arXiv subjects

Phillip L. Geissler

Publications and source records attributed to Phillip L. Geissler.

At least 37 records · Page 2Linked to original sources

arXiv2018

Rare behavior of growth processes via umbrella sampling of trajectories

We compute probability distributions of trajectory observables for reversible and irreversible growth processes. These results reveal a correspondence between reversible and irreversible processes, at particular points in parameter space, in terms of their typical and atypical trajectories. Thus key features of growth processes can be insensitive to the precise form of the rate constants used to generate them, recalling the insensitivity to microscopic details of certain equilibrium behavior. We obtained these results using a sampling method, inspired by the "s-ensemble" large-deviation formalism, that amounts to umbrella sampling in trajectory space. The method is a simple variant of existing approaches, and applies to ensembles of trajectories controlled by the total number of events. It can be used to determine large-deviation rate functions for trajectory observables in or out of equilibrium.

cond-mat.stat-mech↗

arXiv2016

Near-optimal protocols in complex nonequilibrium transformations

The development of sophisticated experimental means to control nanoscale systems has motivated efforts to design driving protocols which minimize the energy dissipated to the environment. Computational models are a crucial tool in this practical challenge. We describe a general method for sampling an ensemble of finite-time, nonequilibrium protocols biased towards a low average dissipation. We show that this scheme can be carried out very efficiently in several limiting cases. As an application, we sample the ensemble of low-dissipation protocols that invert the magnetization of a 2D Ising model and explore how the diversity of the protocols varies in response to constraints on the average dissipation. In this example, we find that there is a large set of protocols with average dissipation close to the optimal value, which we argue is a general phenomenon.

cond-mat.stat-mech↗

arXiv2016

On the microscopic origin and macroscopic implications of lane formation in mixtures of oppositely-driven particles

Colloidal particles of two types, driven in opposite directions, can segregate into lanes [Vissers et al. Soft Matter 7, 2352 (2011)]. This phenomenon can be reproduced by two-dimensional Brownian dynamics simulations of model particles [Dzubiella et al. Phys. Rev. E 65, 021402 (2002)]. Here we use computer simulation to assess the generality of lane formation with respect to variation of particle type and dynamical protocol. We find that laning results from rectification of diffusion on the scale of a particle diameter: oppositely-driven particles must, in the time taken to encounter each other in the direction of the drive, diffuse in the perpendicular direction by about one particle diameter. This geometric constraint implies that the diffusion constant of a particle, in the presence of those of the opposite type, grows approximately linearly with Peclet number, a prediction confirmed by our numerics over a range of model parameters. Such environment-dependent diffusion is statistically similar to an effective interparticle attraction; consistent with this observation, we find that oppositely-driven non-attractive colloids display features characteristic of the simplest model system possessing both interparticle attractions and persistent motion, the driven Ising lattice gas [Katz, Leibowitz, Spohn, J. Stat. Phys. 34, 497 (1984)]. These features include long-ranged correlations in the disordered regime, and a critical regime characterized by a change in slope of the particle current with Peclet number and by fluctuations that grow with system size. By analogy, we suggest that lane formation in the driven colloid system is in the macroscopic limit a phase transition, but that macroscopic phase separation would not occur in finite time upon starting from disordered initial conditions.

cond-mat.stat-mech↗

arXiv2015

Preserving Correlations Between Trajectories for Efficient Path Sampling

Importance sampling of trajectories has proved a uniquely successful strategy for exploring rare dynamical behaviors of complex systems in an unbiased way. Carrying out this sampling, however, requires an ability to propose changes to dynamical pathways that are substantial, yet sufficiently modest to obtain reasonable acceptance rates. Satisfying this requirement becomes very challenging in the case of long trajectories, due to the characteristic divergences of chaotic dynamics. Here we examine schemes for addressing this problem, which engineer correlation between a trial trajectory and its reference path, for instance using artificial forces. Our analysis is facilitated by a modern perspective on Markov Chain Monte Carlo sampling, inspired by non-equilibrium statistical mechanics, which clarifies the types of sampling strategies that can scale to long trajectories. Viewed in this light, the most promising such strategy guides a trial trajectory by manipulating the sequence of random numbers that advance its stochastic time evolution, as done in a handful of existing methods. In cases where this "noise guidance" synchronizes trajectories effectively, as the Glauber dynamics of a two-dimensional Ising model, we show that efficient path sampling can be achieved even for very long trajectories.

cond-mat.stat-mech↗

arXiv2014

Dominance of extreme statistics in a prototype many-body Brownian ratchet

Many forms of cell motility rely on Brownian ratchet mechanisms that involve multiple stochastic processes. We present a computational and theoretical study of the nonequilibrium statistical dynamics of such a many-body ratchet, in the specific form of a growing polymer gel that pushes a diffusing obstacle. We find that oft-neglected correlations among constituent filaments impact steady-state kinetics and significantly deplete the gel's density within molecular distances of its leading edge. These behaviors are captured quantitatively by a self-consistent theory for extreme fluctuations in filaments' spatial distribution.

cond-mat.stat-mech↗

arXiv2014

Efficiency and Large Deviations in Time-Asymmetric Stochastic Heat Engines

In a stochastic heat engine driven by a cyclic non-equilibrium protocol, fluctuations in work and heat give rise to a fluctuating efficiency. Using computer simulations and tools from large deviation theory, we have examined these fluctuations in detail for a model two-state engine. We find in general that the form of efficiency probability distributions is similar to those described by Verley et al. [2014 Nat Comm, 5 4721], in particular featuring a local minimum in the long-time limit. In contrast to the time-symmetric engine protocols studied previously, however, this minimum need not occur at the value characteristic of a reversible Carnot engine. Furthermore, while the local minimum may reside at the global minimum of a large deviation rate function, it does not generally correspond to the least likely efficiency measured over finite time. We introduce a general approximation for the finite-time efficiency distribution, $P(η)$, based on large deviation statistics of work and heat, that remains very accurate even when $P(η)$ deviates significantly from its large deviation form.

cond-mat.stat-mech↗

arXiv2014

Heterogeneity-induced large deviations in activity and (in some cases) entropy production

We solve a simple model that supports a dynamic phase transition and show conditions for the existence of the transition. Using methods of large deviation theory we analytically compute the probability distribution for activity and entropy production rates of the trajectories on a large ring with a single heterogeneous link. The corresponding joint rate function demonstrates two dynamical phases - one localized and the other delocalized, but the marginal rate functions do not always exhibit the underlying transition. Symmetries in dynamic order parameters influence the observation of a transition, such that distributions for certain dynamic order parameters need not reveal an underlying dynamical bistability. Solution of our model system furthermore yields the form of the effective Markov transition matrices that generate dynamics in which the two dynamical phases are at coexistence. We discuss the implications of the transition for the response of bacterial cells to antibiotic treatment, arguing that even simple models of a cell cycle lacking an explicit bistability in configuration space will exhibit a bistability of dynamical phases.

cond-mat.stat-mech↗

arXiv2014

Dynamic phase transitions in simple driven kinetic networks

We analyze the probability distribution for entropy production rates of trajectories evolving on a class of out-of-equilibrium kinetic networks. These networks can serve as simple models for driven dynamical systems, which are of particular importance in biological processes, where energy fluxes typically result in non-equilibrium dynamics. By analyzing the fluctuations in the entropy production, we demonstrate the emergence, in a large system size limit, of a dynamic phase transition between two distinct dynamical regimes.

cond-mat.stat-mech↗

arXiv2013

Patterns without patches: Hierarchical assembly of complex structures from simple building blocks

Nanoparticles with "sticky patches" have long been proposed as building blocks for the self-assembly of complex structures. The synthetic realizability of such patchy particles, however, greatly lags behind predictions of patterns they could form. Using computer simulations, we show that structures of the same genre can be obtained from a solution of simple isotropic spheres, provided control only over their sizes and a small number of binding affinities. In a first step, finite clusters of well-defined structure and composition emerge from natural dynamics with high yield. In effect a kind of patchy particle, these clusters can further assemble into a variety of complex superstructures, including filamentous networks, ordered sheets, and highly porous crystals.

cond-mat.soft↗

arXiv2013

Rare-event trajectory ensemble analysis reveals metastable dynamical phases in lattice proteins

We explore the dynamical large-deviations of a lattice heteropolymer model of a protein by means of path sampling of trajectories. We uncover the existence of non-equilibrium dynamical phase-transitions in ensembles of trajectories between active and inactive dynamical phases, whose nature depends on properties of the interaction potential. When the full heterogeneity of interactions due to the amino-acid sequence is preserved, as in a fully interacting model or in a heterogeneous version of the Gō model where only native interactions are considered, the transition is between the equilibrium native state and a highly native but kinetically trapped state. In contrast, for the homogeneous Gō model, where there is a single native energy and the sequence plays no role, the dynamical transition is a direct consequence of the static bi-stability between unfolded and native states. In the heterogeneous case the native-active and native-inactive states, despite their static similarity, have widely varying dynamical properties, and the transition between them occurs even in lattice proteins whose sequences are designed to make them optimal folders.

cond-mat.soft↗

arXiv2013

Coexistence between fluid and crystalline phases of proteins in photosynthetic membranes

Photosystem II (PSII) and its associated light-harvesting complex II (LHCII) are highly concentrated in the stacked grana regions of photosynthetic thylakoid membranes. Within the membrane, PSII-LHCII supercomplexes can be arranged in disordered packings, ordered arrays, or mixtures thereof. The physical driving forces underlying array formation are unknown, complicating attempts to determine a possible functional role for arrays in regulating light harvesting or energy conversion efficiency. Here we introduce a coarse-grained model of protein interactions in coupled photosynthetic membranes, focusing on just two particle types that feature simple shapes and potential energies motivated by structural studies. Reporting on computer simulations of the model's equilibrium fluctuations, we demonstrate its success in reproducing diverse structural features observed in experiments, including extended PSII-LHCII arrays. Free energy calculations reveal that the appearance of arrays marks a phase transition from the disordered fluid state to a system-spanning crystal, which can easily be arrested by thermodynamic constraints or slow dynamics. The region of fluid-crystal coexistence is broad, encompassing much of the physiologically relevant parameter regime. Our results suggest that grana membranes lie at or near phase coexistence, conferring significant structural and functional flexibility to this densely packed membrane protein system.

cond-mat.soft↗

arXiv2012

Adsorption of solutes at liquid-vapor interfaces: Insights from lattice gas models

The adsorption behavior of ions at liquid-vapor interfaces exhibits several unexpected yet generic features. In particular, energy and entropy are both minimum when the solute resides near the surface, for a variety of ions in a range of polar solvents, contrary to predictions of classical theories. Motivated by this generality, and by the simple physical ingredients implicated by computational studies, we have examined interfacial solvation in highly schematic models, which resolve only coarse fluctuations in solvent density and cohesive energy. Here we show that even such lattice gas models recapitulate surprising thermodynamic trends observed in detailed simulations and experiments. Attention is focused on the case of two dimensions, for which approximate energy and entropy profiles can be calculated analytically. Simulations and theoretical analysis of the lattice gas highlight the role of capillary wave-like fluctuations in mediating adsorption. They further point to ranges of temperature and solute-solvent interaction strength where surface propensity is expected to be strongest.

cond-mat.stat-mech↗

arXiv2012

Metastability in pressure-induced structural transformations of CdSe/ZnS core/shell nanocrystals

The kinetics and thermodynamics of structural transformations under pressure depend strongly on particle size due to the influence of surface free energy. By suitable design of surface structure, composition, and passivation it is possible, in principle, to prepare nanocrystals in structures inaccessible to bulk materials. However, few realizations of such extreme size-dependent behavior exist. Here we show with molecular dynamics computer simulation that in a model of CdSe/ZnS core/shell nanocrystals the core high pressure structure can be made metastable under ambient conditions by tuning the thickness of the shell. In nanocrystals with thick shells, we furthermore observe a wurtzite to NiAs transformation, which does not occur in the pure bulk materials. These phenomena are linked to a fundamental change in the atomistic transformation mechanism from heterogenous nucleation at the surface to homogenous nucleation in the crystal core. Our results suggest a new route towards expanding the range of available nanoscale materials.

cond-mat.mtrl-sci↗

arXiv2012

Transferable Pair Potentials for CdS and ZnS Crystals

A set of interatomic pair potentials is developed for CdS and ZnS crystals. We show that a simple energy function, which has been used to describe the properties of CdSe [J. Chem. Phys. 116, 258 (2002)], can be parametrized to accurately describe the lattice and elastic constants, and phonon dispersion relations of bulk CdS and ZnS in the wurtzite and rocksalt crystal structures. The predicted coexistence pressure of the wurtzite and rocksalt structures, as well as the equation of state are in good agreement with experimental observations. These new pair potentials enable the study of a wide range of processes in bulk and nanocrystalline II-VI semiconductor materials.

cond-mat.mtrl-sci↗

arXiv2011

Consequences of local inter-strand dehybridization for large-amplitude bending fluctuations of double-stranded DNA

The wormlike chain (WLC) model of DNA bending accurately reproduces single-molecule force-extension profiles of long (kilobase) chains. These bending statistics over large scales do not, however, establish a unique microscopic model for elasticity at the 1-10 bp scale, which holds particular interest in biological contexts. Here we examine a class of microscopic models which allow for disruption of base pairing (i.e., a `melt' or `kink', generically an `excitation') and consequently enhanced local flexibility. We first analyze the effect on the excitation free energy of integrating out the spatial degrees of freedom in a wormlike chain. Based on this analysis, we present a formulation of these models that ensures consistency with the well-established thermodynamics of melting in long chains. Using a new method to calculate cyclization statistics of short chains from enhanced-sampling Monte Carlo simulations, we compute J-factors of a meltable wormlike chain (MWLC) over a broad range of chain lengths, including very short molecules (30 bp) that have not yet been explored experimentally. For chains longer than about 120 bp, including most molecules studied to date in the laboratory, we find that melting excitations have little impact on cyclization kinetics. Strong signatures of melting, which might be resolved within typical experimental scatter, emerge only for shorter chains.

cond-mat.stat-mech↗

arXiv2010

Microscopic implications of S-DNA

Recent experiments [J. van Mameren et al. PNAS 106, 18231 (2009)] provide a detailed spatial picture of overstretched DNA, showing that under certain conditions the two strands of the double helix separate at about 65 pN. It was proposed that this observation rules out the existence of an elongated, hybridized form of DNA ('S-DNA'). Here we argue that the S-DNA picture is consistent with the observation of unpeeling during overstretching. We demonstrate that assuming the existence of S-DNA does not imply DNA overstretching to consist of the complete or near-complete conversion of the molecule from B- to S-form. Instead, this assumption implies in general a more complex dynamic coexistence of hybridized and unhybridized forms of DNA. We argue that such coexistence can rationalize several recent experimental observations.

cond-mat.soft↗

arXiv2009

Large-scale simulations of fluctuating biological membranes

We present a simple, and physically motivated, coarse-grained model of a lipid bilayer, suited for micron scale computer simulations. Each ~25 nm^2 patch of bilayer is represented by a spherical particle. Mimicking forces of hydrophobic association, multi-particle interactions suppress the exposure of each sphere's equator to its implicit solvent surroundings. The requirement of high equatorial density stabilizes two-dimensional structures without necessitating crystalline order, allowing us to match both the elasticity and fluidity of natural lipid membranes. We illustrate the model's versatility and realism by characterizing membrane response to a prodding nanorod.

cond-mat.soft↗

arXiv2009

Faster strain fluctuation methods through partial volume updates

Elastic systems that are spatially heterogeneous in their mechanical response pose special challenges for molecular simulations. Standard methods for sampling thermal fluctuations of a system's size and shape proceed through a series of homogeneous deformations, whose magnitudes can be severely restricted by its stiffest parts. Here we present a Monte Carlo algorithm designed to circumvent this difficulty, which can be prohibitive in many systems of modern interest. By deforming randomly selected subvolumes alone, it naturally distributes the amplitude of spontaneous elastic fluctuations according to intrinsic heterogeneity. We describe in detail implementations of such "slice moves" that are consistent with detailed balance. Their practical application is illustrated for a random network of cross-linked polymers.

cond-mat.mtrl-sci↗