viscous forces, as well as physical alteration of the pore space through mechanical or chemical processes like fracturing, compaction, precipitation, and dissolution. An inherent feature of many porous and granular systems is their multiscale heterogeneity. An extreme example is in geosciences, where heterogeneity and mechanisms at the microscopic scales (e.g., in nanometer-sized pores) could strongly affect the behavior at the field scale (km-sized reservoirs). The multiscale, nonequilibrium nature of these systems is manifested by the emergence of complex, preferential flow patterns and dependencies on the path (hysteresis) and rate of external driving forces. Modeling, understanding, predicting, and even controlling the evolution of the flow and deformation in these systems is a substantial scientific challenge across disciplines including engineering, physics, geosciences and mathematics and plays a crucial role in multiple practical applications.
Reservoir computing in simulated neuronal cultures: Effectof network structure
(American Institute of Physics (AIP), 2026-02-17) Mats Houben, Akke; Haeb, Anna-Christina; García Ojalvo, Jordi; Soriano i Fradera, Jordi
Biological neurons are emerging as attractive candidates for artificial intelligence and machine learning applications given their natural energy efficiency and self-repair capacity. However, they differ from their idealized artificial counterparts. Biological neurons have highly variable and noisy dynamics and display intrinsic spontaneous activity instead of purely input-driven dynamics. Moreover, biological neuronal networks have physically constrained and highly plastic connections, leading to a complex and ever evolving connectivity structure. Here, we investigate (numerically and with preliminary experimental data) the stability of the input responses of neuronal cultures using a reservoir computing framework. Utilizing a numerical model for the growth and activity of neuronal cultures, previously used to model experimental data, we investigate the effect of large-scale network topology, specifically homogeneous vs modular architectures, on fading memory, reservoir performance under increasingly noisy dynamics, and robustness to network rewiring. We find that modular networks exhibit longer fading memory time, sustain higher performance under noisy conditions, and are more robust to connectivity rewiring than homogeneous networks. Finally, we observe no relationship between some characteristics of the network adjacency matrix (specifically its spectral properties) and reservoir computing performance.
Unravel the rotational and translational behavior of a single squirmer in flexible polymer solutionsat diﬀerent Reynolds numbers
(Springer Nature, 2025-12-01) Qi, Kai; Zhou, H.Y.; Corato, Marco de; Stratford, Kevin; Pagonabarraga Mora, Ignacio
Microorganisms such as bacteria and algae navigate complex fluids, where their dynamics are vital for medical and industrial applications. However, the influence of the Reynolds number (Re) on the transport and rotational behavior of microswimmers in viscoelastic media remains poorly understood. Here, we investigate these effects for a model squirmer in flexible polymer solutions across a range of Re using Lattice Boltzmann simulations. The interaction between swimmer activity and polymer heterogeneity strongly affects behavior, with rotational enhancement up to 1400-fold and reduced self-propulsion and diffusivity for squirmers. These effects result from hydrodynamic and mechanical interactions: polymers wrap ahead of pushers and accumulate behind pullers, enhancing rotation while hindering translation through forces and torques from direct contacts or asymmetric flows. The influence of Re and squirmer-polymer boundary conditions (no-slip vs. repulsive) is also examined. Notably, no-slip conditions intensify effects above a critical Reynolds number (). Below this value, stronger viscous drag minimizes differences. Our findings emphasize the crucial role of polymer-swimmer interactions in shaping microswimmer behavior in viscoelastic media, informing microrobotic design in complex environments.
Protocol for tailored in vitro neuronal networks on high-density microelectrode arrays with polydimethylsiloxane microstructures
(Elsevier B.V., 2026-03-20) Haeb, Anna-Christina; Yamamoto, Hideaki; Roach, Paul; Merryweather, Daniel; Sato, Y.; Tornero, Daniel; Soriano i Fradera, Jordi
Complementary metal-oxide-semiconductor (CMOS)-based high-density microelectrode arrays (HD-MEAs) enable neuronal recordings with high spatiotemporal resolution. However, integrating polydimethylsiloxane (PDMS) microstructures onto HD-MEA surfaces to control network architecture is currently challenging and platform specific. Here, we present a protocol for PDMS fabrication, HD-MEA chip preparation, PDMS-HD-MEA microstructure alignment, and cell culture, including alternatives. Our results show reproducible formation of modular networks with characteristic activity patterns across different systems. This protocol supports engineering of defined neuronal architectures while maintaining compatibility with various HD-MEA systems.
Emerging leaders in nanotechnology
(Frontiers Media, 2025-06-12) Guimaraes, Marcos H. D.; Badilescu, Simona; Mohapatra, Satyabrata; Franzese, Giancarlo
This Research Topic of Frontiers in Nanotechnology celebrates the achievements of emerging leaders driving innovation in the broad field of nanoscience and nanotechnology. The diverse articles in this Research Topic reflect the wide variety of Research Topic within nanoscience and nanotechnology. This Research Topic brings together contributions spanning fundamental and applied research, from two-dimensional materials and catalytic nanostructures to biotechnology and education in nanotechnology. Each research article, as well as the perspective article, showcases the work of young scientists who are shaping the future of the field by using sophisticated instruments and methods, introducing novel ideas, interdisciplinary approaches, and opening new scientific frontiers.
Multiscale Field Theory for Network Flows
(American Physical Society, 2025-05-07) Mikaberidze, Guram; Artime, Oriol; Díaz Guilera, Albert; D'Souza, Raissa M.
Network flows are pervasive, including the movement of people, transportation of goods, transmission of energy, and dissemination of information; they occur on a range of empirical interconnected systems, from designed infrastructure to naturally evolved networks. Despite the broad spectrum of applications, because of their domain-specific nature and the inherent analytic complexity, a comprehensive theory of network flows is lacking. We introduce a unifying treatment for network flows that considers the fundamental properties of packet symmetries, conservation laws, and routing strategies. For example, electrons in power grids possess interchangeability symmetry, unlike packages sent by postal mail, which are distinguishable. Likewise, packets can be conserved, such as cars in road networks, or dissipated, such as Internet packets that time out. We introduce a hierarchy of analytical field-theoretic approaches to capture the different scales of complexity required. Mean-field analysis uncovers the nature of the transition through which flow becomes unsustainable upon unchecked growth of demand. Mesoscopic field theory accurately accounts for complicated network structures, packet symmetries, and conservation laws and yet is capable of admitting closed-form solutions. Finally, the full-scale field theory allows us to study routing strategies ranging from random diffusion to shortest path. Our theoretical results indicate that flow bottlenecks tend to be near sources for interchangeable packets and near sinks for distinguishable ones, and that dissipation hinders the maximum sustainable throughput for interchangeable packets but can enhance throughput for distinguishable packets. Finally, we showcase the flexibility of our multiscale theory by applying it in two distinct domains of road networks and the C. elegans neuronal network. Our work paves the way for a more unifying and comprehensive theory of network flows.
Unraveling the relevance of graphene-fluid hydrodynamic coupling on the exfoliation of graphitein water
(American Chemical Society, 2025-08-11) Qi, Kai; Fonte, Claudio P.; Stratford, Kevin; Zhang, Yuqing; Jiang, Xiujun; Pagonabarraga Mora, Ignacio
Liquid-phase exfoliation via shear flow is a widely adopted technique for the large-scale production of graphene. However, the underlying nano- and microscale exfoliation mechanisms remain poorly understood. In this work, we address this issue by performing hybrid nonequilibrium hydrodynamic simulations of coarse-grained defect-free graphite nanoplatelets immersed in a mesoscopic water fluid via the lattice Boltzmann method. This approach enables us to investigate graphene exfoliation up to 100 nm in length. Nonequilibrium effects, such as tumbling, alignment, and bending, are demonstrated. In particular, we reveal that due to the graphene-fluid hydrodynamic coupling, the graphite dynamics distorts the surrounding shear flow and reduces the local shear stress, thereby leading to an increase in the critical shear rate by a factor of 2 ∼ 4. This statement is fully supported by a theoretical analysis using a force-based criterion, i.e., overcoming the maximum interlayer van der Waals attraction, and hierarchical simulations: athermal and no coupling; athermal and hydrodynamic coupling; and thermal and hydrodynamic coupling. Our work unravels the paramount relevance of hydrodynamic coupling on graphene exfoliation and paves the way toward achieving large-scale nonequilibrium graphene simulations reminiscent of experiments.
Colloidal Model for Investigating Optimal Efficiency in Weakly Coupled Ratchet Motors
(American Physical Society, 2025-07-09)
We investigate the transport of superparamagnetic colloidal particles along self-assembled tracks using a periodically applied magnetic field as a model for ratchetlike mechanisms. Through video microscopy and simulations, we examine how different factors influence transport efficiency. The findings reveal that processive motion can be achieved without residual attraction, with optimal transport efficiency governed by the combined effects of particle size ratios, actuation frequency, track roughness, and asymmetry in the applied potential. Additionally, we explore alternative strategies, including weak residual attraction and alternating magnetic fields, to further enhance efficiency. These findings provide valuable insights for the development of synthetic micro- and nanomotors with potential applications in drug delivery and environmental remediation.

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