arXiv subjects

Kurt Kremer

Publications and source records attributed to Kurt Kremer.

At least 37 records · Page 2Linked to original sources

arXiv2019

Microscopic reweighting for non-equilibrium steady states dynamics

Computer simulations generate trajectories at a single, well-defined thermodynamic state point. Statistical reweighting offers the means to reweight static and dynamical properties to different equilibrium state points by means of analytic relations. We extend these ideas to non-equilibrium steady states by relying on a maximum path entropy formalism subject to physical constraints. Stochastic thermodynamics analytically relates the forward and backward probabilities of any pathway through the external non-conservative force, enabling reweighting both in and out of equilibrium. We avoid the combinatorial explosion of microtrajectories by systematically constructing pathways through Markovian transitions. We further identify a quantity that is invariant to dynamical reweighting, analogous to the density of states in equilibrium reweighting.

physics.comp-ph↗

arXiv2019

Clustering of entanglement points in highly strained polymer melts

Polymer melts undergoing large deformation by uniaxial elongation are studied by molecular dynamics simulations of bead-spring chains in melts. Applying a primitive path analysis to strongly deformed polymer melts, the role of topological constrains in highly entangled polymer melts is investigated and quantified. We show that the over-all, large scale conformations of the primitive paths (PPs) of stretched chains follow affine deformation while the number and the distribution of entanglement points along the PPs do not. Right after deformation, PPs of chains retract in both directions parallel and perpendicular to the elongation. Upon further relaxation we observe a long-lived clustering of entanglement points. Together with the delayed relaxation time this leads to a metastable inhomogeneous distribution of topological constraints in the melts.

cond-mat.soft↗

arXiv2019

Relative Resolution: A Hybrid Formalism for Fluid Mixtures

We show here that molecular resolution is inherently hybrid in terms of relative separation: If molecules are close to each other, they must be characterized by a fine-grained (geometrically detailed) model, yet if molecules are far from each other, they may be described by a coarse-grained (isotropically simplified) model. We notably present an analytical expression for relating the two models by energy conservation. This hybrid framework is correspondingly capable of retrieving the structural and thermal behavior of various multi-component and multi-phase fluids across state space.

cond-mat.soft↗

arXiv2018

ESPResSo++ 2.0: Advanced methods for multiscale molecular simulation

Molecular simulation is a scientific tool dealing with challenges in material science and biology. This is reflected in a permanent development and enhancement of algorithms within scientific simulation packages. Here, we present computational tools for multiscale modeling developed and implemented within the ESPResSo++ package. These include the latest applications of the adaptive resolution scheme, the hydrodynamic interactions through a lattice Boltzmann solvent coupled to particle-based molecular dynamics, the implementation of the hierarchical strategy for equilibrating long-chained polymer melts and a heterogeneous spatial domain decomposition. The software design of ESPResSo++ has kept its highly modular C++ kernel with a Python user interface. Moreover, it was enhanced by automatic scripts parsing configurations from other established packages providing scientists with a rapid setup possibility for their simulations.

cond-mat.soft↗

arXiv2018

Chain retraction in highly entangled stretched polymer melts

We use computer simulations to study the relaxation of strongly deformed highly entangled polymer melts in the non-linear viscoelastic regime, focusing on anisotropic chain conformations after isochoric elongation. The Doi-Edwards tube model and its GLaMM extension, incorporating contour length fluctuation and convective constraint release, predict a retraction of the polymer chain extension in all directions, setting in immediately after deformation. This prediction has been challenged by experiment, simulation, and other theoretical studies, questioning the general validity of the tube concept. For very long chains we observe the initial contraction of the chain extension parallel and perpendicular to the stretching direction. However, the effect is significantly weaker than predicted by the GLaMM model. We also show that the first anisotropic term of an expansion of the 2D scattering function qualitatively agrees to predictions of the GLaMM model, providing an option for direct experimental tests.

cond-mat.soft↗

arXiv2018

Relative Resolution: A Multipole Approximation at Appropriate Distances

Recently, we introduced Relative Resolution as a hybrid formalism for fluid mixtures [1]. The essence of this approach is that it switches molecular resolution in terms or relative separation: While nearest neighbors are characterized by a detailed fine-grained model, other neighbors are characterized by a simplified coarse-grained model. Once the two models are analytically connected with each other via energy conservation, Relative Resolution can capture the structural and thermal behavior of (nonpolar) multi-component and multi-phase systems across state space. The current work is a natural continuation of our original communication [1]. Most importantly, we present the comprehensive mathematics of Relative Resolution, basically casting it as a multipole approximation at appropriate distances; the current set of equations importantly applies for all systems (e.g, polar molecules). Besides, we continue examining the capability of our multiscale approach in molecular simulations, importantly showing that we can successfully retrieve not just the statics but also the dynamics of liquid systems. We finally conclude by discussing how Relative Resolution is the inherent variant of the famous "cell-multipole" approach for molecular simulations.

cond-mat.stat-mech↗

arXiv2018

Hierarchical modeling of polystyrene melts: From soft blobs to atomistic resolution

We demonstrate that hierarchical backmapping strategies incorporating generic blob-based models can equilibrate melts of high-molecular-weight polymers, described with chemically specific, atomistic, models. The central idea behind these strategies, is first to represent polymers by chains of large soft blobs (spheres) and efficiently equilibrate the melt on mesoscopic scale. Then, the degrees of freedom of more detailed models are reinserted step by step. The procedure terminates when the atomistic description is reached. Reinsertions are feasible computationally because the fine-grained melt must be re-equilibrated only locally. To develop the method, we choose a polymer with sufficient complexity. We consider polystyrene (PS), characterized by stereochemistry and bulky side groups. Our backmapping strategy bridges mesoscopic and atomistic scales by incorporating a blob-based, a moderately CG, and a united-atom model of PS. We demonstrate that the generic blob-based model can be parameterized to reproduce the mesoscale properties of a specific polymer -- here PS. The moderately CG model captures stereochemistry. To perform backmapping we improve and adjust several fine-graining techniques. We prove equilibration of backmapped PS melts by comparing their structural and conformational properties with reference data from smaller systems, equilibrated with less efficient methods.

cond-mat.soft↗

arXiv2018

Polymorphism of syndiotactic polystyrene crystals from multiscale simulations

Syndiotactic polystyrene (sPS) exhibits complex polymorphic behavior upon crystallization. Computational modeling of polymer crystallization has remained a challenging task because the relevant processes are slow on the molecular time scale. We report herein a detailed characterization of sPS-crystal polymorphism by means of coarse-grained (CG) and atomistic (AA) modeling. The CG model, parametrized in the melt, shows remarkable transferability properties in the crystalline phase. Not only is the transition temperature in good agreement with atomistic simulations, it stabilizes the main $α$ and $β$ polymorphs, observed experimentally. We compare in detail the propensity of polymorphs at the CG and AA level and discuss finite-size as well as box-geometry effects. All in all, we demontrate the appeal of CG modeling to efficiently characterize polymer-crystal polymorphism at large scale.

cond-mat.soft↗

arXiv2018

Spatially Resolved Thermodynamic Integration: An Efficient Method to Compute Chemical Potentials of Dense Fluids

Many popular methods for the calculation of chemical potentials rely on the insertion of test particles into the target system. In the case of liquids and liquid mixtures, this procedure increases in difficulty upon increasing density or concentration, and the use of sophisticated enhanced sampling techniques becomes inevitable. In this work we propose an alternative strategy, spatially resolved thermodynamic integration, or SPARTIAN for short. Here, molecules are described with atomistic resolution in a simulation subregion, and as ideal gas particles in a larger reservoir. All molecules are free to diffuse between subdomains adapting their resolution on the fly. To enforce a uniform density profile across the simulation box, a single-molecule external potential is computed, applied, and identified with the difference in chemical potential between the two resolutions. Since the reservoir is represented as an ideal gas bath, this difference exactly amounts to the excess chemical potential of the target system. The present approach surpasses the high density/concentration limitation of particle insertion methods because the ideal gas molecules entering the target system region spontaneously adapt to the local environment. The ideal gas representation contributes negligibly to the computational cost of the simulation, thus allowing one to make use of large reservoirs at minimal expenses. The method has been validated by computing excess chemical potentials for pure Lennard-Jones liquids and mixtures, SPC and SPC/E liquid water, and aqueous solutions of sodium chloride. The reported results well reproduce literature data for these systems.

cond-mat.soft↗

arXiv2017

In silico screening of drug-membrane thermodynamics reveals linear relations between bulk partitioning and the potential of mean force

The partitioning of small molecules in cell membranes---a key parameter for pharmaceutical applications---typically relies on experimentally-available bulk partitioning coefficients. Computer simulations provide a structural resolution of the insertion thermodynamics via the potential of mean force, but require significant sampling at the atomistic level. Here, we introduce high-throughput coarse-grained molecular dynamics simulations to screen thermodynamic properties. This application of physics based models in a large-scale study of small molecules establishes linear relationships between partitioning coefficients and key features of the potential of mean force. This allows us to predict the structure of the insertion from bulk experimental measurements for more than 400,000 compounds. The potential of mean force hereby becomes an easily accessible quantity---already recognized for its high predictability of certain properties, e.g., passive permeation. Further, we demonstrate how coarse graining helps reduce the size of chemical space, enabling a hierarchical approach to screening small molecules.

cond-mat.soft↗

arXiv2017

Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes

Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a permanent development of new simulation methods and optimization algorithms. In computational terms, those methods require parallelization schemes that make a productive use of computational resources for each simulation and from its genesis. Here, we introduce the heterogeneous domain decomposition approach which is a combination of an heterogeneity sensitive spatial domain decomposition with an \textit{a priori} rearrangement of subdomain-walls. Within this approach, the theoretical modeling and scaling-laws for the force computation time are proposed and studied as a function of the number of particles and the spatial resolution ratio. We also show the new approach capabilities, by comparing it to both static domain decomposition algorithms and dynamic load balancing schemes. Specifically, two representative molecular systems have been simulated and compared to the heterogeneous domain decomposition proposed in this work. These two systems comprise an adaptive resolution simulation of a biomolecule solvated in water and a phase separated binary Lennard-Jones fluid.

physics.comp-ph↗

arXiv2017

From Classical to Quantum and Back: Hamiltonian Adaptive Resolution Path Integral, Ring Polymer, and Centroid Molecular Dynamics

Path integral-based simulation methodologies play a crucial role for the investigation of nuclear quantum effects by means of computer simulations. However, these techniques are significantly more demanding than corresponding classical simulations. To reduce this numerical effort, we recently proposed a method, based on a rigorous Hamiltonian formulation, which restricts the quantum modeling to a small but relevant spatial region within a larger reservoir where particles are treated classically. In this work, we extend this idea and show how it can be implemented along with state-of-the-art path integral simulation techniques, such as ring polymer and centroid molecular dynamics, which allow the approximate calculation of both quantum statistical and quantum dynamical properties. To this end, we derive a new integration algorithm which also makes use of multiple time-stepping. The scheme is validated via adaptive classical--path-integral simulations of liquid water. Potential applications of the proposed multiresolution method are diverse and include efficient quantum simulations of interfaces as well as complex biomolecular systems such as membranes and proteins.

cond-mat.stat-mech↗

arXiv2017

Efficient potential of mean force calculation from multiscale simulations: solute insertion in a lipid membrane

The determination of potentials of mean force for solute insertion in a membrane by means of all-atom molecular dynamics simulations is often hampered by sampling issues. A multiscale approach to conformational sampling was recently proposed by Bereau and Kremer (2016). It aims at accelerating the sampling of the atomistic conformational space by means of a systematic backmapping of coarse-grained snapshots. In this work, we first analyze the efficiency of this method by comparing its predictions for propanol insertion into a 1,2-Dimyristoyl-sn-glycero-3-phosphocholine membrane (DMPC) against reference atomistic simulations. The method is found to provide accurate results with a gain of one order of magnitude in computational time. We then investigate the role of the coarse-grained representation in affecting the reliability of the method in the case of a 1,2-Dioleoyl-sn-glycero-3-phosphocholine membrane (DOPC). We find that the accuracy of the results is tightly connected to the presence a good configurational overlap between the coarse-grained and atomistic models---a general requirement when developing multiscale simulation methods.

physics.chem-ph↗

arXiv2017

Sequence transferable coarse-grained model of amphiphilic copolymer

Polymer properties are inherently multi-scale in nature, where delicate local interaction details play a key role in describing their global conformational behavior. In this context, deriving coarse-grained (CG) multi-scale models for polymeric liquids is a non-trivial task. Further complexities arise when dealing with copolymer systems with varying microscopic sequences, especially when they are of an amphiphilic nature. In this work, we derive a segment-based generic CG model for amphiphilic copolymers consisting of repeat units of hydrophobic (methylene) and hydrophilic (ethylene oxide) monomers. The system is a simulation analogue of polyacetal copolymers [Samanta et al., Macromolecules 49, 1858 (2016)]. The CG model is found to be transferable over a wide range of copolymer sequences and also to be consistent with existing experimental data.

cond-mat.soft↗

arXiv2017

Small activity differences drive phase separation in active-passive polymer mixtures

Recent theoretical studies found that mixtures of active and passive colloidal particles phase separate but only at very high activity ratio. The high value poses serious obstacles for experimental exploration of this phenomenon. Here we show using simulations that when the active and passive particles are polymers, the critical activity ratio decreases with the polymer length. This not only facilitates the experiments but also has implications on the DNA organization in living cell nuclei. Entropy production can be used as an accurate indicator of this non-equilibrium phase transition.

cond-mat.soft↗

arXiv2017

Detailed analysis of Rouse mode and dynamic scattering function of highly entangled polymer melts in equilibrium

We present large-scale molecular dynamics simulations for a coarse-grained model of polymer melts in equilibrium. From detailed Rouse mode analysis we show that the time-dependent relaxation of the autocorrelation function (ACF) of modes $p$ can be well described by the effective stretched exponential function due to the crossover from Rouse to reptation regime. The ACF is independent of chain sizes $N$ for $N/p<N_e$ ($N_e$ is the entanglement length), and there exists a minimum of the stretching exponent as $N/p \rightarrow N_e$. As $N/p$ increases, we verify the crossover scaling behavior of the effective relaxation time $τ_{{\rm eff},p}$ from the Rouse regime to the reptation regime. We have also provided evidence that the incoherent dynamic scattering function follows the same crossover scaling behavior of the mean square displacement of monomers at the corresponding characteristic time scales. The decay of the coherent dynamic scattering function is slowed down and a plateau develops as chain sizes increase at the intermediate time and wave length scales. The tube diameter extracted from the coherent dynamic scattering function is equivalent to the previous estimate from the mean square displacement of monomers.

cond-mat.soft↗

arXiv2016

A multi-resolution model to capture both global fluctuations of an enzyme and molecular recognition in the ligand-binding site

In multi-resolution simulations, different system components are simultaneously modelled at different levels of resolution, these being smoothly coupled together. In the case of enzyme systems, computationally expensive atomistic detail is needed in the active site to capture the chemistry of substrate binding. Global properties of the rest of the protein also play an essential role, determining the structure and fluctuations of the binding site; however, these can be modelled on a coarser level. Similarly, in the most computationally efficient scheme only the solvent hydrating the active site requires atomistic detail. We present a methodology to couple atomistic and coarse-grained protein models, while solvating the atomistic part of the protein in atomistic water. This allows a free choice of which protein and solvent degrees of freedom to include atomistically, without loss of accuracy in the atomistic description. This multi-resolution methodology can successfully model stable ligand binding, and we further confirm its validity via an exploration of system properties relevant to enzymatic function. In addition to a computational speedup, such an approach can allow the identification of the essential degrees of freedom playing a role in a given process, potentially yielding new insights into biomolecular function.

physics.bio-ph↗

arXiv2016

Equilibration of High Molecular-Weight Polymer Melts: A Hierarchical Strategy

A strategy is developed for generating equilibrated high molecular-weight polymer melts described with microscopic detail by sequentially backmapping coarse-grained (CG) configurations. The microscopic test model is generic but retains features like hard excluded volume interactions and realistic melt densities. The microscopic representation is mapped onto a model of soft spheres with fluctuating size, where each sphere represents a microscopic subchain with $N_{\rm b}$ monomers. By varying $N_{\rm b}$ a hierarchy of CG representations at different resolutions is obtained. Within this hierarchy, CG configurations equilibrated with Monte Carlo at low resolution are sequentially fine-grained into CG melts described with higher resolution. A Molecular Dynamics scheme is employed to slowly introduce the microscopic details into the latter. All backmapping steps involve only local polymer relaxation thus the computational efficiency of the scheme is independent of molecular weight, being just proportional to system size. To demonstrate the robustness of the approach, microscopic configurations containing up to $n=1000$ chains with polymerization degrees $N=2000$ are generated and equilibration is confirmed by monitoring key structural and conformational properties. The extension to much longer chains or branched polymers is straightforward.

cond-mat.soft↗