arXiv subjects

Mark D. Shattuck

Publications and source records attributed to Mark D. Shattuck.

At least 19 recordsLinked to original sources

arXiv2026

Effect of sub-critical fluid shear flow on granular bed strength

Interactions between fluids and granular materials are prevalent on the Earth's surface. In the case of fluid flow over a sediment bed, the fluid imparts a shear stress to the granular materials. When the applied shear stress is above a critical value, the grains become entrained in the fluid flow. Prior experimental studies have shown that granular beds subjected to a sub-critical fluid flow can strengthen in the same direction as the sub-critical flow. In contrast, granular beds can become weaker in the direction opposite to the sub-critical fluid flow. To investigate the grain-scale mechanisms that control directional strengthening and weakening, we perform discrete element method (DEM) simulations of granular beds subjected to model fluid flows in two (2D) and three (3D) dimensions with varied inter-particle static friction coefficients and conditioning flow speeds. In these studies, the sub-critical grain motion does not cause significant bed compaction. Instead, we find that the strength of a granular bed in a particular direction is highly correlated with the fraction of {\it surface} grains that can be dislodged by a fluid force applied in that direction. Further, the anisotropic bed strength only persists over a finite time scale that is set by the Shields number. We also show that inter-particle static friction is not required for bed strength anisotropy, but varying the friction affects the magnitude of the anisotropy. This research enhances the grain-scale understanding of erosion of granular beds caused by fluid flows and underscores the importance of tracking the history of the fabric of the bed surface since it couples strongly to bed strength.

cond-mat.soft↗

arXiv2026

Preserving elastic anisotropy with tessellations of granular packings

Multiscale periodic metamaterials have been designed for numerous applications, such as impact absorption, acoustic cloaking, photonic band gaps, and mechanical logic gates. This prior work has focused on optimizing mesoscale structure for desired bulk isotropic properties. In contrast, we seek to develop materials with highly anisotropic elastic properties. To quantify elastic anisotropy, we introduce two rotationally invariant, normalized quantities that characterize the anisotropic response to shear and compression, respectively, $A_G$ and $A_C$. We find that typical crystalline solids possess average elastic anisotropy $\overline{A}_G \approx 0.15$ and $\overline{A}_C \approx 0.09$. Compared to atomic crystals, jammed granular materials can attain elastic anisotropies that are several orders of magnitude larger. Since grain rearrangements reduce anisotropy in granular materials, to preserve strong elastic anisotropy, we design tessellated granular materials that consist of multiple connected grain-filled voxels, which limit rearrangements and enable highly anisotropic elastic properties. Bulk granular packings with $N$ grains prepared at pressure $p$ have maximal anisotropy for $pN^2\sim1$ and become isotropic in the large-$pN^2$ limit. We show that homogeneously tessellated granular systems can inherit the elastic response of the constituent voxel configurations with elastic anisotropy up to $100$ times that of crystalline compounds over a range of $pN^2$. We show further methods to tune the elastic anisotropy of tessellations by designing heterogeneously patterned voxel configurations and tessellations that allow large boundary deformations.

cond-mat.soft↗

arXiv2025

Droplet Breakup Against an Isolated Obstacle

We describe combined experiments and simulations of droplet breakup during flow-driven interactions with a circular obstacle in a quasi-two-dimensional microfluidic chamber. Due to a lack of in-plane confinement, the droplets can also slip past the obstacle without breaking. Droplets are more likely to break when they have a higher flow velocity, larger size (relative to the obstacle radius R), smaller surface tension, and for head-on collisions with the obstacle. We also observe that droplet-obstacle collisions are more likely to result in breakup when the height of the sample chamber is increased. We define a nondimensional breakup number Bk ~ Ca, where Ca is the Capillary number, that accounts for changes in the likelihood of droplet break up with variations in these parameters. As Bk increases, we find in both experiments and discrete element method (DEM) simulations of the deformable particle model that the behavior changes from droplets never breaking (Bk << 1) to always breaking for Bk >> 1, with a rapid change in the probability of droplet breakup near Bk = 1. We also find that Bk ~ S^(4/3), where S characterizes the symmetry of the collision, which implies that the minimum symmetry required for breakup is controlled by a characteristic distance h ~ R.

physics.flu-dyn↗

arXiv2025

Cell Shape Emerges from Motion

We perform cell segmentation on images from experimental studies of confluent, mobile cells in epithelial monolayers and show that these systems possess a broad, positively-skewed shape parameter distribution $P(\mathcal{A})$, where $\mathcal{A}=p^2/4\pi a$, $p$ is the perimeter, and $a$ is area of each cell. $P(\mathcal{A})$ is peaked at a value higher than the typical shape parameter $\mathcal{A}^* \sim 1.15$ that occurs for randomly packed, static confluent cell monolayers. The distribution does not arise from a heterogeneous population of cells with different fixed $\mathcal{A}$, nor can it arise from cell shape fluctuations from strains below the elastic limit. Instead, we find that all cells in each monolayer sample $\mathcal{A}$ values that span the full shape parameter distribution. We develop a deformable particle model that allows cell perimeter to adapt to local forces during cell motion, and this model recovers $P(\mathcal{A})$ to within $5\%$ for both MDCK and HaCaT epithelial cell monolayers. These results emphasize that confluent epithelial monolayers of mobile cells generate a well-defined broad shape parameter distribution that is independent of the initial cell shapes.

cond-mat.soft↗

arXiv2025

SCUDDO: An unsupervised clustering algorithm for single-cell Hi-C maps using diagonal diffusion operators

Motivation: Advances in high-throughput chromatin conformation capture have provided insight into the three-dimensional structure and organization of chromatin. While bulk Hi-C experiments capture spatio-temporally averaged chromatin interactions across millions of cells, single-cell Hi-C experiments report on the chromatin interactions of individual cells. Supervised and unsupervised algorithms have been developed to embed single-cell Hi-C maps and identify different cell types. However, single-cell Hi-C maps are often difficult to cluster due to their high sparsity, with state-of-the-art algorithms achieving a maximum Adjusted Rand Index (ARI) of only < 0.4 on several datasets while requiring labels for training. Results: We introduce a novel unsupervised algorithm, Single-cell Clustering Using Diagonal Diffusion Operators (SCUDDO), to embed and cluster single-cell Hi-C maps. We evaluate SCUDDO on three previously difficult-to-cluster single-cell Hi-C datasets, and show that it can outperform other current algorithms in ARI by > 0.2. Further, SCUDDO outperforms all other tested algorithms even when we restrict the number of intrachromosomal maps for each cell type and when we use only a small fraction of contacts in each Hi-C map. Thus, SCUDDO can capture the underlying latent features of single-cell Hi-C maps and provide accurate labeling of cell types even when cell types are not known a priori. Availability: SCUDDO is freely available at www.github.com/lmaisuradze/scuddo. The tested datasets are publicly available and can be downloaded from the Gene Expression Omnibus.

q-bio.GN↗

arXiv2025

Particle-scale origin of quadrupolar non-affine displacement fields in granular solids

In this work, we identify the local structural defects that control the non-affine displacement fields in jammed disk packings subjected to athermal, quasistatic (AQS) simple shear. While complex non-affine displacement fields typically occur during simple shear, isolated effective quadrupoles are also observed and their probability increases with increasing pressure. We show that the emergence of an isolated effective quadrupole requires the breaking of an interparticle contact that is aligned with low-frequency, spatially extended vibrational modes. Since the Eshelby inhomogeneity problem gives rise to quadrupolar displacement fields in continuum materials, we reformulate and implement Eshelby's equivalent inclusion method (EIM) for jammed disk packings. Using EIM, we show that we can reconstruct the non-affine displacement fields for jammed disk packings in response to applied shear as a sum of discrete Eshelby-like defects that are caused by mismatches in the local stiffnesses of triangles formed from Delaunay triangulation of the disk centers.

cond-mat.soft↗

arXiv2025

Evolution of Adaptive Force Chains in Reconfigurable Granular Metamaterials

Under an externally applied load, granular packings form force chains that depend on the contact network and moduli of the grains. In this work, we investigate packings of variable modulus (VM) particles, where we can direct force chains by changing the Young's modulus of individual particles within the packing on demand. Each VM particle is made of a silicone shell that encapsulates a core made of a low-melting-point metallic alloy (Field's metal). By sending an electric current through a co-located copper heater, the Field's metal internal to each particle can be melted via Joule heating, which softens the particle. As the particle cools to room temperature, the alloy solidifies and the particle recovers its original modulus. To optimize the mechanical response of granular packings containing both soft and stiff particles, we employ an evolutionary algorithm coupled with discrete element method simulations to predict the patterns of particle moduli that will yield specific force outputs on the assembly boundaries. The predicted patterns of particle moduli from the simulations were realized in experiments using 2D assemblies of VM particles and the force outputs on the assembly boundaries were measured using photoelastic techniques. These studies represent a step towards making robotic granular metamaterials that can dynamically adapt their mechanical properties in response to different environmental conditions or perform specific tasks on demand.

cond-mat.soft↗

arXiv2025

Tuning the Size and Stiffness of Inflatable Particles

We describe size-varying cylindrical particles made from silicone elastomers that can serve as building blocks for robotic granular materials. The particle size variation, which is achieved by inflation, gives rise to changes in stiffness under compression. We design and fabricate inflatable particles that can become stiffer or softer during inflation, depending on key parameters of the particle geometry, such as the ratio of the fillet radius to the wall thickness, r/t. We also conduct numerical simulations of the inflatable particles and show that they only soften during inflation when localization of large strains occurs in the regime r/t -> 0. This work introduces novel particle systems with tunable size and stiffness that can be implemented in numerous soft robotic applications.

cond-mat.soft↗

arXiv2025

The effect of stereochemical constraints on the structural properties of folded proteins

Proteins are composed of chains of amino acids that fold into complex three-dimensional structures. Several key features, such as the radius of gyration, fraction of core amino acids $f_{\rm core}$, packing fraction $\langle \phi\rangle$ of core amino acids, and structure factor $S(q)$ define the structure of folded proteins. It is well-known that folded proteins are compact with a radius of gyration $R_g(N) \sim N^{\nu}$ that obeys power-law scaling with the number of amino acids $N$ and $\nu \sim 1/3$, $f_{\rm core} \approx 0.09$, and $\langle \phi \rangle \approx 0.55$. We also investigate the {\it internal} scaling of the radius of gyration $R_g(n)$ versus the chemical separation $n$ between amino acids for subchains of length $n$ and show that it does not obey simple power-law scaling with $\nu \sim 1/3$. Instead, $R_g(n) \sim n^{\nu_{1,2}}$ with a larger exponent $\nu_1 > 1/3$ for small $n$ and smaller exponent $\nu_{2} < 1/3$ for large $n$. To develop a minimal model for proteins that recapitulates these defining structural features, we carry out collapse simulations for a series of coarse-grained models with increasing complexity. We show that a model, which coarse-grains amino acids into a single spherical backbone bead and several variable-sized side-chain beads and enforces bend- and dihedral-angle constraints for the backbone, recapitulates $R_g(n)$, $f_{\rm core}$, $\langle \phi \rangle$, and $S(q)$ for more than $2500$ x-ray crystal structures of proteins.

cond-mat.soft↗

arXiv2024

Assessment of scoring functions for computational models of protein-protein interfaces

A goal of computational studies of protein-protein interfaces (PPIs) is to predict the binding site between two monomers that form a heterodimer. The simplest version of this problem is to rigidly re-dock the bound forms of the monomers, which involves generating computational models of the heterodimer and then scoring them to determine the most native-like models. Scoring functions have been assessed previously using rank- and classification-based metrics, however, these methods are sensitive to the number and quality of models in the scoring function training set. We assess the accuracy of seven PPI scoring functions by comparing their scores to a measure of structural similarity to the x-ray crystal structure (i.e. the DockQ score) for a non-redundant set of heterodimers from the Protein Data Bank. For each heterodimer, we generate re-docked models uniformly sampled over DockQ and calculate the Spearman correlation between the PPI scores and DockQ. For some targets, the scores and DockQ are highly correlated; however, for many targets, there are weak correlations. Several physical features can explain the difference between difficult- and easy-to-score targets. For example, strong correlations exist between the score and DockQ for targets with highly intertwined monomers and many interface contacts. We also develop a new score based on only three physical features that matches or exceeds the performance of current PPI scoring functions. These results emphasize that PPI prediction can be improved by focusing on correlations between the PPI score and DockQ and incorporating more discriminating physical features into PPI scoring functions.

q-bio.BM↗

arXiv2024

Flow and clogging of capillary droplets

Capillary droplets form due to surface tension when two immiscible fluids are mixed. We describe the motion of gravity-driven capillary droplets flowing through narrow constrictions and obstacle arrays in both simulations and experiments. Our new capillary deformable particle model recapitulates the shape and velocity of single oil droplets in water as they pass through narrow constrictions in microfluidic chambers. Using this experimentally validated model, we simulate the flow and clogging of single capillary droplets in narrow channels and obstacle arrays and find several important results. First, the capillary droplet speed profile is nonmonotonic as the droplet exits the narrow orifice, and we can tune the droplet properties so that the speed overshoots the terminal speed far from the constriction. Second, in obstacle arrays, we find that extremely deformable droplets can wrap around obstacles, which leads to decreased average droplet speed in the continuous flow regime and increased probability for clogging in the regime where permanent clogs form. Third, the wrapping mechanism causes the clogging probability in obstacle arrays to become nonmonotonic with surface tension $\Gamma$. At large $\Gamma$, the droplets are nearly rigid and the clogging probability is large since the droplets can not squeeze through the gaps between obstacles. With decreasing $\Gamma$, the clogging probability decreases as the droplets become more deformable. However, in the small-$\Gamma$ limit the clogging probability increases, since the droplets are extremely deformable and cause clogs as they wrap around the obstacles. The results from these studies are important for developing a predictive understanding of capillary droplet flows through complex and confined geometries.

physics.comp-ph↗

arXiv2024

Protein folding as a jamming transition

Proteins fold to a specific functional conformation with a densely packed hydrophobic core that controls their stability. We develop a geometric, yet all-atom model for proteins that explains the universal core packing fraction of $\phi_c=0.55$ found in experimental measurements. We show that as the hydrophobic interactions increase relative to the temperature, a novel jamming transition occurs when the core packing fraction exceeds $\phi_c$. The model also recapitulates the global structure of proteins since it can accurately refold to native-like structures from partially unfolded states.

cond-mat.soft↗

arXiv2024

Computational modeling of the physical features that influence breast cancer invasion into adipose tissue

Breast cancer invasion into adipose tissue strongly influences disease progression and metastasis. The degree of cancer cell invasion into adipose tissue depends on numerous biochemical and physical properties of cancer cells, adipocytes, and other key components of adipose tissue. We model breast cancer invasion into adipose tissue as a physical process by carrying out simulations of active, cohesive spherical particles (cancer cells) invading into confluent packings of deformable polyhedra (adipocytes). We quantify the degree of invasion by calculating the interfacial area $A_t$ between cancer cells and adipocytes. We determine the long-time value of $A_t$ versus the activity and strength of the cohesion between cancer cells, as well as mechanical properties of the adipocytes and extracellular matrix (ECM) in which the adipocytes are embedded. We show that the degree of invasion collapses onto a master curve by plotting it versus a dimensionless energy scale $E_c$, which grows linearly with mean-square fluctuations and persistence time of the cancer cell velocities, is inversely proportional to the pressure of the system, and has an offset that increases with the cancer cell cohesive energy. The condition, $E_c \gg 1$, indicates that cancer cells will invade the adipose tissue, whereas for $E_c \ll 1$, the cancer cells and adipocytes remain demixed. We also show that constraints on adipocyte positions by the ECM decrease $A_t$ relative to that obtained for unconstrained adipocytes. Finally, spatial heterogeneity in structural and mechanical properties of the adipocytes in the presence of ECM impedes invasion relative to adipose tissue with uniform properties.

physics.bio-ph↗

arXiv2023

Identifying topologically associating domains using differential kernels

Chromatin is a polymer complex of DNA and proteins that regulates gene expression. The three-dimensional structure and organization of chromatin controls DNA transcription and replication. High-throughput chromatin conformation capture techniques generate Hi-C maps that can provide insight into the 3D structure of chromatin. Hi-C maps can be represented as a symmetric matrix where each element represents the average contact probability or number of contacts between two chromatin loci. Previous studies have detected topologically associating domains (TADs), or self-interacting regions in Hi-C maps within which the contact probability is greater than that outside the region. Many algorithms have been developed to identify TADs within Hi-C maps. However, most TAD identification algorithms are unable to identify nested or overlapping TADs and for a given Hi-C map there is significant variation in the location and number of TADs identified by different methods. We develop a novel method, KerTAD, using a kernel-based technique from computer vision and image processing that is able to accurately identify nested and overlapping TADs. We benchmark this method against state-of-the-art TAD identification methods on both synthetic and experimental data sets. We find that KerTAD consistently has higher true positive rates (TPR) and lower false discovery rates (FDR) than all tested methods for both synthetic and manually annotated experimental Hi-C maps. The TPR for KerTAD is also largely insensitive to increasing noise and sparsity, in contrast to the other methods. We also find that KerTAD is consistent in the number and size of TADs identified across replicate experimental Hi-C maps for several organisms. KerTAD will improve automated TAD identification and enable researchers to better correlate changes in TADs to biological phenomena, such as enhancer-promoter interactions and disease states.

q-bio.GN↗

arXiv2023

Mechanical Plasticity of Cell Membranes Enhances Epithelial Wound Closure

During epithelial wound healing, cell morphology near the healed wound and the healing rate vary strongly among different developmental stages even for a single species like \textit{Drosophila}. We develop deformable particle (DP) model simulations to understand how variations in cell mechanics give rise to distinct wound closure phenotypes in the \textit{Drosophila} embryonic ectoderm and larval wing disc epithelium. We find that plastic deformation of the cell membrane can generate large changes in cell shape consistent with wound closure in the embryonic ectoderm. Our results show that the embryonic ectoderm is best described by cell membranes with an elasto-plastic response, whereas the larval wing disc is best described by cell membranes with an exclusively elastic response. By varying the mechanical response of cell membranes in DP simulations, we recapitulate the wound closure behavior of both the embryonic ectoderm and the larval wing disc.

physics.bio-ph↗

arXiv2023

Modeling the effects of varying Ti concentration on the mechanical properties of Cu-Ti alloys

The mechanical properties of Cu-Ti alloys have been characterized extensively through experimental studies. However, a detailed understanding of why the strength of Cu increases after a small fraction of Ti atoms is added to the alloy is still missing. In this work, we address this question using density functional theory (DFT) and molecular dynamics (MD) simulations with modified embedded atom method (MEAM) interatomic potentials. First, we performed calculations of uniaxial tension deformations of small bicrystalline Cu cells using DFT static simulations. We then carried out uniaxial tension deformations on much larger bicrystalline and polycrystalline Cu cells using MEAM MD simulations. In bicrystalline Cu, the inclusion of Ti increases the grain boundary separation energy and maximum tensile stress. The DFT calculations demonstrate that the increase in tensile stress can be attributed to an increase in the local charge density arising from Ti. MEAM simulations in larger bicrystalline systems have shown that increasing the Ti concentration decreases the density of stacking faults. This observation is enhanced in polycrystalline Cu, where the addition of Ti atoms, even at concentrations as low as 1.5 at.%, increases the yield strength and elastic modulus of the material compared to pure Cu. Under uniaxial tensile loading, the addition of small amounts of Ti hinders the formation of partial Shockley dislocations in the grain boundaries of Cu, leading to reduced local deformation. These results shed light on the role of Ti in determining the mechanical properties of polycrystalline Cu and will enable the engineering of grain boundaries and the inclusion of Ti to improve degradation resistance.

cond-mat.mtrl-sci↗

arXiv2023

The connection between polymer collapse and the onset of jamming

Previous studies have shown that the interiors of proteins are densely packed, reaching packing fractions that are as large as those found for static packings of individual amino-acid-shaped particles. How can the interiors of proteins take on such high packing fractions given that amino acids are connected by peptide bonds and many amino acids are hydrophobic with attractive interactions? We investigate this question by comparing the structural and mechanical properties of collapsed attractive disk-shaped bead-spring polymers to those of three reference systems: static packings of repulsive disks, of attractive disks, and of repulsive disk-shaped bead-spring polymers. We show that attractive systems quenched to temperatures below the glass transition $T \ll T_g$ and static packings of both repulsive disks and bead-spring polymers possess similar interior packing fractions. Previous studies have shown that static packings of repulsive disks are isostatic at jamming onset, i.e. the number of contacts $N_c$ matches the number of degrees of freedom, which strongly influences their mechanical properties. We find that repulsive polymers are hypostatic at jamming onset, but effectively isostatic when including quartic modes. While attractive disk and polymer packings are hyperstatic, we identify a definition for interparticle contacts for which they can also be considered as effectively isostatic. As a result, we show that the mechanical properties (e.g. scaling of the potential energy with excess contact number and low-frequency contribution to the density of vibrational modes) of weakly attractive disk and polymer packings are similar to those of ${\it isostatic}$ repulsive disk and polymer packings. Our results demonstrate that static packings generated via attractive collapse or compression of repulsive particles possess similar structural and mechanical properties.

cond-mat.soft↗

arXiv2023

Designing the pressure-dependent shear modulus using tessellated granular metamaterials

Jammed packings of granular materials display complex mechanical response. For example, the ensemble-averaged shear modulus $\left\langle G \right\rangle$ increases as a power-law in pressure $p$ for static packings of soft spherical particles that can rearrange during compression. We seek to design granular materials with shear moduli that can either increase {\it or} decrease with pressure without particle rearrangements even in the large-system limit. To do this, we construct {\it tessellated} granular metamaterials by joining multiple particle-filled cells together. We focus on cells that contain a small number of bidisperse disks in two dimensions. We first study the mechanical properties of individual disk-filled cells with three types of boundaries: periodic boundary conditions (PBC), fixed-length walls (FXW), and flexible walls (FLW). Hypostatic jammed packings are found for cells with FLW, but not in cells with PBC and FXW, and they are stabilized by quartic modes of the dynamical matrix. The shear modulus of a single cell depends linearly on $p$. We find that the slope of the shear modulus with pressure, $λ_c < 0$ for all packings in single cells with PBC where the number of particles per cell $N \ge 6$. In contrast, single cells with FXW and FLW can possess $λ_c > 0$, as well as $λ_c < 0$, for $N \le 16$. We show that we can force the mechanical properties of multi-cell granular metamaterials to possess those of single cells by constraining the endpoints of the outer walls and enforcing an affine shear response. These studies demonstrate that tessellated granular metamaterials provide a novel platform for the design of soft materials with specified mechanical properties.

cond-mat.soft↗