arXiv subjects

Achille Giacometti

Publications and source records attributed to Achille Giacometti.

At least 19 recordsLinked to original sources

arXiv2026

Theory of associating polymers with annealed and quenched sticker disorder: Mean-field solution and phase behavior

We develop a density-functional theory for solutions of associating polymers where attractions among charged monomers (stickers) are represented by local binary degrees of freedom, which are randomly placed along the chains. Extending the original Garel and Orland's field-theoretic scheme for single-chain systems to an ensemble of interacting chains, we give the exact formulations of the model in both cases of annealed and quenched distributions of charges which we solve at the mean-field level. The solution produces qualitatively different free energy functionals. In the annealed case, the theory naturally yields a nontrivial scalar order parameter for the fraction of bonded sticker monomers and a self-consistent mass-action law at the saddle point. By contrast, in the quenched case no independent bonding order parameter emerges and the main effect is a renormalization of the effective two-body and three-body interaction parameters. The formulation is microscopic at the Hamiltonian level and, within the same field-theoretic framework, provides a systematic starting point for fluctuation corrections beyond the mean-field approximation.

cond-mat.soft↗

arXiv2026

Information Transmission and Processing in G-Protein-Coupled-Receptor Complexes

G-protein-coupled receptors (GPCRs) are central to cellular information processing, yet the physical principles governing their switching behavior remain incompletely understood. We present a first principles theoretical framework, grounded in nonequilibrium thermodynamics, to describe GPCR switching as observed in light-controlled impedance assays. The model identifies two fundamental control parameters: (1) ATP/GTP-driven chemical flux through the receptor complex, and (2) the free-energy difference between phosphorylated and dephosphorylated switch states. Together, these parameters defin the switch configuration. The model predicts that GPCRs can occupy one of three quasi-stable configurations, each corresponding to a local maximum in information transmission. Active states support chemical flux and exist in an on or off switch configuration, whereas inactive states lack flux, introducing a distinction absent in conventional phosphorylation models. The model takes two ligand-derived inputs: fixed structural features and inducible conformations (e.g. cis or trans). It shows that phosphatase activity, modeled as an energy barrier, chiefly governs on/off occupancy, whereas the kinase sustains flux without directly determining the switch configuration. Comparison with experimental data confirms the predicted existence of multiple quasi-stable states modulated by ligand conformation. Importantly, this framework generalizes beyond GPCRs to encompass a wider class of biological switching systems driven by nonequilibrium chemical flux.

q-bio.MN↗

arXiv2025

Plumbing Analog of Molecular Computation

Biological information processing often arises from mesoscopic molecular systems operating far from equilibrium, yet their complexity can make the underlying principles difficult to visualize. In this study, we introduce a macroscopic hydraulic model that serves as an intuitive analog for the molecular switching behavior exhibited by G protein-coupled receptors (GPCRs) on the cell membrane. The hydraulic system reproduces the essential structural and functional features of the molecular switch, including the presence of up to three distinct steady state solutions, the characteristic shapes of these solutions, and the physical interpretation of the control parameters governing the behavior of the system. By mapping water flow, energy barrier height, and siphoning dynamics onto biochemical flux, activation energy, and state transitions, the model provides a transparent representation of the mechanisms that regulate GPCR activation. The correspondence between the hydraulic analog and the molecular system suggests several experimentally testable hypotheses about GPCR function. In particular, the model highlights the central role of energy flux, driven by imbalances in ATP/ADP or GTP/GDP concentrations, in activating the molecular switch and maintaining nonequilibrium signaling states. It also identifies two key parameters that primarily determine switch behavior: the energy difference between the active and inactive states and the effective height of the energy barrier that separates them. These results imply that GPCR signaling dynamics may be governed by generalizable physical principles rather than by biochemical details alone. The hydraulic framework thus offers a tractable platform for interpreting complex molecular behavior and may aid in the development of predictive models of GPCR function in diverse physiological contexts.

q-bio.SC↗

arXiv2025

Material-Based Intelligence: Self-organizing, Autonomous and Adaptive Cognition Embodied in Physical Substrates

The design of intelligent materials often draws parallels with the complex adaptive behaviors of biological organisms, where robust functionality stems from sophisticated hierarchical organization and emergent long-distance coordination among a myriad local components. Current synthetic materials, despite integrating advanced sensors and actuators, predominantly demonstrate only simple, pre-programmed stimulus-response functionalities, falling short of robustly autonomous intelligent behavior. These systems typically execute tasks determined by rigid design or external control, fundamentally lacking the intricate internal feedback loops, dynamic adaptation, self-generated learning, and genuine self-determination characteristic of biological agents. This perspective proposes a fundamentally different approach focusing on architectures where material-based intelligence is not pre-designed, but arises spontaneously from self-organization harnessing far-from-equilibrium dynamics. This work explores interdisciplinary concepts from material physics, chemistry, biology, and computation, identifying concrete pathways toward developing materials that not only react, but actively perceive, adapt, learn, self-correct, and potentially self-construct, moving beyond biomimicry to cultivate fully synthetic, self-evolving systems without external control. This framework outlines the fundamental requirements for, and constraints upon, future architectures where complex, goal-directed functionalities emerge synergistically from integrated local processes, distinguishing material-based intelligence from traditional hardware-software divisions. This demands that concepts of high-level goals and robust, replicable memory mechanisms are encoded and enacted through the material's inherent dynamics, inherently blurring the distinction between system output and process.

cond-mat.soft↗

arXiv2025

Thermodynamics of Biological Switches

We derive a formulation of the First Law of nonequilibrium thermodynamics for biological information-processing systems by partitioning entropy in the Second Law into microscopic and mesoscopic components and by assuming that natural selection promotes optimal information processing and transmission. The resulting framework demonstrates how mesoscopic information-based subsystems can attain nonequilibrium steady states (NESS) sustained by external energy and entropy fluxes, such as those generated by ATP/ADP imbalances in vivo. Moreover, mesoscopic systems may reach NESS before microscopic subsystems, leading to ordered structures in entropy flow analogous to eddies in a moving stream.

cond-mat.stat-mech↗

arXiv2025

Space-filling discrete helices

Proteins are linear chain molecules that play a central role in life and health. Protein native state folds are modular assemblies of space-filling building blocks of α-helices, \{beta}-sheets and tight turns. Here we deduce the structures of a countable set of space-filling helical forms of a uniform discrete thick string from first principles with no additional input or adjustable parameters. These forms occur in correspondence with the natural numbers, loosely analogous to the energy levels in a Bohr atom. We find the remarkable result that one of these helical forms is an excellent candidate for an α-helix through seemingly improbable quantum chemistry coincidences that fit the geometrical requirements. Our work suggests that geometry and chemistry are complementary ways of looking at proteins and suggests a route for developing a unified framework for understanding proteins.

physics.bio-ph↗

arXiv2025

Entropy of self-avoiding branching polymers: mean field theory and Monte Carlo simulations

We study the statistics of branching polymers with excluded-volume interactions, by modeling them as single self-avoiding trees on a generic regular periodic lattice with coordination number $q$. Each lattice site can be occupied at most by one tree node, and the fraction of occupied sites can vary from dilute to dense conditions. By adopting the statistics of rooted-directed trees as a proxy for that of undirected trees without internal loops and by an exact mapping of the model into a field theory, we compute the entropy and the mean number of branch-nodes within a mean field approximation and in the thermodynamic limit. In particular, we find that the mean number of branch-nodes is independent of both the lattice details and the lattice occupation, depending only on the associated chemical potential. Monte Carlo simulations in $d=2,3,4$ provide evidence of the remarkable accuracy of the mean field theory, more accurate for higher dimensions.

cond-mat.stat-mech↗

arXiv2025

Intelligent Soft Matter: Towards Embodied Intelligence

Intelligent soft matter stands at the intersection of materials science, physics, and cognitive science, promising to change how we design and interact with materials. This transformative field seeks to create materials that possess life-like capabilities, such as perception, learning, memory, and adaptive behavior. Unlike traditional materials, which typically perform static or predefined functions, intelligent soft matter dynamically interacts with its environment. It integrates multiple sensory inputs, retains experiences, and makes decisions to optimize its responses. Inspired by biological systems, these materials intend to leverage the inherent properties of soft matter: flexibility, self-evolving, and responsiveness to perform functions that mimic cognitive processes. By synthesizing current research trends and projecting their evolution, we present a forward-looking perspective on how intelligent soft matter could be constructed, with the aim of inspiring innovations in fields such as biomedical devices, adaptive robotics, and beyond. We highlight new pathways for integrating design of sensing, memory and action with internal low-power operations and discuss challenges for practical implementation of materials with "intelligent behavior". These approaches outline a path towards to more robust, versatile and scalable materials that can potentially act, compute, and "think" by their inherent intrinsic material behaviour beyond traditional smart technologies relying on external control.

cond-mat.soft↗

arXiv2025

Unveiling Crystalline Order from Glassy Behavior of Charged Rods at Very Low Salt Concentrations

Charged colloids can form ordered structures like Wigner crystals or glasses at very low concentrations due to long-range electrostatic repulsions. Here, we combine small-angle x-ray scattering (SAXS) and optical experiments with simulations to investigate the phase behavior of charged rodlike colloids across a wide range of salt concentrations and packing fractions. At ultra low ionic strength and packing fractions, we reveal both experimentally and numerically a direct transition from a nematic to a crystalline smectic-B phase, previously identified as a glass state. This transition, bypassing the smectic-A intermediate phase, results from minimizing Coulomb repulsion and maximizing entropic gains due to fluctuations in the crystalline structure. This demonstrates how long-range electrostatic repulsion significantly alters the phase behavior of rod-shaped particles and highlights its key-role in driving the self-organization of anisotropic particles.

cond-mat.soft↗

arXiv2024

Theory of polymers in binary solvent solutions: mean-field free energy and phase behavior

We present a lattice model for polymer solutions, explicitly incorporating interactions with a bath of solvent and cosolvent molecules. By exploiting the well-known analogy between polymer systems and the $O(n)$-vector spin model in the limit $n \to 0$, we derive an exact field-theoretic expression for the partition function of the system. The latter is then evaluated at the saddle point, providing a mean-field estimate of the free energy. The resulting expression, which conforms to the Flory-Huggins type, is then used to analyze the system's stability with respect to phase separation, complemented by a numerical approach based on convex hull evaluation. We demonstrate that this simple lattice model can effectively explain the behavior of a variety of seemingly unrelated polymer systems, which have been predominantly investigated in the past only through numerical simulations. This includes both, single-chain and multi-chain, solutions. Our findings emphasize the fundamental, mutually competing, roles of solvent and cosolvent in polymer systems.

cond-mat.soft↗

arXiv2024

Phase behaviour and self-assembly of semiflexible polymers in poor-solvent solutions

Using Langevin dynamics complemented by Wang-Landau Monte Carlo simulations, we study the phase behavior of single and multiple semiflexible polymer chains in solution under poor-solvent conditions. In the case of a single chain, we obtain the full phase diagram in the temperature-bending rigidity (stiffness) plane and we provide connections with a classical mean field result on a lattice as well as with past results on the same model. At low bending rigidity and upon cooling, we find a second order coil-globule transition, followed by a subsequent first order globule-crystal transition at lower temperatures. The obtained crystals have the shape of a twisted rod whose length increases with the increase of the stiffness of the chain. Above a critical value of the stiffness, we also find a direct first order globule-crystal transition, with the crystal having the form of a twisted toroid. Close to the triple point, we find a region with isoenergetic structures with frequent switching from rods to toroids, with the toroid eventually becoming the only observed stable phase at higher stiffness. The model is then extended to many thermally equilibrated chains in a box and the analogous phase diagram is deduced where the chains are observed to first fold into a globule bundle at low stiffness upon cooling, and then rearrange into a nematic bundle via a nucleation process involving an isotropic-nematic transition. As in the single chain counterpart, above a critical stiffness the chains are observed to undergo a direct transition from a gas of isotropically distributed chains to a nematic bundle as the temperature decreases in agreement with recent suggestions from mean field theory. The consequences of these findings for self-assembly of biopolymers in solutions are discussed.

cond-mat.soft↗

arXiv2024

Self-Assembly and Phase Behavior of Janus Rods: Competition Between Shape and Potential Anisotropy

We characterize the self-assembly and phase behavior of Janus rods over a broad range of temperatures and volume fractions, using Langevin dynamics simulations and free energy calculations. The Janus rods consist of a line of fused overlapping spheres that interact via a soft-core repulsive potential, with the addition of an attractive pseudo-square-well tail to a fraction of the spheres (the coverage) ranging from 5\% to 100\% of sites. Competition between the stability of liquid crystal phases originating from shape anisotropy and assembly driven by directional interactions gives rise to a rich polymorphism that depends on the coverage. At low density near the Boyle temperature, we observe the formation of spherical and tubular micelles at low coverage, while at higher coverage randomly oriented monolayers form as the attractive parts of the rods overlap. At higher density, bilayer structures appear and merge to form smectic and crystalline lamellar phases. All of these structures gradually become unstable as the temperature is increased until eventually regular nematic and smectic phases appear, consistent with the hard rod limit. Our results indicate that the intermediate regime where shape-entropic effects compete with anisotropic attractions provided by site specificity is rich in structural possibilities, and should help guide the design of rod-like colloids for specific applications.

cond-mat.soft↗

arXiv2024

Solvent Quality and Nonbiological Oligomer Folding: Revisiting Conventional Paradigms

We report on extensive molecular dynamics atomistic simulations of a \textit{meta}-substituted \textit{poly}-phenylacetylene (pPA) foldamer dispersed in three solvents, water \ce{H2O}, cyclohexane \ce{cC6H12}, and \textit{n}-hexane \ce{nC6H14}, and for three oligomer lengths \textit{12mer}, \textit{16mer} and \textit{20mer}. At room temperature, we find a tendency of the pPA foldamer to collapse into a helical structure in all three solvents but with rather different stability character, stable in water, marginally stable in n-hexane, unstable in cyclohexane. In the case of water, the initial and final number of hydrogen bonds of the foldamer with water molecules is found to be unchanged, with no formation of intrachain hydrogen bonding, thus indicating that hydrogen bonding plays no role in the folding process. In all three solvents, the folding is found to be mainly driven by electrostatics, nearly identical in the three cases, and largely dominant compared to van der Waals interactions that are different in the three cases. This scenario is also supported by the analysis of distribution of the bond and dihedral angles and by a direct calculation of the solvation and transfer free energies via thermodynamic integration. The different stability in the case of cyclohexane and n-hexane notwithstanding their rather similar chemical composition can be traced back to the different entropy-enthalpy compensation that is found similar for water and n-hexane, and very different for cyclohexane. A comparison with the same properties for \textit{poly}-phenylalanine oligomers underscores the crucial differences between pPA and peptides. To highlight how these findings can hardly be interpreted in terms of a simple "good" and "poor" solvent picture, a molecular dynamics study of a bead-spring polymer chain in a Lennard-Jones fluid is also included.

cond-mat.soft↗

arXiv2024

Network topology mapping of Chemical Compounds Space

We define bipartite and monopartite relational networks of chemical elements and compounds using two different datasets of inorganic chemical and material compounds, as well as study their topology. We discover that the connectivity between elements and compounds is distributed exponentially for materials, and with a fat tail for chemicals. Compounds networks show similar distribution of degrees, and feature a highly-connected club due to oxygen. Chemical compounds networks appear more modular than material ones, while the communities detected reveal different dominant elements specific to the topology. We successfully reproduce the connectivity of the empirical chemicals and materials networks by using a family of fitness models, where the fitness values are derived from the abundances of the elements in the aggregate compound data. Our results pave the way towards a relational network-based understanding of the inherent complexity of the vast chemical knowledge atlas, and our methodology can be applied to other systems with the ingredient-composite structure.

cond-mat.stat-mech↗

arXiv2024

Amino acid characteristics in protein native state structures

We present a geometrical analysis of the protrusion statistics of side chains in more than 4,000 high-resolution protein structures. We employ a coarse-grained representation of the protein backbone viewed as a linear chain of Cα atoms and consider just the heavy atoms of the side chains. We study the large variety of behaviors of the amino acids based on both rudimentary structural chemistry as well as geometry. Our geometrical analysis uses a backbone Frenet coordinate system for the common study of all amino acids. Our analysis underscores the richness of the repertoire of amino acids that is available to nature to design protein sequences that fit within the putative native state folds.

cond-mat.soft↗

arXiv2023

III. Geometrical framework for thinking about globular proteins: turns in proteins

We have shown recently that the notion of poking pairwise interactions along a chain provides a unifying framework for understanding the formation of both secondary and the tertiary protein structure based on symmetry and geometry. $α$-helices and $β$-sheets are found to be special geometries that have systematic poking contacts in a repetitive manner with the contacts being local along the $α$-helix and non-local along a pair of adjacent strands within a $β$-sheet. Pairwise poking interactions also govern tertiary structure formation, but they are weaker and there are no special geometrical constraints as in secondary structure formation. Here we demonstrate that protein turns, the most prevalent non-repetitive structural element in proteins, are instances of local (as in $α$-helices) and isolated (non-repetitive) poking pairwise contacts for which the geometrical constraints are partially relaxed. This simple and purely geometrical definition of protein turns (also sometimes known as reverse turns, $β$-turns, $β$-bends, hairpin bends, $3_{10}$ bends, kinks, widgets, ...) provides a simple framework for unifying them. We present the results of a systematic analysis and identify their structural classes as well as their respective amino acid preferences.

cond-mat.soft↗

arXiv2023

Janus helices: From fully attractive to hard helices

The phase diagram of hard helices differs from its hard rods counterpart by the presence of chiral "screw" phases stemming from the characteristic helical shape, in addition to the conventional liquid crystal phases also found for rod-like particles. Using extensive Monte Carlo and Molecular Dynamics simulations, we study the effect of the addition of a short-range attractive tail representing solvent-induced interactions to a fraction of the sites forming the hard helices, ranging from a single-site attraction to fully attractive helices for a specific helical shape. Different temperature regimes exist for different fractions of the attractive sites, as assessed in terms of the relative Boyle temperatures, that are found to be rather insensitive to the specific shape of the helical particle. The temperature range probed by the present study is well above the corresponding Boyle temperatures, with the phase behaviour still mainly entropically dominated and with the existence and location of the various liquid crystal phases only marginally affected. The pressure in the equation of state is found to decrease upon increasing the fraction of attractive beads and/or on lowering the temperature at fixed volume fraction, as expected on physical grounds. All screw phases are found to be stable within the considered range of temperatures with the smectic phase becoming more stable on lowering the temperature. By contrast, the location of the transition lines do not display a simple dependence on the fraction of attractive beads in the considered range of temperatures.

cond-mat.soft↗

arXiv2023

Phase behaviour of semiflexible lattice polymers in poor-solvent solution: mean-field theory and Monte Carlo simulations

We study a solution of interacting semiflexible polymers with curvature energy in poor-solvent conditions on the d-dimensional cubic lattice using mean-field theory and Monte Carlo computer simulations. Building upon past studies on a single chain, we construct a field-theory representation of the system and solve it within a mean-field approximation supported by Monte Carlo simulations in d=3. A gas-liquid transition is found in the temperature-density plane that is then interpreted in terms of real systems. Interestingly, we find this transition to be independent of the bending rigidity. Past classical Flory-Huggins and Flory mean-field results are shown to be particular cases of this more general framework. Perspectives in terms of guiding experimental results towards optimal conditions are also proposed.

cond-mat.soft↗