Corey S O'Hern

Yale University, New Haven, Connecticut, United States

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Publications (140)313.5 Total impact

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    ABSTRACT: 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 $\dot\gamma_c\approx 0.3$ s$^{-1}$ which corresponds to P\'{e}clet 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.
    07/2014;
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    W. Wendell Smith, Po-Yi Ho, Corey S. O'Hern
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    ABSTRACT: 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: $\alpha$-, $\beta$-, and $\gamma$-synuclein, the microtubule-associated protein $\tau$, and prothymosin $\alpha$. 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.
    07/2014;
  • Alice Qinhua Zhou, Corey S O'Hern, Lynne Regan
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    ABSTRACT: The side-chain dihedral angle distributions of all amino acids have been measured from myriad high-resolution protein crystal structures. However, we do not yet know the dominant interactions that determine these distributions. Here, we explore to what extent the defining features of the side-chain dihedral angle distributions of different amino acids can be captured by a simple physical model. We find that a hard-sphere model for a dipeptide mimetic that includes only steric interactions plus stereochemical constraints is able to recapitulate the key features of the back-bone dependent observed amino acid side-chain dihedral angle distributions of Ser, Cys, Thr, Val, Ile, Leu, Phe, Tyr, and Trp. We find that for certain amino acids, performing the calculations with the amino acid of interest in the central position of a short α-helical segment improves the match between the predicted and observed distributions. We also identify the atomic interactions that give rise to the differences between the predicted distributions for the hard-sphere model of the dipeptide and that of the α-helical segment. Finally, we point out a case where the hard-sphere plus stereochemical constraint model is insufficient to recapitulate the observed side-chain dihedral angle distribution - namely the distribution P(χ3 ) for Met. © Proteins 2014;. © 2014 Wiley Periodicals, Inc.
    Proteins Structure Function and Bioinformatics 06/2014; · 3.34 Impact Factor
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    ABSTRACT: We propose a "phase diagram" for particulate systems with purely repulsive contact forces, such as granular media and colloids. We characterize two classes of behavior as a function of the input kinetic energy per degree of freedom T_{0} and packing fraction deviation from jamming onset Δϕ=ϕ-ϕ_{J} using simulations of frictionless disks. Isocoordinated solids (ICS) exist above jamming; they possess an average contact number equal to the isostatic value z_{iso}. ICS display "strict" harmonic 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. In contrast, hypocoordinated solids (HCS) occur above and below jamming and possess fluctuating networks of interparticle contacts but do not undergo cage-breaking particle rearrangements. The density of vibrational frequencies for the HCS is not a collection of sharp peaks at ω_{k}^{d}, but it does possess a common form over a range of Δϕ and T_{0}.
    Physical review. E, Statistical, nonlinear, and soft matter physics. 06/2014; 89(6-1):062203.
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    ABSTRACT: We perform molecular dynamics simulations to compress binary hard spheres into jammed packings as a function of the compression rate $R$, size ratio $\alpha$, 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 $\alpha \gtrsim 0.8$ that do not de-mix, $R_c$ decreases strongly with $\Delta \phi_J$, as $R_c \sim \exp(-1/\Delta \phi_J^2)$, where $\Delta \phi_J$ is the difference between the average packing fraction of the amorphous packings and random crystal structures at $R_c$. Systems with $\alpha \lesssim 0.8$ partially de-mix, which promotes crystallization, but we still find a strong correlation between $R_c$ and $\Delta \phi_J$. We show that known metal-metal BMGs occur in the regions of the $\alpha$ 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 $\alpha$ to increase packing efficiency, while maximizing $\alpha$ to prevent de-mixing.
    04/2014;
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    ABSTRACT: A fundamental question in protein science is what is the intrinsic propensity for an amino acid to be in an α-helix, β-sheet, or other backbone dihedral angle (Ф-ψ) conformation. This question has been been hotly debated for many years because including all protein crystal structures from the protein database increases the probabilities for α-helical structures, while experiments on small peptides observe that β-sheet-like conformations predominate. We perform molecular dynamics (MD) simulations of a hard-sphere model for Ala dipeptide mimetics that includes steric interactions between non-bonded atoms and bond length and angle constraints with the goal of evaluating the role of steric interactions in determining protein backbone conformational preferences. We find four key results. For the hard-sphere MD simulations, we show that 1) β-sheet structures are roughly three and half times more probable than α-helical structures, 2) transitions between α-helix and β-sheet structures only occur when the backbone bond angle τ (N-Cα-C) is greater than 110°, and 3) the probability distribution of τ for Ala conformations in the ‘bridge’ region of Φ-ϕ space is shifted to larger angles compared to other regions. In contrast, 4) the distributions obtained from Amber and CHARMM MD simulations in the bridge regions are broader and have increased τ compared to those for hard sphere simulations and from high-resolution protein crystal structures. Our results emphasize the importance of hard-sphere interactions and local stereochemical constraints that yield strong correlations between Φ-ϕ conformations and τ.
    Protein Science 04/2014; · 2.74 Impact Factor
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    ABSTRACT: 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 $\mu$, $P_m(\mu)$, can be expressed as a power-series in $\mu$. Using this form for $P_m(\mu)$, 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 $\mu$ and $N$.
    02/2014;
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    Prasanta Pal, Jerzy Blawzdziewicz, Corey S. O'Hern
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    ABSTRACT: 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 $\Sigma(t)$ for this Q1D model displays several dynamical regimes: 1) short-time diffusion $\Sigma(t) \sim t$, 2) a plateau in the mean-square displacement caused by caging behavior, 3) single-file diffusion characterized by anomalous scaling $\Sigma(t) \sim t^{0.5}$ at intermediate times, and 4) a crossover to long-time diffusion $\Sigma(t) \sim t$ 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 $\phi$ 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 $t_D(\phi)$. We find that $t_D$ obeys power-law scaling, $t_D\sim (\phi^* - \phi)^{-\alpha}$, where both $\phi^*$ (signaling complete kinetic arrest) and $\alpha>0$ depend on the system topology.
    01/2014;
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    ABSTRACT: The physical nature of the bacterial cytoplasm is poorly understood even though it determines cytoplasmic dynamics and hence cellular physiology and behavior. Through single-particle tracking of protein filaments, plasmids, storage granules, and foreign particles of different sizes, we find that the bacterial cytoplasm displays properties that are characteristic of glass-forming liquids and changes from liquid-like to solid-like in a component size-dependent fashion. As a result, the motion of cytoplasmic components becomes disproportionally constrained with increasing size. Remarkably, cellular metabolism fluidizes the cytoplasm, allowing larger components to escape their local environment and explore larger regions of the cytoplasm. Consequently, cytoplasmic fluidity and dynamics dramatically change as cells shift between metabolically active and dormant states in response to fluctuating environments. Our findings provide insight into bacterial dormancy and have broad implications to our understanding of bacterial physiology, as the glassy behavior of the cytoplasm impacts all intracellular processes involving large components.
    Cell 12/2013; · 31.96 Impact Factor
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    ABSTRACT: We introduce Iterative Feature Removal (IFR) as an unbiased approach for selecting features with diagnostic capacity from large data sets. The algorithm is based on recently developed tools in machine learning that are driven by sparse feature selection goals. When applied to genomic data, our method is designed to identify genes that can provide deeper insight into complex interactions while remaining directly connected to diagnostic utility. We contrast this approach with the search for a minimal best set of discriminative genes, which can provide only an incomplete picture of the biological complexity. Microarray data sets typically contain far more features (genes) than samples. For this type of data, we demonstrate that there are many equivalently-predictive subsets of genes. We iteratively train a classifier using features identified via a sparse support vector machine. At each iteration, we remove all the features that were previously selected. We found that we could iterate many times before a sustained drop in accuracy occurs, with each iteration removing approximately 30 genes from consideration. The classification accuracy on test data remains essentially flat even as hundreds of top-genes are removed.Our method identifies sets of genes that are highly predictive, even when comprised of genes that individually are not. Through automated and manual analysis of the selected genes, we demonstrate that the selected features expose relevant pathways that other approaches would have missed. Our results challenge the paradigm of using feature selection techniques to design parsimonious classifiers from microarray and similar high-dimensional, small-sample-size data sets. The fact that there are many subsets of genes that work equally well to classify the data provides a strong counter-result to the notion that there is a small number of "top genes" that should be used to build classifiers. In our results, the best classifiers were formed using genes with limited univariate power, thus illustrating that deeper mining of features using multivariate techniques is important.
    BMC Genomics 11/2013; 14(1):832. · 4.40 Impact Factor
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    ABSTRACT: To successfully design new proteins and understand the effects of mutations in natural proteins, we must understand the geometric and physicochemical principles underlying protein structure. The side chains of amino acids in peptides and proteins adopt specific dihedral angle combinations; however, we still do not have a fundamental quantitative understanding of why some side-chain dihedral angle combinations are highly populated and others are not. Here we employ a hard-sphere plus stereochemical constraint model of dipeptide mimetics to enumerate the side-chain dihedral angles of leucine (Leu) and isoleucine (Ile), and identify those conformations that are sterically allowed versus those that are not as a function of the backbone dihedral angles ϕ and ψ. We compare our results with the observed distributions of side-chain dihedral angles in proteins of known structure. With the hard-sphere plus stereochemical constraint model, we obtain agreement between the model predictions and the observed side-chain dihedral angle distributions for Leu and Ile. These results quantify the extent to which local, geometrical constraints determine protein side-chain conformations.
    Biophysical Journal 11/2013; 105(10):2403-2411. · 3.67 Impact Factor
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    ABSTRACT: We perform numerical simulations of repulsive, frictionless athermal disks in two and three spatial dimensions undergoing cyclic quasistatic simple shear to investigate particle-scale reversible motion. We identify three classes of steady-state dynamics as a function of packing fraction ϕ and maximum strain amplitude per cycle γ_{max}. Point-reversible states, where particles do not collide and exactly retrace their intracycle trajectories, occur at low ϕ and γ_{max}. Particles in loop-reversible states undergo numerous collisions and execute complex trajectories but return to their initial positions at the end of each cycle. For sufficiently large ϕ and γ_{max}, systems display irreversible dynamics with nonzero self-diffusion. Loop-reversible dynamics enables the reliable preparation of configurations with specified structural and mechanical properties over a broad range of ϕ.
    Physical Review E 11/2013; 88(5-1):052205. · 2.31 Impact Factor
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    ABSTRACT: Bulk metallic glasses (BMGs) are produced by rapidly thermally quenching supercooled liquid metal alloys below the glass transition temperature at rates much faster than the critical cooling rate Rc below which crystallization occurs. The glass-forming ability of BMGs increases with decreasing Rc, and thus good glass-formers possess small values of Rc. We perform molecular dynamics simulations of binary Lennard-Jones (LJ) mixtures to quantify how key parameters, such as the stoichiometry, particle size difference, attraction strength, and heat of mixing, influence the glass-formability of model BMGs. For binary LJ mixtures, we find that the best glass-forming mixtures possess atomic size ratios (small to large) less than 0.92 and stoichiometries near 50:50 by number. In addition, weaker attractive interactions between the smaller atoms facilitate glass formation, whereas negative heats of mixing (in the experimentally relevant regime) do not change Rc significantly. These results are tempered by the fact that the slowest cooling rates achieved in our simulations correspond to ∼10(11) K/s, which is several orders of magnitude higher than Rc for typical BMGs. Despite this, our studies represent a first step in the development of computational methods for quantitatively predicting glass-formability.
    The Journal of Chemical Physics 09/2013; 139(12):124503. · 3.12 Impact Factor
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    ABSTRACT: Recently a new class of materials emerged with the assembly of DNA-coated phospholipid nanodiscs into columnar BioNanoStacks. Within these stacks, lipid discs are periodically incorporated, resulting into quasi one dimensional superstructures. With each disc surrounded by two recombinant scaffolding proteins, we decided to examine whether the poly-Histidine-tags of these proteins could be utilized to bind additional molecules or particles to these BioNanoStacks. Here we demonstrate that patterning of gold nanoparticles onto these BioNanoStacks is indeed possible. Binding occurs via a nickel-mediated interaction between the nanogolds Nitrilotriacetic acid and the Histidine-tags of the scaffold proteins surrounding the nanodiscs. Using Monte Carlo simulations, we determine that the binding of the nanogold particles to the stacks is not a random event. By comparing the simulation and experimental results, we find that there are preferred binding sites, which affects the binding statistics.
    Langmuir 09/2013; · 4.38 Impact Factor
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    Carl F. Schreck, Corey S. O'Hern, Mark D. Shattuck
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    ABSTRACT: 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.
    Granular Matter 09/2013; 16(2). · 1.50 Impact Factor
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    ABSTRACT: 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 $\Delta \phi=\phi - \phi_J$ using numerical simulations of purely repulsive frictionless disks. Iso-coordinated solids (ICS) only occur above jamming for $\Delta \phi > \Delta \phi_c(T_0)$; 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 $\omega_k^d$ 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 $\Delta \phi > \Delta \phi^*_-(T_0)$, $\Delta \phi < \Delta \phi^*_+(T_0)$, and $\Delta \phi > \Delta \phi_{cb}(T_0)$. 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 $D(\omega)$ is not a collection of sharp peaks at $\omega_k^d$, and its precise form depends on the measurement method. For $\Delta \phi > \Delta \phi_{cb}(T_0)$ and $\Delta \phi < \Delta \phi^*_{-}(T_0)$, the system behaves as a hard-particle liquid.
    07/2013;
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    ABSTRACT: We experimentally investigate the role of sample size on the viscosity of a bulk metallic glass by examining pressure driven flows in nm-scale confinement. A Pt57.5Cu14.7Ni5.3P22.5 metallic glass in the super-cooled liquid state is extruded into isolated cylindrical pores of varying nano-scale dimensions, down to 40 nm. The apparent viscosity of the liquid as a function of sample size is determined from the filling depth by appropriate corrections to the Hagen-Poiseuille equation. We observe a striking, sudden increase of the apparent viscosity for dimensions below approximately 100 nm. Results are discussed in the framework of confinement of collective shear events.
    Applied Physics Letters 06/2013; 102(22). · 3.79 Impact Factor
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    ABSTRACT: Amorphous packings of frictionless, spherical particles are isostatic at jamming onset, with the number of constraints (contacts) equal to the number of degrees of freedom. Their structural and mechanical properties are controlled by the interparticle contact network. In contrast, amorphous packings of frictional particles are typically hyperstatic at jamming onset. We perform extensive numerical simulations in two dimensions of the geometrical asperity (GA) model for static friction to further investigate the role of isostaticity. In the GA model, interparticle forces are obtained by summing up purely repulsive central forces between periodically spaced circular asperities on contacting grains. We compare the packing fraction, contact number, mobilization distribution, and vibrational density of states (in the harmonic approximation) using the GA model to those generated using the Cundall-Strack approach. We find that static packings of frictional disks obtained from the GA model are mechanically stable and isostatic when we consider interactions between asperities on contacting particles. The crossover in the structural and mechanical properties of static packings from frictionless to frictional behavior as a function of the static friction coefficient coincides with a change in the type of interparticle contacts and the disappearance of a peak in the density of vibrational modes for the GA model. These results emphasize that mesoscale features of the model for static friction play an important role in determining the properties of granular packings.
    Physical Review Letters 05/2013; 110(19):198002. · 7.73 Impact Factor
  • Corey S O'Hern, Mark D Shattuck
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    ABSTRACT: By efficiently exploring the huge variety of possible grain shapes, computer algorithms that mimic evolution make possible the design of grains that pack into configurations with the desired mechanical or structural properties.
    Nature Material 04/2013; 12(4):287-8. · 35.75 Impact Factor
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    ABSTRACT: The complex interactions between granular media and flowing fluid play a principal role in shaping landscapes via erosion. Despite a large body of work in granular materials and large scale topographical changes in granular beds due to fluid flow, the detailed physical mechanisms that underlie particle entrainment into a fluid flow from an erodible bed and the coupling between hydrodynamic shear and internal rearrangement remain poorly understood. To address these questions, we perform experimental studies of pulsed shear flow across granular beds. We characterize the fluid flow using particle tracking techniques and monitor changes in the structural properties of the granular packing and contour of the granular bed.
    03/2013;

Publication Stats

1k Citations
313.50 Total Impact Points

Institutions

  • 2003–2014
    • Yale University
      • • Department of Physics
      • • Department of Molecular Biophysics and Biochemistry
      New Haven, Connecticut, United States
  • 2013
    • University of South Florida
      • Department of Physics
      Tampa, FL, United States
  • 2012
    • University of New Haven
      New Haven, Connecticut, United States
    • New Jersey Institute of Technology
      • Department of Mathematical Sciences
      Newark, NJ, United States
  • 2010
    • Areté Associates
      Arlington, Virginia, United States
  • 2007–2009
    • Brandeis University
      • Martin Fisher School of Physics
      Waltham, MA, United States
  • 1999–2003
    • University of California, Los Angeles
      • Department of Chemistry and Biochemistry
      Los Angeles, CA, United States
  • 2002
    • University of Chicago
      • James Franck Institute
      Chicago, IL, United States