arXiv subjects

James W. Swan

Publications and source records attributed to James W. Swan.

At least 19 recordsLinked to original sources

arXiv2025

Potential of mean force and underscreening of polarizable colloids in concentrated electrolytes

This study uses advanced numerical methods to estimate the mean force potential (PMF) between charged, polarizable colloidal particles in dense electrolytes. We observe that when the Debye screening length, $λ_{\mathrm{D}}$, is below the hydrated ion size, the PMF shows discernible oscillations of purely electrostatic origin as opposed to chemical affinity, in addition to the expected decay in DLVO theory. Moreover, our findings suggest concentrated electrolytes are significantly less efficient at muting electrostatic interactions in electrostatically stabilized colloidal suspensions, potentially having significant implications for our understanding of colloidal stability and the forces that govern the behavior of concentrated charged soft matter systems beyond DLVO theory.

cond-mat.soft↗

arXiv2024

Immersed boundary method for dynamic simulation of polarizable colloids of arbitrary shape in explicit ion electrolytes

We develop a computational method for modeling electrostatic interactions of arbitrarily-shaped, polarizable objects on colloidal length scales, including colloids/nanoparticles, polymers, and surfactants, dispersed in explicit ion electrolytes and nonionic solvents. Our method computes the nonuniform polarization charge distribution induced in a colloidal particle by both externally applied electric fields and local electric fields arising from other charged objects in the dispersion. This leads to expressions for electrostatic energies, forces, and torques that enable efficient molecular dynamics and Brownian dynamics simulations of colloidal dispersions in electrolytes, which can be harnessed to accurately predict structural and transport properties. We describe an implementation in which colloidal particles are modeled as rigid composites of small spherical beads that tessellate the surface of the particle. The electrostatics calculations are accelerated using a spectrally-accurate particle-mesh-Ewald technique implemented on a graphics processing unit (GPU) and regularized such that the electrostatic calculations are well-defined even for overlapping bodies. We demonstrate the effectiveness of this approach through a series of calculations, including the induced dipole moments and forces for one, two, and lattices of spherical colloids in an electric field; the induced dipole moment and torque for anisotropic particles in an electric field; the equilibrium distribution of ions in the double layer around charged colloids; the dynamics of charged colloids; and ions in the double layer around a polarizable colloid exposed to an electric field.

cond-mat.soft↗

arXiv2022

Scientific Machine Learning for Modeling and Simulating Complex Fluids

The formulation of rheological constitutive equations -- models that relate internal stresses and deformations in complex fluids -- is a critical step in the engineering of systems involving soft materials. While data-driven models provide accessible alternatives to expensive first-principles models and less accurate empirical models in many engineering disciplines, the development of similar models for complex fluids has lagged. The diversity of techniques for characterizing non-Newtonian fluid dynamics creates a challenge for classical machine learning approaches, which require uniformly structured training data. Consequently, early machine learning constitutive equations have not been portable between different deformation protocols or mechanical observables. Here, we present a data-driven framework that resolves such issues, allowing rheologists to construct learnable models that incorporate essential physical information, while remaining agnostic to details regarding particular experimental protocols or flow kinematics. These scientific machine learning models incorporate a universal approximator within a materially objective tensorial constitutive framework. By construction, these models respect physical constraints, such as frame-invariance and tensor symmetry, required by continuum mechanics. We demonstrate that this framework facilitates the rapid discovery of accurate constitutive equations from limited data, and that the learned models may be used to describe more kinematically complex flows. This inherent flexibility admits the application of these 'digital fluid twins' to a range of material systems and engineering problems. We illustrate this flexibility by deploying a trained model within a multidimensional computational fluid dynamics simulation -- a task that is not achievable using any previously developed data-driven rheological equation of state.

cond-mat.soft↗

arXiv2022

A Data-Driven Method for Automated Data Superposition with Applications in Soft Matter Science

The superposition of data sets with internal parametric self-similarity is a longstanding and widespread technique for the analysis of many types of experimental data across the physical sciences. Typically, this superposition is performed manually, or recently by one of a few automated algorithms. However, these methods are often heuristic in nature, are prone to user bias via manual data shifting or parameterization, and lack a native framework for handling uncertainty in both the data and the resulting model of the superposed data. In this work, we develop a data-driven, non-parametric method for superposing experimental data with arbitrary coordinate transformations, which employs Gaussian process regression to learn statistical models that describe the data, and then uses maximum a posteriori estimation to optimally superpose the data sets. This statistical framework is robust to experimental noise, and automatically produces uncertainty estimates for the learned coordinate transformations. Moreover, it is distinguished from black-box machine learning in its interpretability -- specifically, it produces a model that may itself be interrogated to gain insight into the system under study. We demonstrate these salient features of our method through its application to four representative data sets characterizing the mechanics of soft materials. In every case, our method replicates results obtained using other approaches, but with reduced bias and the addition of uncertainty estimates. This method enables a standardized, statistical treatment of self-similar data across many fields, producing interpretable data-driven models that may inform applications such as materials classification, design, and discovery.

physics.data-an↗

arXiv2022

Parameterization of hydrodynamic friction in a model for sheared suspensions of rough particles

We propose a method to parameterize a coarse grained model for the hydrodynamic friction between nearly touching rough spheres in suspension flows. The frictional resistance due to surface roughness primarily alters the sliding and rolling modes of motion of rough particles. Stokesian dynamics simulations incorporating a near-field pairwise resistance model accounting for these enhanced frictional modes were employed to compute particle trajectories in shear flow. In this model, the resistance to sliding and rolling modes of motion are augmented from a weakly diverging log$(1/h)$ form for smooth spheres to a strongly diverging $1/h$ form for rough spheres to account for the additional resistance due to squeezing flows between surface asperities, where $h$ is the mean surface separation between particles. We determine new bounds on the relative magnitude of the augmentations to the resistance to different modes of motion using inequality constraints reflecting the positive definiteness of the Stokes resistance tensor for a pair of rough particles. Using the simulations of a particle pair in a shear flow, a simple model for angular rotation rate of the pair centerline is computed as a function of its orientation in the shear flow and the free parameters of the hydrodynamic resistance model: the friction coupling strength, $α$, and friction coupling range, $h_0$. Values of $α$ and $h_0$ for real-world rough particles can then be inferred by matching the pair rotation rate in the model to experimental observations when a dilute rough particle suspension is subjected to a linear shear flow. The same model is used to calculate the hydrodynamic contribution to the high frequency viscosity of rough particle suspensions. For different $α$ and $h_0$, we observe that the viscosity diverges differently depending on $h_0$.

cond-mat.soft↗

arXiv2022

Medium Amplitude Parallel Superposition (MAPS) Rheology, Part 1: Mathematical Framework and Theoretical Examples

A new mathematical representation for nonlinear viscoelasticity is presented based on application of the Volterra series expansion to the general nonlinear relationship between shear stress and shear strain history. This theoretical and experimental framework, which we call Medium Amplitude Parallel Superposition (MAPS) Rheology, reveals a new material property, the third order complex modulus, which describes completely the weakly nonlinear response of a viscoelastic material in an arbitrary simple shear flow. In this first part, we discuss several theoretical aspects of this mathematical formulation and new material property. For example, we show how MAPS measurements can be performed in strain- or stress-controlled contexts and provide relationships between the weakly nonlinear response functions measured in each case. We show that the MAPS response function is a super-set of the response functions that have been previously reported in medium amplitude oscillatory shear and parallel superposition rheology experiments. We also show how to exploit inherent symmetries of the MAPS response function to reduce it to a minimal domain for straightforward measurement and visualization. We compute this material property for a few constitutive models to illustrate the potential richness of the data sets generated by MAPS experiments. Finally, we discuss the MAPS framework in the context of some other nonlinear, time-dependent rheological probes and explain how the MAPS methodology has a distinct advantage over these others because it generates data embedded in a very high dimensional space without driving fluid mechanical instabilities, and is agnostic to the flow protocol.

cond-mat.soft↗

arXiv2021

Locally Feasibly Projected Sequential Quadratic Programming for Nonlinear Programming on Arbitrary Smooth Constraint Manifolds

High-dimensional nonlinear optimization problems subject to nonlinear constraints can appear in several contexts including constrained physical and dynamical systems, statistical estimation, and other numerical models. Feasible optimization routines can sometimes be valuable if the objective function is only defined on the feasible set or if numerical difficulties associated with merit functions or infeasible termination arise during the use of infeasible optimization routines. Drawing on the Riemannian optimization and sequential quadratic programming literature, a practical algorithm is constructed to conduct feasible optimization on arbitrary implicitly defined constraint manifolds. Specifically, with $n$ (potentially bound-constrained) variables and $m < n$ nonlinear constraints, each outer optimization loop iteration involves a single $O(nm^2)$-flop factorization, and computationally efficient retractions are constructed that involve $O(nm)$-flop inner loop iterations. A package, LFPSQP.jl, is created using the Julia language that takes advantage of automatic differentiation and projected conjugate gradient methods for use in inexact/truncated Newton steps.

math.OC↗

arXiv2021

Thermally Fluctuating, Semiflexible Sheets in Simple Shear Flow

We perform Brownian dynamics simulations of semiflexible colloidal sheets with hydrodynamic interactions and thermal fluctuations in shear flow. As a function of the ratio of bending rigidity to shear energy (a dimensionless quantity we denote $S$) and the ratio of bending rigidity to thermal energy, we observe a dynamical transition from stochastic flipping to crumpling and continuous tumbling. This dynamical transition is broadened by thermal fluctuations, and the value of $S$ at which it occurs is consistent with the onset of chaotic dynamics found for athermal sheets. The effects of different dynamical conformations on rheological properties such as viscosity and normal stress differences are also quantified. Namely, the viscosity in a dilute dispersion of sheets is found to decrease with increasing shear rate (shear-thinning) up until the dynamical crumpling transition, at which point it increases again (shear-thickening), and non-zero first normal stress differences are found that exhibit a local maximum with respect to temperature at large $S$ (small shear rate). These results shed light on the dynamical behavior of fluctuating 2D materials dispersed in fluids and should greatly inform the design of associated solution processing methods.

cond-mat.soft↗

arXiv2021

Underscreening and hidden ion structures in large scale simulations of concentrated electrolytes

The electrostatic screening length predicted by Debye-Hückel theory decreases with increasing ionic strength, but recent experiments have found that the screening length can instead increase in concentrated electrolytes. This phenomenon, referred to as underscreening, is believed to result from ion-ion correlations and short-range forces such as excluded volume interactions among ions. We use Brownian Dynamics to simulate a version of the Restrictive Primitive Model for electrolytes over a wide range of ion concentrations, ionic strengths, and ion excluded volume radii for binary electrolytes. We measure the decay of the charge-charge correlation among ions in the bulk, and compare it against scaling trends found experimentally and determined in certain weak coupling theories of ion-ion correlation. Moreover, we find that additional large scale ion structures emerge at high concentrations. In this regime, the frequency of oscillations computed from the charge-charge correlation function is not dominated by electrostatic interactions but rather by excluded volume interactions and with oscillation periods on the order of the ion diameter. We also find that the nearest neighbor correlation of ions sharing the same charge transitions from negative at small concentrations to positive at high concentrations, representing the formation of small, like-charge ion clusters. We conclude that the increase in local charge density due to the formation of these clusters and the topological constraints of macroscopic charged surfaces can help explain the degree of underscreening observed experimentally.

cond-mat.soft↗

arXiv2021

On the unsteady and lineal translation of a sphere through a viscoelastic fluid

The unsteady, lineal translation of a solid spherical particle through viscoelastic fluids described by the Johnson-Segalman and Giesekus models is studied analytically. Solutions for the pressure and velocity fields as well as the force on the particle are expanded as a power series in the Weissenberg number. The momentum balance and constitutive equation are solved asymptotically for a steadily translating particle up to second order in the particle velocity, and rescaling of the pressure and velocity in the frequency domain is used to relate the solutions for steady lineal translation to those for unsteady lineal translation. The unsteady force at third order in the particle velocity is then calculated through application of the Lorentz reciprocal theorem, and it is shown that this weakly nonlinear contribution to the force can be expressed as part of a Volterra series. Through a series of examples, it is shown that a truncated representation of this Volterra series, which can be manipulated to describe the velocity in terms of an imposed force, is useful for analyzing specific time-dependent particle motions. Two examples studied using this relationship are the force on a particle suddenly set into motion and the velocity of a particle in response to a suddenly imposed steady force. Additionally, the weakly nonlinear response of particle captured by a harmonic trap moving lineally through the fluid is computed. This is an analog to active microrheology experiments, and can be used to explain how weakly nonlinear responses manifest in active microrheology experiments with spherical probes.

physics.flu-dyn↗

arXiv2021

Buckling, Crumpling, and Tumbling of Semiflexible Sheets in Simple Shear Flow

As 2D materials such as graphene, transition metal dichalcogenides, and 2D polymers become more prevalent, solution processing and colloidal-state properties are being exploited to create advanced and functional materials. However, our understanding of the fundamental behavior of 2D sheets and membranes in fluid flow is still lacking. In this work, we perform numerical simulations of athermal semiflexible sheets with hydrodynamic interactions in shear flow. For sheets initially oriented in the flow-gradient plane, we find buckling instabilities of different mode numbers that vary with bending stiffness and can be understood with a quasi-static model of elasticity. For different initial orientations, chaotic tumbling trajectories are observed. Notably, we find that sheets fold or crumple before tumbling but do not stretch again upon applying greater shear.

cond-mat.soft↗

arXiv2021

Medium Amplitude Parallel Superposition (MAPS) Rheology of a Wormlike Micellar Solution

The weakly nonlinear rheology of a surfactant solution of wormlike micelles is investigated from both a modeling and experimental perspective using the framework of medium amplitude parallel superposition (MAPS) rheology. MAPS rheology defines material functions, such as the third order complex compliance, which span the entire weakly nonlinear response space of viscoelastic materials to simple shear deformations. Three-tone oscillatory shear deformations are applied to obtain feature-rich data characterizing the third order complex compliance with high data throughput. Here, data for a CPyCl solution are compared to the analytical solution for the MAPS response of a reptation-reaction constitutive model, which treats micelles as linear polymers that can break apart and recombine in solution. Regression of the data to the model predictions provides new insight into how these breakage and recombination processes are affected by shear, and demonstrates the importance of using information-rich data to infer precise estimates of model parameters.

cond-mat.soft↗

arXiv2021

The Medium Amplitude Response of Nonlinear Maxwell-Oldroyd Type Models in Simple Shear

A general framework for Maxwell-Oldroyd type differential constitutive models is examined, in which an unspecified nonlinear function of the stress and rate-of-deformation tensors is incorporated into the well-known corotational version of the Jeffreys model discussed by Oldroyd. For medium amplitude simple shear deformations, the recently developed mathematical framework of medium amplitude parallel superposition (MAPS) rheology reveals that this generalized nonlinear Maxwell model can produce only a limited number of distinct signatures, which combine linearly in a well-posed basis expansion for the third order complex viscosity. This basis expansion represents a library of MAPS signatures for distinct constitutive models that are contained within the generalized nonlinear Maxwell model. We describe a framework for quantitative model identification using this basis expansion, and discuss its limitations in distinguishing distinct nonlinear features of the underlying constitutive models from medium amplitude shear stress data. The leading order contributions to the normal stress differences are also considered, revealing that only the second normal stress difference provides distinct information about the weakly nonlinear response space of the model. After briefly considering the conditions for time-strain separability within the generalized nonlinear Maxwell model, we apply the basis expansion of the third order complex viscosity to derive the medium amplitude signatures of the model in specific shear deformation protocols. Finally, we use these signatures for estimation of model parameters from rheological data obtained by these different deformation protocols, revealing that three-tone oscillatory shear deformations produce data that is readily able to distinguish all features of the medium amplitude, simple shear response space of this generalized class of constitutive models.

cond-mat.soft↗

arXiv2020

Short and soft: multi-domain organization, tunable dynamics and jamming in suspensions of grafted colloidal cylinders with small aspect ratio

The yet virtually unexplored class of soft colloidal rods with small aspect ratio is investigated and shown to exhibit a very rich phase and dynamic behavior, spanning from liquid to nearly melt state. Instead of nematic order, these short and soft nanocylinders alter their organization with increasing concentration from isotropic liquid with random orientation to one with preferred local orientation and eventually a multi-domain arrangement with local orientational order. The latter gives rise to a kinetically suppressed state akin to structural glass with detectable terminal relaxation, which, on increasing concentration reveals features of hexagonally packed order as in ordered block copolymers. The respective dynamic response comprises four regimes, all above the overlapping concentration of 0.02 g/ml: I) from 0.03 to 0.1 g/mol the system undergoes a liquid-to-solid like transition with a structural relaxation time that grows by four orders of magnitude. II) from 0.1 to 0.2 g/ml a dramatic slowing-down is observed and is accompanied by an evolution from isotropic to multi-domain structure. III) between 0.2 and 0.6 g/mol the suspensions exhibit signatures of shell interpenetration and jamming, with the colloidal plateau modulus depending linearly on concentration. IV) at 0.74 g/ml in the densely jammed state, the viscoelastic signature of hexagonally packed cylinders from microphase-separated block copolymers is detected. These properties set short and soft nanocylinders apart from long colloidal rods (with large aspect ratio) and provide insights for fundamentally understanding the physics in this intermediate soft colloidal regime, as well as and for tailoring the flow properties of non-spherical soft colloids.

cond-mat.soft↗

arXiv2020

Medium Amplitude Parallel Superposition (MAPS) Rheology, Part 2: Experimental Protocols and Data Analysis

An experimental protocol is developed to directly measure the new material functions revealed by medium amplitude parallel superposition (MAPS) rheology. This experimental protocol measures the medium amplitude response of a material to a simple shear deformation composed of three sine waves at different frequencies. Imposing this deformation and measuring the mechanical response reveals a rich data set consisting of up to 19 measurements of the third order complex modulus at distinct three-frequency coordinates. We discuss how the choice of the input frequencies influences the features of the MAPS domain studied by the experiment. A polynomial interpolation method for reducing the bias of measured values from spectral leakage and variance due to noise is discussed, including a derivation of the optimal range of amplitudes for the input signal. This leads to the conclusion that conducting the experiment in a stress-controlled fashion possesses a distinct advantage to the strain-controlled mode. The experimental protocol is demonstrated through measurements of the MAPS response of a model complex fluid: a surfactant solution of wormlike micelles. The resulting data set is indeed large and feature-rich, while still being acquired in a time comparable to similar medium amplitude oscillatory shear (MAOS) experiments. We demonstrate that the data represents measurements of an intrinsic material function by studying its internal consistency, its compatibility with low-frequency predictions for Coleman-Noll simple fluids, and its agreement with data obtained via MAOS amplitude sweeps. Finally, the data is compared to predictions from the corotational Maxwell model to demonstrate the power of MAPS rheology in determining whether a constitutive model is consistent with a material's time-dependent response.

cond-mat.soft↗

arXiv2018

Modelling a Hydrodynamic Instability in Freely Settling Colloidal Gels

Attractive colloidal dispersions, suspensions of fine particles which aggregate and frequently form a space spanning elastic gel are ubiquitous materials in society with a wide range of applications. The colloidal networks in these materials can exist in a mode of free settling when the network weight exceeds its compressive yield stress. An equivalent state occurs when the network is held fixed in place and used as a filter through which the suspending fluid is pumped. In either scenario, hydrodynamic instabilities leading to loss of network integrity occur. Experimental observations have shown that the loss of integrity is associated with the formation of eroded channels, so-called streamers, through which the fluid flows rapidly. However, the dynamics of growth and subsequent mechanism of collapse remain poorly understood. Here, a phenomenological model is presented that describes dynamically the radial growth of a streamer due to erosion of the network by rapid fluid back flow. The model exhibits a finite-time blowup -- the onset of catastrophic failure in the gel -- due to activated breaking of the inter-colloid bonds. Brownian dynamics simulations of hydrodynamically interacting and settling colloids in dilute gels are employed to examine the initiation and propagation of this instability, which is in good agreement with the theory. The model dynamics are also shown to accurately replicate measurements of streamer growth in two different experimental systems. The predictive capabilities and future improvements of the model are discussed and a stability-state diagram is presented providing insight into engineering strategies for avoiding settling instabilities in networks meant to have long shelf lives.

physics.flu-dyn↗

arXiv2018

From Hindered to Promoted Settling in Dispersions of Attractive Colloids: Simulation, Modeling, and Application to Macromolecular Characterization

The settling of colloidal particles with short-ranged attractions is investigated via highly resolved immersed boundary simulations. At modest volume fractions, we show that inter-colloid attractions lead to clustering that reduces the hinderance to settling imposed by fluid back flow. For sufficient attraction strength, increasing the particle concentration grows the particle clusters, which further increases the mean settling rate in a physical mode termed promoted settling. The immersed boundary simulations are compared to recent experimental measurements of the settling rate in nanoparticle dispersions for which particles are driven to aggregate by short-ranged depletion attractions. The simulations are able to quantitatively reproduce the experimental results. We show that a simple, empirical model for the settling rate of adhesive hard sphere dispersions can be derived from a combination of the experimental and computational data as well as analytical results valid in certain asymptotic limits of the concentration and attraction strength. This model naturally extends the Richardson-Zaki formalism used to describe hindered settling of hard, repulsive spheres. Experimental measurements of the collective diffusion coefficient in concentrated solutions of globular proteins are used to illustrate inference of effective interaction parameters for sticky, globular macromolecules using this new empirical model. Finally, application of the simulation methods and empirical model to other colloidal systems are discussed.

cond-mat.soft↗

arXiv2017

How Confinement-Induced Structures Alter the Contribution of Hydrodynamic and Short-Ranged Repulsion Forces to the Viscosity of Colloidal Suspensions

Understanding the correlation between structure and rheology in colloidal suspensions is important as these suspensions are crucial in industrial applications. Moreover, colloids exhibit a wide range of structures under confinement that could considerably alter the viscosity. Here, we use a combination of experiments and simulations to elucidate how confinement induced structures alter the relative contributions of hydrodynamic and repulsive forces to produce up to a ten fold change in the viscosity. We use a custom built confocal rheoscope to image the particle configurations of a colloidal suspension while simultaneously measuring the viscosity. We find a non-monotonic trend to the viscosity under confinement that is strongly correlated with the microstructure. As the gap decreases below 15 particle diameters, the viscosity first decreases from its bulk value, shows fluctuations with the gap, and then sharply increases for gaps below three particle diameters. Further, we compare our experimental results to two simulations techniques that enables us to determine the relative contributions of hydrodynamic and short range repulsive stresses. The first method uses the lubrication approximation to find the hydrodynamic stress and includes a short range repulsive force between the particles and the second is a Stokesian dynamics simulation that calculates the full hydrodynamic stress in the suspension. We find that the decrease in the viscosity at moderate confinements has a significant contribution from both the hydrodynamic and repulsive forces whereas the increase in viscosity at gaps less than three particle diameters arises primarily from short range repulsive forces. These results provide new insights to the unique rheological behavior of confined suspensions and further enable us to tune the viscosity by changing properties such as the gap, polydispersity, and the volume fraction.

cond-mat.soft↗