Mainz Materials Simulation Days 2017
June 12, 2017 - June 14, 2017 CECAM-DE-SMSM Max Planck Institute for Polymer Research Mainz, Germany
Friederike Schmid Institute of Physics, Johannes Gutenberg University, Mainz, Germany
Burkhard Dünweg Max Planck Institute for Polymer Research, Mainz, Germany
Kostas Daoulas Max Planck Institute for Polymer Research, Mainz, Germany
Kurt Kremer Max Planck Institute for Polymer Research, Mainz, Germany
Astrid Chase Institute of Physics, Johannes Gutenberg University, Mainz, Germany
1 Description
Please consult also the special page http://www.mpip-mainz.mpg.de/4874119/MMSD2017 for this event!
The Mainz Materials Simulation Days are by now an established series of biennial meetings organized by the Max Planck Institute for Polymer Research and the University of Mainz in Germany.
As a topic for the 2017 meeting, we have chosen "Hybrid simulations involving particles and field theory", where we have in mind systems with hydrodynamic and/or electrostatic interactions, but also polymer systems simulated by a hybrid algorithm involving chains of particles and a Mean Field background. We hope that bringing these complementary approaches together will result in inspiring new ideas.
2 Program
Day 1 - Monday June 12, 2017
Startup
• 10:00 to 11:00 - Registration
• 11:00 to 11:10 - Welcome
Oral Session I (Maria Lukacova, Rudolf Hilfer)
• 11:10 to 11:50 - Presentation
• 11:50 to 12:10 - Presentation
Lunch
• 12:10 to 13:30 - Lunch
Oral Session II (Marcus Mueller, Stephan Baeurle, Venkat Ganesan)
• 13:30 to 14:10 - Presentation
• 14:10 to 14:50 - Presentation
• 14:50 to 15:30 - Presentation
Poster session I
• 15:30 to 17:00 - Poster Session
Oral session III (Doros Theodorou, Hsiao-Ping Hsu)
• 17:00 to 17:40 - Presentation
• 17:40 to 18:00 - Presentation
Conference Dinner at Bonnheimer Hof, Hackenheim (Bus Transfer)
• 18:30 to 22:00 - Social Dinner
Day 2 - Tuesday June 13, 2017
Oral Session IV (Kirsten Martens, Marco Ellero, Andreas Troester)
• 9:00 to 9:40 - Presentation
• 9:40 to 10:20 - Presentation
• 10:20 to 10:40 - Presentation
Coffee
• 10:40 to 11:10 - Coffee Break
Oral Session V (Robin Ball, Mehmet Sayer)
• 11:10 to 11:50 – Presentation
• 11:50 to 12:10 - Presentation
Lunch
• 12:10 to 13:30 - Lunch
Oral Session VI (Jens Harting, Roland Winkler, Tapan Chandra Adhyapak, Fabian Kössel)
• 13:30 to 14:10 - Presentation
• 14:10 to 14:50 - Presentation
• 14:50 to 15:10 - Presentation
• 15:10 to 15:30 - Presentation
Coffee break
• 15:30 to 16:00 - Coffee Break
Oral Session VII (Monica Olvera de la Cruz, Daniel Vega)
• 16:00 to 16:40 - Presentation
• 16:40 to 17:00 - Presentation
Poster Session II (With Drinks and Snacks)
• 17:00 to 19:00 - Poster Session
Day 3 - Wednesday June 14, 2017
Oral Session VII (Tony Maggs, Christian Holm, Omar Valsson)
• 9:00 to 9:40 - Presentation
• 9:40 to 10:20 - Presentation
• 10:20 to 10:40 - Presentation
Coffee
• 10:40 to 11:10 - Coffee Break
Oral Session IX (Christoph Scherer, Agur Sevink)
• 11:10 to 11:30 – Presentation
• 11:30 to 12:10 - Presentation
Famous Last Words
• 12:10 to 12:30 - Closing Word
Lunch
• 12:30 to 14:00 - Lunch
3 Abstracts Invited Talks
How to bridge large scale differences? Maria Lukacova [1], Burkhard Dünweg [2], Nehzat Emamy [1], Stefanie Stalter [1], Paul Strasser 1], Nikita Tretyakov [2], Peter Virnau [1], Leonid Yelash [1], [1] Institute of Mathematics, University of Mainz; [2] MPI Polymer Research Mainz, Germany
In this contribution we present two examples of modeling multiscale problems such as the polymer- solvent mixtures and colloid-polymer systems. Of course, the most accurate description of such complex soft matter systems would be obtained by the molecular dynamics (MD). However, such microscale model is computationally inefficient if large scale regions in space and time need to be simulated. We present two approaches how to overcome this restriction and obtain practically tractable simulation techniques to bridge macroscopic and microscopic models. First, we present a new reduced-order hybrid multiscale method that is based on the combination of the discontinuous Galerkin method and molecular dynamics simulations, see [1]. We follow here the framework of the heterogeneous multiscale method that makes use of the scale separation into macro and micro- levels. On the macro-level the governing equations of the incompressible flow are the continuity and momentum equations. The equations are solved using a high-order accurate discontinuous Galerkin method. The missing information on the macro-level is represented by the unknown stress tensor that is evaluated by means of the molecular dynamics simulations on the micro-level. The data obtained from the MD simulations underlie relatively large stochastic errors that can be controlled by means of the least-square approximation. Moreover, in order to reduce a large number of computationally expensive MD runs we use the reduced order approach. We split the computations into an off-line phase of expensive training and an on-line phase of fast multiple queries. In the training phase we use the Greedy sampling algorithm as a model reduction technique to replace the unknown nonlinear stress-strain function by a reliable low-dimensional approximation. Numerical experiments confirm the robustness of our newly developed hybrid MD- dG method. In the second part of our talk we present a new second order energy dissipative finite volume-finite difference scheme to treat macroscopic equations aiming at the modeling of the dynamics of complex polymer-solvent mixtures. This model consists of the Cahn–Hilliard equation for diffuse interface phase fields and the Oldroyd-B equations for the hydrodynamics of the polymeric mixture, cf. [2]. A complementary approach to study the same physical system is realized by simulations of a microscopic model based on a hybrid Lattice Boltzmann-MD scheme. These latter simulations provide initial conditions for the numerical solution of the macroscopic equations. Our ultimate goal is the systematic coarse-graining of simulation models by means of optimal control of well-chosen observables, such as structure factors. The present research has been supported by the German Science Foundation under the grant TRR 146 “Multiscale Simulation Methods for Soft Matter Systems.”
[1] N. Emamy, M. Lukacova-Medvidova, S. Stalter, P. Virnau, and L. Yelash Reduced-order hybrid multiscale method combining the Molecular Dynamics and the Discontinuous-Galerkin method, 2017, submitted. [2] M. Lukacova-Medvidova, B. Dünweg, P. Strasser, and N. Tretyakov: Energy-stable numerical schemes for multiscale simulations of polymer-solvent mixtures, to appear in Mathematical Analysis of Continuum Mechanics and Industrial Applications II, Proceedings of the International Conference CoMFoS16, Springer Singapore, 2017.
Process directed self-assembly of copolymers Marcus Müller [1] [1] Georg-August University, Göttingen, Germany
Process-directed self-assembly of block copolymers refers to rapid thermodynamic processes that reproducibly direct the kinetics of structure formation from a starting, unstable state into a selected, metastable mesostructure. We investigate the kinetics of self-assembly of linear block copolymers after different rapid changes of thermodynamic control parameters (e.g., photochemical transformations [1], stretching [2], or pressure changes [3]). These thermodynamic processes convert an initial, equilibrium mesophase of the copolymer material into a well-defined but unstable, starting state. The spontaneous structure formation that ensues from this unstable state becomes trapped in a metastable mesostructure, and we systematically explore, which metastable mesostructures can be fabricated. Strategies and challenges for studying process-directed self- assembly by particle-based simulations and self-consistent field theory are discussed and the role of non-equilibrium chain conformations and the diffusive dynamics is highlighted.
[1] Process-accessible states of copolymers D.W. Sun and M. Müller, Phys. Rev. Lett. 118, 067801 (2017) [2] Alignment of copolymer morphology by planar step elongation during spinodal self-assembly M. Müller and J. Tang, Phys. Rev. Lett. 115, 228301 (2015) [3] Directing the self-assembly of block copolymers into a metastable complex network phase via a deep and rapid quench M. Müller and D.W. Sun, Phys. Rev. Lett. 111, 267801 (2013)
Exploring the Performance Enhancement Potential of the Tapering Technology for Blockcopolymer Solar Cells using a Multiscale Solar-cell Algorithm Stephan Baeurle [1], Anton Pershin [1], Sergii Donets [1] [1] Institute of Physical and Theoretical Chemistry, University of Regensburg, D-93040 Regensburg, Germany
Tapered block copolymers offer an exciting opportunity to tailor the interfacial region between different components while conserving the phase-separated mesoscale structure. In this presentation, we explore their usefulness for optimizing the photovoltaic performance of polymer bulk heterojunctions. This is achieved by applying a recently developed multiscale solar-cell algorithm [1,2,3], to investigate the effect of random tapering at the chemical junctions between the electron-donor- (D) and electron-acceptor- (A) blocks on the photovoltaic properties of various lamellar-like polyfluorene-based block-copolymer systems. Our simulation results [2] reveal that introducing a tapered middle block with optimal length leads to a significant increase of the exciton dissociation efficiency and deteriorates the charge transport efficiency only moderately. This results in a gain of the internal quantum efficiency from 25 up to 39 % by increasing the thickness of the active layer of the solar cell from 10 up to 50 nm in direction to the DA interface.
1] A. Pershin, S. Donets, S.A. Baeurle, Polymer 55 3736 (2014). [2] A. Pershin, S. Donets, S.A. Baeurle, Polymer 55 1507 (2014). [3] S. Donets, A. Pershin, S.A. Baeurle, Org. Electron. 22 216 (2015).
Interactions and Complexation in Polyelectrolyte-Nanoparticle/Protein Systems Venkat Ganesan [1], Rituparna Samantha [1], Victor Pryamitsyn [1], Gunja Pandav [1] [1] The University of Texas at Austin, USA
Polyelectrolyte (PE)-protein and PE-particle mixtures form an important class of systems in which their phase behavior and complexation characteristics play a crucial role in influencing their properties. Despite the practical importance of PE-particle mixtures, the parameters governing the interactions and their phase behavior characteristics have had much less theoretical work compared to their neutral counterparts. Recently, we have developed two pronged approach which allows us to study the effective interactions and the phase behavior in mixtures of charged nanoparticles (CNP) and polyelectrolytes (PE). On the one hand, we have adapted polymer self- consistent field theory approach to study the hierarchy of the two-, three- and multi-body interactions between CNP's. We have found that for the strong PE's and in the absence of polarization interactions, the CNP-CNP interactions are essentially pairwise and involve an interplay of depletion attraction and electrostatic repulsions. To study the phase behavior of such systems, we have adapted the single chain in mean-field simulation approach to effect a hybrid, multibody simulation of the PE-CNP systems, and have extended it to accommodate the effects arising from dielectric inhomogeneities. Using such an approach, we study the phase behavior and complexation characteristics in a variety of systems.
Brownian Dynamics/kinetic Monte Carlo Strategy for the Linear and Nonlinear Viscoelastic Properties of Polymer Melts Doros Theodorou [1], Aristotelis Sgouros [1], Georgios G. Vogiatzis [1], [1]Grigorios Megariotis [1] National Technical University of Athens, Athens, Greece
Atomistic simulations have been useful for predicting the viscoelastic properties of polymers but face great difficulties in accessing the dynamics of dense, well entangled long-chain melts with relaxation times longer than μs. A plethora of coarse-grained models have been developed to address longer time scales. Here we present a mesoscopic, mixed particle- and field-based Brownian Dynamics/kinetic Monte Carlo methodology for the simulation of entangled polymer melts. Our work differs from earlier efforts in the field in that it derives the effective interactions and parameters invoked at the mesoscopic level from detailed atomistic simulations. The motion of polymeric beads, consisting of several Kuhn segments, is dictated by a Helmholtz energy function incorporating bonded, slip-spring, and nonbonded interaction contributions. Bonded contributions are expressed as sums of stretching and bending potentials of mean force extracted from detailed molecular dynamics (MD) simulations of shorter-chain melts. The Helmholtz energy of nonbonded interactions is derived from an equation of state (here the Sanchez-Lacombe) and is computed as a functional of the local density by passing an orthogonal grid through the simulation box [1]. The entanglement effect is introduced by the slip-springs [2], whose terminal positions are altered through a kinetic Monte Carlo hopping scheme, with rate-controlled creation/destruction processes at chain ends. The rate constants are consistent with the Helmholtz energy function employed and satisfy microscopic reversibility at equilibrium. We apply this methodology to melts of cis-1,4 polyisoprene of molar masses 21 to 120 kg/mol and linear polyethylene of chain lengths C260 to C2080. Estimates of the melt compressibility, the chain dimensions, the chain self-diffusivity, the longest relaxation time, the stress relaxation modulus, the zero-shear viscosity, the storage and loss moduli from ms-long equilibrium BD/kMC simulations are in excellent agreement with MD results for the shorter-chain melts and with experiment. The BD/kMC scheme is extended to simulate Couette flow using Lees-Edwards periodic boundary conditions over a range of Weissenberg numbers (Wi) from 10-3 to 105. Predictions for the shear viscosity as a function of shear rate, the first and second normal stress difference coefficients, the startup shear stress, as well as for changes in chain conformation and entangled structure with increasing Wi are in favorable agreement with experimental and atomistic simulation evidence. A strategy is introduced for incorporating elementary events of adsorption/desorption of beads onto solid surfaces with rate constants extracted from detailed atomistic simulations, to facilitate the study of interfacial flow phenomena.
[1] G.G. Vogiatzis, G. Megariotis, D.N. Theodorou, Macromolecules DOI: 10.1021/acs.macromol.6b01705 (2017) [2] V.C. Chappa, D.C. Morse, A. Zippelius, M. Müller, Phys. Rev. Lett. 109 148302 (2012).
Out-of-equilibrium phase transitions in sheared disordered systems in a multi-scale approach Kirsten Martens [1] [1] Université Grenoble Alpes & CNRS, France
In this talk I will discuss approaches on different scales, such as molecular dynamic simulations of model systems, lattice models and mean-field descriptions for the so-called yielding transition and the non-linear rheology of driven yield-stress materials. Despite the fact that the mesocopic models require some phenomenological ingredients, notably the detailed local yielding rules, they have been shown to match several aspects of the mechanical response very well, such as avalanche statistics, mechanical noise descriptions and rheological features, like for example shear banding and creep dynamics. Further the development of a mesoscopic approach provides an ideal tool to test basic assumptions for different flow phenomena and can serve as a bridge to large scale descriptions of the complex yielding dynamics.
[1] Non-linear rheology in a model biological tissue, Daniel A. Matoz-Fernandez, Elisabeth Agoritsas, Jean- Louis Barrat, Eric Bertin and Kirsten Martens, Phys. Rev. Lett. 118, 158105 (2017). [2] Driving rate dependence of avalanche statistics and shapes at the yielding transition, C. Liu, E.E. Ferrero, F. Puosi, J.-L. Barrat and K. Martens, Phys. Rev. Lett. 116, 065501 (2016). [3] Probing relevant ingredients in mean-field approaches for the athermal rheology of yield stress materials, F. Puosi, J. Olivier and K. Martens, Soft Matter 11, 7639 (2015). [4] Rheology of athermal solids: Revisiting simplified scenarios and the concept of mechanical noise temperature, A. Nicolas, K. Martens and J.-L. Barrat , EPL 107, 44003 (2014). [5] Spontaneous formation of permanent shear bands in a mesoscopic model of flowing disordered matter, K. Martens, L. Bocquet, J.-L. Barrat, Soft Matter, 8 (15), 4197 (2012).
Towards modeling and simulation of dense particle suspension with non- Newtonian matrices Marco Ellero [1] [1] Swansea University
Particulate suspensions are ubiquitous in nature and industrial applications, and the understanding of their flow properties represents therefore a challenging technical problem. Although the dilute and semi-dilute rheological behaviors of suspension with a simple Newtonian matrix are well understood, when the solid concentration increases towards the maximum packing fraction several new issues arise. In very dense systems, particles under flow can get very close to each other, entering the so-called lubrication regime [1]. From a computational perspective, reproducing correctly the lubrication interaction between two particles in a very thin separation gap is a very challenging task due to the singular character of the force. Issues of stability and accuracy in the lubrication problem has been recently solved by means of a novel and general semi-implicit splitting strategy which allows to integrate efficiently the particle equations of motion and speed-up the simulations significantly [2]. Another challenging fundamental aspect is represented by the effect of the non-Newtonian properties of the matrix. For very dense systems the choice of the lubrication model is critical. In this talk we will discuss novel models of matrix viscoelasticity, as well as lubrication models designed for some dense particulate systems. In particular we will focus on weak shear-thinning solvent media [3], pseudo-yield stress fluids [4] and possible extensions to discontinuous shear-thickening media [5]. Some comparisons for the rheology of these systems with experimental data will be also provided [6,7]
[1] A. Vazquez-Quesada, M. Ellero, “Rheology and microstructure of non-colloidal suspensions under shear studied with Smoothed Particle Hydrodynamics”, J. Non-Newt. Fluid Mech, 233, 37-47 (2016). [2] X. Bian, M Ellero, “A splitting integration scheme for the SPH simulation of concentrated particle suspensions”, Computer Physics Communications 185 (1), 53-62 (2014). [3] A. Vazquez-Quesada, R.I. Tanner, M. Ellero, “Shear Thinning of Noncolloidal Suspensions”,Phys. Rev. Lett, 117 (10), 108001 (2016). [4] A. Vazquez-Quesada, M. Ellero , “Analytical solution for the lubrication force between two spheres in a bi- viscous fluid “, Physics of Fluids 28 (7), 073101 (2016). [5] A. Vazquez-Quesada, M. Ellero, “Interparticle lubrication interaction model in discontinuous shear- thickening media“, in preparation (2017). [6] Mahmud, A., S. Dai, A. Vazquez-Quesada, Ellero, and R. Tanner" Investigating the Causes of Shear- Thinning in Non-Colloidal Suspensions: simulations and experiments. J. Non-Newtonian Fluid Mechanics, under review (2017). [7] A. Vazquez-Quesada, M. Ellero , “Rheology of non-colloidal suspensions with viscoelastic matrices“, in preparation (2017).
Wavelet Monte Carlo dynamics: a new algorithm for simulating the hydrodynamics of if interacting Brownian Robin Ball [1], Oliver Dyer [2] [1] University of Warwick, Coventry, UK , [2] University of Warwick, Coventry, UK
We present a new algorithm for the Brownian dynamics of soft matter systems which evolves time by spatially correlated Monte Carlo moves. We show that using vector wavelets as its basic moves reproduces hydrodynamics in the low Reynolds number regime with velocities correlated according to the Oseen tensor. When small moves are removed, the correlations closely approximate the Rotne-Prager tensor. We also include plane wave moves to provide the longest range correlations, adaptable to both infinite and periodic systems.[1] The computational cost of the algorithm scales with the number of particles N as N ln N in homogeneous systems and as N in dilute systems. In comparison to established lattice Boltzmann and Brownian dynamics algorithms, we show that the wavelet method is the clear winner in dilute conditions, and is still competitive with lattice Boltzmann results [2,3] up to volume fractions of several percent. We demonstrate the power of the new method by addressing the delicate difference [4,5] between short and long time centre of mass diffusion for polymer coils up to N=50.
[1] O.T. Dyer and R.C. Ball, J. Chem. Phys. 147 124111 (2017). [2] T. T. Pham, U. D. Schiller, J. R. Prakash and B. Dünweg, J. Chem. Phys. 131 164114 (2009). [3] A. Jain, P. Sunthar, B. Dünweg and J. R. Prakash, Phys. Rev. E 85, 066703 (2012). [4] M. Fixman, J Chem Phys 42 3831 (1965). [5] B. Liu and B. Dünweg, J. Chem. Phys. 118 8061 (2003).
Separation and assembly of colloidal particles by capillary, magnetic and electrostatics forces Jens Harting [1,2] [1] Forschungszentrum Jülich, Helmholtz Institute Erlangen-Nürnberg for Renewable Energy, Fürther Str. 248, 90429 Nürnberg, Germany, [2] Department of Applied Physics, Eindhoven University of Technology, Postbus 513, 5600MB Eindhoven, The Netherlands
Colloidal particles are known to be very efficient stabilizers for fluid interfaces with applications in the food and cosmetics industry, enhanced oil recovery, drug delivery or waste water management. Capillary interactions between particles with different shape, contact angle on the particle surface, or particle-particle interactions are also promising candidates to self-assemble complex structures for the production of new soft materials or applications in the printing and coating industries. We present computer simulations based on a hybrid lattice Boltzmann and molecular dynamics method [1] and demonstrate the impact of the particle shape and its wettability on the detachment energy of acolloidal particle [2] and demonstrate new ways to self-assemble complex structures by means of capillary interactions and external magnetic fields to steer the movement of ellipsoidal particles [3,4].We then introduce spherical magnetic Janus particles with a hydrophobic and a hydrophilic side and demonstrate that their capillary interactions can be tuned by a well-controlled external magnetic field[5,6]. At last, we introduce a new algorithm to simulate electrokinetic effects in multiphase flows and colloidal suspensions and demonstrate its ability with several benchmark examples.
[1] F. Jansen, J. Harting, “ From Bijels to Pickering emulsions: a lattice Boltzmann study” , Physical Review E 83, 046707 (2011) [2] G. B. Davies, T. Krüger, P. V. Coveney, J. Harting, “ Detachment energies of spheroidal particles from fluid-fluid interfaces” , Journal of Chemical Physics 141, 154902 (2014) [3] G. B. Davies, T. Krüger, P. V. Coveney, J. Harting, F. Bresme, “ Interface deformations affect the orientation transition of magnetic ellipsoidal particles adsorbed at fluid-fluid interfaces” , Soft Matter 10, 6742 (2014) [4] G. B. Davies, T. Krüger, P. V. Coveney, J. Harting, F. Bresme, “ Assembling ellipsoidal particles at fluid interfaces using switchable dipolar capillary interactions” , Advanced Materials 26, 6715 (2014) [5] Q. Xie, G. B. Davies, F. Günther, J. Harting, “ Tunable dipolar capillary deformations for magnetic Janus particles at fluid-fluid interfaces” , Soft Matter 11, 3581 (2015) [6] Q. Xie, G. B. Davies, J. Harting, “ Controlled capillary assembly of magnetic Janus particles at fluid-fluid interfaces” , Soft Matter 12, 6566 (2016)
Hydrodynamics in adaptive resolution particle simulations: Multiparticle collision dynamics Roland G. Winkler [1] [1] Forschungszentrum Jülich, Germany
Multiparticle collision dynamics (MPC), a particle-based mesoscale simulation technique for fluids, has been developed into one of the major simulation techniques for complex fluids during the last decade. MPC captures thermal fluctuations and is easily coupled with, e.g., molecular dynamics simulations for embedded objects [1,2]. We have analyzed its hydrodynamic properties [3] and investigated the velocity correlation functions of embedded polymers [4]. In the context of adaptive resolution particle simulations, we investigated the extent to which hydrodynamic properties are maintained, when an atomistic description of a particle dynamics - based on molecular dynamics simulations (MD) - is coupled with a mesoscopic description of the fluid based on the MPC method – operating via stochastic interactions between particles [5]. The volumina containing particles of atomistic and mesoscopic nature are coupled via a transition region, where the nature of particles is changed gradually. This takes into account that (i) there are different types of interactions between MD particles and MPC particles and their combination, (ii) the time steps of the MPC and MD dynamics are different, (iii) the atomistic and mesoscopic thermodynamic properties are different. Our simulation studies, combining Lennard– Jones particles as model system for an atomistic and MPC for the coarse-grained fluid, show that a stable system can be established with a constant fluid density all-over the system and correct hydrodynamics. However, not all thermodynamic properties can be maintained simultaneously in the various parts of the system.
[1] G. Gompper, T. Ihle, D. M. Kroll, R. G. Winkler, Adv. Polym. Sci. 221, 1 (2009) [2] R. Kapral, Adv. Chem. Phys. 140, 89 (2008) [3] C.-C. Huang, G. Gompper, R. G. Winkler, Phys. Rev. E 86, 056711 (2012) [4] C. C. Huang, G. Gompper, R. G. Winkler, J. Chem. Phys. 138, 144902 (2013) [5] U. Alekseeva, R. G. Winkler, G. Sutmann, J. Comp. Phys. 314, 14 (2016)
Magnetoelastic Polymers and Membranes Monica Olvera de la Cruz [1] [1] Nothwestern University
Paramagnetic materials hold tremendous potential for precision control of matter due to their tunable interactions in dynamic magnetic fields. Magnetic filaments and membranes can be synthesized by joining superparamagnetic beads with linkers, giving rise to interesting phenomena due to the combinations of their elastic and magnetic properties, which have found diverse applications, such as actuators and swimmers. Flexible superparamagnetic filaments under the influence of processing magnetic fields are studied here using simulations and a continuum approximation analysis. We find that individual filaments can be made to exert controllable tensile forces along the precession axis. These forces are exploited for microscopic actuation. In bulk, the precession frequency affects filament aggregation and conformation by changing the net torques on the filament ends. Using a time-dependent precession angle allows considerable freedom in choosing properties for filament aggregates. Open and closed membranes composed of linked paramagnetic beads are also studied via analytical and numerical methods. We characterize these shapes in terms of the area and material parameters of the membrane, as well as of the strength and precession angle of the magnetic field. In particular, we show how depending on the precession angle open membranes may form either rippled or helicoidal surfaces, whereas closed membranes may elongate or flatten. These membranes might be suitable for actuation and for constructing devices with controllable conformational changes such as artificial muscles.
Long-ranged interactions and local algorithms Anthony C. Maggs [1] [1] CNRS, ESPCI, PSL Research University
Maxwell's equations are a local dynamical system that generate an effective long-ranged interaction, described by Coulomb's law. Inspired by this observation we construct other dynamical systems that can be used to simulate charged media, including a purely local Monte Carlo algorithm. We will also emphasize the use of Legendre transforms to construct new, convex free energy functionals that can be used in the simulation of electrolytes.
[1] A minimizing principle for the Poisson-Boltzmann equation, A. C. Maggs 2012 EPL 98 16012. [2] Long-ranged electrostatics from local algorithms. Soft Matter, 2011, 7, 3260. Joerg Rottler, A.C. Maggs.
Influence of the permittivity gradient on static and dynamic properties of charged macromolecules Christian Holm[1] [1] University Stuttgart, Stuttgart, Germany
Dissolved ions can alter the local permittivity of water, nevertheless most theories and simulations ignore this fact. We present a novel algorithm for treating spatial and temporal variations in the permittivity, and show several examples where this leads to large qualitative and quantitative differences. A dynamic example is the equivalent conductivity of a salt-free polyelectrolyte solution. Our new approach quantitatively reproduces experimental results unlike simulations with a constant permittivity that even qualitatively fail to describe the data. We can relate this success to a change in the ion distribution close to the polymer due to the built-up of a permittivity gradient.
[1] F. Fahrenberger, O.A. Hickey, J. Smiatek, C. Holm, „The influence of charged-induced variations in the local permittivity on the static and dynamic properties of polyelectrolyte solutions“. J. Chem. Phys. 143, 243140, (2015). [2] F. Fahrenberger, O.A. Hickey, J. Smiatek, C. Holm, „Importance of Varying Permittivity on the Conductivity of Polyelectrolyte Solutions“, Phys. Rev. Lett.115, 118301 (2015). [3] F. Fahrenberger, C. Holm, „Computing the Coulomb interaction in inhomogeneous dielectric media via a local electrostatics lattice algorithm“ Phys. Rev. E 90, 063304, (2014). [4] F. Fahrenberger, Z. Xu, C. Holm, „Simulation of electric double layers around charged colloids in aqueous solution of variable permittivity“, J. Chem. Phys. 141 064902 (2014)
Reinserting Collisions in Mean Field Hybrid Methodology Agur Sevink [1] [1] Leiden University
Structure at a variety of length scales is known to contribute to the function that membranes play as a permeable, responsive and functionally active barrier in nature. In contrast, most of the current computational approaches suited for simulating membranes are restricted in terms of resolution, either at the lower - molecular - or the higher - macroscopic - end of the scale. To capture membrane related phenomena by computational modelling, and to better quantify the molecular mechanisms that underlie the emergent behavior that is experimentally observable, computational approaches should be developed that account, at least to some degree, for both basic length scales simultaneously, either by selective coarsening in existing molecular treatments or by introducing molecular detail in existing coarser treatments. One of the approaches aimed at efficiently mixing continuum and discrete representations, MD-SCF of Milano and Kawakatsu,[1] starts from the discrete (particle) representation of coarse-grained molecular dynamics (CGMD), with bonded interactions provided by appropriately chosen force fields, and replaces the forces due to ‘hard’ non-bonded interactions by those derived from much ‘softer’ interactions at the continuum level, i.e. the mean-field chemical potentials of self-consistent field theory (SCF), after projecting particles to their concentration fields. Most of their validation work has employed CGMD Martini force fields [2] for the bonded interactions, which has the advantage that many parameters for membrane components are readily available. Owing to this treatment of non-bonded interactions, which does not require a neighbor list and enables efficient parallelization,[3] the computational performance is much improved compared to Martini CGMD, while it does not appear to affect the structural properties of the simulated membranes.[4] It should be noted, however, that introducing ‘soft’ non-bonded interactions affects the usual transfer of momentum in CGMD, owing to the lack of particle collisions at the continuum level. Recently, we proposed a way to reinsert collisions by coupling Newton’s equations of motion of MD-SCF (streaming step) to the collision step of Multiparticle Collision Dynamics (MPCD), rendering a hybrid MD-SCF/MPCD scheme that retains the attractive efficiency of MD-SCF. Although the scheme is reminiscent of the MD-MPCD hybrid of Kapral, [5,6] it differs in the treatment of the solvent, which is idealized in MD-MPCD, whereas solvent compressibility can efficiently be tuned via the SCF chemical potential in MD-SCF. In this presentation, we will discuss properties of this new approach and show results of a few applications.
[1] G. Milano and T. Kawakatsu, J. Chem. Phys. 130, 214106 (2009) [2] S. J. Marrink, H. J. Risselada, S. Yefimov, D. P. Tieleman, A. H. de Vries, J. Phys. Chem. B 111, 7812 (2007) [3] Y. Zhao, A. De Nicola,T. Kawakatsu, G. Milano, J. Comp. Chem. 33, 868 (2012) [4] A. De Nicola, Y. Zhao, T. Kawakatsu, D. Roccatano, G. Milano, J. Chem. Theor. Comp. 7, 2947 (2011) [5] R. Kapral, Adv. Chem. Phys. 140, 89 (2008) [6] G. Gompper, T. Ihle, D.M. Kroll, R.G. Winkler, Adv. Polym. Sci. 221, 1 (2009)
4 Abstracts Contributed Talks
Numerical simulation of hydrodynamic field theories with hysteresis for two phase flow in porous media Rudolf Hilfer [1] [1] University of Stuttgart, Stuttgart, Germany
Hysteresis in relative permeabilities is shown to allow propagation of nonmonotone saturation profiles within the well-studied nonlinear field theory for two-phase flow in porous media [1]. Nonmonotone saturation profiles are commonly referred to as saturation overshoot. The phenomenon of saturation overshoot depends sensitively on the constitutive parameters, on initial conditions, and on boundary conditions. Two hysteresis models are discussed and compared. The shape of overshoot solutions can change as a function of time or remain fixed and time independent. Traveling-wave-like overshoot profiles of fixed width exist in experimentally accessible regions of parameter space. They are compared quantitatively against experiment.
[1] R. Steinle and R. Hilfer, Phys.Rev.E vol.95, 043112 (2017)
Linear and Non-linear Viscoelasticity of Polymer Melts: Primitive Path Analysis Hsiao-Ping Hsu [1], Kurt Kremer [1] [1] Max Planck Institute for Polymer Research, Mainz, Germany
Polymer melt dynamics is strongly affected by entanglement effects due to topological constraints between chains both in the linear and non-linear viscoelastic regime. Starting from fully equilibrated and highly entangled bead-spring chains in melts [1,2,3], we deform these melts by isochoric elongation with fixed strain rate. The strain rate is chosen to be fast compared to the Rouse relaxation time of a whole chain but slow compared to the local relaxation time of an entanglement length of unperturbed chains. Stress relaxation is studied in the linear and non-linear viscoelastic regime and related to results of a primitive path analysis (PPA) [4]. Through PPA we show that the entanglement points are identified quantitatively according to the curvature in the primitive paths of chains, and the distribution of entanglement points of polymer melts becomes inhomogeneous. We have also observed that the tension forces both along the original paths and along primitive paths in the stretching direction follow the same pattern. Finally, we clarify that the entanglement length of deformed melts in the non-linear viscoelastic regime, as determined by PPA, is different from that of unperturbed melts [5].
[1] H.-P. Hsu and K. Kremer, J. Chem. Phys. 144 154907 (2016) [2] L. A. Moreira, G. Zhang, F. M üller, T. Stuehn, and K. kremer, Macromol. Theory Simul. 24 419 (2015). [3] G. Zhang, L. A. Moreira, T. Stuehn, K. Ch. Daoulas, and K. Kremer, ACS Macro Lett. 3 198 (2014). [4] R. Everaers, S. K. Sukumaran, G. S. Grest, C. Svaneborg, A. Sivasubramanian, and K. Kremer, Science 303 823 (2004). [5] H.-P. Hsu and K. Kremer, preprint (2017).
Interplay of fast and slow degrees of freedom in the disk to slab transition Andreas Troester [1], C. Moritz, C. Dellago [2] [1] TU Wien, Institute of Materials Chemistry, Getreidemarkt 9, 1060 Vienna, Austria, [2] Faculty of Physics, University of Vienna, Boltzmanngasse 5, 1090 Vienna, Austria
Rare transitions between long-lived stable states are often analyzed in terms of free energy landscapes computed as functions of a few collective variables. Here, using transitions between geometric phases as example, we demonstrate that the effective dynamics of a system along these variables are an essential ingredient in the description of rare events and that the static perspective provided by the free energy alone may be misleading. In particular, we investigate the disk-to-slab transition in the two-dimensional Ising model starting with a calculation of a two-dimensional free energy landscape and the distribution of committor probabilities. While at first sight it appears that the committor is incompatible with the free energy, they can be reconciled with each other using a two-dimensional Smoluchowski equation that combines the free energy landscape with state dependent diffusion coefficients. These results illustrate that dynamical information is not only required to calculate rate constants, but may also be necessary to understand how a given process occurs.
Interface driven conformation change and aggregation in proteins/peptides Mehmet Sayar [1], Cahit Dalgicdir, Beytullah Ozgur [1], Farhad Ramezanghorbani [1] [1] Koc University, College of Engineering, Istanbul, Turkey
Conformation and assembly of proteins and peptides are not solely determined by their sequence, but are also strongly dependent on their environment. Interfaces, whether they are macroscopic (e.g. air/water interface, membrane), or molecular (e.g. surrounding molecules hydrophobic surfaces) strongly influence the conformation of proteins/peptides by enforcing strict partitioning of the hydrophobic/hydrophilic residues. In this study, by using molecular dynamics and enhanced simulation techniques, we investigate the conformational behavior of peptides in bulk water, at the air/water interface, and in the presence of other peptides. We demonstrate the role of the interface in altering both the preferred conformation and the self-assembly behavior of these peptides. By analyzing the potential of mean force curves between two peptides in different environments, we show that both the conformation and self-assembly behavior for such peptides strongly depends on the interplay between electrostatic forces, hydrophobic effect, and their strong tendency to form backbone hydrogen bonds. These all atom analysis are typically rather limited in terms of time and length scale. Coarse grained (CG) models are used extensively to overcome these barriers. However, with their reduced degrees of freedom validity of CG models is strictly restricted to the particular state that they are parametrized for. Development of CG models for proteins and peptides, which display large conformational changes in different environments, requires parametrization in more than a single state point. Here, we demonstrate how such transferable CG models can be developed by relying on properly chosen all atom reference states.
1) Dalgicdir, C., Globisch, C., Peter, C., & Sayar, M., ``Tipping the Scale from Disorder to Alpha-helix: Folding of Amphiphilic Peptides in the Presence of Macroscopic and Molecular Interfaces.'', PLoS Comput. Biol. 11, e1004328 (2015) 2) Dalgicdir, C & Sayar, M., ``Conformation and Aggregation of LKalpha14 Peptide in Bulk Water and at the Air/Water Interface'', J. Phys. Chem. B, 2015, 119 (49), pp 15164–-15175 3) Ozgur B., Sayar M., ``Assembly of Triblock Amphiphilic Peptides into One-Dimensional Aggregates and Network Formation'', J. Phys. Chem. B 2016, 120 (39), 10243-10257 4) Ozgur B., Sayar M., ``Assembly of Huntingtin headpiece into α-helical bundles'', Biointerphases 2017, 12 (2), 02D413
Size zero vs. fat bodies: cell-size effects on swimming behavior Tapan Chandra Adhyapak [1], Sara Jabbari-Farouji [1] [1] Institut für Physik, Johannes Gutenberg-Universität Mainz, Germany
We present a minimal model for rigid spherical microswimmers and investigate the role of the finite body size of the swimmers on their self-propulsion, flow and hydrodynamic interactions. The model is the first order approximation of rigid-bodied microswimmers, such as bacteria and algae, with relatively flexible propelling appendages. Although hydrodynamic interactions are crucial for many distinctive collective behaviors of the microswimmers [1], how these interactions are modified by their finite body-size in presence of self-propulsion is poorly understood. We find that the flow modified by the swimmer surfaces significantly affect the hydrodynamic interactions even at distances considerably larger then the swimmer size. We derive the full mobility matrix that connects the linear and angular velocities of one swimmer to the active and passive forces and torques acting on all the other [2]. Our investigation of the mobilities then reveals crucial dependences of the interactions between different swimmers on their size.
[1] J. Elgeti, R.G. Winkler, and G. Gompper, Rep. Prog. Phys. 78, 056601 (2015). [2] T.C. Adhyapak and S. Jabbari-Farouji, Size effects on the dynamics of rigid spherical microswimmers, in preparation.
Stochastic sampling method for a kinetic theory of active magnetic sampling method for a kinetic theory of active magnetic suspensions Fabian Kössel [1], Sara Jabbari Farouji [1] [1] Johannes Gutenberg-Universität Mainz, Germany
Inspired by the dynamical behavior of magnetotactic bacteria, we present a minimal kinetic model for dilute suspensions of magnetic, self-propelled particles. We study the collective dynamics arising from the interplay between the hydrodynamic interactions and the coupling to an external magnetic field. Our kinetic theory couples a Fokker-Planck equation for active particles in an external magnetic field to the Stokes flow equation. We combine the linear stability analysis with numerical solutions to investigate their collective behavior. The numerical solution of the kinetic equations involves a hybrid simulation technique that combines stochastic sampling with a spectral method for flow field solution. We observe traveling bands that are similar to magnetotactic bands observed for bacteria in an external field in experiments.
Coupling Between Curvature and Pattern Configurations in Block Copolymers Free Standing Membranes and Thin Films Daniel Vega [1], Anabella A. Abate [1], Gabriel Catalini [1], Aldo D. Pezzutti [1], Leopoldo R. Gómez [1], Richard A. Register [2], Giang Thi Vu [3], Friederike Schmid [3] [1] Instituto de Física del Sur, UNS - CONICET. Bahía Blanca. Argentina. [1] Instituto de Física del Sur, UNS - CONICET. Bahía Blanca. Argentina. [2] Dep. of Chem. and Biol. Eng., Princeton University, Princeton, New Jersey, USA. [3] Institut für Physik, Johannes Gutenberg Universität Mainz, Mainz, Germany.
Both, experiments and theory on curved block copolymer thin films and free-standing membranes have shown that the mechanisms of phase transition, kinetics of ordering, structure of defects and equilibrium pattern configurations are deeply affected by the intrinsic and extrinsic geometry in which the system is embedded [1,3]. Here we employed a Brazovskii free energy model and self- consistent field theory (SCFT) calculations to analyze the coupling between the smectic textures developed by cylinder forming block copolymer systems and the mean curvature of the film. For weak curvatures, it was found that the free energy of the block copolymer film follows a Helfrich form, with a bending constant that depends on the pattern orientation with regard to the directions of main curvature. The strong anisotropy in the bending constant explains the main geometrical features of the out-of-plane deformations observed in free-standing block copolymer membranes, where disclinations act as sources of Gaussian curvature [4]. These results are in very good agreement with experimental data of poly(styrene)-copoly( ethylene-alt-propylene) membranes and thin films deposited onto curved substrates.
[1] D. A. Vega, L. R. Gómez, A. D. Pezzutti, F. Pardo, P. M. Chaikin and R. A. Register, Soft Matter 9 9385 (2013). [2] A. D. Pezzutti, L. R. Gómez, and D. A. Vega, Soft Matter 11 2866 (2015). [3] L. R. Gómez, N. A. García, V. Vitelli, J. Lorenzana, and D. A. Vega. Nature Communications 6 6856 (2015). [4] E. A. Matsumoto, D.A. Vega, A. D. Pezzutti, N. A. García, P. M. Chaikin, and R. A. Register, PNAS 112 12639 (2015).
Bridging Time Scales with Variationally Enhanced Sampling Omar Valsson [1] [1] Max Planck Institute for Polymer Research, Mainz, Germany
The usefulness of atomistic simulations is generally hampered by the presence of several metastable states separated by high barriers leading to kinetic bottlenecks. Transitions between metastable states are thus rare events that occur on much longer time scales than one can simulate in practice. Numerous enhanced sampling methods have been suggested to alleviate this time scale problem, including methods based on identifying a few crucial order parameters or collective variables and enhancing their fluctuations through the introduction of an external biasing potential [1]. Here will we discuss Variationally Enhanced Sampling [2], a generally applicable enhanced sampling method which is based on a rigorous variational principle [2]. In this approach an external bias potential that acts in the space spanned by the collective variables is constructed by minimizing a convex functional. The underlying free energy landscape as a function of the selected collective variables can be obtained directly from the bias that minimizes this functional. We present numerous examples which show the flexibility, practicality, and usefulness of the method. We will furthermore discuss how the variational property of the method can be used to extend the method in novel and innovative ways, including for example: to obtain kinetics of rare events from atomistic simulations [3]; to accelerate nucleation events by employing a physical model from classical nucleation theory [4]; and to parameterize coarse-grained phenomenological models from microscopic simulations [5]. We will also introduce the VES code [6], an open-source library for the PLUMED 2 [7] plugin that implements methods based on Variationally Enhanced Sampling. The VES code can be used with a wide range of molecular dynamics codes. The code is furthermore designed in modular way to allow for a quick implementation of new features within Variationally Enhanced Sampling.
[1] O. Valsson, P. Tiwary, and M. Parrinello, Annu. Rev. Phys. Chem. 67 159-184 (2016) (doi: 10.1146/annurev-physchem-040215-112229) [2] O. Valsson and M. Parrinello, Phys. Rev. Lett. 113 090601 (2014) (doi: 10.1103/PhysRevLett.113.090601) [3] J. McCarty, O. Valsson, P. Tiwary. and M. Parrinello, Phys. Rev. Lett. 115 070601 (2015) (doi: 10.1103/PhysRevLett.115.070601) [4] P. Piaggi, O. Valsson, and M. Parrinello, Faraday Discuss. 195 557–568 (2016) (doi: 10.1039/C6FD00127K) [5] M. Invernizzi, O. Valsson, and M. Parrinello, Proc. Natl. Acad. Sci. USA 114 3370-3374 (2017) (doi: 10.1073/pnas.1618455114) [6] VES Code, a library that implements enhanced sampling methods based on Variationally Enhanced Sampling written by O. Valsson. For the current version, see http://www.ves-code.org [7] G.A. Tribello, M. Bonomi, D. Branduardi, C. Camilloni, G. Bussi, Comp. Phys. Comm. 185, 604 (2014). See http://www.plumed.org
Evaluating many-body effects in systematic coarse-graining Christoph Scherer [1], Denis Andrienko [1] [1] Max Planck Institute for Polymer Research
Particle based coarse-graining (CG) is a systematic way of reduction of the number of degrees of freedom describing a physical system. It involves three steps: choice of the CG degrees of freedom, identification of a merit function which quantifies the difference between the fine- and coarse-grained representations, and determination of the CG potential energy surface (PES).The entire procedure is sensitive to the number and types of basis-functions employed in the CG representations: for example, the incorporation of nonbonded three-body interactions in a coarse- grained water model helps to reproduce both thermodynamic and structural properties [1,2]. In this work, we investigate the effect of extending the basis set to three-body interactions for several organic solvents and formulate clear criteria for when these many-body terms are required. The coarse-graining scheme is implemented in the VOTCA-CSG toolkit [3].
[1] V. Molinero, E. B. Moore, J. Phys. Chem. B, 113, 4008 (2009) [2] L. Larini, L. Lu, G.A. Voth, J. Chem. Phys. 132, 164107 (2010) [3] V. Rühle, C. Junghans, A. Lukyanov, K. Kremer, D. Andrienko, J. Chem. Theory. Comput. 5, 3211 (2009)
5 Posters
Accessing Non-Equilibrium via Markov State Modelling Marius Bause [1], Kurt Kremer [1], Tristan Bereau [1] [1] Max Planck Institute for Polymer Research, Mainz, Germany
Markov State Models (MSM) are a discrete representation of the kinetics of a given system constructed by course-graining of microtrajectories. While frequently applied to equilibrium systems, a protocol for driven steady state systems has not been developed due to loss of dynamic properties like detailed balance. We propose to apply the principle of Maximum Caliber by Jayne's, postulating that the distribution of paths is given by the maximal path entropy encoding a chosen set of prior information. This reduces the computational effort of constructing an MSM by providing new microscopic relations from macrosopic path-ensemble assumptions. Simultaneously the markovian assumption alleviates the combinatorial explosion of microtrajetories. The method is tested on a minimal model under non-conservative forces.
[1] Bowman, Gregory R., Vijay S. Pande, and Frank Noé, Vol. 797. Springer Science & Business Media, 2013. [2] Jaynes, Edwin T. Annual Review of Physical Chemistry 31.1 (1980): 579-601.
Anisotropic potentials between colloids using a field expansion Martin Girard [1], Trung Dac Nguyen [1], Monica Olvera de la Cruz [1] [1] Northwestern University, Evanston, USA
Description of anisotropic interactions between functionalized colloids is still an ongoing research problem. In order to study complex behavior such as colloidal crystallization a large number of colloids are required and the usual approach is to tesselate the surface of particles with beads and assign them interactions. This is a relatively slow approach that fails if the functionalization is extended in space (e.g. a polymer-coated particle). We describe an approach based on making a spatial series of the density field around the colloid. The energy is then expressed as overlap integrals between interacting fields, obtaining expression similar to those of ab initio molecular dynamics using a local density basis. The calculation method avoid Pulay forces by relying on tabulated Fourier integrals. With this method, we have calculated phase diagrams of charged Janus particles interacting through Yukawa potentials by integrating the method in the LAMMPS MD package. The method is able to explore phase space in regions where the Debye length is comparable to the particle size at relatively high computation speeds.
Predicting Free Energies of Polymer Nematics: Monte Carlo Simulations vs. Self Consistent Field Theory Cristina Greco [1], Ying Jiang [2], Jeff Z. Y. Chen [3], Kurt Kremer [1], Kostas Ch. Daoulas [1] [1] Max Planck Institute for Polymer Research, Mainz, Germany, [2] School of Chemistry and Environment, Center of Soft Matter Physics and its Applications, Beihang University, Beijing, China, [3] Department of Physics and Astronomy, University of Waterloo, Waterloo, Canada
Due to their semiflexible structure, many conjugated polymers for organic electronics form liquid crystalline (LC) phases. These have attracted considerable interest, since processing from a LC phase can improve morphological order in the final solid-state film [1]. Among theoretical approaches to LC polymers, Self-Consistent Field (SCF) theory is particularly powerful, as it provides straightforward access to morphology, conformational properties and thermodynamic behavior [2]. These advantages come from approximations, such as neglecting fluctuations and certain correlations. We investigate [3] the effect of the SCF approximations on the description of the thermodynamics of polymer nematics, focusing on neglected correlations due to non-bonded interactions. Polymers are represented as discrete worm-like chains, and the non-bonded interactions are described by combining an isotropic repulsive and an anisotropic attractive Maier- Saupe (MS) potential. This coarse-grained (CG) model is studied with Monte Carlo (MC) simulations and SCF theory. The former provides an exact description of the statistical mechanics, serving as a reference for validating the SCF theory. Simulations and SCF theory are compared on the level of Helmholtz free energies, calculated as a function of the strength of the MS interactions. In MC simulations free energies are obtained via a special thermodynamic integration (TI) scheme, which reversibly connects the isotropic and nematic states using an auxiliary orienting field [4]. To implement the TI we address important methodological issues, e.g. the effect of the rotational Goldstone mode. The differences in the free energies in MC and SCF [3] demonstrate the importance of local non-bonded correlations. We find that they cannot be compensated by simple renormalization of the strength of MS interactions in SCF. In our model, correlations can be reduced by increasing the range of interactions. In this regime, representative of a drastically CG model, SCF theory reproduces well the free energy in MC simulations.
[1] I. McCulloch, M. Heeney, C. Bailey, K. Genevicius, I. Macdonald, M. Shkunov, D. Sparrowe, S. Tierney, R. Wagner, W. M Zhang, M. L. Chabinyc, R. J. Kline, M. D. McGehee, and M. F. Toney, Nat. Mater. 5, 328 (2006) [2] Y. Jiang, C. Greco, K. Ch. Daoulas, and J. Z. Y. Chen, Polymers 9, 48 (2017) [3] C. Greco, Y. Jiang, J. Z. Y. Chen, K. Kremer, and K. Ch. Daoulas, J. Chem. Phys. 145, 184901 (2016) [4] D. Frenkel and B. M. Mulder, Mol. Phys. 1985, 55, 1171
Calculation of excess chemical potential of liquids via Hamiltonian Adaptive Resolution Simulation Maziar Heidari [1], Robinson Cortes-Huerto [1], Kurt Kremer [1], Raffaello Potestio [1], [1] Max Planck Institute for Polymer Research, Mainz, Germany
The calculation of chemical potential of liquids is a relevant and challenging problem in computational chemistry and physics. Employing the multi-scale Hamiltonian Adaptive Resolution Simulation (H-AdResS) [1, 2] method, we propose a method to calculate the excess chemical potential of dense liquids. In H-AdResS, the simulation domain is subdivided in regions of high and low resolutions, coupled through a hybrid region. Since the dynamics of particles are obtained from a global Hamiltonian, the generated statistical ensembles of the system are well-defined. Here, the fluid within the high resolution region is coupled with an ideal gas of non-interacting particles, and to enforce a uniform density profile an external force is computed on-the-fly and applied. The potential energy of this external field is related to the Gibbs free energy difference between the two resolutions, which allows one to obtain from it the excess chemical potential of the fluid with respect to the ideal gas. We validated this method by calculating the excess chemical potentials of model systems and sodium chloride aqueous solutions.
[1] R. Potestio, S. Fritsch, P. Espanol, R. Delgado-Buscalioni, K. Kremer, R. Everaers, and D. Donadio, Phys. Rev. Lett. 110, 108301 (2013) [2] M. Heidari, R. Cortes-Huerto, D. Donadio and R. Potestio, Eur. Phys. J. Spec. Top. (2016) 225: 1505
Systematic reduction of chemical compound space using coarse-graining and clustering algorithms Kiran Kanekal [1], Kurt Kremer [1], Tristan Bereau [1] [1] Max Planck Institute for Polymer Research, Mainz, Germany
Increasing the efficiency of materials design and discovery remains a significant challenge for both experimentalists and theoreticians. Traditionally, direct molecular design approaches—in which the structure and chemistry of a molecule are known before its relevant properties are determined— have been the standard method for development of new drugs, catalysts, and clean energy materials. As the computational efficiency and predictive accuracy of in silico methods has increased, inverse molecular design strategies are quickly becoming feasible alternatives. However, the size of chemical compound space is prohibitively large for the fast generation of hypersurfaces that define structure-property relationships, which are necessary for implementing inverse molecular design [1]. In this work, we use a dataset consisting of all small organic molecules with up to 8 “heavy” atoms [2] (i.e. excluding hydrogen atoms) as an initial proxy for the entire chemical compound space. This relatively small slice of the total space consists of ~100,000 molecules. We demonstrate a reduction of this space in two steps. First, we apply the AutoMartini algorithm developed by Bereau and Kremer [3] to systematically determine a coarse-grained representation for each molecule in the dataset. We subsequently cluster molecules by using similarity measures corresponding to specific chemical and structural descriptors. We then assess the extent to which the initial chemical compound space was reduced and whether the diversity of the space is sufficiently reflected in its coarse-grained counterpart. The resolution of the coarse- grained space can then be tuned either by introducing new bead types or by reducing the number of atoms assigned to a bead. This framework will provide a means for efficient high throughput sampling of chemical compound space (as highlighted by Menichetti and coworkers in their work).
[1] D. Xiao, I. Warnke, J. Bedford and V. S. Batista, in Chemical Modelling: Volume 10, The Royal Society of Chemistry, 2014, vol. 10, pp. 1–31. [2] T. Fink and and Jean-Louis Reymond*, J. Chem. Inf. Model., 2007, 47, 342–353. [3] T. Bereau and K. Kremer, J. Chem. Theory Comput., 2015, 11, 2783–2791.
Testing Nucleation Theory for Colloidal Crystals Peter Koß [1], Antonia Statt [2], Peter Virnau [1], Kurt Binder [1] [1] Johannes Gutenberg University Mainz; Germany; [2] Princeton University, Princeton, USA
A fluid in equilibrium, confined in a finite volume, with a density exceeding the onset of freezing, may exhibit phase coexistence with a crystal nucleus surrounded by liquid or a gas. Classical nucleation theory predicts that the barrier of homogeneous nucleation is given by two contributions, the free energy gained by the creation of a crystal droplet and the free energy loss due to surface tension of the newly created interface. We obtain the excess free energy due to the surface of the crystalline nucleus by using a computational method suitable for the estimation of the chemical potential of dense fluids. Our analysis method is appropriate for crystal nuclei of all shapes, without suffering from ambiguities occurring when one needs a microscopic identification of the crystalline droplet. We present a novel analysis method to determine the coexistence pressure between fluid and crystal, and report that the nucleation barrier for a soft version of the effective Asakura- Oosawa model [1] is compatible with a spherical shape, and consistent with classical nucleation theory [2].
[1] M. Dijkstra, R. van Roij and R. Evans, Phys. Rev. E 59, 5744-5771 (1999). [2] A. Statt, P. Virnau, and K. Binder, Phys. Rev. Lett. 114, 026101 (2015).
Charge effect on the stability of micelles in polymer/surfactant solutions: Dissipative particle dynamics simulation Anastasia Markina[1], Alexander Buglakov[1], Alexey Gavrilov[1], Viktor Ivanov[1], Pavel Komarov[2][3] [1] Lomonosov MSU [2] Tver State University, Tver, Russia [3] Institute of Organoelement Compounds RAS, Moscow, Russia
Dissolution and precipitation of polymers in different solvents is an important field of interest in polymer science because it plays the key role in many technological process in the industry, such as fiber production, surface covering, environmental protection, drug delivery, etc. This presentation provides a model to describe a polymer film formation as a result of precipitation of polymeric micelles stabilized by a surfactant.We have developed a coarse-grained model for the aqueous solution of an acrylic copolymer and a surfactant. We use the method of dissipative particle dynamics [1-3]. Electric charges on surfactant molecules and counter-ions are taken into account explicitly, and we use for electrostatic interactions the computational scheme developed in Ref.[2]. The aim is to study the structure and to perform the analysis of stability of micelles in polymer/surfactant solutions, as well as to search for optimal conditions of a film formation from aqueous solutions of polymer micelles stabilized by surfactants. To model the film formation we apply an algorithm for evaporation of the solvent (water). As an illustration of the capabilities of the computational scheme, we demonstrate our results of the influence of various parameters of the model (concentration of components, parameters of volume interaction and of electrostatic interaction) on the characteristics of the emerging films.Mixed micelles of polymer with uncharged surfactant tend to aggregate (as well as uncharged colloids). Systems with charged surfactant molecules can behave differently depending on the strength of the electrostatic interaction. Both with a weak electrostatic contribution and with a strong contribution, the small micelles are unstable, coagulate into micelles of larger size, and form uniform films upon solvent evaporation. If we want to stabilize the small size of micelles in the emulsion, we need to find the optimal value of charges (for example, the optimum value of added salt).
[1] R. Groot, P. Warren, J. Chem. Phys., 107, 4423 (1997). [2] A. Gavrilov, A. Chertovich, E. Kramarenko, Macromolecules, 49, 1103 (2016). [3] P. Español, P. Warren, J. Chem. Phys., 146, 150901 (2017).
Macroscopic composition of poly(bithiophene-alt-thienothiophene) (PBTTT) Anton Melnyk [1], Denis Andrienko [1] [1] Max Planck Institute for Polymer Research, Mainz, Germany
We combine the solid-state NMR measurements with molecular dynamics simulations to gain more insight into a macroscopic composition of the conjugated homopolymer poly(2,5-bis(3- tetradecylthiophen-2-yl)thieno[3,2-b]thiophene) (PBTTT-C16) in a powder. The local structural and dynamical properties of backbones and side-chains, as measured in the SS-NMR experiments, are used to test the three simulated mesophases: (i) crystalline backbones and side chains, (ii) lamellar backbones with disordered side chains, and (iii) completely amorphous chains. The relative composition of these mesophases in the sample is then determined from the resolved SS-NMR spectra and measured dynamic order parameters, which are then complemented with their simulated microscopic counterparts. We find that the powder composition has only 28% of the completely crystalline mesophase. The remaining parts are 23% lamellar and 49% amorphous. The suggested protocol is general and can be used for similar homopolymers.
High-throughput screening of chemical compounds via molecular dynamics simulations Roberto Menichetti [1], Kiran H. Kanekal [1], K. Kremer [1], T. Bereau [1] [1] Max Planck Institute for Polymer Research, Mainz, Germany
The increasing request for new materials with tunable physical and chemical properties calls for a rational optimization of molecular structures, a highly nontrivial task because of the overwhelming size of chemical space. In an "in silico" search for structure-property relationships aiming at inverse molecular design, the extensive computational resources required by molecular dynamics simulations performed with the atomistic detail is currently unfeasible for spanning large regions of chemical compound space. On the other hand, coarse-grained models provide a means to mitigate the computational expense, while still capturing the relevant physical properties. In this work, we perform a screening of a small subset of chemical space which aims at analyzing the free energy of insertion of a compound in a phospholipid membrane. Such a screening is performed via high- throughput coarse-grained molecular dynamics simulations, and allows us to identify simple relationships between bulk properties and key features characterizing the thermodynamic stability of a compound in a bilayer environment. By connecting the reduced, coarse-grained chemical space to the atomistic one, we are able to show that these results are representative of the transmembrane behavior of a set of 400000 small molecules.
Enhanced Sampling Calculation of Chemical Potential in Fluids Claudio Perego [1], Michele Parrinello [2] [3] [1] Max Planck Institute for Polymer Research , Mainz, Germany [2] Swiss Federal Institute of Technology, Zurich, Switzerland [3] Università della Svizzera Italiana, Lugano, Switzerland
Chemical potential is a key thermodynamic quantity in the study of liquid systems, regulating a wide range of phenomena, such as phase transitions and chemical reactions. The calculation of chemical potential in dense fluids represents a long-standing challenge in molecular simulations. In the classical techniques, building on Widom's method, chemical potential is computed by sampling the energy of insertion of a test particle. The largest contributions to the resulting estimate come from the low energy insertions, in which the test particle is placed in a proper cavity within the system particles. In dense liquids such cavities are rarely available, and the sampling is mostly restricted to large insertion energies, strongly limiting the accuracy of the result. Here I present a new method for computing the chemical potential in dense liquids. This technique relies on a biasing approach that extends the insertion sampling to the relevant low energy region, inaccessible in unbiased simulations. The method is tested with both homogeneous and non- homogeneous Lennard-Jones fluids. As a result an accurate chemical potential estimate is obtained even at very large densities, where the classical approach fails.
[1] C.Perego, F. Giberti and M. Parrinello, Eur. Phys. J-Spec. Top. 225 1621 (2016)
Rescuing coarse-grained kinetics using Markov state models Joseph Rudzinski [1], Kurt Kremer [1], Tristan Bereau [1] [1] Max Planck Institute for Polymer Research, Mainz, Germany
Low-resolution, coarse-grained (CG) models are routinely employed for investigating complex condensed-phase processes on length and time scales unattainable for higher resolution, e.g., atomically-detailed, models. The sampling efficiency of CG models, attained through a combination of reduced molecular friction and softer interaction potentials, comes at the cost of obscuring the connection to the true dynamical properties of the underlying system. Although it is possible to recover the dynamics via a generalized Langevin formalism, this approach offers a daunting computational and conceptual challenge for complex systems that give rise to hierarchical dynamics, i.e., kinetic processes coupled over various timescales. As an alternative, we consider a top-down, Markov state modeling-based framework for characterizing and correcting the hierarchy of slow kinetic processes generated from CG simulations. In this work, we overview several distinct efforts in overcoming the theoretical and practical challenges of such an approach. First, a Bayesian scheme is developed which identifies essential adjustments to a Markov state model, generated from CG simulations, in order to achieve consistent kinetics with respect to given reference data for the system. We then apply this method to two CG peptide models and demonstrate that the resulting information may be directly and effectively employed for model reparametrization. In both cases, the reparametrization results in an improved hierarchy of slow kinetic processes, while retaining the fundamental properties of the original model. To better characterize the utility of the proposed methodology in the context of combining CG protein folding simulations with experimental reference data, we perform a detailed investigation of structure- kinetic relationships for CG helix-coil transitions. Finally, to broaden the utility of our approach, we propose a method that employs generic order parameters to build Markov state models for diffusion processes in many-particle systems. Overall, the work provides a unique route for interpreting the kinetic properties generated by CG models for complex systems and demonstrates specific promise in a range of applications from proteins to complex liquids.
[1] J.F. Rudzinski, K. Kremer, T. Bereau, J. Chem. Phys. 144 051102 (2016) [2] J.F. Rudzinski, T. Bereau, Eur. Phys. J. Spec. Top. doi:10.1140/epjst/e2016-60114-5 (2016)
Reduced order hybrid multiscale method combining the regularized data from MD simulations with the macroscopic flow solver Stefanie Stalter [1], Nehzat Emamy [1], Leonid Yelash [1], Maria Lukacova [1], and Peter Virnau [1] [1] Johannes Gutenberg Universität Mainz, Germany
We introduce a reduced-order method to simulate the dynamics of complex materials (e.g. polymer/colloid systems) combining the continuum and atomistic descriptions. We follow the framework of heterogeneous multi-scale method (HMM), separating the scales to macro- and micro-levels. On the macro-level, the governing equations of the incompressible flow are the continuity and momentum equations, which are solved using a high-order accurate discontinuous Galerkin Finite Element Method (dG) and implemented in the BoSSS code. The missing information on the macro-level to solve the momentum equation is the stress tensor, which is computed from molecular Dynamics (MD) simulations on the micro-level. The data obtained from the MD simulations underlie relatively large stochastic errors, which can be controlled by means of the least square approximation. In order to reduce a large number of MD runs for the coupled simulations, we split the computations into an offline phase of expensive training and an online phase of fast multiple queries. In the training phase, we use the Greedy sampling algorithm as a model reduction technique to replace the nonlinear functionality of the stress tensor on the strain by a smooth low-dimensional reliable approximation.
Implementation of the stress tensor in the LAPW method Andreas Troester [1] [1] TU Wien, Institute of Materials Chemistry, Getreidemarkt 9, 1060 Vienna [1]
The successful theoretical derivation and practical implementation of the stress tensor in all- electron density functional theory codes of the LAPW type is a long-standing and pressing problem. Here we present some theoretical calculations and results for hydrostatic pressure as implemented in the WIEN2k code. Similar to the structure of force formulas, we derive Hellmann-Feynman and Pulay contributions to the full stress tensor. Comparison of our thereby calculated pressure to that obtained from fits of the total energy to an equation of state are presented for Al and Si cubic crystals.
Monte Carlo Simulation of Amyloid Protofibril Formation Matthew Wilson [1], Guangjie Shi[ 1], Thomas Wuest [2], David P. Landau [1], Friederike Schmid [3] [1] University of Georgia, USA, [2] Scientific IT Services, Zurich, Switzerland, [3] Johannes Gutenberg University, Mainz, Germany
Aggregation processes of amyloid protofibrils are studied using the replica-exchange Wang- Landau (REWL) [1] algorithm to simulate multiple interacting model peptides. The H0P model [2], which adds an additional neutral polarity group to the classic hydrophobic-polar (HP) model [3], is used for simplicity and efficiency. Constituent peptides are modeled as short, intrinsically disordered H0P sequences, which do not form globular structures individually but self-assemble to form various aggregated structures. Using the parallelized sampling framework, the density of states is determined and the minimal energy state is identified. From thermodynamic quantities, the effects of peptide concentration are studied for the formation of protofibrillar structures.
[1] T. Vogel, Y. W. Li, T. Wuest, and D. P. Landau, Phys. Rev. E 90, 023302 (2014). [2] G. Shi, T. Wuest, Y. W. Li, and D. P. Landau, J. Phys.: Conf. Ser. 640, 012017 (2015). [3] K. A. Dill, Biochemistry 24, 1501 (1985); K. F. Lau and K. A. Dill, Macromolecules 22, 3986 (1989).
Kinetic properties of liquid crystals from coarse-grained and atomistic molecular dynamics simulations Svenja Woerner [1], Joseph Rudzinski [1], Kurt Kremer [1] Tristan Bereau [1] [1] Max-Planck-Institute for Polymer Research, Mainz, Germany
Liquid crystals display liquid-like behavior while maintaining a long-range crystalline order, giving rise to unique material properties. To understand macroscopic processes, e.g. phase transitions, large systems need to be studied on time scales not accessible by atomistic models. Coarse grained models make these sizes and time scales accessible. In this work we investigate the liquid crystal mesogen 8AB8, containing a stiff, photoisomerizable azobenzene core with flexible alkyl tails. Mukherjee et al. have previously developed a coarse-grained model of 8AB8, which displays the correct thermodynamic and structural properties. Not only is it able to form a smectic phase, the model also reproduces the transition temperature of the disordered to smectic phase transition of the underlying atomistic model. Reducing the degrees of freedom usually leads to a non-trivial modification of the timescales for different processes sampled by the coarse-grained model. Two well-characterized translocation pathways in the smectic A phase are studied in detail, utilizing a Markov state model framework to systematically assess the differences in the transport kinetics between the coarse-grained and atomistic models. Investigating the precise source of the discrepancies between the two models implicates an approach for reparameterization of the coarse-grained model. Such a model, which retains efficiency while generating correct large-scale kinetics, could provide insight into the relation between emergent phenomena and microscopic properties.
6 Participant List
Organizers Chase, Astrid Institute of Physics, Johannes Gutenberg University, Mainz, Germany Daoulas, Kostas Max Planck Institute for Polymer Research, Mainz, Germany Duenweg, Burkhard Max Planck Institute for Polymer Research, Mainz, Germany Kremer, Kurt Max Planck Institute for Polymer Research, Mainz, Germany Schmid, Friederike Institute of Physics, Johannes Gutenberg University, Mainz, Germany
Adhyapak, Tapan Chandra - Institut für Physik, Johannes Gutenberg-Universität, Mainz, Germany Andrienko, Denis - Max Planck Institute for Polymer Research, Mainz, Germany Ardham, Vikram Reddy - TU Darmstadt, Germany Baeurle, Stephan - University of Regensburg, Regensburg, Germany Ball, Robin - Dept of Physics, University of Warwick, United Kingdom Bause, Marius - Max Planck Institute for Polymer Research, Mainz, Germany Bereau, Tristan - Max Planck Institute for Polymer Research, Mainz, Germany Doi, Masao - Beihang University, Beijing, China Egorov, Sergei – University of Virigina, Charlottesville, USA Ellero, Marco - College of Engineering, University of Swansea, UK, United Kingdom Fiorentini, Raffaele - Max Planck Institute for Polymers, Mainz, Germany Ganesan, Venkat - University of Texas at Austin, USA Girard, Martin - Northwestern University, Evanston, USA Greco, Cristina - Max Planck Institute for Polymer Research, Mainz, Germany Harting, Jens - Technische Universität Eindhoven, The Netherlands Heidari, Maziar - Max Planck Institute for Polymer Research, Mainz, Germany Hilfer, Rudolf - ICP, University of Stuttgart, Germany Holm, Christian - Institute for Computational Physics, University of Stuttgart, Germany Hsu, Hsiao-Ping - Max Planck Institute for Polymer Research, Mainz, Germany Jabbari-Farouji, Sara - Johannes Gutenberg-Universität, Mainz, Germany Kanekal, Kiran - Max Planck Institute for Polymer Research, Mainz, Germany Kobayashi, Hideki - Max Planck Institute for Polymer Research, Mainz, Germany Koß, Peter – Johannes Gutenberg University, Mainz, Germany Kössel, Fabian - Johannes Gutenberg-Universität Mainz, Germany Lukacova, Maria - Johannes Gutenberg University, Mainz, Germany Maggs, Anthony C. - ESPCI, Paris, France Mantha, Sriteja - Johannes Gutenberg University, Mainz, Germany Markina, Anastasia - Faculty of Physics, Lomonosov Moscow State University, Russian Federation Martens, Kirsten - University Grenoble Alpes & CNRS, France Martzel, Nicolas – Michelin, France Melnyk, Anton – Max Planck Institute of Polymer Research, Mainz, Germany Menichetti, Roberto - Max Planck Institute for Polymer Research, Mainz, Germany Mondal, Anirban - Max Planck Institute for Polymer Research, Mainz, Germany Mukherji, Debashish - Max Planck Institute for Polymer Research, Mainz, Germany Müller, Marcus - Georg-August University, Göttingen, Germany Nikoubashman, Arash - Johannes Gutenberg University, Mainz, Germany Ntim, Samuel - Johannes Gutenberg Universität, Mainz, Germany Ohkuma, Takahiro - Bridgestone Corporation, Japan Olvera de la Cruz, Monica - Northwestern University, Evanston, USA Paterson, Leanne - Max Planck Institute for Polymer Research, Mainz, Germany Perego, Claudio - Swiss Federal Institute of Technology in Zurich (ETHZ), Lugano, Switzerland Qi, Shuanhu – Johannes Gutenberg University, Mainz, Germany Rudzinski, Joseph - Max Planck Institute for Polymer Research, Mainz, Germany Sayar, Mehmet - Koc University, Turkey Scherer, Christoph - Max Planck Institute for Polymer Research, Mainz, Germany Schirmacher, Walter - Johannes Gutenberg-Universität, Mainz, Germany Schnell, Benoît - Michelin, France Sen Gupta, Bhaskar - Max Planck Institute for Polymer Research, Mainz, Germany Sevink, Agur - Leiden University, The Netherlands Singh, Manjesh - Max Planck Institute for Polymer Research, Mainz, Germany Smrek, Jan - Max Planck Institute for Polymer Research, Mainz, Germany Spiller, Dominic - Max Planck Institute for Polymer Research, Mainz, Germany Srivastva, Deepika – Johannes Gutenberg Universität, Mainz, Germany Stalter, Stefanie – Johannes Gutenberg University Mainz, Germany Sulpizi, Marialore – Johannes Gutenberg University, Mainz, Germany Theodorou, Doros - National Technical University of Athens (GR), Greece Tretyakov, Nikita - Max Planck Institute for Polymer Research, Mainz, Germany Troester, Andreas - Institute of Materials Chemistry, TU Vienna, Getreidemarkt 9, 1060 Wien, Austria Valsson, Omar - Max Planck Institute for Polymer Research, Mainz, Germany Vargas Guzman, Horacio - Max Planck Institut for Polymer Research, Mainz, Germany Vega, Daniel - Instituto de Física del Sur - UNS - CONICET, Argentina Virnau, Peter – Johannes Gutenberg University, Mainz, Germany Vu, Giang Thi – Johannes Gutenberg University, Mainz, Germany Wilson, Matthew - University of Georgia, Athens, USA Winkler, Roland G. - Forschungszentrum Jülich, Germany Woerner, Svenja - Max Planck Institute for Polymer Research, Mainz, Germany Zhang, Guojie - Institute for Theoretical Physics, Georg-August University, Göttingen, Germany Zhang, Jianrui - Max Planck Institute for Polymer Research, Mainz, Germany Zhang, Jianguo - Max Planck Institute for Polymer Research, Mainz, Germany Zhou, Jiajia - Beihang University, Beijing, China