Schedule for: 25w5387 - Particulates across Scales: Mathematical Modeling, Computation, and Applications

A buffet dinner is served daily between 5:30pm and 7:30pm in Vistas Dining Room, top floor of the Sally Borden Building.

Breakfast is served daily between 7 and 9am in the Vistas Dining Room, the top floor of the Sally Borden Building.

A brief introduction to BIRS with important logistical information, technology instruction, and opportunity for participants to ask questions.

This talk will highlight two phenomena involving soft matter that defy an obvious explanation. In each case, the combination of modeling and experiments will be needed in the future to gain insight.First, we discuss hydrogels that contain microscale particulates (starch granules). These hydrogels have viscoelastic properties that enable them to absorb impact. We will show that the gels are able to protect fragile or delicate objects(like eggs and fruit) from breaking or being crushed. The mechanism by which starch works is unknown. An open question is whether it is connected to starch’s ability to shear-thicken water.Second, we have discovered that gels (as well as animal and plant tissues) can be reversibly adhered to metals by applying a low DC voltage (5 V) for a short time (3 min). Metals that can be adhered to acrylamide gels follow the electrochemical series: i.e., their reduction potential exceeds a critical value (e.g., Cu, Pb, Sn adhere, but not Ni, Fe,Zn). We speculate that adhesion arises via electrochemical reactions that generate bonds at the metal-gel interface.The precise nature of these bonds remains an open question.

Cellular materials composed of a continuous solid network and voids filled with gas (i.e., foams) or liquid are commonly found in nature and have widespread use in industrial applications including thermal insulation and impact dissipation. The geometry of the pores and the composition of the pore wall directly impact the mechanical properties of the materials. Although nature has utilized cellular materials for many different purposes (e.g., wood), precisely tuning the structure and properties in synthetic porous materials is difficult. Here, the presentation will cover recent advances in porous, hierarchically ordered hydrogels where physically crosslinked spherical micelles form pore walls that surround water cavities.The mechanical response under uniaxial extension is dictated by the micrometer pores at low strain and the nanoscale micelles at high strain. Extremely low elastic moduli (< 1 kPa), high elasticity (extendingmore than 12-times initial length), strain-hardening, and completely reversible extension all derive from the deformation of both the micrometer-sized pores and the nanoscale micelles, which is reminiscent of natural cellular solids. Control of the material microstructure and pore orientation over many orders of magnitude (e.g., nm – μm) using bottom-up self-assembly methods reveals new possibilities for creating multiscale materials with structure dependent mechanical properties.

The Discrete Element Method (DEM) typically employs spherical or convex particle representations. However, certain applications - such as shredded polymers & batteries, or hydrogels - demand models that allow (i) extreme compactability and (ii) particle interlocking to be modeled. Unfortunately, advanced contact, or cohesive force closures are often not sufficient to approximate these two aspects of granular flow.Soft tetrapods, i.e., deformable multi-sphere parcels, are a promising shape candidate for modeling such a flow behavior. Our tetrapod model also features a novel bond softness model that retains the computational efficiency of the classical (rigid) multi-sphere approach used in the DEM.We investigate the impact of the tetrapods’ properties in multiple applications ranging from recycling to hydrogels. We demonstrate that tetrapods are a promising tool for modeling interlocking and compactable materials. Finally, we correlate the shape and size of tetrapods to the uncertainty inherent to our simulations. Specifically, we find that this uncertainty is positively correlated with both tetrapod size and the interlocking parameter ξ/D that quantifies the tetrapods’ non-convexity.Guidelines for calibrating tetrapod parameters for accurately modeling materials based on mean and variability measured in experiments are presented.

Rotational impact is a major cause of traumatic brain injury (TBI). In our previous work, we approximated the brain as a hydrogel sphere suspended in a liquid bath and simulated the impact through abrupt changes in rotational speed, achieving good agreement between numerical and experimental results. In this talk, we present recent parametric studies of hydrogel deformation under rotation. The hydrogel is modeled as a poroelastic material saturated with aNewtonian interstitial fluid. Its deformation, along with the evolution of the hydrogel-fluid interface, is tracked using an arbitrary Lagrangian-Eulerian (ALE) method. The governing equations are solved monolithically using a finite element method. We systematically investigate the effects of rotational acceleration, the density ratio between the hydrogel and the surroundingfluid, and the hydrogel’s elastic moduli and permeability. These studies aim to deepen our understanding of hydrogel dynamics under rotational impact, with implications for modelingTBI.

Lunch is served daily between 11:30am and 1:30pm in the Vistas Dining Room, the top floor of the Sally Borden Building.

Rod-like nanoparticles (RNPs) have been shown to diffuse faster than spherical ones in polymeric hydrogels, but the underlying physics is not well understood. We develop a 3D Brownian dynamics model to investigate this phenomenon, representing the gel as a random network of rigid fibers in water and incorporating both steric repulsion and adhesive interactions. In non-adhesive gels, RNP diffusivity increases monotonically with aspect ratio while its hydrodynamic diameter is kept constant, in agreement with the predictions of an obstruction scaling (OS) model. However, our model predicts a much higher diffusivity than the OS model, by up to 5 times for higher aspect ratios. To rationalize this discrepancy, we demonstrate that RNPs experience a skewed pore-size distribution in favor of the larger pores; they spend more time in coarser regions of the gel than in denser regions. Moreover, the RNPs execute a meandering motion in the coarser regions with pronounced rotational and transverse diffusion. In contrast, in denser regions, restricted rotation results in predominantly longitudinal diffusion. This anisotropy in diffusion further elevates the translational diffusivity of RNPs. Our model also reveals a competition between the steric and adhesive interactions, where steric repulsion limits access to adhesion sites, and produces a diffusivity intermediate between the purely steric and purely adhesive cases. Overall, our results show an even greater advantage to RNPs, in terms of rapid diffusion in hydrogels, than previously anticipated by the OS model.

Shear thickening in concentrated suspensions occurs when the imposed stress drives particles together to form a frictional contact network. This implies a balancing resisting force, whose magnitude sets the threshold for the imposed stress to induce contacts. Using an established simulation technique and motivated by recent work showing the rapid onset of system-spanning rigid structures (identified by a pebble game algorithm) with increase of volume fraction [1], we show that the number of contacts in the network is an increasing function of stress, but it also fluctuates during flow. The contacts reduce the degrees of freedom available to the particles, resulting in strong correlations that lead to long range correlation, particularly of the rotational motion. We go on to explore the development of minimally rigid structures in the shear-thickened suspension as it approaches jamming at high stress, and show that, for a 2D suspension, the onset of large rigid clusters exhibits critical behavior [2]; the role of particle stiffness and extension of the results to 3D suspensions are explored.

Particle-to-particle hydrodynamic force and torque fluctuations is a well documented feature of particle-laden flows. Classical correlations ignore these fluctuations and only require the knowledge of the locally averaged solid volume fraction and Reynolds number to estimate the hydrodynamic momentum transfer (primarily the drag force). However, in the case of the drag force, the magnitude of these fluctuations can be as large as the average value, thus preventing coarse-grained numerical models of particle-laden flows from delivering high fidelity predictions. Recent advances on this problem involve taking advantage of the local microstructure surrounding each individual particle and using a description of this microstructure as an additional input parameter for deterministic hydrodynamic drag, lift and torque predictions. Modelling the functional dependence of the hydrodynamic force and torque on the microstructure constitutes a significant challenge, and so far only the reverse problem of the flow past a random array of stationary particles has been thoroughly investigated in the literature. I will discuss various so-called microstructure informed models of hydrodynamic force and torque fluctuations in a random array of particles that we recently proposed and the challenges lying ahead to provide the multiphase flow community with high fidelity and deterministic hydrodynamic force and torque models that are compatible with the coarse-grained two-way Euler-Lagrange formalism.

The dynamics of nonspherical particles in shear flow in the Stokes regime are linear following periodic orbits (Jeffery, 1922) constrained in one of an infinite set of orbits depending on the initial condition.With inertia, the particle motion is determined by the particle Reynolds number (Rep) and Stokes number(St), estimating the effects of fluid and particle inertia, respectively. We review the transitions in dynamical states with Rep and St showing existence of multiple stable states, and at certain critical parameter, emergence of a motionless (steady) state through an infinite-period saddle-node bifurcation with universal scaling regardless of the confinement (particle spacing) or geometric aspect ratio. AS an example, we show that bifurcations between rotational states when increasing Rep occur in the followin order for a spheroid of aspect ratio 4:(a) Subcritical Hopf bifurcation,(b) Supercritical pitchfork bifurcation,(c) Supercritical Hopf bifurcation,(d) Saddle-node bifurcation of limit cycles, and(e) Infinite-period saddle-node bifurcation.We will then discuss the dynamics of soft particles (red blood cells, RBC) in shear flow based on membrane elasticity. Finally, we will discuss the physics of the migration of hard particles from micro to nanoscale suspended in concentrated microscale soft particles (RBC) in shear flow.

A buffet dinner is served daily between 5:30pm and 7:30pm in Vistas Dining Room, top floor of the Sally Borden Building.

Breakfast is served daily between 7 and 9am in the Vistas Dining Room, the top floor of the Sally Borden Building.

In this talk, I will discuss our recent efforts in understanding the dynamics of weakly magnetic nanoparticle suspensions in non-uniform magnetic fields. I will present the results for two scenarios, where magnetic field gradients are produced using either a conical pole of an electromagnet and/or by introducing a magnetized wire. Thee xperiments are conducted within a closed rectangular cuvette, with a wire positioned between the poles of an electromagnet. Two types of nanoparticles—paramagnetic manganese oxide and diamagnetic bismuth oxide—are studied across a broad range of concentrations (10–100 mg/L), magnetic field strengths (0.25–1 T), and wire diameters(0.8–3 mm). The experimental results reveal that paramagnetic manganese oxide nanoparticles exhibit significant magnetophoretic behavior, leading to particle depletion within the cuvette. The depletion rate is independent of the initial particle concentration but strongly depends on the magnetic field gradient. In contrast, diamagnetic nanoparticles exhibit markedly different behavior, with their magnetophoresis dynamics showing minimal dependence on magnetic field strength, while being inversely proportional to the wire diameter. Transient concentration gradients emerge within thecuvette, which we hypothesize are driven by magnetic Grashof number. Multiphysics numerical simulations reveal formation of field-induced particle clusters in weakly paramagnetic nanoparticles, which enhance magnetophoresis.

Microorganisms often actively respond to multiple external stimuli to navigate towards their preferred niches. This talk will discuss experimental and theoretical work investigating the behaviour of dense suspensions of microorganisms subject to externals fields and fluid flows. We investigate the movement of magnetotactic bacteria, whose swimming direction is influenced by magnetic fields, as well as gravitactic microorganisms, which align themselves with gravity. We demonstrate that the interplay between hydrodynamic interactions among individuals - which are significant in the case of dense suspensions - and the application of external fields, gives rise to striking collective behaviour, particle assembly, and rheology at the population level.

The use of magnetic fields is one of the most efficient means of assembling and manipulating colloidal structures in fluid medium. More recently, it presented a convenient means of powering active colloidal structures and soft robots. We will discuss the principles of magnetic driven propulsion of actively motile particle structures and the means to analyze them by computational fluidic dynamic (CFD) simulations. Assemblies of Janus polymer-metal microcubes can store energy through magnetic polarization and can be actuated by external fields. The microbot“flapping” does not induce net motility in Newtonian fluid, however, these clusters can become self-motile in non-Newtonian media. We explain the origin of the propulsion by CFD analysis ofthe fluid dissipation in a “coupled scallop” geometry. Further, we will show how fluid media with non-Newtonian rheology could change profoundly the propulsion dynamics and hydrodynamic interactions of magnetic microrollers. We report and analyze the microroller dynamics in Newtonian fluids and their dissipative active motion in shear-thinning fluids, leading to a stunning reversal in the propulsion direction, which we refer to as “moonwalking.”Two-dimensional CFD analysis unravels the nature of the forces acting on the moonwalking micro-rollers. We calculate the velocity gradient distribution around the rotating particles usingCOMSOL simulation and reveal that the reversal of the motility direction is a result of the imbalance of forces around the particles due to localized non-uniform shear-thinning. We further demonstrate and analyze by simulations the non-reciprocal collisions and interactions between micro-rollers of different sizes. These results are a step towards the understanding of the dissipative collective motion of microbot swarms in complex fluids.

Axisymmetric microscopic particles tumble in simple shear flow following Jeffery's orbits, a well-known behavior. However, this is not the case for helicoidal objects. A helical appendage of a bacterium, called a flagellum, interacts with the shear flow in such a way that it orients the cell perpendicular to the flow direction. This emergent behavior, known as bulk rheotaxis, arises from the coupling between the helical structure and the flow. We present a general hydrodynamic theory describing particle–flow interactions and numerical simulations for the diffusion processes of such active particles using generalized Taylor dispersion theory.

The hydrodynamic interactions between a sedimenting microswimmer and a wall, both rigid and deformable, have ubiquitous biological and technological applications. A plethora of gravity-induced swimming dynamics near a boundary (a rigid wall or a deformable membrane) provides a platform for designing artificial microswimmers to generate directed propulsion through their translation–rotation coupling near a boundary. In this talk, I first focus on the case of a rigid, planar wall. With collaborators, we provide exact solutions for a squirmer (a model swimmer of spherical shape with a prescribed slip velocity) facing either towards or away from a planar wall perpendicular to gravity. We then use boundary integral simulations to examine the detailed bifurcations of the swimming dynamics of a sedimenting squirmer next to a rigid wall. Next, I present the studies on the interactions between a rigid particle and an inextensible elastic membrane of a vesicle that encloses the forced rigid particle. Under a constant force on the rigid particle (such as gravity), the rigid particle moves towards the vesicle membrane, and the lubrication thin film between the particle and the membrane eventually drains out, as both simulations and asymptotic calculations show. We predict a draining scaling in agreement with the numerical simulations. We suggest that in experiments, the vesicle membrane will eventually rupture and the particle inside the vesicle may be released. This collaboration is with Henry Shum, Deneveyagam Palaniappan, and Bryan Quaife.

Meet in foyer of TCPL to participate in the BIRS group photo. The photograph will be taken outdoors, so dress appropriately for the weather. Please don't be late, or you might not be in the official group photo!

Lunch is served daily between 11:30am and 1:30pm in the Vistas Dining Room, the top floor of the Sally Borden Building.

In this work, we study the flow-field induced by a sedimenting particle in a viscous, density stratified fluid. We consider the scenario where buoyancy forces become comparable to viscous forces much earlier than inertia. In the absence of fluid inertia and density diffusion, it is known that the flow field consists of a ‘reverse-jet’ behind the particle and a set of axisymmetric, horizontal recirculating cells surrounding the particle. We demonstrate that the reverse-jet region, interestingly, possesses an intricate structure of vertical recirculating cells, whose number increases with downstream distance while their width decreases. In the case of no density diffusion, the axial velocity exhibits a Stokesian-like 1/z decay along the rear-stagnation streamline. For small but non-zero density diffusion, the axial velocity behavior changes from 1/z decay to an exponential decay after a ‘secondary screening length’: a length scale that depends on the ratio of convection to diffusion of density (i.e. Peclet number). Furthermore, the density diffusion smears out the vertical recirculating cells after a ‘tertiary screening length’, beyond which the flow exhibits a faster algebraic decay. We provide analytical expressions for the extent of this vertical cell structure and discuss its implications on the drag and fluid drift calculations.

Interface-resolved direct numerical simulations of clustered settling suspensions in a periodic domain are performed to study the filtered drag force for inhomogeneous particle-laden flows. Our results show that, for the homogeneous system, the filtered drag is independent of the filter size, whereas for the clustered particle-laden flows, the averaged drag becomes smaller than the homogeneous drag at the filter size above 4 particle diameters. The drag reduction saturates at the filter size being comparable to the cluster size in the horizontal direction. A new correlation is proposed to account for the mesoscale effect on the filtered drag force by using drift velocity and variance of solid volume fraction, based on modification of existing models. The existing models for the drift velocity and the variance of solid volume fraction are assessed using our DNS data. A new model for the drift velocity and the variance of solid volume fraction is proposed, based on the combination and modification of the previous models. All mesoscale models considered can predict well the filtered drag with comparable accuracy (though our model is slightly better), and are superior to the homogeneous drag model for the clustered system.

A buffet dinner is served daily between 5:30pm and 7:30pm in Vistas Dining Room, top floor of the Sally Borden Building.

Breakfast is served daily between 7 and 9am in the Vistas Dining Room, the top floor of the Sally Borden Building.

Nanoparticles irreversibly trapped at liquid-fluid interfaces solidify at high densities, producing solid-like interfaces that support complex structure. The two characteristic length scales of this system, particle diameter (tens of nanometres) and capillary length (millimetres), describe huge material aspect ratios (~10 7 ). These nanoparticle assemblies exhibit massive mechanical anisotropy; their surface shear modulus is largely constant (approx. 1 N m -1 ), while their bending modulus can be tuned from k B T to 10 6 k B T by varying system composition [1]. We demonstrate that aqueous droplets can be placed at these solid-like oil-water interfaces without coalescing with the underlying aqueous sub-phase for extended periods of time [2]. Interfacially mediated capillary forces give rise to mm-scale attractions between L-sized droplets leading to novel scaling behaviour in droplet dynamics that are captured by a simple theory. Combining this effect with droplet printing allows us to make a liquid material that builds itself (Figure below). Finally, we show how both the droplets and the solid-like interfaces can incorporate energy conversion mechanisms, producing a novel platform for the fabrication of active matter [3].

Stabilizing and structuring liquid–liquid interfaces to create hierarchical functional architectures has emerged as a promising area of research in materials science and engineering. In the present study, we leverage the self-assembly of amphiphilic liquids, such as surfactants and lipids, to stabilize fluidic interfaces. This stabilization arises from the phase transformation of nanoscale assemblies (e.g., micelles) into nanostructured gels, driven by local compositional changes. Small-angle X-ray scattering (SAXS) confirms the formation of nanostructures at the interface, such as lamellar domains with characteristic spacings on the order of ~10 nm. Shear rheology further reveals shear-thinning behavior, indicative of the dynamic and tunable nature of the interfacial gel. Building on these insights, we implement a liquid–liquid 3D printing technique in which a surfactant-rich liquid is extruded into a stabilizing aqueous or oil bath, enabling the fabrication of constructs with controlled internal nano- and microscale architectures.

Life is sustained by exploiting nano/microscale soft structures and interfaces to direct the non-equilibrium chemical processes that govern motion, organization, and growth. It is fundamentally important to understand how materials self-organize or evolve under dissipative conditions in synthetic systems, such as chemically minimal colloids. I will present work aimed at understanding the non-equilibrium properties of emulsions and liquid interfaces, including droplet chemotactic motions, solubilization, and partitioning, which impact emergent physical phenomena. For example, partitioning is usually defined under equilibrium conditions, but solubilizing active droplets are far from equilibrium; such droplets persist for extended times but ultimately disappear due to droplet dissolution and micellar solubilization. Consequently, equilibrium properties like oil-water partition coefficients may not accurately describe properties of out-of-equilibrium droplets. We believe that the study of such active solubilizing droplets provides a means to both uncover a chemically-tunable platform for probing active matter but also contributes to fundamental understanding of how fluid phases and interfaces behave when far from equilibrium.

In this talk, we present two physical phenomena that involve the interplay of non-colloidal particles and the fluid-fluid interface. First, known as granular rafts, fluid-fluid interfaces laden with heavy, discrete particles are simple composite materials that exhibit both elastic and granular properties. We demonstrate their dual nature by compressing them to the point of failure. Our compression experiments reveal that the granular rafts fail via two distinct modes: system-wide buckling and the expulsion of individual particles, the latter of which cannot be captured by the existing continuum model. To rationalize the experimental observations, we build a "composite" model that compares the energy required for buckling to that required to expel a single particle from the interface. In the second part of the talk, we start with non-colloidal particles that are entrained in the viscous oil. When the suspension displaces air inside a rectilinear Hele-Shaw cell, the suspended particles are shown to accumulate on the advancing oil-air interface and destabilize the front. Known as `particle-induced viscous fingering’, this surprising instability leads to the simultaneous formation of particle clusters and the interfacial fingers whose dynamics are coupled. In this talk, we uncover the new regimes of pattern formation due to the presence of the side walls and discuss their potential physical mechanisms.

In this talk, we consider interface instability of a Hele-Shaw problem. We first review the classic single interface setup, in particular the self-similar theory and shape control idea presented https://doi.org/10.1103/PhysRevLett.102.174501 . We then focus on the computation of multi-interface problems with interfaces either dispersed in the viscous fluid region or embedded inside one another. We develop an efficient boundary integral method and compute the interface dynamics of this complex fluid. Numerical results reveal that, depending on the geometries of interfaces and physical parameters, like fluid viscosity, we can use multi-interface to promote or inhibit the classic Saffman-Taylor type instability. Following the self-similar theory, one can pre-select a desired limiting morphology and realize it with a much smaller interface size, by a multi-interface setup.

Lunch is served daily between 11:30am and 1:30pm in the Vistas Dining Room, the top floor of the Sally Borden Building.

A buffet dinner is served daily between 5:30pm and 7:30pm in Vistas Dining Room, top floor of the Sally Borden Building.

Breakfast is served daily between 7 and 9am in the Vistas Dining Room, the top floor of the Sally Borden Building.

Liquid organic hydrogen carriers (LOHCs) are promising media for hydrogen storage, transport, and generation. However, their dehydrogenation in aqueous environment is severely limited by phase immiscibility, resulting in sluggish reaction kinetics. In this study, we investigated a base-catalyzed hydrogen evolution reaction using binary LOHC-alcohol microdroplets combined with a 0.5 M NaOH solution. As efficient microscopic reacting entities, the binary microdroplets at certain mixing ratios achieved up to a 8-fold increase in hydrogen production. This enhancement is particularly pronounced for the binary mixture of polymeric LOHC and a long-chain alcohol with a maximal production rate at an equal mixing ratio where both in-drop and on-drop reactions take place. By following the hydrogen bubble evolution from a single binary droplet, we uncovered a transition in hydrogen bubble formation modes, from in-drop at low mixing ratios, to clustering at intermediate ratios, and on-drop at high ratios, each correlating with distinct hydrogen production rates. Notably, the droplet-based approach achieved a high hydrogen yield in the absence of hazardous solvents or metal catalysts. The produced hydrogen is further demonstrated to power a fuel cell, showcasing its direct application in energy generation. These findings highlight the potential of tuning the composition of reactive microdroplets to unlock highly efficient hydrogen production and utilization pathways.

We propose a novel method for efficient production of microbubbles based on a tapered capillary with an interiorly attached filament. When gas-liquid displacement driven by an input pressure occurs in the capillary, the gas cone ruptures close to the orifice of the capillary. The generated microbubbles can be pushed out of the capillary and collected by a liquid tank when the pressure is appropriately selected. A liquid column is employed in the straight part of the capillary, which can sustain the liquid film near the capillary orifice and hence the bubble generation by transporting liquid along the filament. Within the working pressure range, increasing the input air pressure leads to a decrease in the microbubble diameter. The minimum diameter of the microbubbles is approximately equal to the orifice diameter of the tapered capillary. In our experiments, microbubbles with a minimum diameter of 1.56 μm can be realized. Theoretically, we derive a one-dimensional unsteady lubrication equation describing the evolution of the gas–liquid interface in a tapered tube. The bubble pinch-off is justified by the numerical solution of the lubrication equation. In particular, the predicted bubble diameters are in agreement with the experimental measurements.

The deformation and breakup of sub-Kolmogorov-scale droplets are of relevance to a variety of applications, including top-down production of pharmaceutical nanoparticles. However, the mechanisms driving breakup in this fundamental flow regime remain poorly understood, likely due to challenges arising from the scale separation between the droplets and the bulk flow. At the sub-Kolmogorov scale of the droplet, viscous forces dominate the fluid inertia, and the local flow around the droplets can be accurately described by the Stokes equations. To investigate this regime, we develop a novel boundary element method (BEM) capable of simulating ensembles of droplet trajectories. The numerical method and its validation are described in detail, along with its fast multipole method acceleration and novel adaptive mesh refinement algorithm, which are shown to enhance the accuracy and efficiency of the BEM. Finally, following the approach of Cristini et al. (J. Fluid Mech., vol. 492, 2003), we carry out ensembles of droplet deformation simulations using velocity gradient histories recorded along the trajectories of massless tracers in homogeneous and isotropic turbulence (HIT). By correlating droplet deformation and breakup statistics with the corresponding flow histories, we generate new insights into the multiscale dynamics governing the breakup process.

The Immersed Boundary (IB) method of Peskin (J. Comput. Phys., 1977) is useful for problems that involve fluid-structure interactions or complex geometries. The IB method has been adapted to flows with rigid objects with prescribed motion and other PDEs with given boundary data. IB methods for these problems traditionally involve penalty forces which only approximately satisfy boundary conditions, or they are formulated as constraint problems. In the latter approach, one must find the unknown forces by solving an equation that corresponds to a poorly conditioned first-kind integral equation. This operation can therefore require a large number of iterations of a Krylov method, and since a time-dependent problem requires this solve at each step in time, this method can be prohibitively inefficient without preconditioning. In this talk, we introduce a new, well-conditioned IB formulation for boundary value problems, which we call the Immersed Boundary Double Layer (IBDL) method. In this double layer formulation, the equation for the unknown boundary distribution corresponds to a well-conditioned second-kind integral equation that can be solved efficiently with a small number of iterations of a Krylov method without preconditioning. In addition to this improved efficiency for Stokes and Navier-Stokes equations with Dirichlet boundary conditions, we also demonstrate an advancement that allows us to impose Neumann and Robin boundary conditions, with application to reaction-diffusion equations in chemical systems.

Microfluidic devices that sort cells by their deformability hold significant promise for medical applications including low-cost diagnostics. However, clogging in these microfluidic systems may cause them to change behavior over time, potentially limiting their reliability. Here, we propose a coarse-grained theoretical model to capture the aging of microfluidic devices under different conditions including constant flow and constant pressure. We show how a similar modeling approach may be used to examine the role of applied pressure and shear stress threshold for erosion, a material-dependent property, in deposition of colloidal particles in packings of glass beads.

Lunch is served daily between 11:30am and 1:30pm in the Vistas Dining Room, the top floor of the Sally Borden Building.

Microfluidics offers precise control over the synthesis of nano- and microparticles, allowing systematic tuning of size, morphology, and composition. Despite this potential, broader adoption has been limited by surface fouling, low throughput, and challenges in reproducibility. In this presentation, I will describe our approach to overcoming these barriers by combining automated, AI-augmented control with surface lubrication and scalable microfluidic architectures. Our platform integrates real-time image-based feedback with adjustable flow conditions to reliably generate a range of droplet-based structures—including emulsions, capsules, and lipid nanoparticles—in a high-throughput and reproducible manner. As a representative example, I will discuss gas-encapsulating microcapsules (GEMs), which release their contents in response to hydrostatic pressure. These structures illustrate how microfluidics can facilitate the development of functional particles whose performance is informed by mechanical modeling and biologically inspired design. I will also outline how parallelization and surface lubrication strategies enable a seamless transition from laboratory-scale discovery to scalable manufacturing. These efforts demonstrate how microfluidics can serve as a versatile platform for both the design and production of functional particulate systems, with applications spanning drug delivery, soft robotics, and environmental sensing.

Inverse design of building block features for targeted self-assembly structures is now possible with recent advancements in machine learning and data-driven methods. However, the high dimensionality of the building blocks' parameter space makes it hard to find the globally optimal parameter combinations and will likely result in degenerate solutions. In this talk, we will first review the methodology of using JAX-MD, an end-to-end differentiable molecular dynamics engine, for self-assembly inverse design. We will then address the challenges of selecting appropriate particle parameter sets to optimize for self-limiting assembly. Keeping the same optimizer and increasing the number of tunable parameters, we achieve different optimal building block designs and higher optimization success rates. These results will aid us in developing policies that promote further exploration into the design space when optimization fails and also guide experimentalists on the most important parameters to control when synthesizing patchy particles.

The past decade has brought an ever increasing amount and precision of data gathered from physical systems, as well as a suite of data-driven modeling techniques. One family of techniques aims to recover sparse and mechanistically interpretable dynamical equations from trajectory data. My work here focused on the analysis of the modeling hyperparameters and observational noise robustness. Another family of techniques is sparse sensing, which allows reconstructing a full state of a complex system from observing just a few localized sensors and utilizing training data. My contributions included computing the data-induced effective interactions between the sparse sensors and proposing a regularization to cure state reconstruction instability. Data-driven techniques hold promise for particle systems where interaction potentials and collective arrangement are hard to predict directly from the experimentally synthesized particles. At the same time, I highlight the persistent disconnect between image and particle data formats which opens ground for collaborations.

Discussion of topics, ideas and problems based on one-liner suggestions collected from participants.

A buffet dinner is served daily between 5:30pm and 7:30pm in Vistas Dining Room, top floor of the Sally Borden Building.

Breakfast is served daily between 7 and 9am in the Vistas Dining Room, the top floor of the Sally Borden Building.

Mouse xenografts are cancer research models where human cells are used to create a tumor in a mouse. They are an important tool for cancer research and match real tumor development closer than in-vitro methods, making them a useful stepping stone to human trials. Growth data can be collected from these models in a variety of ways but the most common is size. Modelling this can give insight into the growth of tumors and is useful for evaluating effectiveness of therapies on these mouse models.We fit exponential, logistic, and Gompertz functions to mouse xenograft models withHEC-1A endometrial and LNCaP prostate cancer cells. Xenograft growth was sigmoidal; however exponential models are useful shortly after inoculation and for calculation of the Volume Doubling Time (VDT). VDT was calculated in control and with5 Gy irradiation of HEC-1A cells. Treatment increased the VDT of tumors from 11 ± 2 to38 ± 13 days. This shows that extensive cells in the tumor died reducing the rate of volume increase as dead cells were replaced with living cells. These simple models are for basic interpretation of data; more complex models may better show the effects of radiation.

Yield-stress materials are central to a range of emerging technologies, including additive manufacturing, soft robotics, and the modeling of complex biological fluids. A model system in this domain is Nanoparticle Organic Hybrid Materials (NOHMs)—inorganic nanoparticles coated with tethered oligomers—which exhibit soft glassy rheology due to their amorphous, metastable microstructures. In thermal amorphous materials like NOHMs, yielding involves not only mechanical deformation but also thermally assisted particle rearrangements, yet the interplay between thermal fluctuations and stress-induced dynamics remains poorly understood.In this talk, I will present a multiscale theoretical framework that bridges molecular interactions and bulk rheology in these materials. Using classical density functional theory, we compute the free energy landscape associated with polymer-grafted nanoparticles in random configurations. This energy landscape is then used to inform a thermally activated elastoplastic model that captures how thermal fluctuations influence the yielding transition.Our results, validated against experimental observations, suggest that the energy barriers and metastable states governing flow behavior are highly sensitive to thermal effects. This points to a broader class of questions about how molecular-scale interactions and statistical mechanics can be leveraged to design materials with tailored flow properties.I hope to use this workshop as an opportunity to discuss how ideas from statistical physics, rheology, materials science, and computation can be combined to build a predictive, cross-disciplinary framework for yield-stress materials—contributing to the overarching goal of rational particulate design across application domains.

5-day workshop participants are welcome to use BIRS facilities (TCPL ) until 3 pm on Friday, although participants are still required to checkout of the guest rooms by 11AM.