arXiv subjects

Fred C. MacKintosh

Publications and source records attributed to Fred C. MacKintosh.

At least 19 recordsLinked to original sources

arXiv2026

Stress relaxation in fiber networks via force-dependent stochastic severing

Fiber networks contribute to the mechanical stability of various biological systems, from cells to tissues. Such systems have been modeled by networks of springs or fibers that exhibit rigidity transitions as a function of either connectivity or applied strain. For a fiber network under constant applied strain, severing can reduce the connectivity and destabilize an initially rigid structure. Here, we investigate stress relaxation in spring and fiber networks in the presence of stochastic, force-dependent severing. A computational model to predict stress relaxation with mechanochemical feedback of stress on severing is developed. We also examine the effects of severing on the network topology and onset of rigidity transition. Using 2D triangular lattice-based computer simulations, we explore different limits of the feedback and demonstrate the shift in the onset of rigidity depending on the limit. The limit of tension-suppressed severing delays stress relaxation and shifts the transition into the bending-dominated regime to lower-than-expected connectivity. In contrast, tension-enhanced severing accelerates relaxation and shifts the transition to higher-than-expected connectivity. It is also found that the magnitude of this shift depends on the applied shear strain and the strength of the feedback. Our theoretical approach clarifies some microscopic aspects of these phenomena. Understanding the impact of such feedback mechanisms can provide valuable insights into designing systems by tuning the feedback to the desired response.

cond-mat.soft↗

arXiv2026

Strain-stiffening critical exponents of fiber networks under uniaxial deformation

Disordered fiber networks exhibit a floppy to rigid mechanical phase transition as a function of connectivity. Sub-isostatically connected networks can undergo this transition via straining. Critical exponents governing this transition have been estimated theoretically and by numerical simulations of various types of networks. In this study, we present improved results, achieved through a combination of refined numerical simulations, larger system sizes and incorporation of theoretical predictions for better post-simulation analysis. We also report the evolution of the critical strain and critical exponents as the network is sheared while being subjected to non-volume-preserving uniaxial deformations.

cond-mat.soft↗

arXiv2024

Criticality enhances the reinforcement of disordered networks by rigid inclusions

The mechanical properties of biological materials are spatially heterogeneous. Typical tissues are made up of a spanning fibrous extracellular matrix in which various inclusions, such as living cells, are embedded. While the influence of inclusions on the stiffness of common elastic materials such as rubber has been studied for decades and can be understood in terms of the volume fraction and shape of inclusions, the same is not true for disordered filamentous and fibrous networks. Recent work has shown that, in isolation, such networks exhibit unusual viscoelastic behavior indicative of an underlying mechanical phase transition controlled by network connectivity and strain. How this behavior is modified when inclusions are present is unclear. Here, we present a theoretical and computational study of the influence of rigid inclusions on the mechanics of disordered elastic networks near the connectivity-controlled central force rigidity transition. Combining scaling theory and coarse-grained simulations, we predict and confirm an anomalously strong dependence of the composite stiffness on inclusion volume fraction, beyond that seen in ordinary composites. This stiffening exceeds the well-established volume fraction-dependent stiffening expected in conventional composites, e.g., as an elastic analogue of the classic volume fraction dependent increase in the viscosity of liquids first identified by Einstein. We show that this enhancement is a consequence of the interplay between inter-particle spacing and an emergent correlation length, leading to an effective finite-size scaling imposed by the presence of inclusions. We outline the expected scaling of the shear modulus and strain fluctuations with the inclusion volume fraction and network connectivity, confirm these predictions in simulations, and discuss potential experimental tests and implications for our predictions in real systems.

cond-mat.soft↗

arXiv2024

Nonlinear Poisson effect in affine semiflexible polymer networks

Stretching an elastic material along one axis typically induces contraction along the transverse axes, a phenomenon known as the Poisson effect. From these strains, one can compute the specific volume, which generally either increases or, in the incompressible limit, remains constant as the material is stretched. However, in networks of semiflexible or stiff polymers, which are typically highly compressible yet stiffen significantly when stretched, one instead sees a significant reduction in specific volume under finite strains. This volume reduction is accompanied by increasing alignment of filaments along the strain axis and a nonlinear elastic response, with stiffening of the apparent Young's modulus. For semiflexible networks, in which entropic bending elasticity governs the linear elastic regime, the nonlinear Poisson effect is caused by the nonlinear force-extension relationship of the constituent filaments, which produces a highly asymmetric response of the constituent polymers to stretching and compression. The details of this relationship depend on the geometric and elastic properties of the underlying filaments, which can vary greatly in experimental systems. Here, we provide a comprehensive characterization of the nonlinear Poisson effect in an affine network model and explore the influence of filament properties on essential features of the macroscopic response, including strain-driven alignment and volume reduction.

cond-mat.soft↗

arXiv2024

Field theory for mechanical criticality in disordered fiber networks

Strain-controlled criticality governs the elasticity of jamming and fiber networks. While the upper critical dimension of jamming is believed to be $d_u$=2, non mean-field exponents are observed in numerical studies of 2D and 3D fiber networks. The origins of this remains unclear. In this study we propose a minimal mean-field model for strain-controlled criticality of fiber networks. We then extend this to a phenomenological field theory, in which non mean-field behavior emerges as a result of the disorder in the network structure. We predict that the upper critical dimension for such systems is $d_u$=4 using a Gaussian approximation. Moreover, we identify an order parameter for the phase transition, which has been lacking for fiber networks to date.

cond-mat.soft↗

arXiv2024

Capturing the slow relaxation time of superparamagnetic colloids in time-varying fields

Superparamagnetic colloids present interesting assembly dynamics and propulsion in time-varying magnetic fields due to their magnetic relaxation. However, little is known about the mechanisms governing this magnetic relaxation, which is commonly attributed to the interactions and polydispersity of the ferromagnetic nanoparticles distributed within the colloid. We measure this relaxation from the effective potential between colloids subjected to rotating magnetic fields. Remarkably, our results indicate the presence of magnetic relaxation times much longer than what has been reported, which furthers our understanding of the magnetization of colloids in complex magnetic fields.

cond-mat.soft↗

arXiv2023

Mechanical criticality of fiber networks at a finite temperature

At zero temperature, spring networks with connectivity below Maxwell's isostatic threshold undergo a mechanical phase transition from a floppy state at small strains to a rigid state for applied shear strain above a critical strain threshold. Disordered networks in the floppy mechanical regime can be stabilized by entropic effects at finite temperature. We develop a scaling theory based on a real-space renormalization approach for this mechanical phase transition at finite temperature, yielding relationships between various scaling exponents. Using Monte Carlo simulations, we verify these scaling relations and identify anomalous entropic elasticity with sub-linear $T$-dependence in the linear elastic regime. While our results are consistent prior studies of phase behavior near the isostatic point, the present work also makes predictions relevant to the broad class of disordered thermal semiflexible polymer networks for which the connectivity generally lies far below the isostatic threshold.

cond-mat.soft↗

arXiv2023

Strain-controlled critical slowing down in the rheology of disordered networks

Networks and dense suspensions frequently reside near a boundary between soft (or fluid-like) and rigid (or solid-like) regimes. Transitions between these regimes can be driven by changes in structure, density, or applied stress or strain. In general, near the onset or loss of rigidity in these systems, dissipation-limiting heterogeneous nonaffine rearrangements dominate the macroscopic viscoelastic response, giving rise to diverging relaxation times and power-law rheology. Here, we describe a simple quantitative relationship between nonaffinity and the excess viscosity. We test this nonaffinity-viscosity relationship computationally and demonstrate its rheological consequences in simulations of strained filament networks and dense suspensions. We also predict critical signatures in the rheology of semiflexible and stiff biopolymer networks near the strain stiffening transition.

cond-mat.soft↗

arXiv2023

Structural features and nonlinear rheology of self-assembled networks of cross-linked semiflexible polymers

Disordered networks of semiflexible filaments are common support structures in biology. Familiar examples include fibrous matrices in blood clots, bacterial biofilms, and essential components of cells and tissues of plants, animals, and fungi. Despite the ubiquity of these networks in biomaterials, we have only a limited understanding of the relationship between their structural features and highly strain-sensitive mechanical properties. In this work, we perform simulations of three-dimensional networks produced by the irreversible formation of crosslinks between linker-decorated semiflexible filaments. We characterize the structure of networks formed by a simple diffusion-dependent assembly process and measure their associated steady-state rheological features at finite temperature over a range of applied prestrains that encompass the strain-stiffening transition. We quantify the dependence of network connectivity on crosslinker availability and detail the associated connectivity dependence of both linear elasticity and nonlinear strain stiffening behavior, drawing comparisons with prior experimental measurements of the crosslinker concentration-dependent elasticity of actin gels.

cond-mat.soft↗

arXiv2023

Effective Medium Theory for Mechanical Phase Transitions of Fiber Networks

Networks of stiff fibers govern the elasticity of biological structures such as the extracellular matrix of collagen. These networks are known to stiffen nonlinearly under shear or extensional strain. Recently, it has been shown that such stiffening is governed by a strain-controlled athermal but critical phase transition, from a floppy phase below the critical strain to a rigid phase above the critical strain. While this phase transition has been extensively studied numerically and experimentally, a complete analytical theory for this transition remains elusive. Here, we present an effective medium theory (EMT) for this mechanical phase transition of fiber networks. We extend a previous EMT appropriate for linear elasticity to incorporate nonlinear effects via an anharmonic Hamiltonian. The mean-field predictions of this theory, including the critical exponents, scaling relations and non-affine fluctuations qualitatively agree with previous experimental and numerical results.

cond-mat.soft↗

arXiv2023

Effects of local incompressibility on the rheology of composite biopolymer networks

Fibrous networks such as collagen are common in biological systems. Recent theoretical and experimental efforts have shed light on the mechanics of single component networks. Most real biopolymer networks, however, are composites made of elements with different rigidity. For instance, the extracellular matrix in mammalian tissues consists of stiff collagen fibers in a background matrix of flexible polymers such as hyaluronic acid (HA). The interplay between different biopolymer components in such composite networks remains unclear. In this work, we use 2D coarse-grained models to study the nonlinear strain-stiffening behavior of composites. We introduce a local volume constraint to model the incompressibility of HA. We also perform rheology experiments on composites of collagen with HA. We demonstrate both theoretically and experimentally that the linear shear modulus of composite networks can be increased by approximately an order of magnitude above the corresponding moduli of the pure components. Our model shows that this synergistic effect can be understood in terms of the local incompressibility of HA, which acts to suppress density fluctuations of the collagen matrix with which it is entangled.

cond-mat.soft↗

arXiv2023

Non-affine deformation of semiflexible polymer and fiber networks

Networks of semiflexible or stiff polymers such as most biopolymers are known to deform inhomogeneously when sheared. The effects of such non-affine deformation have been shown to be much stronger than for flexible polymers. To date, our understanding of non-affinity in such systems is limited to simulations or specific 2D models of athermal fibers. Here, we present an effective medium theory (EMT) for non-affine deformation of semiflexible polymer and fiber networks, which is general to both 2D and 3D and in both thermal and athermal limits. The predictions of this model are in good agreement with both prior computational and experimental results for linear elasticity. Moreover, the framework we introduce can be extended to address nonlinear elasticity and network dynamics.

cond-mat.soft↗

arXiv2022

Mechanics of fiber networks under a bulk strain

Biopolymer networks are common in biological systems from the cytoskeleton of individual cells to collagen in the extracellular matrix. The mechanics of these systems under applied strain can be explained in some cases by a phase transition from soft to rigid states. For collagen networks, it has been shown that this transition is critical in nature and it is predicted to exhibit diverging fluctuations near a critical strain that depends on the network's connectivity and structure. Whereas prior work focused mostly on shear deformation that is more accessible experimentally, here we study the mechanics of such networks under an applied bulk or isotropic extension. We confirm that the bulk modulus of subisostatic fiber networks exhibits similar critical behavior as a function of bulk strain. We find different non-mean-field exponents for bulk as opposed to shear. We also confirm a similar hyperscaling relation to what previously found for shear.

cond-mat.soft↗

arXiv2022

Motor-free contractility of active biopolymer networks

Contractility in animal cells is often generated by molecular motors such as myosin, which require polar substrates for their function. Motivated by recent experimental evidence of motor-independent contractility, we propose a robust motor-free mechanism that can generate contraction in biopolymer networks without the need for substrate polarity. We show that contractility is a natural consequence of active binding/unbinding of crosslinkers that breaks the Principle of Detailed Balance, together with the asymmetric force-extension response of semiflexible biopolymers. We calculate the resulting contractile velocity using both a simple coarse-grained model and a more detailed microscopic model for a viscoelastic biopolymer network. Our model may provide an explanation of recent reports of motor-independent contractility in cells. Our results also suggest a mechanism for generating contractile forces in synthetic active materials.

cond-mat.soft↗

arXiv2021

Non-linear stress relaxation of transient-crosslinked biopolymer networks

A long standing puzzle in the rheology of living cells is the origin of the experimentally observed long time stress relaxation. The mechanics of the cell is largely dictated by the cytoskeleton, which is a biopolymer network consisting of transient crosslinkers, allowing for stress relaxation over time. Moreover, these networks are internally stressed due to the presence of molecular motors. In this work we propose a theoretical model that uses a mode-dependent mobility to describe the stress relaxation of such prestressed transient networks. Our theoretical predictions agree favorably with experimental data of reconstituted cytoskeletal networks and may provide an explanation for the slow stress relaxation observed in cells.

physics.bio-ph↗

arXiv2021

Shear-induced phase transition and critical exponents in 3D fiber networks

When subject to applied strain, fiber networks exhibit nonlinear elastic stiffening. Recent theory and experiements have shown that this phenomenon is controlled by an underlying mechanical phase transition that is critical in nature. Growing simulation evidence points to non-mean-field behavior for this transition and a hyperscaling relation has been proposed to relate the corresponding critical exponents. Here, we report simulations on two distinct network structures in 3D. By performing finite-size scaling analysis, we test hyperscaling and identify various critical exponents. From the apparent validity of hyperscaling, as well as the non-mean-field exponents we observe, our results suggest that the upper critical dimension for the strain-controlled phase transition is above three, in contrast to the jamming transition that represents another athermal, mechanical phase transition.

cond-mat.soft↗

arXiv2021

Enhanced ordering in length-polydisperse carbon nanotube solutions at high concentrations as revealed by small angle X-ray scattering

Carbon nanotubes (CNTs) are stiff, all-carbon macromolecules with diameters as small as one nanometer and few microns long. Solutions of CNTs in chlorosulfonic acid (CSA) follow the phase behavior of rigid rod polymers interacting via a repulsive potential and display a liquid crystalline phase at sufficiently high concentration. Here, we show that small-angle X-ray scattering and polarized light microscopy data can be combined to characterize quantitatively the morphology of liquid crystalline phases formed in CNT solutions at concentrations from 3 to 6.5 % by volume. We find that upon increasing their concentration, CNTs self-assemble into a liquid crystalline phase with a pleated texture and with a large inter-particle spacing that could be indicative of a transition to higher-order liquid crystalline phases. We explain how thermal undulations of CNTs can enhance their electrostatic repulsion and increase their effective diameter by an order of magnitude. By calculating the critical concentration, where the mean amplitude of undulation of an unconstrained rod becomes comparable to the rod spacing, we find that thermal undulations start to affect steric forces at concentrations as low as the isotropic cloud point in CNT solutions.

cond-mat.soft↗

arXiv2020

Multi-scale microrheology using fluctuating filaments as stealth probes

The mechanical properties of soft materials can be probed on small length scales by various microrheology methods. A common approach tracks fluctuations of micrometer-sized beads embedded in the medium to be characterized. This approach yields results that depend on the probe size when the medium has structure on length scales comparable to or larger than this size. Here, we introduce a filament-based microrheology (FMR) method using high-aspect-ratio semi-flexible filaments as probes. Such quasi-1D probes are much less invasive due to the nanometer-scale cross section of the probes. Moreover, by imaging the transverse bending modes, we are able to simultaneously determine the micromechanical response of the medium on multiple length scales corresponding bending wavelengths. Here, we use single-walled carbon nanotubes (SWNT) as probes that can be accurately and rapidly imaged based on their stable fluorescence. We model SWNTs as semi-flexible filaments. We find that the viscoelastic properties of sucrose and polymeric hyaluronic acid solutions measured in this way are in good agreement with those measured by conventional micro- and macrorheology.

cond-mat.soft↗