Mobility Tensor Research Articles

Active spheroids in viscosity gradients

In this paper, we explore the hydrodynamics of spheroidal active particles in viscosity gradients. This work provides a more accurate modelling approach, in comparison to spherical particles, for anisotropic organisms such as Paramecium swimming through inhomogeneous environments, but more fundamentally examines the influence of particle shape on viscotaxis. We find that spheroidal squirmers generally exhibit dynamics consistent with their spherical analogues, irrespective of the classification of swimmers as pushers, pullers or neutral swimmers. However, the slenderness of the spheroids tends to reduce the impact of viscosity gradients on their dynamics; when a swimmer becomes more slender, the viscosity difference across its body is reduced, which leads to slower reorientation. We also derive the mobility tensor for passive spheroids in viscosity gradients, generalizing previous results for spheres and slender bodies. This work enhances our understanding of how shape factors into the dynamics of passive and active particles in viscosity gradients, and offers new perspectives that could aid the control of both natural and synthetic swimmers in complex fluid environments.

Finite‐strain poro‐visco‐elasticity with degenerate mobility

AbstractA quasistatic nonlinear model for poro‐visco‐elastic solids at finite strains is considered in the Lagrangian frame using the concept of second‐order nonsimple materials and Kelvin–Voigt‐type viscosity. The elastic stresses satisfy static frame‐indifference, while the viscous stresses satisfy dynamic frame‐indifference. The mechanical equation is coupled to a diffusion equation for a solvent or fluid content. The latter is pulled‐back to the reference configuration. To treat the nonlinear dependence of the mobility tensor on the deformation gradient, the result by Healey and Krömer is used to show that the determinant of the deformation gradient is bounded away from zero. Moreover, the focus is on the physically relevant case of degenerate mobilities. The existence of weak solutions is shown using a staggered time‐incremental scheme and suitable energy‐dissipation inequalities.

Sedimentation of spheroids in Newtonian fluids with spatially varying viscosity

This paper examines the rigid body motion of a spheroid sedimenting in a Newtonian fluid with a spatially varying viscosity field. The fluid is at zero Reynolds number, and the viscosity varies linearly in space in an arbitrary direction with respect to the external force. First, we obtain the correction to the spheroid's rigid body motion in the limit of small viscosity gradients, using a perturbation expansion combined with the reciprocal theorem. Next, we determine the general form of the particle's mobility tensor relating its rigid body motion to an external force and torque. The viscosity gradient does not alter the force/translation and torque/rotation relationships, but introduces new force/rotation and torque/translation couplings that are determined for a wide range of particle aspect ratios. Finally, we discuss results for the spheroid's rotation and centre-of-mass trajectory during sedimentation. A steady orientation arises at long time whose value depends on the viscosity gradient direction and particle shape. These results are significantly different than when no viscosity gradient is present, where the particle stays at its initial orientation for all times. We summarize the observations for prolate and oblate spheroids for different viscosity gradient directions and provide plots for the orientation and centre-of-mass trajectory versus time. We also provide guidelines to extend the analysis when the viscosity gradient exhibits a more complicated spatial behaviour.

Carrier mobility tensor in doped phosphorene due to scattering by charged impurities using the energy loss method

Carrier mobility tensor in doped phosphorene due to scattering by charged impurities using the energy loss method

Upscaling of chemo-mechanical properties of battery electrode material

A variationally consistent model-based computational homogenization approach for transient chemo- mechanically coupled problems is developed based on the classical assumption of first order prolongation of the displacement and chemical potential fields within a Representative Volume Element (RVE). An upscaling procedure is introduced that is based on the assumption of micro-stationarity for the RVE problem. This is motivated by sufficient separation of time-scales. Periodic boundary conditions on the pertinent fields provide the general variational setting for the uniquely solvable RVE-problems. Due to the assumed linearity and micro-stationary, it is possible to use the pertinent sensitivity analysis for the RVE in order to derive effective macro-scale properties in closed form: the elastic stiffness, the insertion strain tensor and the mobility tensor. Statistically representative results are obtained by considering a sufficient number of RVE-realizations with varying volume fractions of the constituents. With the application to structural batteries in mind, a numerical study is conducted for a three-phase RVE microstructure representing a battery electrode material.

Pychastic: Precise Brownian dynamics using Taylor-Itō integrators in Python

In the last decade, Python-powered physics simulations ecosystem has been growing steadily, allowing greater interoperability, and becoming an important tool in numerical exploration of physical phenomena, particularly in soft matter systems. Driven by the need for fast and precise numerical integration in colloidal dynamics, here we formulate the problem of Brownian Dynamics (BD) in a mathematically consistent formalism of the Itō calculus, and develop a Python package to assist numerical computations. We show that, thanks to the automatic differentiation packages, the classical truncated Taylor-Itō integrators can be implemented without the burden of computing the derivatives of the coefficient functions beforehand. Furthermore, we show how to circumvent the difficulties of BD simulations such as calculations of the divergence of the mobility tensor in the diffusion equation and discontinuous trajectories encountered when working with dynamics on S^2S2 and SO(3)SO(3). The resulting Python package, Pychastic, is capable of performing BD simulations including hydrodynamic interactions at speeds comparable to dedicated implementations in lower-level programming languages, but with a much simpler end-user interface.

Codebase release 0.2 for Pychastic

In the last decade, Python-powered physics simulations ecosystem has been growing steadily, allowing greater interoperability, and becoming an important tool in numerical exploration of physical phenomena, particularly in soft matter systems. Driven by the need for fast and precise numerical integration in colloidal dynamics, here we formulate the problem of Brownian Dynamics (BD) in a mathematically consistent formalism of the Itō calculus, and develop a Python package to assist numerical computations. We show that, thanks to the automatic differentiation packages, the classical truncated Taylor-Itō integrators can be implemented without the burden of computing the derivatives of the coefficient functions beforehand. Furthermore, we show how to circumvent the difficulties of BD simulations such as calculations of the divergence of the mobility tensor in the diffusion equation and discontinuous trajectories encountered when working with dynamics on S^2S2 and SO(3)SO(3). The resulting Python package, Pychastic, is capable of performing BD simulations including hydrodynamic interactions at speeds comparable to dedicated implementations in lower-level programming languages, but with a much simpler end-user interface.

Pair dynamics of active force dipoles in an odd-viscous fluid.

We discuss the lateral dynamics of two active force dipoles, which interact with each other via hydrodynamic interactions in a thin fluid layer that is active and chiral. The fluid layer is modeled as a two-dimensional (2D) compressible fluid with an odd viscosity, while the force dipole (representing an active protein or enzyme) induces a dipolar flow. Taking into account the momentum decay in the 2D fluid, we obtain analytically the mobility tensor that depends on the odd viscosity and includes nonreciprocal hydrodynamic interactions. We find that the particle pair shows spiral behavior due to the transverse flow induced by the odd viscosity. When the magnitude of the odd viscosity is large as compared with the shear viscosity, two types of oscillatory behaviors are seen. One of them can be understood as arising from closed orbits in dynamical systems, and its circular trajectories are determined by the ratio between the magnitude of the odd viscosity and the force dipole. In addition, the phase diagrams of the particle dipolar angles are obtained numerically. Our findings reveal that the nonreciprocal response leads to complex dynamics of active particles embedded in an active fluid with odd viscosity.

Incompressible limit for a fluid mixture

In this paper we discuss the incompressible limit for multicomponent fluids in the isothermal ideal case. Both a direct limit-passage in the equation of state and the low Mach-number limit in rescaled PDEs are investigated. Using the relative energy inequality, we obtain convergence results for the densities and the velocity-field under the condition that the incompressible model possesses a sufficiently smooth solution, which is granted at least for a short time. Moreover, in comparison to single-component flows, uniform estimates and the convergence of the pressure are needed in the multicomponent case because the incompressible velocity field is not divergence-free. We show that certain constellations of the mobility tensor allow to control gradients of the entropic variables and yield the convergence of the pressure in L1.

Fast simulation of particulate suspensions enabled by graph neural network

Predicting the dynamic behaviors of particles in suspension subject to hydrodynamic interaction (HI) and external drive can be critical for many applications. By harvesting advanced deep learning techniques, the present work introduces a new framework, hydrodynamic interaction graph neural network (HIGNN), for inferring and predicting the particles’ dynamics in Stokes suspensions. It overcomes the limitations of traditional approaches in computational efficiency, accuracy, and/or transferability. In particular, by uniting the data structure represented by a graph and the neural networks with learnable parameters, the HIGNN constructs surrogate modeling for the mobility tensor of particles which is the key to predicting the dynamics of particles subject to HI and external forces. To account for the many-body nature of HI, we generalize the state-of-the-art GNN by introducing higher-order connectivity into the graph and the corresponding convolutional operation. For training the HIGNN, we only need the data for a small number of particles in the domain of interest, and hence the training cost can be maintained low. Once constructed, the HIGNN permits fast predictions of the particles’ velocities and is transferable to suspensions of different numbers/concentrations of particles in the same domain and to any external forcing. It has the ability to accurately capture both the long-range HI and short-range lubrication effects. We demonstrate the accuracy, efficiency, and transferability of the proposed HIGNN framework in a variety of systems. The requirement on computing resource is minimum: most simulations only require a desktop with one GPU; the simulations for a large suspension of 100,000 particles call for up to 6 GPUs.

A toy model of misfolded protein aggregation and neural damage propagation in neurodegenerative diseases

Neurodegenerative diseases (NDs) result from the transformation and accumulation of misfolded proteins within the nervous system. Several mathematical models have been proposed to investigate the biological processes underlying NDs, focusing on the kinetics of polymerization and fragmentation at the microscale and on the spread of neural damage at a macroscopic level. The aim of this work is to bridge the gap between microscopic and macroscopic approaches proposing a toy partial differential model able to take into account both the short-time dynamics of the misfolded proteins aggregating in plaques and the long-term evolution of tissue damage. Using mixtures theory, we consider the brain as a biphasic material made of misfolded protein aggregates and of healthy tissue. The resulting Cahn–Hilliard type equation for the misfolded proteins contains a growth term depending on the local availability of precursor proteins, that follow a reaction–diffusion equation. The misfolded proteins also possess a chemotactic mass flux driven by gradients of neural damage, that is caused by local accumulation of misfolded protein and that evolves slowly according to an Allen-Cahn equation. The diffuse interface approach is new for NDs and allows both to consider five different time-scales, from phase separation to neural damage propagation, and to reduce the computational costs compared to existing multi-scale models, allowing a time-step adaptivity. We present here numerical simulations in a simple two-dimensional domain, considering both isotropic and anisotropic mobility coefficients of the misfolded protein and the diffusion of the neural damage, finding that the spreading front of the neural damage follows the direction of the largest eigenvalue of the mobility tensor. In both cases, we computed two biomarkers for quantifying the aggregation in plaques and the evolution of neural damage, that are in qualitative agreement with the characteristic Jack curves for many NDs.

Diffusion and sedimentation in colloidal suspensions using multiparticle collision dynamics with a discrete particle model.

We study self-diffusion and sedimentation in colloidal suspensions of nearly hard spheres using the multiparticle collision dynamics simulation method for the solvent with a discrete mesh model for the colloidal particles (MD+MPCD). We cover colloid volume fractions from 0.01 to 0.40 and compare the MD+MPCD simulations to experimental data and Brownian dynamics simulations with free-draining hydrodynamics (BD) as well as pairwise far-field hydrodynamics described using the Rotne-Prager-Yamakawa mobility tensor (BD+RPY). The dynamics in MD+MPCD suggest that the colloidal particles are only partially coupled to the solvent at short times. However, the long-time self-diffusion coefficient in MD+MPCD is comparable to that in experiments, and the sedimentation coefficient in MD+MPCD is in good agreement with that in experiments and BD+RPY, suggesting that MD+MPCD gives a reasonable description of hydrodynamic interactions in colloidal suspensions. The discrete-particle MD+MPCD approach is convenient and readily extended to more complex shapes, and we determine the long-time self-diffusion coefficient in suspensions of nearly hard cubes to demonstrate its generality.

Helical trajectories of swimming cells with a flexible flagellar hook

The flexibility of the bacterial flagellar hook is believed to have substantial consequences for microorganism locomotion. Using a simplified model of a rigid flagellum and a flexible hook, we show that the paths of axisymmetric cell bodies driven by a single flagellum in Stokes flow are generically helical. Phase-averaged resistance and mobility tensors are produced to describe the flagellar hydrodynamics, and a helical rod model which retains a coupling between translation and rotation is identified as a distinguished asymptotic limit. A supercritical Hopf bifurcation in the flagellar orientation beyond a critical ratio of flagellar motor torque to hook bending stiffness, which is set by the spontaneous curvature of the flexible hook, the shape of the cell body, and the flagellum geometry, can have a dramatic effect on the cell's trajectory through the fluid. Although the equilibrium hook angle can result in a wide variance in the trajectory's helical pitch, we find a very consistent prediction for the trajectory's helical amplitude using parameters relevant to swimming P. aeruginosa cells.

Defect capturing and charging dynamics and their effects on magneto-transport of electrons in quantum wells

The calculated defect corrections to the polarization and dielectric functions for Bloch electrons in quantum wells are presented. These results were employed to derive the first two moment equations from the Boltzmann transport theory and then applied to explore the role played by defects on the magneto-transport of Bloch electrons. Additionally, we have derived analytically the inverse momentum-relaxation time and mobility tensor for Bloch electrons by making use of the screened defect-corrected polarization function. Based on quantum-statistical theory, we have investigated the defect capture and charging dynamics by employing a parameterized physics-based model for defects to obtain defect wave functions. Both capture and relaxation rates, as well as the density for captured Bloch electrons, were calculated self-consistently as functions of temperature, doping density and chosen defect parameters. By applying the energy-balance equation, the number of occupied energy levels and the chemical potential of defects were determined, with which the transition rate for defect capturing was obtained. By applying these results, the defect energy-relaxation, capture and escape rates, and Bloch-electron chemical potential were calculated self-consistently for a non-canonical subsystem of Bloch electrons. At the same time, the energy- and momentum-relaxation rates of Bloch electrons, as well as the current suppression factor, were also investigated quantitatively. By combining all these results, the temperature dependence of the Hall and longitudinal mobilities was presented for Bloch electrons in either single- or multi-quantum wells.

3D-to-2D Transition of Anion Vacancy Mobility in CsPbBr3 under Hydrostatic Pressure.

Anion vacancy migration in the orthorhombic Pnma phase of the lead-halide perovskite CsPbBr3 under hydrostatic pressure is studied computationally. Density functional theory calculations are used to determine transition states, activation enthalpies, and attempt frequencies for vacancies to hop between nearby lattice sites, under pressure in the range 0.0-2.0 GPa. The resulting data are used to parametrize a kinetic model of vacancy migration under the influence of an electric field, which is solved in the steady state to determine the anion vacancy mobility tensor as a function of pressure. It is found that the mobility tensor becomes increasingly anisotropic with increasing pressure, such that at 2.0 GPa, the mobility within the (010) lattice plane is 3 orders of magnitude greater than the mobility normal to it. The results demonstrate the potentially significant influence of pressure, and by extension, other forms of stress, on defect migration in lead-halide perovskites.

Nonreciprocal response of a two-dimensional fluid with odd viscosity.

We discuss the linear hydrodynamic response of a two-dimensional active chiral compressible fluid with odd viscosity. The viscosity coefficient represents broken time-reversal and parity symmetries in the 2D fluid and characterizes the deviation of the system from a passive fluid. Taking into account the hydrodynamic coupling to the underlying bulk fluid, we obtain the odd viscosity-dependent mobility tensor, which is responsible for the nonreciprocal hydrodynamic response to a point force. Furthermore, we consider a finite-size disk moving laterally in the 2D fluid and demonstrate that the disk experiences a nondissipative lift force in addition to the dissipative drag one.

Self-diffusion of nonspherical particles fundamentally conflicts with effective sphere models

Modeling diffusion of nonspherical particles presents an unsolved and considerable challenge, despite its importance for the understanding of crowding effects in biology, food technology and formulation science. A common approach in experiment and simulation is to map nonspherical objects on effective spheres to subsequently use the established predictions for spheres to approximate phenomena for nonspherical particles. Using numerical evaluation of the hydrodynamic mobility tensor, we show that this so-called effective sphere model fundamentally fails to represent the self-diffusion in solutions of ellipsoids as well as rod-like assemblies of spherical beads. The effective sphere model drastically overestimates the slowing down of self-diffusion down to volume fractions below 0.01. Furthermore, even the linear term relevant at lower volume fraction is inaccurate, linked to a fundamental misconception of effective sphere models. To overcome the severe problems related with the use of effective sphere models, we suggest a protocol to predict the short-time self-diffusion of rod-like systems, based on simulations with hydrodynamic interactions that become feasible even for more complex molecules as the essential observable shows a negligible system-size effect.

Extended diffusion theory: Recovering dynamics from biased/accelerated molecular simulations.

Dynamical properties are of great importance in determining the behavior of synthetic and natural molecules, but capturing them by computational methods is a nontrivial task. Very often the time scales of the relevant phenomena are far beyond the typical time windows accessible by classical Molecular Dynamics (MD) simulations, currently limited to the order of microseconds on standard laboratory workstations. On the other hand, biased and accelerated simulations allow for fast and thorough exploration of the molecular conformational space, but they lose the dynamic information. The problem of recovering dynamics from biased/accelerated simulations is a very active field of research, but no totally robust/reliable solutions have been given yet. In this paper it is shown how the Smoluchowski equation, in the framework of Diffusion Theory (DT), can be used to bridge this gap, and dynamical properties, in the form of time correlation functions (TCFs), can be extracted also from such kind of simulations. DT is first extended (EDT) to express the mobility tensors entering the Smoluchowski operator in terms of a recently introduced unified and regularized Rotne-Prager-Yamakawa approximation, [P. J. Zuk, E. Wajnryb, K. A. Mizerski, P. Szymczak, J. Fluid. Mech. 2014, 741, R5, 1-13] also involving mixed rotation-translation contributions, and rotation-rotation terms beside the classical translation-translation ones, so far used in DT. Then, the method is applied to recover the dynamics of a nontrivial example of a peptide in explicit water from the first 200 ns of a Replica Exchange Molecular Dynamics simulation, which is a popular computational method that destroys the long time dynamics. EDT dynamics were found to favorably compare against those coming from a standard MD simulation of the same system, requiring a time window of 30 μs to converge. This result shows that EDT is a tool of practical value to recover the long time dynamics of systems in diffusive regimes from biased/accelerated simulations, to be exploited in those cases when direct evaluation by standard MD is unfeasible.

Particle motion nearby rough surfaces

We study the hydrodynamic coupling between particles and solid, rough boundaries characterized by random surface textures. Using the Lorentz reciprocal theorem, we derive analytical expressions for the grand mobility tensor of a spherical particle and find that roughness-induced velocities vary nonmonotonically with the characteristic wavelength of the surface. In contrast to sedimentation near a planar wall, our theory predicts continuous particle translation transverse and perpendicular to the applied force. Most prominently, this motion manifests itself in a variance of particle displacements that grows quadratically in time along the direction of the force. This increase is rationalized by surface roughness generating particle sedimentation closer to or farther from the surface, which entails a significant variability of settling velocities.

Flickering Polarons Extending over Ten Nanometres Mediate Charge Transport in High‐Mobility Organic Crystals

AbstractProgress in the design of high‐mobility organic semiconductors has been hampered by an incomplete fundamental understanding of the elusive charge carrier dynamics mediating electrical current in these materials. To address this problem, a novel fully atomistic non‐adiabatic molecular dynamics approach termed fragment orbital‐based surface hopping (FOB‐SH) that propagates the electron‐nuclear motion has been further improved and, for the first time, used to calculate the full 2D charge mobility tensor for the conductive planes of six structurally well characterized organic single crystals, in good agreement with available experimental data. The nature of the charge carrier in these materials is best described as a flickering polaron constantly changing shape and extensions under the influence of thermal disorder. Thermal intra‐band excitations from modestly delocalized band edge states (up to 5 nm or 10–20 molecules) to highly delocalized tail states (up to 10 nm or 40–60 molecules in the most conductive materials) give rise to short, ≈ 10 fs‐long bursts of the charge carrier wavefunction that drives the spatial displacement of the polaron, resulting in carrier diffusion and mobility. This study implies that key to the design of high‐mobility materials is a high density of strongly delocalized and thermally accessible tail states.