arXiv subjects

Thomas Voigtmann

Publications and source records attributed to Thomas Voigtmann.

At least 19 recordsLinked to original sources

arXiv2026

Using microrheology to study dynamical heterogeneities

Dynamical heterogeneities are one of the hallmarks of supercooled liquids, and their properties and relevance have been studied with theory, simulations and experiments. In this work, we propose to monitor the dynamics of tracer particles (passive microrheology) to analyze the dynamical heterogeneities in a system of hard colloids close to the glass transition density, using Langevin dynamics simulations and mode coupling theory. Different observables, typical in the study of the dynamical heterogeneities are adapted to be calculated from the trajectory of a single tracer particle. The tracer dynamics shows a transition from a regime where it is most decoupled from the bath for small tracer size to a strong coupling regime for large tracers. Both theory and simulations show that the non-Gaussian parameter of the tracer is maximal for tracer sizes at the crossover between both regimes, and is highly dependent on the bath density. The dynamic susceptibility is also studied, but this parameter shows a minor dependence on both the tracer size or the bath density. Finally, the existence of regions with different mobility is also studied with microrheology. Although the tracer trajectory indeed shows stages with increased mobility, the estimated size of the regions decreases with the bath density, contrary to the results from cluster analysis in the bulk.

cond-mat.soft↗

arXiv2026

Non-Monotonic Dynamical Correlations Across The Glass Crossover

The dramatic slowing down of structural relaxation in supercooled liquids is accompanied by the emergence of dynamic heterogeneity. A monotonically increasing dynamical correlation length, measured at the $\alpha$-timescale, is one of the remarkable features of this phenomenon. Here we show that this picture is incomplete: the dynamical correlation length measured in the $\beta$-relaxation regime exhibits a striking non-monotonic temperature dependence, reaching a maximum near the mode-coupling crossover temperature $T_c$ and decreasing upon further cooling, even as local dynamical fluctuations continue to intensify. This behavior suggests a crossover from spatially extended, maximally cooperative motion near $T_c$ to increasingly compact and localized relaxation events below it. We demonstrate that this evolution is quantitatively captured by stochastic beta-relaxation theory, an extension of mode-coupling theory beyond mean-field that explicitly predicts an avoided dynamical transition in finite dimensions. Our results provide the first direct spatial evidence in favor of the avoided-transition picture of the mode-coupling crossover, and establish the peak of the $\beta$-regime correlation length as a robust indicator of the mode-coupling crossover.

cond-mat.soft↗

arXiv2026

Molecular Dynamics simulations of Al-Ti metallic alloy melts using a transferable machine-learning potential

We investigate the structural and dynamical properties of binary aluminum-titanium liquid metallic alloys, as a function of temperature and composition. We make use of MD-simulations, using a transferable machine-learning potential developed by Song et al. [Nature Communications 15, 10208 (2024)], and compare our results to experimental data. Although this potential was initially trained on solid properties, we find good agreement between the experimental data and the simulation results for the liquid state. The excess volume and compositional changes of the structure are captured well by the machine-learned potential. The simulation allows to disentangle local packing from chemical-ordering effects; the latter are found to be weak in Al-Ti. Dynamical quantities like the viscosity and the diffusion coefficients are also discussed.

cond-mat.mtrl-sci↗

arXiv2025

Spreading droplets of yield-stress fluids with and without gravity

We investigate the effect of gravity on the spreading of droplets of yield stress fluids, by performing both microgravity experiments (in a drop tower) and experiments under terrestrial gravity. We investigate the dependence of the final droplet shape on yield stress and gravity. Droplets are deposited on a thin film of the same material, allowing to directly test scaling laws derived from the thin-film equation for viscoplastic fluids. Microgravity conditions allow to vary independently the two relevant dimensionless numbers, the Bond number, B, and the plastocapillary number, J, and thus to disentangle the influence of surface tension from that of the yield stress on the droplet shapes. Simulations using a visco-elastic model with shear thinning complement the experiments and show good agreement regarding the droplet shapes. Possible deviations arising in the regime of non-negligible elastic effects and large plastocapillary numbers (large yield stress) are discussed.

physics.flu-dyn↗

arXiv2025

Shear-Rate Dependent Surface Tension of Glass-Forming Fluids

We investigate the interface of a glass-forming fluid showing non-Newtonian rheology. By applying shear flow in the interface, we detect that the surface tension depends on the shear rate. Importantly, the standard way of determining surface tension from the pressure drop across the interface gives rise to an effective surface tension in the non-Newtonian fluid that mixes bulk and interface properties. We show how the pressure anisotropy can be used to clearly define the bulk and interface regions and extract a genuine shear-rate dependent surface tension. The results have implications for measurement techniques related to interfacial rheology of complex fluids.

cond-mat.soft↗

arXiv2024

Homogeneous Nucleation of Undercooled Al-Ni melts via a Machine-Learned Interaction Potential

Homogeneous nucleation processes are important for understanding solidification and the resulting microstructure of materials. Simulating this process requires accurately describing the interactions between atoms, hich is further complicated by chemical order through cross-species interactions. The large scales needed to observe rare nucleation events are far beyond the capabilities of ab initio simulations. Machine-learning is used for overcoming these limitations in terms of both accuracy and speed, by building a high-dimensional neural network potential for binary Al-Ni alloys, which serve as a model system relevant to many industrial applications. The potential is validated against experimental diffusion, viscosity, and scattering data, and is applied to large-scale molecular dynamics simulations of homogeneous nucleation at equiatomic composition, as well as for pure Ni. Pure Ni nucleates in a single-step into an fcc crystal phase, in contrast to previous results obtained with a classical empirical potential. This highlights the sensitivity of nucleation pathways to the underlying atomic interactions. Our findings suggest that the nucleation pathway for AlNi proceeds in a single step toward a B2 structure, which is discussed in relation to the pure elements counterparts.

cond-mat.mtrl-sci↗

arXiv2023

Feature Selection for High-Dimensional Neural Network Potentials with the Adaptive Group Lasso

Neural network potentials are a powerful tool for atomistic simulations, allowing to accurately reproduce \textit{ab initio} potential energy surfaces with computational performance approaching classical force fields. A central component of such potentials is the transformation of atomic positions into a set of atomic features in a most efficient and informative way.In this work, a feature selection method is introduced for high dimensional neural network potentials, based on the Adaptive Group Lasso (AGL) approach. It is shown that the use of an embedded method, taking into account the interplay between features and their action in the estimator, is necessary to optimize the number of features. The method's efficiency is tested on three different monoatomic systems, including Lennard-Jones as a simple test case, Aluminium as a system characterized by predominantly radial interactions, and Boron as representative of a system with strongly directional interactions. The AGL is compared with unsupervised filter methods and found to perform consistently better in reducing the number of features needed to reproduce the reference simulation data. {In particular, our results show the importance of taking into account model predictions in feature selection for interatomic potentials.

cond-mat.dis-nn↗

arXiv2023

Microscopic theory for nonequilibrium correlation functions in dense active fluids

One of the key hallmarks of dense active matter in the liquid, supercooled, and solid phases is so-called equal-time velocity correlations. Crucially, these correlations can emerge spontaneously, i.e., they require no explicit alignment interactions, and therefore represent a generic feature of dense active matter. This indicates that for a meaningful comparison or possible mapping between active and passive liquids one not only needs to understand their structural properties, but also the impact of these velocity correlations. This has already prompted several simulation and theoretical studies, though they are mostly focused on athermal systems and thus overlook the effect of translational diffusion. Here we present a fully microscopic method to calculate nonequilibrium correlations in systems of thermal active Brownian particles (ABPs). We use the integration through transients (ITT) formalism together with (active) mode-coupling theory (MCT) and analytically calculate qualitatively consistent static structure factors and active velocity correlations. We complement our theoretical results with simulations of both thermal and athermal ABPs which exemplify the disruptive role that thermal noise has on velocity correlations.

cond-mat.soft↗

arXiv2023

Residual stresses couple microscopic and macroscopic scales

We show how residual stresses emerge in a visco-elastic material as a signature of its past flow history, through an interplay between flow-modified microscopic relaxation and macroscopic features of the flow. Long-lasting temporal-history dependence of the microscopic dynamics and nonlinear rheology are incorporated through the mode-coupling theory of the glass transition (MCT). The theory's integral constitutive equation (ICE) is coupled to continuum mechanics in a finite-element method (FEM) scheme that tracks the flow history through the Finger tensor. The method is suitable for a calculation of residual stresses from a "first-principles" starting point following well-understood approximations. As an example, we calculate within a schematic version of MCT the stress-induced optical birefringence pattern of an amorphous solid cast into the shape of a slab with a cylindrical obstacle and demonstrate how FEM-MCT can predict the dependence of material properties on the material's processing history.

cond-mat.soft↗

arXiv2022

Spreading of droplets under various gravitational accelerations

We describe a setup to perform systematic studies on the spreading of droplets of complex fluids under microgravity conditions. Tweaking the gravitational acceleration under which droplets are deposited provides access to different regimes of the spreading dynamics, quantified through the Bond number. In particular, microgravity allows to form large droplets while remaining in the regime where surface tension effects and internal driving stresses are predominant over hydrostatic forces. The VIP-DROP2 experimental module provides a versatile platform to study a wide range of complex fluids through the deposition of axisymmetric droplets. The module offers the possibility to deposit droplets on a precursor layer, which can be composed of the same or of a different fluid. Besides, it allows to deposit four droplets simultaneously, while conducting shadowgraphy on all of them, and observing either the flow field (through particle image velocimetry), or the stress distribution inside the droplet in the case of stress birefringent fluids. Developed for a drop tower catapult system, it is designed to withstand a vertical acceleration of up to 30 times Earth's gravitational acceleration in the downwards direction, and can operate remotely, under microgravity conditions. We provide a detailed description of the module, and exemplary data analysis for droplets spreading on-ground and in microgravity.

physics.flu-dyn↗

arXiv2022

Interatomic machine learning potentials for aluminium: application to solidification phenomena

In studying solidification process by simulations on the atomic scale, the modeling of crystal nucleation or amorphisation requires the construction of interatomic interactions that are able to reproduce the properties of both the solid and the liquid states. Taking into account rare nucleation events or structural relaxation under deep undercooling conditions requires much larger length scales and longer time scales than those achievable by \textit{ab initio} molecular dynamics (AIMD). This problem is addressed by means of classical MD simulations using a well established high dimensional neural network potential trained on a relevant set of configurations generated by AIMD. Our dataset contains various crystalline structures and liquid states at different pressures, including their time fluctuations in a wide range of temperatures considering only their energy labels. Applied to elemental aluminium, the resulting potential is shown to be efficient to reproduce the basic structural, dynamics and thermodynamic quantities in the liquid and undercooled states without the need to include neither explicitly the forces nor all kind of configurations in the training procedure. The early stage of crystallization is further investigated on a much larger scale with one million atoms, allowing us to unravel features of the homogeneous nucleation mechanisms in the fcc phase at ambient pressure as well as in the bcc phase at high pressure with unprecedented accuracy close to the \textit{ab initio} one. In both case, a single step nucleation process is observed.

cond-mat.mtrl-sci↗

arXiv2022

From sub-aging to hyper-aging in structural glasses

We demonstrate non-equilibrium scaling laws for the aging dynamics in glass formers that emerge from combining a recent application of Onsager's theory of irreversible processes with the equilibrium scaling laws of glassy dynamics. Different scaling regimes are predicted for the evolution of the system's structural relaxation time $τ$ with age (waiting time $t_w$), depending on the depth of the quench from the liquid into the glass: \emph{simple aging} ($τ\sim t_w$) applies for quenches close to the critical point of mode-coupling theory (MCT) and implies \emph{sub-aging} ($τ\approx\ t_w^δ$ with $δ<1$) as a broad cross-over for quenches to nearly-arrested equilibrium states; \emph{hyper-aging} (or \emph{super-aging}, $τ\sim t_w^{δ'}$ with $δ'>1$) emerges for quenches deep into the glass. The latter is cut off by non-mean-field fluctuations that we account for within a recent extension of MCT, the stochastic $β$-relaxation theory (SBR). We exemplify the scaling laws by a schematic model that allows to quantitatively fit recent simulation results for density-quenched hard-sphere-like particles.

cond-mat.soft↗

arXiv2021

A gravity-independent powder-based additive manufacturing process tailored for space applications

The future of space exploration missions will rely on technologies increasing their endurance and self-sufficiency, including for manufacturing objects on-demand. We propose a process for handling and additively manufacturing powders that functions independently of the gravitational environment and with no restriction on feedstock powder flowability. Based on a specific sequence of boundary loads applied to the granular packing, powder is transported to the printing zone, homogenized and put under compression to increase the density of the final part. The powder deposition process is validated by simulations that show the homogeneity and density of deposition to be insensitive to gravity and cohesion forces within the DEM model. We further provide an experimental proof of concept of the process by successfully 3D printing parts on-ground and in weightlessness, on parabolic flight. Powders exhibiting high and low flowability are used as model feedstock material to demonstrate the versatility of the process, opening the way for additive manufacturing of recycled material.

cond-mat.mtrl-sci↗

arXiv2021

Mode-Coupling Theory for Tagged-Particle Motion of Active Brownian Particles

We derive a mode-coupling theory (MCT) to describe the dynamics of tracer particles in dense systems of active Brownian particles (ABPs) in two spatial dimensions. The ABP undergo translational and rotational Brownian dynamics, and are equipped with a fixed self-propulsion speed along their orientational vector that describes their active motility. The resulting equations of motion for the tagged-particle density correlation functions describe the various cases of tracer dynamics close to the glass transition: that of a passive colloidal particle in a suspension of ABP, that of a single active particle in a glass-forming passive host suspensions, and that of active tracers in a bath of active particles. Numerical results are presented for these cases assuming hard-sphere interactions among the particles. The qualitative and quantitative accuracy of the theory is tested against event-driven Brownian dynamics (ED-BD) simulations of active and passive hard disks. Simulation and theory are found in quantitative agreement, provided one adjusts the overall density (as known from the passive description of glassy dynamics), and allows for a rescaling of self-propulsion velocities in the active host system. These adjustments account for the fact that ABP-MCT generally overestimates the tendency for kinetic arrest. We also confirm in the simulations a peculiar feature of the transient and stationary dynamical density correlation functions regarding their lack of symmetry under time reversal, demonstrating the non-equilibrium nature of the system and how it manifests itself in the theory.

cond-mat.soft↗

arXiv2021

Tracer Dynamics in Crowded Active-Particle Suspensions

We derive equations of motion for the mean-squared displacement (MSD) of an active Brownian particle (ABP) in a crowded environment modeled by a dense system of passive Brownian particles, and of a passive tracer particle in a dense active-Brownian particle system, using a projection-operator scheme. The interaction of the tracer particle with the dense host environment gives rise to strong memory effects. Evaluating these approximately in the framework of a recently developed mode-coupling theory for the glass transition in active Brownian particles (ABP-MCT), we discuss the various regimes of activity-induced super-diffusive motion and density-induced sub-diffusive motion. The predictions of the theory are shown to be in good agreement with results from an event-driven Brownian dynamics simulation scheme for the dynamics of two-dimensional active Brownian hard disks.

cond-mat.soft↗

arXiv2021

Non-monotonic dynamic correlations beneath the surface of glass-forming liquids

Collective motion over increasing length scales is a signature of the vitrification process of liquids. We demonstrate the emergence of distinct static and dynamic length scales probed near the free surface in fully equilibrated glass-forming liquid films, and their connection to the bulk properties of the system. In contrast to a monotonically growing static correlation length, the dynamic correlation length that measures the extent of surface-dynamics acceleration into the bulk, displays a striking non-monotonic temperature evolution that is robust also against changes in detailed interatomic interaction. The maximum of dynamic correlations defines a cross-over temperature $T_*$ that we show to agree with a morphological change of cooperative rearrangement regions (CRR) of fast particles in the bulk liquids. The cross-over occurs at a temperature larger than the critical temperature Tc of mode-coupling theory (MCT). We link it to the point where fast-particle motion decouples from structural relaxation that can be defined rigorously within a recent extension of MCT, the stochastic $β$-relaxation theory (SBR).

cond-mat.stat-mech↗

arXiv2020

Transport Coefficients in Dense Active Brownian Particle Systems: Mode-Coupling Theory and Simulation Results

We discuss recent advances in developing a mode-coupling theory of the glass transition (MCT) of two-dimensional systems of active Brownian particles (ABP). We specifically discuss the case of a single ABP tracer in a glass-forming passive host suspension; a case that has recently been studied in experiments on colloidal Janus particles. We employ event-driven Brownian dynamics (ED-BD) computer simulations to test the ABP-MCT, and find good agreement between the two for the MSD. The ED-BD simulation results also compare well to experimental data, although a peculiar non-monotonic mapping of self-propulsion velocities is required. The ABP-MCT predicts a specific self-propulsion dependence of the Stokes-Einstein relation between the long-time diffusion coefficient and the host-system viscosity that matches well the results from simulation. An application of ABP-MCT within the integration-through transients (ITT) framework to calculate the density-renormalized effective swim velocity of the interacting ABP agrees qualitatively with the ED-BD simulation data at densities close to the glass transition, and quantitatively for the full density range only after the mapping of packing fractions employed for the passive system.

cond-mat.soft↗

arXiv2020

Scaling equations for mode-coupling theories with multiple decay channels

Multiple relaxation channels often arise in the dynamics of liquids where the momentum current associated to the particle-conservation law splits into distinct contributions. Examples are strongly confined liquids for which the currents in lateral and longitudinal direction to the walls are very different, or fluids of nonspherical particles with distinct relaxation patterns for translational and rotational degrees of freedom. Here, we perform an asymptotic analysis of the slow structural relaxation close to kinetic arrest as described by mode-coupling theory (MCT) with several relaxation channels. Compared to standard MCT, the presence of multiple relaxation channels significantly changes the structure of the underlying equations of motion and leads to additional, non-trivial terms in the asymptotic solution. We show that the solution can be rescaled, and thus prove that the well-known $ β$-scaling equation of MCT remains valid even in the presence of multiple relaxation channels. The asymptotic treatment is validated using a novel schematic model. We demonstrate that the numerical solution of this schematic model can indeed be described by the derived asymptotic scaling laws close to kinetic arrest. Additionally, clear traces of the existence of two distinct decay channels are found in the low-frequency susceptibility spectrum, suggesting that clear footprints of the additional relaxation channels can in principle be detected in simulations or experiments of confined or molecular liquids.

cond-mat.stat-mech↗