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Corey S. O'Hern

Publications and source records attributed to Corey S. O'Hern.

At least 73 records · Page 4Linked to original sources
arXiv2017

Packing in Protein Cores

Proteins are biological polymers that underlie all cellular functions. The first high-resolution protein structures were determined by x-ray crystallography in the 1960s. Since then, there has been continued interest in understanding and predicting protein structure and stability. It is well-established that a large contribution to protein stability originates from the sequestration from solvent of hydrophobic residues in the protein core. How are such hydrophobic residues arranged in the core? And how can one best model the packing of these residues? Here we show that to properly model the packing of residues in protein cores it is essential that amino acids are represented by appropriately calibrated atom sizes, and that hydrogen atoms are explicitly included. We show that protein cores possess a packing fraction of $ϕ\approx 0.56$, which is significantly less than the typically quoted value of 0.74 obtained using the extended atom representation. We also compare the results for the packing of amino acids in protein cores to results obtained for jammed packings from disrete element simulations composed of spheres, elongated particles, and particles with bumpy surfaces. We show that amino acids in protein cores pack as densely as disordered jammed packings of particles with similar values for the aspect ratio and bumpiness as found for amino acids. Knowing the structural properties of protein cores is of both fundamental and practical importance. Practically, it enables the assessment of changes in the structure and stability of proteins arising from amino acid mutations (such as those identified as a result of the massive human genome sequencing efforts) and the design of new folded, stable proteins and protein-protein interactions with tunable specificity and affinity.

cond-mat.soft↗
arXiv2016

The effects of cooling rate on particle rearrangement statistics: Rapidly cooled glasses are more ductile and less reversible

Amorphous solids, such as metallic, polymeric, and colloidal glasses, display complex spatiotemporal response to applied deformations. In contrast to crystalline solids, during loading, amorphous solids exhibit a smooth crossover from elastic response to plastic flow. In this study, we investigate the mechanical response of binary Lennard-Jones glasses to athermal, quasistatic pure shear as a function of the cooling rate used to prepare them. We find several key results concerning the connection between strain-induced particle rearrangements and mechanical response. We show that more rapidly cooled glasses undergo more frequent and larger particle rearrangements than slowly cooled glasses. We find that the ratio of the shear to bulk moduli decreases with increasing cooling rate, which suggests that more rapidly cooled glasses are more ductile than slowly cooled samples. In addition, we characterized the degree of reversibility of particle motion during cyclic shear. We find that irreversible particle motion occurs even in the putative linear regime of stress versus strain. However, slowly cooled glasses, which undergo smaller rearrangements, are more reversible under cyclic shear than rapidly cooled glasses. Thus, we show that more ductile glasses are also less reversible.

cond-mat.soft↗
arXiv2016

Reconstruction of Ordinary Differential Equations From Time Series Data

We develop a numerical method to reconstruct systems of ordinary differential equations (ODEs) from time series data without {\it a priori} knowledge of the underlying ODEs using sparse basis learning and sparse function reconstruction. We show that employing sparse representations provides more accurate ODE reconstruction compared to least-squares reconstruction techniques for a given amount of time series data. We test and validate the ODE reconstruction method on known 1D, 2D, and 3D systems of ODEs. The 1D system possesses two stable fixed points; the 2D system possesses an oscillatory fixed point with closed orbits; and the 3D system displays chaotic dynamics on a strange attractor. We determine the amount of data required to achieve an error in the reconstructed functions to less than $0.1\%$. For the reconstructed 1D and 2D systems, we are able to match the trajectories from the original ODEs even at long times. For the 3D system with chaotic dynamics, as expected, the trajectories from the original and reconstructed systems do not match at long times, but the reconstructed and original models possess similar Lyapunov exponents. Now that we have validated this ODE reconstruction method on known models, it can be employed in future studies to identify new systems of ODEs using time series data from deterministic systems for which there is no currently known ODE model.

physics.data-an↗
arXiv2015

Random close packing in protein cores

Shortly after the determination of the first protein x-ray crystal structures, researchers analyzed their cores and reported packing fractions $ϕ\approx 0.75$, a value that is similar to close packing equal-sized spheres. A limitation of these analyses was the use of `extended atom' models, rather than the more physically accurate `explicit hydrogen' model. The validity of using the explicit hydrogen model is proved by its ability to predict the side chain dihedral angle distributions observed in proteins. We employ the explicit hydrogen model to calculate the packing fraction of the cores of over $200$ high resolution protein structures. We find that these protein cores have $ϕ\approx 0.55$, which is comparable to random close-packing of non-spherical particles. This result provides a deeper understanding of the physical basis of protein structure that will enable predictions of the effects of amino acid mutations and design of new functional proteins.

q-bio.BM↗
arXiv2015

Onset and cessation of motion in hydrodynamically sheared granular beds

We performed molecular dynamics simulations of granular beds driven by a model hydrodynamic shear flow to elucidate general grain-scale mechanisms that determine the onset and cessation of sediment transport. By varying the Shields number (the nondimensional shear stress at the top of the bed) and particle Reynolds number (the ratio of particle inertia to viscous damping), we explore how variations of the fluid flow rate, particle inertia, and fluid viscosity affect the onset and cessation of bed motion. For low to moderate particle Reynolds numbers, a critical boundary separates mobile and static states. Transition times between these states diverge as this boundary is approached both from above and below. At high particle Reynolds number, inertial effects become dominant, and particle motion can be sustained well below flow rates at which mobilization of a static bed occurs. We also find that the onset of bed motion (for both low and high particle Reynolds numbers) is described by Weibullian weakest-link statistics, and thus is crucially dependent on the packing structure of the granular bed, even deep beneath the surface.

cond-mat.soft↗
arXiv2015

Beyond packing of hard spheres: The effects of core softness, non-additivity, intermediate-range repulsion, and many-body interactions on the glass-forming ability of bulk metallic glasses

When a liquid is cooled well below its melting temperature at a rate that exceeds the critical cooling rate $R_c$, the crystalline state is bypassed and an amorphous glassy state forms instead. $R_c$ (or the corresponding critical casting thickness $d_c$) characterizes the glass-forming ability (GFA) of each material. While silica is an excellent glass-former with small $R_c<10^{-2}$ K/s, pure metals and most alloys are poor glass-formers with large $R_c>10^{10}$ K/s. Only in the past thirty years have bulk metallic glasses (BMGs) been identified with $R_c$ approaching that for silica. Recent simulations have shown that hard-sphere models are able to identify the atomic size ratio and number fraction regime where BMGs exist with critical cooling rates more than 13 orders of magnitude smaller than those for pure metals. However, there are many other features of interatomic potentials beyond hard-core interactions. How do these other features affect the glass-forming ability of BMGs? We perform molecular dynamics simulations to determine how variations in the softness and non-additivity of the repulsive core and form of the interatomic pair potential at intermediate distances affect the GFA of binary alloys. These variations in the interatomic pair potential allow us to introduce geometric frustration and change the crystal phases that compete with glass formation. We also investigate the effect of tuning the strength of the many-body interactions from zero to the full embedded atom model on the GFA for pure metals. We then employ the full embedded atom model for binary BMGs and show that hard-core interactions play the dominant role in setting the GFA of alloys, while other features of the interatomic potential only change the GFA by one to two orders of magnitude.

cond-mat.mtrl-sci↗
arXiv2015

Magnetic alignment of block copolymer microdomains by intrinsic chain anisotropy

We examine the role of intrinsic chain susceptibility anisotropy in magnetic field directed self-assembly of a block copolymer using \textit{in situ} X-ray scattering. Alignment of a lamellar mesophase is observed on cooling across the disorder-order transition with the resulting orientational order inversely proportional to the cooling rate. We discuss the origin of the susceptibility anisotropy, $Δχ$, that drives alignment, and calculate its magnitude using coarse-grained molecular dynamics to sample conformations of surface-tethered chains, finding $Δχ\approx 2\times10^{-8}$. From field-dependent scattering data we estimate grains of $\approx1.2$ $μ$m are present during alignment. These results demonstrate that intrinsic anisotropy is sufficient to support strong field-induced mesophase alignment and suggest a versatile strategy for field control of orientational order in block copolymers.

cond-mat.soft↗
arXiv2015

Outcome prediction in mathematical models of immune response to infection

Clinicians need to predict patient outcomes with high accuracy as early as possible after disease inception. In this manuscript, we show that patient-to-patient variability sets a fundamental limit on outcome prediction accuracy for a general class of mathematical models for the immune response to infection. However, accuracy can be increased at the expense of delayed prognosis. We investigate several systems of ordinary differential equations (ODEs) that model the host immune response to a pathogen load. Advantages of systems of ODEs for investigating the immune response to infection include the ability to collect data on large numbers of `virtual patients', each with a given set of model parameters, and obtain many time points during the course of the infection. We implement patient-to-patient variability $v$ in the ODE models by randomly selecting the model parameters from Gaussian distributions with variance $v$ that are centered on physiological values. We use logistic regression with one-versus-all classification to predict the discrete steady-state outcomes of the system. We find that the prediction algorithm achieves near $100\%$ accuracy for $v=0$, and the accuracy decreases with increasing $v$ for all ODE models studied. The fact that multiple steady-state outcomes can be obtained for a given initial condition, i.e. the basins of attraction overlap in the space of initial conditions, limits the prediction accuracy for $v>0$. Increasing the elapsed time of the variables used to train and test the classifier, increases the prediction accuracy, while adding explicit external noise to the ODE models decreases the prediction accuracy. Our results quantify the competition between early prognosis and high prediction accuracy that is frequently encountered by clinicians.

q-bio.QM↗
arXiv2015

Shear accelerated crystallization in a supercooled atomic liquid

A bulk metallic glass forming alloy is subjected to shear flow in its supercooled state by compression of a short rod to produce a flat disc. The resulting material exhibits enhanced crystallization kinetics during isothermal annealing as reflected in the decrease of the crystallization time relative to the non-deformed case. The transition from quiescent to shear-accelerated crystallization is linked to strain accumulated during shear flow above a critical shear rate $\dotγ_c\approx 0.3$ s$^{-1}$ which corresponds to Péclet number, $Pe\sim\mathcal{O}(1)$. The observation of shear accelerated crystallization in an atomic system at modest shear rates is uncommon. It is made possible here by the substantial viscosity of the supercooled liquid which increases strongly with temperature in the approach to the glass transition. We may therefore anticipate the encounter of non-trivial shear-related effects during thermoplastic deformation of similar systems.

cond-mat.mtrl-sci↗
arXiv2015

Asymmetric crystallization during cooling and heating in model glass-forming systems

We perform molecular dynamics (MD) simulations of the crystallization process in binary Lennard-Jones systems during heating and cooling to investigate atomic-scale crystallization kinetics in glass-forming materials. For the cooling protocol, we prepared equilibrated liquids above the liquidus temperature $T_l$ and cooled each sample to zero temperature at rate $R_c$. For the heating protocol, we first cooled equilibrated liquids to zero temperature at rate $R_p$ and then heated the samples to temperature $T > T_l$ at rate $R_h$. We measured the critical heating and cooling rates $R_h^*$ and $R_c^*$, below which the systems begin to form a substantial fraction of crystalline clusters during the heating and cooling protocols. We show that $R_h^* > R_c^*$, and that the asymmetry ratio $R_h^*/R_c^*$ includes an intrinsic contribution that increases with the glass-forming ability (GFA) of the system and a preparation-rate dependent contribution that increases strongly as $R_p \rightarrow R_c^*$ from above. We also show that the predictions from classical nucleation theory (CNT) can qualitatively describe the dependence of the asymmetry ratio on the GFA and preparation rate $R_p$ from the MD simulations and results for the asymmetry ratio measured in Zr- and Au-based bulk metallic glasses (BMG). This work emphasizes the need for and benefits of an improved understanding of crystallization processes in BMGs and other glass-forming systems.

cond-mat.soft↗
arXiv2014

The glass-forming ability of model metal-metalloid alloys

Bulk metallic glasses (BMGs) are amorphous alloys with desirable mechanical properties and processing capabilities. To date, the design of new BMGs has largely employed empirical rules and trial-and-error experimental approaches. Ab initio computational methods are currently prohibitively slow to be practically used in searching the vast space of possible atomic combinations for bulk glass formers. Here, we perform molecular dynamics simulations of a coarse-grained, anisotropic potential, which mimics interatomic covalent bonding, to measure the critical cooling rates for metal-metalloid alloys as a function of the atomic size ratio $σ_S/σ_L$ and number fraction $x_S$ of the metalloid species. We show that the regime in the space of $σ_S/σ_L$ and $x_S$ where well-mixed, optimal glass formers occur for patchy and LJ particle mixtures coincides with that for experimentally observed metal-metalloid glass formers. Our simple computational model provides the capability to perform combinatorial searches to identify novel glass-forming alloys.

cond-mat.mtrl-sci↗
arXiv2014

Calibrated Langevin dynamics simulations of intrinsically disordered proteins

We perform extensive coarse-grained (CG) Langevin dynamics simulations of intrinsically disordered proteins (IDPs), which possess fluctuating conformational statistics between that for excluded volume random walks and collapsed globules. Our CG model includes repulsive steric, attractive hydrophobic, and electrostatic interactions between residues and is calibrated to a large collection of single-molecule fluorescence resonance energy transfer data on the inter-residue separations for 36 pairs of residues in five IDPs: $α$-, $β$-, and $γ$-synuclein, the microtubule-associated protein $τ$, and prothymosin $α$. We find that our CG model is able to recapitulate the average inter-residue separations regardless of the choice of the hydrophobicity scale, which shows that our calibrated model can robustly capture the conformational dynamics of IDPs. We then employ our model to study the scaling of the radius of gyration with chemical distance in 11 known IDPs. We identify a strong correlation between the distance to the dividing line between folded proteins and IDPs in the mean charge and hydrophobicity space and the scaling exponent of the radius of gyration with chemical distance along the protein.

q-bio.BM↗
arXiv2014

Can the packing efficiency of binary hard spheres explain the glass-forming ability of bulk metallic glasses?

We perform molecular dynamics simulations to compress binary hard spheres into jammed packings as a function of the compression rate $R$, size ratio $α$, and number fraction $x_S$ of small particles to determine the connection between the glass-forming ability (GFA) and packing efficiency in bulk metallic glasses (BMGs). We define the GFA by measuring the critical compression rate $R_c$, below which jammed hard-sphere packings begin to form "random crystal" structures with defects. We find that for systems with $α\gtrsim 0.8$ that do not de-mix, $R_c$ decreases strongly with $Δϕ_J$, as $R_c \sim \exp(-1/Δϕ_J^2)$, where $Δϕ_J$ is the difference between the average packing fraction of the amorphous packings and random crystal structures at $R_c$. Systems with $α\lesssim 0.8$ partially de-mix, which promotes crystallization, but we still find a strong correlation between $R_c$ and $Δϕ_J$. We show that known metal-metal BMGs occur in the regions of the $α$ and $x_S$ parameter space with the lowest values of $R_c$ for binary hard spheres. Our results emphasize that maximizing GFA in binary systems involves two competing effects: minimizing $α$ to increase packing efficiency, while maximizing $α$ to prevent de-mixing.

cond-mat.mtrl-sci↗
arXiv2014

The statistics of frictional families

We develop a theoretical description for mechanically stable frictional packings in terms of the difference between the total number of contacts required for isostatic packings of frictionless disks and the number of contacts in frictional packings, $m=N_c^0-N_c$. The saddle order $m$ represents the number of unconstrained degrees of freedom that a static packing would possess if friction were removed. Using a novel numerical method that allows us to enumerate disk packings for each $m$, we show that the probability to obtain a packing with saddle order $m$ at a given static friction coefficient $μ$, $P_m(μ)$, can be expressed as a power-series in $μ$. Using this form for $P_m(μ)$, we quantitatively describe the dependence of the average contact number on friction coefficient for static disk packings obtained from direct simulations of the Cundall-Strack model for all $μ$ and $N$.

cond-mat.soft↗
arXiv2014

Quasi-One Dimensional Models for Glassy Dynamics

We describe numerical simulations and analyses of a quasi-one-dimensional (Q1D) model of glassy dynamics. In this model, hard rods undergo Brownian dynamics through a series of narrow channels connected by $J$ intersections. We do not allow the rods to turn at the intersections, and thus there is a single, continuous route through the system. This Q1D model displays caging behavior, collective particle rearrangements, and rapid growth of the structural relaxation time, which are also found in supercooled liquids and glasses. The mean-square displacement $Σ(t)$ for this Q1D model displays several dynamical regimes: 1) short-time diffusion $Σ(t) \sim t$, 2) a plateau in the mean-square displacement caused by caging behavior, 3) single-file diffusion characterized by anomalous scaling $Σ(t) \sim t^{0.5}$ at intermediate times, and 4) a crossover to long-time diffusion $Σ(t) \sim t$ for times $t$ that grow with the complexity of the circuit. We develop a general procedure for determining the structural relaxation time $t_D$, beyond which the system undergoes long-time diffusion, as a function of the packing fraction $ϕ$ and system topology. This procedure involves several steps: 1) define a set of distinct microstates in configuration space of the system, 2) construct a directed network of microstates and transitions between them, 3) identify minimal, closed loops in the network that give rise to structural relaxation, 4) determine the frequencies of `bottleneck' microstates that control the slow dynamics and time required to transition out of them, and 5) use the microstate frequencies and lifetimes to deduce $t_D(ϕ)$. We find that $t_D$ obeys power-law scaling, $t_D\sim (ϕ^* - ϕ)^{-α}$, where both $ϕ^*$ (signaling complete kinetic arrest) and $α>0$ depend on the system topology.

cond-mat.soft↗
arXiv2013

Vibrations of Jammed Disk Packings with Hertzian Interactions

Contact breaking and Hertzian interactions between grains can both give rise to nonlinear vibrational response of static granular packings. We perform molecular dynamics simulations at constant energy in 2D of frictionless bidisperse disks that interact via Hertzian spring potentials as a function of energy and measure directly the vibrational response from the Fourier transform of the velocity autocorrelation function. We compare the measured vibrational response of static packings near jamming onset to that obtained from the eigenvalues of the dynamical matrix to determine the temperature above which the linear response breaks down. We compare packings that interact via single-sided (purely repulsive) and double-sided Hertzian spring interactions to disentangle the effects of the shape of the potential from contact breaking. Our studies show that while Hertzian interactions lead to weak nonlinearities in the vibrational behavior (e.g. the generation of harmonics of the eigenfrequencies of the dynamical matrix), the vibrational response of static packings with Hertzian contact interactions is dominated by contact breaking as found for systems with repulsive linear spring interactions.

cond-mat.soft↗
arXiv2013

Vibrations in jammed solids: Beyond linear response

We propose a `phase diagram' for particulate systems that interact via purely repulsive contact forces, such as granular media and colloidal suspensions. We identify and characterize two distinct classes of behavior as a function of the input kinetic energy per degree of freedom $T_0$ and packing fraction deviation above and below jamming onset $Δϕ=ϕ- ϕ_J$ using numerical simulations of purely repulsive frictionless disks. Iso-coordinated solids (ICS) only occur above jamming for $Δϕ> Δϕ_c(T_0)$; they possess average coordination number equal to the isostatic value ($< z> = z_{\rm iso}$) required for mechanically stable packings. ICS display harmonic vibrational response, where the density of vibrational modes from the Fourier transform of the velocity autocorrelation function is a set of sharp peaks at eigenfrequencies $ω_k^d$ of the dynamical matrix evaluated at $T_0=0$. Hypo-coordinated solids (HCS) occur both above and below jamming onset within the region defined by $Δϕ> Δϕ^*_-(T_0)$, $Δϕ< Δϕ^*_+(T_0)$, and $Δϕ> Δϕ_{cb}(T_0)$. In this region, the network of interparticle contacts fluctuates with $< z> \approx z_{\rm iso}/2$, but cage-breaking particle rearrangements do not occur. The HCS vibrational response is nonharmonic, {\it i.e} the density of vibrational modes $D(ω)$ is not a collection of sharp peaks at $ω_k^d$, and its precise form depends on the measurement method. For $Δϕ> Δϕ_{cb}(T_0)$ and $Δϕ< Δϕ^*_{-}(T_0)$, the system behaves as a hard-particle liquid.

cond-mat.soft↗