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Joachim Dzubiella

Publications and source records attributed to Joachim Dzubiella.

At least 19 recordsLinked to original sources

Tunable Signal Penetration and Response Plateaus in Bistable Mechanical Media

Dynamically processing mechanical signals is crucial for soft robotics and mechanosensing, where classical viscoelastic materials lack intrinsic tunability. We show that internal bistability actively controls the response and signal attenuation in mechanical (meta)materials. In our model, bistable elements switch discretely with a predefined timescale between states distinguished by potential energy $ε$, equilibrium length $Δl$, and spring constant $Δk$. The system is simulated via microscopic Brownian dynamics coupled to Poisson switching with rate $ν$, and described macroscopically by a nonlinear continuum field theory. Crucially, the model yields closed-form analytical solutions for the linear response and spatial penetration depth, revealing two phenomena: a universal screening mechanism (akin to the electrostatic 'skin effect') reducing spatial signal penetration when the driving frequency exceeds the internal relaxation rate, and a frequency-insensitive response plateau from timescale separation. The screening length is controlled primarily by the conformational length change $Δl$, while the attenuation regime and plateau are tuneable via the switching rate $ν$. A systematic parameter study exposes a fundamental design trade-off: larger $Δl$ strengthens dissipation but raises the energy barrier for state transitions, eventually causing state-locking where damping vanishes. Optimal attenuation thus requires a compromise between pronounced bistability and a surmountable barrier. Due to its analytical tractability, our framework provides explicit design rules for fine-tuning the adaptive response of bistable media. It applies to diverse experimental systems-from biopolymers to synthetic catch bonds and metamaterials-enabling the predictive engineering of intelligent soft matter for frequency-selective signal processing.

cond-mat.soft↗

Non-equilibrium (thermo)dynamics of colloids under mobile piston compression

We investigate the non-equilibrium compression of a confined hard-sphere colloidal fluid driven by a mobile boundary within dynamical density functional theory. The system consists of a fluid confined between two parallel walls, one acting as an overdamped piston subjected to a sudden increase in external pressure. The piston motion is controlled by a mobility parameter $K$, which sets the relative timescale between mechanical driving and diffusive relaxation. By varying $K$ over several orders of magnitude, we identify a crossover from quasi-static compression to a diffusion-limited strongly driven regime. For small $K$, the system evolves close to equilibrium and the total injected work approaches the equilibrium free-energy difference. For large $K$, the piston rapidly adjusts and the dynamics becomes governed by diffusive relaxation, leading to saturation in the piston trajectory, pressure--position relation, particle currents, and center-of-mass velocity. In this regime, the injected work and entropy production are bounded, reflecting constraints imposed by diffusive transport. The maximum injected power scales linearly with $K$, while the entropy-production peak exhibits a crossover from quadratic growth to saturation, with peak times displaying $1/K$ scaling. The entropy change of the thermal bath interpolates between a reversible limit and a strongly driven dissipative regime. Finally, the evolution of configurational entropy and external potential energy reveals a dynamical decoupling between confinement and structural relaxation, including transient non-monotonic behavior. These results provide a quantitative thermodynamic characterization of boundary-driven compression.

cond-mat.soft↗

Nonequilibrium friction and free energy estimates for kinetic coarse-graining -- Driven particles in responsive media

Predicting the molecular friction and energy landscapes under nonequilibrium conditions is key to coarse-graining the dynamics of selective solute transport through complex, fluctuating and responsive media, e.g., polymeric materials such as hydrogels, cellular membranes or ion channels. The analysis of equilibrium ensembles already allows such a coarse-graining for very mild nonequilibrium conditions. Yet in the presence of stronger external driving and/or inhomogeneous setups, the transport process is governed apart from a potential of mean force also by a nontrivial position- and velocity-dependent friction. It is therefore important to find suitable and efficient methods to estimate the mean force and the friction landscape, which then can be used in a low-dimensional, coarse-grained Langevin framework to predict the system's transport properties and timescales. In this work, we evaluate different coarse-graining approaches based on constant-velocity constraint simulations for generating such estimates using two model systems, which are a 1D responsive barrier as a minimalistic model and a single tracer driven through a 3D bead-spring polymer membrane as a more sophisticated problem. Finally, we demonstrate that the estimates from 3D constant-velocity simulations yield the correct velocity-dependent friction, which can be directly utilized for coarse-grained (1D) Langevin simulations with constant external driving forces.

cond-mat.soft↗

Collective dynamics and elasto-chemical cluster waves in communicating colloids with explicit size response

Chemical communication, response, and feedback are key requirements for the function of adaptive materials with life-like properties. However, how communication on the single cell-level impacts the collective structural, dynamical and mechanical behavior of active soft matter is not well understood. Here, we report how communication controls the spatiotemporal structure and phase behavior of active, hydrogel-based colloidal liquids using Brownian particle-based simulations with explicit resolution of the chemical signaling waves as well as the individual particle's elastic response to communication and crowding. We find a rich topology of nonequilibrium active phases, vastly tuneable by the signaling magnitude, in particular, active melting, synchronization transitions from uncorrelated to antiphase oscillatory liquids, or to in-phase oscillations with accompanying elasto-chemical cluster waves. Our work employs minimal physical principles required for communication-mediated dynamics of microscopic, fluctuating systems, thus uncovering universal aspects in signaling soft systems.

cond-mat.soft↗

Nonequilibrium relaxation of soft responsive colloids

Stimuli-responsive macromolecules display large conformational changes during their dynamics, sometimes switching states, and are an integral property for the development of soft functional materials. Here, we introduce a mean-field dynamical density functional theory (DDFT) for a model of responsive colloids (RCs) to study the nonequilibrium dynamics of a colloidal dispersion in time-dependent external fields, with a focus on the coupling of translational and conformational dynamics during their relaxation. Specifically, we consider soft Gaussian particles with a bimodal size distribution between two confining walls with time-dependent (switching-on and off) external gravitational and osmotic fields. We find a rich relaxation behavior of the systems in excellent agreement with particle-based Brownian dynamics (BD) computer simulations. In particular, we find time-asymmetric relaxations of integrated observables (wall pressures, mean size, liquid center-of-mass) for activation/deactivation of external potentials, respectively, which are tuneable by the ratio of translational and conformational diffusion time scales. Our work paves thus the way for studying the nonequilibrium relaxation dynamics of complex soft matter with multiple degrees of freedom and hierarchical relaxations.

cond-mat.soft↗

Tracer dynamics in polymer networks: generalized Langevin description

Tracer diffusion in polymer networks and hydrogels is relevant in biology and technology, while it also constitutes an interesting model process for the dynamics of molecules in fluctuating, heterogeneous soft matter. Here, we study systematically the time-dependent dynamics and (non-Markovian) memory effects of tracers in polymer networks based on (Markovian) implicit-solvent Langevin simulations. In particular, we consider spherical tracer solutes at high dilution in regular, tetrafunctional bead-spring polymer networks, and control the tracer-network Lennard-Jones (LJ) interactions and the polymer density. Based on the analysis of the memory (friction) kernels, we recover the expected long-time transport coefficients, and demonstrate how the short-time tracer dynamics, polymer fluctuations, and the viscoelastic response are interlinked. Further, we fit the characteristic memory modes of the tracers with damped harmonic oscillations and identify LJ contributions, bond vibrations, and slow network relaxations, which enter the kernel with an almost linear scaling with the LJ attractions. This procedure proposes a reduced functional form for the tracer memory, allowing for a convenient inter- and extrapolation of the memory kernels. This leads eventually to highly efficient simulations utilizing the generalized Langevin equation (GLE), in which the polymer network acts as an additional thermal bath with tuneable intensity.

cond-mat.soft↗

Intramolecular Structural Heterogeneity altered by Long-range Contacts in an Intrinsically Disordered Protein

Short-range interactions and long-range contacts drive the 3D folding of structured proteins. The proteins' structure has a direct impact on their biological function. However, nearly 40% of the eukaryotes proteome is composed of intrinsically disordered proteins (IDPs) and protein regions that fluctuate between ensembles of numerous conformations. Therefore, to understand their biological function, it is critical to depict how the structural ensemble statistics correlate to the IDPs' amino acid sequence. Here, using small-angle x-ray scattering (SAXS) and time-resolved Förster resonance energy transfer (trFRET), we study the intra-molecular structural heterogeneity of the neurofilament low intrinsically disordered tail domain (NFLt). Using theoretical results of polymer physics, we find that the Flory scaling exponent of NFLt sub-segments correlates linearly with their net charge, ranging from statistics of ideal to self-avoiding chains. Surprisingly, measuring the same segments in the context of the whole NFLt protein, we find that regardless of the peptide sequence, the segments' structural statistics are more expanded than when measured independently. Our findings show that while polymer physics can, to some level, relate the IDP's sequence to its ensemble conformations, long-range contacts between distant amino acids play a crucial role in determining intra-molecular structures. This emphasizes the necessity of advanced polymer theories to fully describe IDPs ensembles with the hope it will allow us to model their biological function.

physics.bio-ph↗

Synergistic chemomechanical dynamics of feedback-controlled microreactors

The experimental control of synergistic chemomechanical dynamics of catalytically active microgels (microreactors) is a key prerequisite for the design of adaptive and biomimetic materials. Here, we report a minimalistic model of feedback-controlled microreactors based on the coupling between the hysteretic polymer volume phase transition and a volume-controlled permeability for the internal chemical conversion. We categorize regimes of mono- and bistability, excitability, damped oscillations, as well as sustained oscillatory states with tunable amplitude, as indicated by experiments and representable by the FitzHugh-Nagumo dynamics for neurons. We summarize the features of such a colloidal neuron in bifurcation diagrams with respect to microgel design parameters, such as permeability and relaxation times, as a guide for experimental synthesis.

cond-mat.soft↗

Mean-field models for the chemical fueling of transient soft matter states

The chemical fueling of transient states (CFTS) is a powerful process to control the nonequilibrium structuring and the homeostatic function of adaptive soft matter systems. Here, we introduce a mean-field model of CFTS based on the activation of metastable equilibrium states in a tilted Landau bistable energy landscape along a coarse-grained reaction coordinate (or order parameter) triggered by a nonmonotonic two-step chemical fueling reaction. Evaluation of the model in the quasi-static (QS) limit - valid for fast system relaxation - allows us to extract useful analytical laws for the critical activation concentration and duration of the transient states in dependence of physical parameters, such as rate constants, fuel concentrations, and the system's distance to its equilibrium transition point. We apply our model in the QS limit to recent experiments of CFTS of collapsing responsive microgels and find a very good performance with only a few global and physically interpretable fitting parameters, which can be employed for programmable material design. Moreover, our model framework also allows a thermodynamic analysis of the energy and performed work in the system. Finally, we go beyond the QS limit, where the system's response is slow and retarded versus the chemical reaction, using an overdamped Smoluchowski approach. The latter demonstrates how internal system time scales can be used to tune the time-dependent behavior and programmed delay of the transient states in full nonequilibrium.

cond-mat.soft↗

Feedback-controlled solute transport through chemo-responsive polymer membranes

Polymer membranes are typically assumed to be inert and nonresponsive to the flux and density of the permeating particles in transport processes. Here, we study theoretically the consequences of membrane responsiveness and feedback on the steady-state force--flux relations and membrane permeability using a nonlinear-feedback solution-diffusion model of transport through a slab-like membrane. Therein, the solute concentration inside the membrane depends on the bulk concentration, $c_0$, the driving force, $f$, and the polymer volume fraction, $ϕ$. In our model, solute accumulation in the membrane causes a sigmoidal volume phase transition of the polymer, changing its permeability, which, in return, affects the membrane's solute uptake. This feedback leads to nonlinear force--flux relations, $j(f)$, which we quantify in terms of the system's differential permeability, $\mathcal{P}_\text{sys}^Δ\propto {\mathrm{d}j}/{\mathrm{d}f}$. We find that the membrane feedback can increase or decrease the solute flux by orders of magnitude, triggered by a small change in the driving force, and largely tunable by attractive versus repulsive solute--membrane interactions. Moreover, controlling the input, $c_0$ and $f$, can lead to steady-state bistability of $ϕ$ and hysteresis in the force--flux relations. This work advocates that the fine-tuning of the membrane's chemo-responsiveness will enhance the nonlinear transport control features, providing great potential for future (self-)regulating membrane devices.

cond-mat.soft↗

Hydration structure of diamondoids from reactive force fields

Diamondoids are promising materials for applications in catalysis and nanotechnology. Since many of their applications are in aqueous environments, to understand their function it is essential to know the structure and dynamics of the water molecules in their first hydration shells. In this study, we develop an improved reactive force field (ReaxFF) parameter set for atomistically resolved molecular dynamics simulations of hydrated diamondoids to characterize their interfacial water structure. We parameterize the force field and validate the water structure against geometry-optimized structures from density functional theory. We compare the results to water structures around diamondoids with all partial charges set to zero, and around charged smooth spheres, and find qualitatively similar water structuring in all cases. However, the response of the water molecules is most sensitive to the partial charges in the atomistically resolved diamondoids. From the systematic exclusion of atomistic detail we can draw generic conclusions about the nature of the hydrophobic effect at nanoparticle interfaces and link it to the interfacial water structure. The interactions between discrete partial charges on short length scales affect the hydration structures strongly but the hydrophobic effect seems to be stable against these short scale surface perturbations. Our methods and the workflow we present are transferable to other hydrocarbons and interfacial systems.

cond-mat.mes-hall↗

Active responsive colloids driven by intrinsic dichotomous noise

We study the influence of intrinsic noise on the structure and dynamics of responsive colloids (RCs) which actively change their size and mutual interactions. The colloidal size is explicitly resolved in our RC model as an internal degree of freedom (DOF) in addition to the particle translation. A Hertzian pair potential between the RCs leads to repulsion and shrinking of the particles, resulting in an explicit responsiveness of the system to self-crowding. To render the colloids active, their size is internally driven by a dichotomous noise, randomly switching ('breathing') between growing and shrinking states with a predefined rate, as motivated by recent experiments on synthetic active colloids. The polydispersity of this dichotomous active responsive colloid (D-ARC) model can be tuned by the parameters of the noise. Utilizing stochastic computer simulations, we study crowding effects on the spatial distributions, relaxation times, and self-diffusion of dense suspensions of the D-ARCs. We find a substantial influence of the 'built-in' intrinsic noise on the system's behavior, in particular, transitions from unimodal to bimodal size distributions for an increasing colloid density as well as intrinsic noise-modified diffusive translational dynamics. We conclude that controlling the noise of internal DOFs of a macromolecule or cell is a powerful tool for active colloidal materials to enable autonomous changes in the system's collective structure and dynamics towards the adaption of macroscopic properties to external perturbations.

cond-mat.soft↗

Machine learning frontier orbital energies of nanodiamonds

Nanodiamonds have a wide range of applications including catalysis, sensing, tribology and biomedicine. To leverage nanodiamond design via machine learning, we introduce the new dataset ND5k, consisting of 5,089 diamondoid and nanodiamond structures and their frontier orbital energies. ND5k structures are optimized via tight-binding density functional theory (DFTB) and their frontier orbital energies are computed using density functional theory (DFT) with the PBE0 hybrid functional. We also compare recent machine learning models for predicting frontier orbital energies for similar structures as they have been trained on (interpolation on ND5k), and we test their abilities to extrapolate predictions to larger structures. For both the interpolation and extrapolation task, we find best performance using the equivariant graph neural network PaiNN. The second best results are achieved with a message passing neural network using a tailored set of atomic descriptors proposed here.

physics.chem-ph↗

Nonequilibrium free energy during polymer chain growth

During fast diffusion-influenced polymerization, nonequilibrium behavior of the polymer chains and the surrounding reactive monomers has been reported recently. Based on the laws of thermodynamics, the emerging nonequilibrium structures should be characterisable by some "extra free energy" (excess over the equilibrium Helmholtz free energy). Here, we study the nonequilibrium thermodynamics of chain-growth polymerization of ideal chains in a dispersion of free reactive monomers, using off-lattice, reactive Brownian Dynamics (R-BD) computer simulations in conjunction with approximative statistical mechanics and relative entropy (Gibbs-Shannon and Kullback-Leibler) concepts. In case of fast growing polymers, we indeed report increased nonequilibrium free energies of several kBT compared to equilibrium and near-equilibrium, slowly growing chains. Interestingly, the extra free energy is a non-monotonic function of the degree of polymerization and thus also of time. Our decomposition of the thermodynamic contributions shows that the initial dominant extra free energy is stored in the nonequilibrium inhomogeneous density profiles of the free monomer gas (showing density depletion and wakes) in the vicinity of the active center at the propagating polymer end. At later stages of the polymerization process, we report significant extra contributions stored in the nonequilibrium polymer conformations. Finally, our study implies a nontrivial relaxation kinetics and restoring of the extra free energy during the equilibration process after polymerization.

cond-mat.soft↗

Active interaction switching controls the dynamic heterogeneity of soft colloidal dispersions

We employ Reactive Dynamical Density Functional Theory (R-DDFT) and Reactive Brownian Dynamics (R-BD) simulations to investigate the dynamics of a suspension of active soft Gaussian colloids with binary interaction switching, i.e., a one-component colloidal system in which every particle stochastically switches at predefined rates between two interaction states with different mobility. Using R-DDFT we extend a theory previously developed to access the dynamics of inhomogeneous liquids to study the influence of the switching activity on the self and distinct part of the Van Hove function in bulk solution, and determine the corresponding mean squared displacement of the switching particles. Our results demonstrate that, even though the average diffusion coefficient is not affected by the switching activity, it significantly modifies the non-equilibrium dynamics and diffusion coefficients of the individual particles, leading to a crossover from short to long times, with a regime for intermediate times showing anomalous diffusion. In addition, the self-part of the van Hove function has a Gaussian form at short and long times, but becomes non-Gaussian at intermediates ones, having a crossover between short and large displacements. The corresponding self-intermediate scattering function shows the two-step relaxation patters typically observed in soft materials with heterogeneous dynamics such as glasses and gels. We also introduce a phenomenological Continuous Time Random Walk (CTRW) theory to understand the heterogeneous diffusion of this system. R-DDFT results are in excellent agreement with R-BD simulations and the analytical predictions of CTRW theory, thus confirming that R-DDFT constitutes a powerful method to investigate not only the structure and phase behavior, but also the dynamical properties of non-equilibrium active switching colloidal suspensions.

cond-mat.soft↗

Growth modes of partially fluorinated organic molecules on amorphous silicon dioxide

We study the influence of fluorination on nucleation and growth of the organic para-sexiphenyl molecule (p-6P) on amorphous silicon dioxide ($α$-SiO$_2$) by means of atomistically resolved classical molecular dynamics computer simulations. We use a simulation model that mimics the experimental deposition from the vapor and subsequent self-assembly onto the underlying surface. Our model reproduces the experimentally observed orientational changes from lying to upright standing configurations of the grown layers. We demonstrate that the increase in the number of fluorinated groups inside the p-6P leads to a smoother, layer-by-layer growth on the $α$-SiO$_2$ surface: We observe that in the first layers, due to strong molecule-substrate interactions the molecules first grow in chiral (fan-like) structures, where each consecutive molecule has a higher angle, supported by molecules lying underneath. Subsequently deposited molecules bind to the already standing molecules of the chiral structures until all molecules are standing. The growth of chiral islands is the main mechanism for growth of the fluorinated p-6P derivative, while the p-6P, due to the lower interaction with the underlying substrate, forms less chiral structures. This leads to a lower energy barrier for step-edge crossing for the fluorinated molecules. We find that partial fluorination of the p-6P molecule can in this way significantly alter its growth behaviour by modifying the rough, 3D growth into a smooth, layer-by-layer growth. This has implications for the rational design of molecules and their functionalized forms which could be tailored for a desired growth behavior and structure formation.

cond-mat.mes-hall↗

Modulating internal transition kinetics in responsive macromolecules by collective crowding

Packing and crowding are used in biology as mechanisms to (self-)regulate internal molecular or cellular processes based on collective signalling. Here, we study how the transition kinetics of an internal switch of responsive macromolecules is modified collectively by their spatial packing. We employ Brownian dynamics simulations of a model of responsive colloids (RCs), in which an explicit internal degree of freedom, here, the particle size, moving in a bimodal energy landscape responds self-consistently to the density fluctuations of the crowded environment. We demonstrate that populations and transition times for the two-state switching kinetics can be tuned over one order of magnitude by self-crowding. An exponential scaling law derived from a combination of Kramers' and liquid state perturbation theory is in very good agreement with the simulations.

cond-mat.soft↗

Nanochannels and nanodroplets in polymer membranes controlling ionic transport

Polymer materials with low water uptake exhibit a highly heterogeneous interior, characterized by water clusters in the form of nanodroplets and nanochannels. Here, based on our recent insights from computer simulations, we argue that water cluster structure has large implications for ionic transport and selective permeability in polymer membranes. Importantly, we demonstrate that the two key quantities for transport, the ion diffusion and the solvation free energy inside the polymer, are extremely sensitive to molecular details of the water clusters. In particular, we highlight the significance of water droplet interface potentials and the nature of hopping diffusion through transient water channels. These mechanisms can be harvested and fine-tuned to optimize selectivity in ionic transport in a wide range of applications.

cond-mat.soft↗