arXiv subjects

Gerhard Gompper

Publications and source records attributed to Gerhard Gompper.

At least 73 records · Page 4Linked to original sources

arXiv2019

Sculpting vesicles with active particles: Less is more

Biological cells are able to generate intricate structures and respond to external stimuli, sculpting their membrane from within. Simplified biomimetic systems can aid in understanding the principles which govern these shape changes and elucidate the response of the cell membrane under strong deformations. Here, a combined experimental and simulation approach is used to identify the conditions under which different non-equilibrium shapes and distinct active shape fluctuations can be obtained by enclosing self-propelled particles in giant vesicles. Interestingly, the most pronounced shape changes are observed at relatively low particle loadings, starting with the formation of tether-like protrusions to highly branched, dendritic structures. At high volume fractions, globally deformed vesicle shapes are observed. The obtained state diagram of vesicles sculpted by active particles predicts the conditions under which local internal forces can generate dramatic cell shape changes, such as branched structures in neurons.

cond-mat.soft↗

arXiv2019

Computational models for active matter

A variety of computational models have been developed to describe active matter at different length and time scales. The diversity of the methods and the challenges in modeling active matter---ranging from molecular motors and cytoskeletal filaments over artificial and biological swimmers on microscopic to groups of animals on macroscopic scales---mainly originate from their out-of-equilibrium character, multiscale nature, nonlinearity, and multibody interactions. In the present review, various modeling approaches and numerical techniques are addressed, compared, and differentiated to illuminate the innovations and current challenges in understanding active matter. The complexity increases from minimal microscopic models of dry active matter toward microscopic models of active matter in fluids. Complementary, coarse-grained descriptions and continuum models are elucidated. Microscopic details are often relevant and strongly affect collective behaviors, which implies that the selection of a proper level of modeling is a delicate choice, with simple models emphasizing universal properties and detailed models capturing specific features. Finally, current approaches to further advance the existing models and techniques to cope with real-world applications, such as complex media and biological environments, are discussed.

cond-mat.soft↗

arXiv2019

Tissue evolution: Mechanical interplay of adhesion, pressure, and heterogeneity

The evolution of various competing cell types in tissues, and the resulting persistent tissue population, is studied numerically and analytically in a particle-based model of active tissues. Mutations change the properties of cells in various ways, including their mechanical properties. Each mutation results in an advantage or disadvantage to grow in the competition between different cell types. While changes in signaling processes and biochemistry play an important role, we focus on changes in the mechanical properties by studying the result of variation of growth force and adhesive cross-interactions between cell types. For independent mutations of growth force and adhesion strength, the tissue evolves towards cell types with high growth force and low internal adhesion strength, as both increase the homeostatic pressure. Motivated by biological evidence, we postulate a coupling between both parameters, such that an increased growth force comes at the cost of a higher internal adhesion strength or vice versa. This tradeoff controls the evolution of the tissue, ranging from unidirectional evolution to very heterogeneous and dynamic populations. The special case of two competing cell types reveals three distinct parameter regimes: Two in which one cell type outcompetes the other, and one in which both cell types coexist in a highly mixed state. Interestingly, a single mutated cell alone suffices to reach the mixed state, while a finite mutation rate affects the results only weakly. Finally, the coupling between changes in growth force and adhesion strength reveals a mechanical explanation for the evolution towards intra-tumor heterogeneity, in which multiple species coexist even under a constant evolutianary pressure.

q-bio.PE↗

arXiv2019

Dissipative particle dynamics with energy conservation: isoenergetic integration and transport properties

Simulations of nano- to micro-meter scale fluidic systems under thermal gradients require consistent mesoscopic methods accounting for both hydrodynamic interactions and proper transport of energy. One such method is dissipative particle dynamics with energy conservation (DPDE), which has been used for various fluid systems with non-uniform temperature distributions. Despite the success of the method, existing integration algorithms have shown to result in an undesired energy drift, putting into question whether the DPDE method properly captures properties of real fluids. We propose a modification of the velocity-Verlet algorithm with local energy conservation for each DPDE particle, such that the total energy is conserved up to machine precision. Furthermore, transport properties of a DPDE fluid are analyzed in detail. In particular, an analytical approximation for the thermal conductivity coefficient is derived, which allows the selection of a specific value a priori. Finally, we provide approximate expressions for the dimensionless Prandtl and Schmidt numbers, which characterize fluid transport properties and can be adjusted independently by a proper selection of model parameters, and therefore, made comparable with those of real fluids. In conclusion, our results strengthen the DPDE method as a very robust approach for the investigation of mesoscopic systems with temperature inhomogeneities.

cond-mat.soft↗

arXiv2019

Deformation and dynamics of erythrocytes govern their traversal through microfluidic devices with a deterministic lateral displacement architecture

Deterministic lateral displacement (DLD) microfluidic devices promise versatile and precise processing of biological samples. However, this prospect has been realized so far only for rigid spherical particles and remains limited for biological cells due to the complexity of cell dynamics and deformation in microfluidic flow. We employ mesoscopic hydrodynamics simulations of red blood cells (RBC) in DLD devices with circular posts to better understand the interplay between cell behavior in complex microfluidic flow and sorting capabilities of such devices. We construct a mode diagram of RBC behavior (e.g. displacement, zig-zagging, and intermediate modes) and identify several regimes of RBC dynamics (e.g. tumbling, tank-treading, and trilobe motion). Furthermore, we link the complex interaction dynamics of RBCs with the post to their effective cell size and discuss relevant physical mechanisms governing the dynamic cell states. In conclusion, sorting of RBCs in DLD devices based on their shear elasticity is in general possible, but requires fine-tuning of flow conditions to targeted mechanical properties of the RBCs.

cond-mat.soft↗

arXiv2019

Filamentous Active Matter: Band Formation, Bending, Buckling, and Defects

Motor proteins drive persistent motion and self-organisation of cytoskeletal filaments. However, state-of-the-art microscopy techniques and continuum modelling approaches focus on large length and time scales. Here, we perform component-based computer simulations of polar filaments and molecular motors linking microscopic interactions and activity to self-organisation and dynamics from the two-filament level up to the mesoscopic domain level. Dynamic filament crosslinking and sliding, and excluded-volume interactions promote formation of bundles at small densities, and of active polar nematics at high densities. A buckling-type instability sets the size of polar domains and the density of topological defects. We predict a universal scaling of the active diffusion coefficient and the domain size with activity, and its dependence on parameters like motor concentration and filament persistence length. Our results provide a microscopic understanding of cytoplasmic streaming in cells and help to develop design strategies for novel engineered active materials.

cond-mat.soft↗

arXiv2019

Local stress and pressure in an inhomogeneous system of spherical active Brownian particles

The stress of a fluid on a confining wall is given by the mechanical wall forces, independent of the nature of the fluid being passive or active. At thermal equilibrium, an equation of state exists and stress is likewise obtained from intrinsic bulk properties; even more, stress can be calculated locally. Comparable local descriptions for active systems require a particular consideration of active forces. Here, we derive expressions for the stress exerted on a local volume of a systems of spherical active Brownian particles (ABPs). Using the virial theorem, we obtain two identical stress expressions, a stress due to momentum flux across a hypothetical plane, and a bulk stress inside of the local volume. In the first case, we obtain an active contribution to momentum transport in analogy to momentum transport in an underdamped passive system, and we introduce an active momentum. In the second case, a generally valid expression for the swim stress is derived. By simulations, we demonstrate that the local bulk stress is identical to the wall stress of a confined system for both, non-interacting ABPs as well as ABPs with excluded-volume interactions. This underlines the existence of an equation of state for a system of spherical ABPs. Most importantly, our calculations demonstrated that active stress is not a wall (boundary) effect, but is caused by momentum transport. We demonstrate that the derived stress expression permits the calculation of the local stress in inhomogeneous systems of ABPs.

cond-mat.soft↗

arXiv2019

Sharp-edged geometric obstacles in microfluidics promote deformability-based sorting of cells

Sorting cells based on their intrinsic properties is a highly desirable objective, since changes in cell deformability are often associated with various stress conditions and diseases. Deterministic lateral displacement (DLD) devices offer high precision for rigid spherical particles, while their success in sorting deformable particles remains limited due to the complexity of cell traversal in DLDs. We employ mesoscopic hydrodynamics simulations and demonstrate prominent advantages of sharp-edged DLD obstacles for probing deformability properties of red blood cells (RBCs). By consecutive sharpening of the pillar shape from circular to diamond to triangular geometry, a pronounced cell bending around an edge is achieved, serving as a deformability sensor. Bending around the edge is the primary mechanism, which governs the traversal of RBCs through such DLD device. This strategy requires an appropriate degree of cell bending by fluid stresses, which can be controlled by the flow rate, and exhibits good sensitivity to moderate changes in cell deformability. We expect that similar mechanisms should be applicable for the development of novel DLD devices that target intrinsic properties of many other cells.

physics.flu-dyn↗

arXiv2019

Sorting of particles suspended in whole blood

An important step in diagnostics is the isolation of specific cells and microorganisms of interest from blood. Since such bioparticles are often present at very low concentrations, throughput needs to be as high as possible. In addition, to ensure simplicity, a minimum of sample preparation is important. Therefore, sorting schemes that function for whole blood are highly desirable. Deterministic lateral displacement (DLD) has proven to be very precise and versatile in terms of a wide range of sorting parameters. To better understand how DLD performs for blood as the hematocrit increases, we have performed measurements and simulations for spherical particles in the micrometer range moving through DLD arrays for different flow velocities and hematocrits ranging from pure buffer to whole blood. We find that the separation function of the DLD array is sustained, even though blood cells introduce a shift in the trajectories and a significant dispersion for particles that are close to the critical size in the device. Simulations qualitatively replicate our experimental observations and help us identify fundamental mechanisms for the effect of hematocrit on the performance of the DLD device.

cond-mat.soft↗

arXiv2018

Traction force microscopy with optimized regularization and automated Bayesian parameter selection for comparing cells

Adherent cells exert traction forces on to their environment, which allows them to migrate, to maintain tissue integrity, and to form complex multicellular structures. This traction can be measured in a perturbation-free manner with traction force microscopy (TFM). In TFM, traction is usually calculated via the solution of a linear system, which is complicated by undersampled input data, acquisition noise, and large condition numbers for some methods. Therefore, standard TFM algorithms either employ data filtering or regularization. However, these approaches require a manual selection of filter- or regularization parameters and consequently exhibit a substantial degree of subjectiveness. This shortcoming is particularly serious when cells in different conditions are to be compared because optimal noise suppression needs to be adapted for every situation, which invariably results in systematic errors. Here, we systematically test the performance of new methods from computer vision and Bayesian inference for solving the inverse problem in TFM. We compare two classical schemes, L1- and L2-regularization, with three previously untested schemes, namely Elastic Net regularization, Proximal Gradient Lasso, and Proximal Gradient Elastic Net. Overall, we find that Elastic Net regularization, which combines L1 and L2 regularization, outperforms all other methods with regard to accuracy of traction reconstruction. Next, we develop two methods, Bayesian L2 regularization and Advanced Bayesian L2 regularization, for automatic, optimal L2 regularization. Using artificial data and experimental data, we show that these methods enable robust reconstruction of traction without requiring a difficult selection of regularization parameters specifically for each data set. Thus, Bayesian methods can mitigate the considerable uncertainty inherent in comparing cellular traction forces.

physics.bio-ph↗

arXiv2018

Mechanics of tissue competition: Interfaces stabilize coexistence

Mechanical forces influence the dynamics of growing tissues. Computer simulations are employed to study the importance of interfacial effects in tissue competition. It was speculated that mechanical pressure determines the competition, where the determining quantity is the homeostatic pressure - the pressure where division and apoptosis balance; the tissue with the higher homeostatic pressure overwhelms the other. Surprisingly, a weaker tissue can persist in stable coexistence with a stronger tissue, if adhesion between them is small enough. An analytic continuum description can quantitatively describe the underlying mechanism and reproduce the resulting pressures and cell-number fractions. Computer simulations furthermore display a variety of coexisting structures, ranging from spherical inclusions to a bicontinuous state.

physics.bio-ph↗

arXiv2018

Collective behavior of self-propelled rods with quorum sensing

Active agents - like phoretic particles, bacteria, sperm, and cytoskeletal filaments in motility assays - show a large variety of motility-induced collective behaviors, such as aggregation, clustering and phase separation. The behavior of dense suspensions of phoretic particles and of bacteria during biofilm formation is determined by two principle physical mechanisms: (i) volume exclusion (short-range steric repulsion) and (ii) quorum sensing (longer-range reduced propulsion due to alteration of the local chemical environment). To systematically characterize such systems, we study semi-penetrable self-propelled rods in two dimensions, with a propulsion force that decreases with increasing local rod density, by employing Brownian Dynamics simulations. Volume exclusion and quorum sensing both lead to phase separation, however, the structure and rod dynamics vastly differ. Quorum sensing enhances the polarity of the clusters, induces perpendicularity of rods at the cluster borders, and enhances cluster formation. For systems, where the rods essentially become passive at high densities, formation of asters and stripes is observed. Systems of rods with larger aspect ratios show more ordered structures compared to those with smaller aspect ratios, due to their stronger alignment, with almost circular asters for strongly density-dependent propulsion force. With increasing range of the quorum-sensing interaction, the local density decreases, asters become less stable, and polar hedgehog clusters and clusters with domains appear. Our results characterize structure formation and dynamics due to the competition of two qualitatively different interaction mechanisms, steric hindrance and quorum sensing, which are both relevant for engineered phoretic microswimmers as well as for bacteria in biofilm formation.

cond-mat.soft↗

arXiv2018

Clustering of microswimmers: Interplay of shape and hydrodynamics

The spatiotemporal dynamics in systems of active self-propelled particles is controlled by the propulsion mechanism in combination with various direct interactions, such as steric repulsion, hydrodynamics, and chemical fields. Yet, these direct interactions are typically anisotropic, and come in different 'flavors', such as spherical and elongated particle shapes for steric repulsion, pusher and puller flow fields for hydrodynamics, etc. The combination of the various aspects is expected to lead to new emergent behavior. However, it is a priori not evident whether shape and hydrodynamics act synergistically or antagonistically to generate motility-induced clustering (MIC) and phase separation (MIPS). We employ a model of prolate spheroidal microswimmers - called squirmers - in quasi-two-dimensional confinement to address this issue by mesoscale hydrodynamic simulations. For comparison, non-hydrodynamic active Brownian particles (ABPs) are considered to elucidate the contribution of hydrodynamic interactions on MIC and MIPS. For spherical particles, the comparison between ABP and hydrodynamic-squirmer ensembles reveals a suppression of MIPS due to hydrodynamic interactions. The fundamental difference between ABPs and squirmers is attributed to an increased reorientation of squirmers by hydrodynamic torques during their collisions. In contrast, for elongated squirmers, hydrodynamics interactions enhance MIPS. Thus, hydrodynamic interactions show opposing effects on MIPS for spherical and elongated microswimmers.

cond-mat.soft↗

arXiv2018

Tunable viscosity modification with diluted particles: When particles decrease the viscosity of complex fluids

While spherical particles are the most studied viscosity modifiers, they are well known only to increase viscosities, in particular at low concentrations. Extended studies and theories on non-spherical particles find a more complicated behavior, but still a steady increase. Involving platelets in combination with complex fluids displays an even more complex scenario that we analyze experimentally and theoretically as a function of platelet diameter, to find the underlying concepts. Using a broad toolbox of different techniques we were able to decrease the viscosity of crude oils although solid particles were added. This apparent contradiction could lead to a wider range of applications.

cond-mat.soft↗

arXiv2018

Steady state sedimentation of ultrasoft colloids

The structural and dynamical properties of ultra-soft colloids - star polymers - exposed to a uniform external force field are analyzed applying the multiparticle collision dynamics approach, a hybrid coarse-grain mesoscale simulation approach, which captures thermal fluctuations and long-range hydrodynamic interactions. In the weak field limit, the structure of the star polymer is nearly unchanged, however in an intermediate regime, the radius of gyration decreases, in particular transverse to the sedimentation direction. In the limit of a strong field, the radius of gyration increases with field strength. Correspondingly, the sedimentation coefficient increases with increasing field strength, passes through a maximum and decreases again at high field strengths. The maximum value depends on the functionality of the star polymer. High field strengths lead to symmetry breaking with trailing, strongly stretched polymer arms and a compact star polymer body. In the weak field linear response regime, the sedimentation coefficient follows the scaling relation of a star polymer in terms of functionality and arm length.

cond-mat.soft↗

arXiv2018

Hydrodynamics of Binary Fluid Mixtures - An Augmented Multiparticle Collison Dynamics Approach

The Multiparticle Collision Dynamics technique (MPC) for hydrodynamics simulations is generalized to binary fluid mixtures and multiphase flows, by coupling the particle-based fluid dynamics to a Ginzburg-Landau free-energy functional for phase-separating binary fluids. To describe fluids with a non-ideal equation of state, an additional density-dependent term is introduced. The new approach is verified by applying it to thermodynamics near the critical demixing point, and interface fluctuations of droplets. The interfacial tension obtained from the analysis of the capillary wave spectrum agrees well with the results based on the Laplace-Young equation. Phase-separation dynamics follows the Lifshitz-Slyozov law.

cond-mat.soft↗

arXiv2018

Collective Dynamics of Self-propelled Semiflexible Filaments

The collective behavior of active semiflexible filaments is studied with a model of tangentially driven self-propelled worm-like chains. The combination of excluded-volume interactions and self-propulsion leads to several distinct dynamic phases as a function of bending rigidity, activity, and aspect ratio of individual filaments. We consider first the case of intermediate filament density. For high-aspect-ratio filaments, we identify a transition with increasing propulsion from a state of free-swimming filaments to a state of spiraled filaments with nearly frozen translational motion. For lower aspect ratios, this gas-of-spirals phase is suppressed with growing density due to filament collisions; instead, filaments form clusters similar to self-propelled rods, as activity increases. Finite bending rigidity strongly effects the dynamics and phase behavior. Flexible filaments form small and transient clusters, while stiffer filaments organize into giant clusters, similarly as self-propelled rods, but with a reentrant phase behavior from giant to smaller clusters as activity becomes large enough to bend the filaments. For high filament densities, we identify a nearly frozen jamming state at low activities, a nematic laning state at intermediate activities, and an active-turbulence state at high activities. The latter state is characterized by a power-law decay of the energy spectrum as a function of wave number. The resulting phase diagrams encapsulate tunable non-equilibrium steady states that can be used in the organization of living matter.

physics.bio-ph↗

arXiv2018

Quantitative modelling of nutrient-limited growth of bacterial colonies in microfluidic cultivation

Nutrient gradients and limitations play a pivotal role in the life of all microbes, both in their natural habitat as well as in artificial, microfluidic systems. Spatial concentration gradients of nutrients in densely packed cell configurations may locally affect the bacterial growth leading to heterogeneous micropopulations. A detailed understanding and quantitative modelling of cellular behaviour under nutrient limitations is thus highly desirable. We use microfluidic cultivations to investigate growth and microbial behaviour of the model organism Corynebacterium glutamicum under well-controlled conditions. With a reaction-diffusion type model, parameters are extracted from steady-state experiments with a one-dimensional nutrient gradient. Subsequentially, we employ particle-based simulations with these parameters to predict the dynamical growth of a colony in two dimensions. Comparing the results of those simulations with microfluidic experiments yields excellent agreement. Our modelling approach lays the foundation for a better understanding of dynamic microbial growth processes, both in nature and in applied biotechnology.

physics.bio-ph↗