CECAM Tutorial Stuttgart, Oct. 2012

Size: px
Start display at page:

Download "CECAM Tutorial Stuttgart, Oct. 2012"

Transcription

1 CECAM Tutorial Stuttgart, Oct ESPResSo++ CECAM Tutorial 1 / 40

2 ESPResSo++ ESPResSo++ is an open-source simulation package designed to perform molecular dynamics and monte carlo simulations of condensed matter systems using traditional and state-of-the-art techniques. The software is extensible due to its modular object-oriented C++ core. It is highly flexible due to its Python scripting interface. The package can be used as a research platform as well as a production tool ESPResSo++ CECAM Tutorial 2 / 40

3 ESPResSo++ Key Features and Advantages Flexibility due to Python/C++ integration Extensibility due to object oriented design Easy script-guided creation of complex topologies Quick incorporation of new interactions and algorithms Use of standard short- and long range interactions: e.g. Lennard-Jones, Morse, FENE, OPLS, Dihedrals, Ewald Coulomb, etc. Efficient implementation of advanced algorithms: e.g. AdResS, Parallel Tempering, dynamic bonds, etc. On-the-fly analysis and visualization Applicable to large systems and large numbers of CPUs Analysis NumPy SciPy PyMol Python scripting language Advanced C++ Kernel Parallelization Time-critical algorithms Data storage Extensible design Visualization VMD ESPResSo++ CECAM Tutorial 3 / 40

4 Multiple parallel systems, controlled by one Python script: 1 2 N Controlling Python script e.g. for Parallel Tempering, Replica Exchange, ESPResSo++ CECAM Tutorial 4 / 40

5 Current developers: ESPResSo++ Team: Torsten Stuehn (MPIP) Vitalii Starchenko (MPIP) Stas Bevc (NIC, Slovenia) Konstantin Koschke (MPIP) Livia Moreira (MPIP) Raffaello Potestio (MPIP) Karsten Kreis (MPIP) Former developers: Thomas Brandes (SCAI) Dirk Reith (SCAI) Axel Arnold (ICP) Olaf Lenz (ICP) Jonathan Halverson (BNL, USA) Victor Ruehle (Cambridge, UK) Christoph Junghans (LANL, USA) ESPResSo++ CECAM Tutorial 5 / 40

6 Outline of the tutorial Inside ESPReSo++ an overview of the C++ class structure Integrator, Interactions, Setting up a simulation with, Integrator and Interactions How to equilibrate a polymer melt Python script Installation of ESPResSo++ Basic Setup Simple Lennard Jones Advanced Lennard Jones with graphical output Polymer Melt C++ Core ESPResSo++ CECAM Tutorial 6 / 40

7 Inside ESPResSo++ Extension LangevinThermostat Integrator Interaction VerletListInteraction < LennardJones > Domain ESPResSo++ CECAM Tutorial 7 / 40

8 Extension LangevinThermostat Integrator Interaction VerletListInteraction < LennardJones > Domain ESPResSo++ CECAM Tutorial 8 / 40

9 Extension LangevinThermostat Integrator Init f i & t &= F i t Interaction VerletListInteraction < LennardJones > MD Loop v i & t + t 2& &= v i t &+& t 2 & &f i t r i & t + t & &= r i t &+& t & &v i t + t 2 f i & t &= F i t Domain v i & t + t & &= v i t + t 2 &+& t 2 & &f i t &&& ESPResSo++ CECAM Tutorial 9 / 40

10 Extension LangevinThermostat Integrator Init Interaction VerletListInteraction < LennardJones > MD Loop f i & t &= F i t v i & t + t 2& &= v i t &+& t 2 & &f i t r i & t + t & &= r i t &+& t & &v i t + t 2 f i & t &= F i t Domain v i & t + t & &= v i t + t 2 &+& t 2 & &f i t &&& ESPResSo++ CECAM Tutorial 10 / 40

11 Extension LangevinThermostat Integrator Init Interaction f i & t &= F i t +&L T, γ, v i t, θ v i & t + t 2& &= v i t &+& t 2 & &f i t VerletListInteraction < LennardJones > MD Loop r i & t + t & &= r i t &+& t & &v i t + t 2 f i & t v i & t + t &= F i t +&L T, γ, v i t + t 2, θ & &= v i t + t 2 &+& t 2 & &f i t &&& Domain ESPResSo++ CECAM Tutorial 11 / 40

12 Extension Integrator FixPositions Init Interaction VerletListInteraction < LennardJones > MD Loop f i & t &= F i t save positions v i & t + t 2& &= v i t &+& t 2 & &f i t r i & t + t & &= r i t &+& t & &v i t + t 2 restore positions f i & t &= F i t Domain v i & t + t & &= v i t + t 2 &+& t 2 & &f i t &&& ESPResSo++ CECAM Tutorial 12 / 40

13 Extension Integrator ForceCapping Init Interaction VerletListInteraction < LennardJones > MD Loop f i & t &= F i t v i & t + t 2& &= v i t &+& t 2 & &f i t r i & t + t & &= r i t &+& t & &v i t + t 2 f i & t &= F i t cap forces v i & t + t & &= v i t + t 2 &+& t 2 & &f i t &&& Domain ESPResSo++ CECAM Tutorial 13 / 40

14 Extension Integrator LangevinThermo/Barostat BerendsenThermo/Barostat (T)DPDThermostat StochasticVelocityRescaling Isokinetic Interaction FixPositions VerletListInteraction < LennardJones > ExtForce / TDForce Domain ForceCapping AdResS ESPResSo++ CECAM Tutorial 14 / 40

15 Extension LangevinThermostat Integrator Interaction VerletListInteraction < LennardJones > Domain ESPResSo++ CECAM Tutorial 15 / 40

16 Extension LangevinThermostat Integrator Interaction Different types of interaction: 2-body (pair) 3-body (angular) 4-body (dihedral) N-body (coulomb k-space) non bonded (Verlet lists) bonded (bond lists) VerletListInteraction < LennardJones > Domain ESPResSo++ CECAM Tutorial 16 / 40

17 Integrator Extension 2-body 3-body 4-body N-body LangevinThermostat VerletList VerletListAdress Interaction VerletListInteraction < LennardJones > VerletListTriple CellListAllPairs CellListAllParticles Domain FixedPairList FixedTripleList FixedQuadrupleList ESPResSo++ CECAM Tutorial 17 / 40

18 2-body Integrator Extension 3-body 4-body N-body LangevinThermostat non bonded interaction templates VerletList VerletListAdress Interaction Interaction types have to be combined with potentials VerletListTriple CellListAllPairs CellListAllParticles Domain VerletListInteraction < LennardJones > FixedPairList FixedTripleList FixedQuadrupleList bonded interaction templates ESPResSo++ CECAM Tutorial 18 / 40

19 Integrator Angular Cosine Reaction FieldGen Tabulated Angular 2-body Tabulated Dihedral Extension FENE Harmonic 3-body Ewald KSpace Soft Cosine Angular Harmonic Ewald RSpace 4-body Cosine Squared Lennard Jones OPLS Tabulated Stillinger Weber Morse N-body Lennard JonesCap LangevinThermostat non bonded interaction templates VerletList VerletListAdress VerletListTriple CellListAllPairs CellListAllParticles Domain FixedPairList FixedTripleList FixedQuadrupleList bonded interaction templates ESPResSo++ CECAM Tutorial 19 / 40

20 Integrator Angular Cosine Reaction FieldGen Tabulated Angular 2-body Tabulated Dihedral Extension FENE Harmonic 3-body Ewald KSpace Soft Cosine Angular Harmonic Ewald RSpace 4-body Cosine Squared Lennard Jones OPLS Tabulated Stillinger Weber Morse N-body Lennard JonesCap LangevinThermostat non bonded interaction templates VerletList VerletListAdress VerletListTriple CellListAllPairs CellListAllParticles Domain FixedPairList C++ code: typedef class VerletListInteractionTemplate < LennardJones > VerletListLennardJones FixedTripleList FixedQuadrupleList bonded interaction templates ESPResSo++ CECAM Tutorial 20 / 40

21 Integrator Angular Cosine Reaction FieldGen Tabulated Angular 2-body Tabulated Dihedral Extension FENE Harmonic 3-body Ewald KSpace Soft Cosine Angular Harmonic Ewald RSpace 4-body Cosine Squared Lennard Jones OPLS Tabulated Stillinger Weber Morse N-body Lennard JonesCap LangevinThermostat non bonded interaction templates VerletList VerletListAdress VerletListTriple CellListAllPairs CellListAllParticles Domain FixedPairList C++ code: typedef class FixedPairListInteractionTemplate < LennardJones > FixedPairListLennardJones FixedTripleList FixedQuadrupleList bonded interaction templates ESPResSo++ CECAM Tutorial 21 / 40

22 Integrator Angular Cosine Reaction FieldGen Tabulated Angular 2-body Tabulated Dihedral Extension FENE Harmonic 3-body Ewald KSpace Soft Cosine Angular Harmonic Ewald RSpace 4-body Cosine Squared Lennard Jones OPLS Tabulated Stillinger Weber Morse N-body Lennard JonesCap LangevinThermostat non bonded interaction templates VerletList VerletListAdress VerletListTriple CellListAllPairs CellListAllParticles Domain FixedPairList C++ code: typedef class VerletListTripleInteractionTemplate < StillingerWeberTripleTerm > VerletListStillingerWeberTripleTerm FixedTripleList FixedQuadrupleList bonded interaction templates ESPResSo++ CECAM Tutorial 22 / 40

23 Extension LangevinThermostat Integrator Interaction VerletListInteraction < LennardJones > Domain ESPResSo++ CECAM Tutorial 23 / 40

24 Extension VerletList Integrator VerletListAdress VerletListTriple Particle lists for different interactions are updated on from Domain LangevinThermostat Domain Interaction VerletListInteraction FixedPairList < LennardJones > FixedTripleList onparticleschanged beforesendparticles afterrecvparticles FixedQuadrupleList ESPResSo++ CECAM Tutorial 24 / 40

25 RNG BC Necessary modules to simulate a standard polymer melt with Langevin dynamics Particles Inter actions Integrator LJ FENE Cos 2 Extension Langevin ESPResSo++ CECAM Tutorial 25 / 40

26 Corresponding Python script : Inter actions RNG BC Particles LJ FENE Cos 2 s1 = () s1.rng = esutil.rng() s1.bc = bc.(<args>) s1.storage = storage.domain(<args>).. <create particlelist>. s1.storage.addparticles(*property_list, particle_list).. <define interactions with parameters>. s1.addinteraction(lj) s1.addinteraction(fene) s1.addinteraction(cossq) Integrator Extensions Langevin i1 = integrator.(s1).. <create thermostat with parameters>. i1.addextension(langevin_thermostat) i1.run(10000) ESPResSo++ CECAM Tutorial 26 / 40

27 Creating an equilibrated configuration of a dense polymer melt Input of system parameters N c, l c, ρ Create random polymer chains Warmup the system Equilibrate the system Output equilibrated configuration Snapshot of an equilibrated dense ring polymer melt, number of chains N c =200, chain length l c =200 particles, density ρ=0.85 [N/V 3 ] ESPResSo++ CECAM Tutorial 27 / 40

28 Creating an equilibrated configuration of a dense polymer melt Input of system parameters N c, l c, ρ Create random polymer chains Specify parameters of the simulation: Number of chains N c Number of monomers per chain (chainlength) l c Number density of the system ρ Warmup the system Equilibrate the system Average end-to-end distance of polymers: & R ee N 1 2 Equilibrated dense polymer melts have a random walk (RW) statistic. Output equilibrated configuration Starting configurations should be random walks ESPResSo++ CECAM Tutorial 28 / 40

29 Creating an equilibrated configuration of a dense polymer melt Input of system parameters N c, l c, ρ Create random polymer chains Warmup the system Equilibrate the system Output equilibrated configuration For each chain we have to define a random start position in the simulation box and then create a random walk with a fixed step length and a number of steps l c ESPResSo++ CECAM Tutorial 29 / 40

30 Creating an equilibrated configuration of a dense polymer melt Input of system parameters N c, l c, ρ Create random polymer chains Warmup the system Equilibrate the system Output equilibrated configuration Chains and therefore particles in a dense random walk system are very likely to have a strong overlap. This results in extremely strong repulsive forces between these overlapping particles ESPResSo++ CECAM Tutorial 30 / 40

31 Creating an equilibrated configuration of a dense polymer melt Input of system parameters N c, l c, ρ Create random polymer chains Warmup the system Equilibrate the system Output equilibrated configuration Solving the equations of motion by simply applying a Velocity-Verlet scheme to RW polymers will lead to a so called explosion of the system due to numerical errors caused by extremely large numbers for the forces between overlapping particles. Measures to be taken to avoid explosion : Decrease basic time step dt of the integrator Apply force capping to some or all of the interactions Gradually decrease the force capping radius Gradually increase epsilon or sigma of the WCA interaction Depending on the density of the system and the polymer model (e.g. totally flexible or bending stiffness included) not all of the above mentioned steps may be necessary ESPResSo++ CECAM Tutorial 31 / 40

32 Creating an equilibrated configuration of a dense polymer melt Input of system parameters N c, l c, ρ Create random polymer chains Warmup the system Equilibrate the system Output equilibrated configuration After the warmup evolve the system by running the Velocity-Verlet integrator with full potentials at the specified temperature for several thousands or millions of steps, depending on the chainlength and the interactions. During the equilibration the following observables of the system should be measured in regular time intervals: Temperature of the system Total energy of the system These will already give some hints about how long equilibration will take. Additionally the mean squared displacement (msd) of the center of mass of the polymer chains could be measured. As soon as this property has reached a value of the order of the size of the radius of gyration equilibration should be finished ESPResSo++ CECAM Tutorial 32 / 40

33 Thank you for your attention! Project website: / 40

Coarse-Grained Models!

Coarse-Grained Models! Coarse-Grained Models! Large and complex molecules (e.g. long polymers) can not be simulated on the all-atom level! Requires coarse-graining of the model! Coarse-grained models are usually also particles

More information

Tutorial 1: Lennard-Jones Liquid ESPResSo Basics

Tutorial 1: Lennard-Jones Liquid ESPResSo Basics Tutorial 1: Lennard-Jones Liquid ESPResSo Basics October 10, 2016 Contents 1 Introduction 2 2 Background 2.1 The Lennard-Jones potential......................... 2.2 Units.......................................

More information

Introduction to molecular dynamics

Introduction to molecular dynamics 1 Introduction to molecular dynamics Yves Lansac Université François Rabelais, Tours, France Visiting MSE, GIST for the summer Molecular Simulation 2 Molecular simulation is a computational experiment.

More information

Long-range Interactions in Particle Simulations ScaFaCoS. Olaf Lenz

Long-range Interactions in Particle Simulations ScaFaCoS. Olaf Lenz Long-range Interactions in Particle Simulations ScaFaCoS 1/33 Outline Many-particle Simulations Short-range Interactions Long-range Interactions: ScaFaCoS If time permits: ESPResSo and coarse-graining

More information

Predici 11 Quick Overview

Predici 11 Quick Overview Predici 11 Quick Overview PREDICI is the leading simulation package for kinetic, process and property modeling with a major emphasis on macromolecular systems. It has been successfully utilized to model

More information

The Lattice Boltzmann Method in ESPResSo: Polymer Diffusion and Electroosmotic Flow

The Lattice Boltzmann Method in ESPResSo: Polymer Diffusion and Electroosmotic Flow ESPResSo Tutorial The Lattice Boltzmann Method in ESPResSo: Polymer Diffusion and Electroosmotic Flow Stefan Kesselheim Georg Rempfer June 14, 2016 Institute for Computational Physics, Stuttgart University

More information

Autocorrelation Study for a Coarse-Grained Polymer Model

Autocorrelation Study for a Coarse-Grained Polymer Model Autocorrelation Study for a Coarse-Grained Polymer Model KaiK.Qi and andmichael M. Bachmann Bachmann he Center for CSP,UGA Simulational Physics he University of Georgia alk given at the 14th Leipzig Workshop

More information

Introduction to Computer Simulations of Soft Matter Methodologies and Applications Boulder July, 19-20, 2012

Introduction to Computer Simulations of Soft Matter Methodologies and Applications Boulder July, 19-20, 2012 Introduction to Computer Simulations of Soft Matter Methodologies and Applications Boulder July, 19-20, 2012 K. Kremer Max Planck Institute for Polymer Research, Mainz Overview Simulations, general considerations

More information

Department of Chemical Engineering University of California, Santa Barbara Spring Exercise 3. Due: Thursday, 5/3/12

Department of Chemical Engineering University of California, Santa Barbara Spring Exercise 3. Due: Thursday, 5/3/12 Department of Chemical Engineering ChE 210D University of California, Santa Barbara Spring 2012 Exercise 3 Due: Thursday, 5/3/12 Objective: To learn how to write & compile Fortran libraries for Python,

More information

Topics in Soft Matter Physics Theory and Modeling Introduction to Computer Modeling & Lab Set-up

Topics in Soft Matter Physics Theory and Modeling Introduction to Computer Modeling & Lab Set-up Topics in Soft Matter Physics Theory and Modeling Introduction to Computer Modeling & Lab Set-up Topics Today VMD Tutorial Molecular Simulation Monte Carlo (MC) Method Molecular Dynamics (MD) Method Euler

More information

Introduction to Benchmark Test for Multi-scale Computational Materials Software

Introduction to Benchmark Test for Multi-scale Computational Materials Software Introduction to Benchmark Test for Multi-scale Computational Materials Software Shun Xu*, Jian Zhang, Zhong Jin xushun@sccas.cn Computer Network Information Center Chinese Academy of Sciences (IPCC member)

More information

Using Molecular Dynamics to Compute Properties CHEM 430

Using Molecular Dynamics to Compute Properties CHEM 430 Using Molecular Dynamics to Compute Properties CHEM 43 Heat Capacity and Energy Fluctuations Running an MD Simulation Equilibration Phase Before data-collection and results can be analyzed the system

More information

JASS Modeling and visualization of molecular dynamic processes

JASS Modeling and visualization of molecular dynamic processes JASS 2009 Konstantin Shefov Modeling and visualization of molecular dynamic processes St Petersburg State University, Physics faculty, Department of Computational Physics Supervisor PhD Stepanova Margarita

More information

Diffusion of Water and Diatomic Oxygen in Poly(3-hexylthiophene) Melt: A Molecular Dynamics Simulation Study

Diffusion of Water and Diatomic Oxygen in Poly(3-hexylthiophene) Melt: A Molecular Dynamics Simulation Study Diffusion of Water and Diatomic Oxygen in Poly(3-hexylthiophene) Melt: A Molecular Dynamics Simulation Study Julia Deitz, Yeneneh Yimer, and Mesfin Tsige Department of Polymer Science University of Akron

More information

On the Dynamics and Disentanglement in Thin and Two-Dimensional Polymer Films

On the Dynamics and Disentanglement in Thin and Two-Dimensional Polymer Films J. Phys. IV France 1 (006) Pr1-1 c EDP Sciences, Les Ulis On the Dynamics and Disentanglement in Thin and Two-Dimensional Polymer Films H. Meyer, T. Kreer, A. Cavallo, J. P. Wittmer and J. Baschnagel 1

More information

Molecular Dynamic Simulation Study of the Volume Transition of PNIPAAm Hydrogels

Molecular Dynamic Simulation Study of the Volume Transition of PNIPAAm Hydrogels Molecular Dynamic Simulation Study of the Volume Transition of PNIPAAm Hydrogels Jonathan Walter 1, Jadran Vrabec 2, Hans Hasse 1 1 Laboratory of Engineering, University of Kaiserslautern, Germany 2 and

More information

General-purpose Coarse-grained. Molecular Dynamics Program COGNAC

General-purpose Coarse-grained. Molecular Dynamics Program COGNAC General-purpose Coarse-grained Molecular Dynamics Program COGNAC (COarse-Grained molecular dynamics program by NAgoya Cooperation) Takeshi Aoyagi JCII, Doi project 0 sec -3 msec -6 sec -9 nsec -12 psec

More information

Table of Contents. Table of Contents LAMMPS trajectories into QuantumATK

Table of Contents. Table of Contents LAMMPS trajectories into QuantumATK Table of Contents Table of Contents LAMMPS trajectories into QuantumATK Preparing a LAMMPS script Running LAMMPS Importing to QuantumATK Postprocessing LAMMPS trajectories References 1 2 2 3 3 5 8 QuantumATK

More information

Simulating Soft Matter with ESPResSo, ESPResSo++ and VOTCA!

Simulating Soft Matter with ESPResSo, ESPResSo++ and VOTCA! Simulating Soft Matter with ESPResSo, ESPResSo++ and VOTCA! Christian Holm! Institut für Computerphysik, Universität Stuttgart Stuttgart, Germany! 1! Intro to Soft Matter Simulations! What is Soft Matter?

More information

Molecular dynamics simulation. CS/CME/BioE/Biophys/BMI 279 Oct. 5 and 10, 2017 Ron Dror

Molecular dynamics simulation. CS/CME/BioE/Biophys/BMI 279 Oct. 5 and 10, 2017 Ron Dror Molecular dynamics simulation CS/CME/BioE/Biophys/BMI 279 Oct. 5 and 10, 2017 Ron Dror 1 Outline Molecular dynamics (MD): The basic idea Equations of motion Key properties of MD simulations Sample applications

More information

k θ (θ θ 0 ) 2 angles r i j r i j

k θ (θ θ 0 ) 2 angles r i j r i j 1 Force fields 1.1 Introduction The term force field is slightly misleading, since it refers to the parameters of the potential used to calculate the forces (via gradient) in molecular dynamics simulations.

More information

Olaf Lenz. MPI for Polymer Research, Mainz. Olaf Lenz October erphysik, Universität Stuttgart, Germany. th Summer School at the ICP

Olaf Lenz. MPI for Polymer Research, Mainz. Olaf Lenz October erphysik, Universität Stuttgart, Germany. th Summer School at the ICP Olaf Lenz MPI for Polymer Research, Mainz http://www.icp.uni-stuttgart.de http://www.icp.uni-stuttgart.de erphysik, Universität Stuttgart, Germany Welcome to the Summer School Welcome to the Summer School

More information

Mesoscopic membrane simulations with mbtools

Mesoscopic membrane simulations with mbtools Mesoscopic membrane simulations with mbtools Tristan Bereau, Mingyang Hu, Patrick Diggins, and Markus Deserno Department of Physics Carnegie Mellon University Pittsburgh, PA USA October 4, 2012 1 Introduction

More information

Molecular Dynamics of Covalent Crystals

Molecular Dynamics of Covalent Crystals Molecular Dynamics of Covalent Crystals J. Hahn and H.-R. Trebin Institut für Theoretische und Angewandte Physik, Universität Stuttgart, D-70550 Stuttgart, Germany Abstract. A molecular mechanics-like

More information

Modeling and visualization of molecular dynamic processes

Modeling and visualization of molecular dynamic processes JASS 2009 Konstantin Shefov Modeling and visualization of molecular dynamic processes St-Petersburg State University Physics faculty Department of Computational Physics Supervisor PhD Stepanova Margarita

More information

SIMCON - Computer Simulation of Condensed Matter

SIMCON - Computer Simulation of Condensed Matter Coordinating unit: 230 - ETSETB - Barcelona School of Telecommunications Engineering Teaching unit: 748 - FIS - Department of Physics Academic year: Degree: 2017 BACHELOR'S DEGREE IN ENGINEERING PHYSICS

More information

Supporting information

Supporting information Electronic Supplementary Material ESI for Physical Chemistry Chemical Physics. This journal is the Owner Societies 2018 Supporting information Understanding three-body contributions to coarse-grained force

More information

Size-Selective Nanoparticle Assembly on Substrates. by DNA Density Patterning

Size-Selective Nanoparticle Assembly on Substrates. by DNA Density Patterning Supporting Information: Size-Selective Nanoparticle Assembly on Substrates by DNA Density Patterning Benjamin D. Myers 1,2, Qing-Yuan Lin 1, Huanxin Wu 3, Erik Luijten 1,3,4, Chad A. Mirkin 1,5,6 and Vinayak

More information

Why Proteins Fold? (Parts of this presentation are based on work of Ashok Kolaskar) CS490B: Introduction to Bioinformatics Mar.

Why Proteins Fold? (Parts of this presentation are based on work of Ashok Kolaskar) CS490B: Introduction to Bioinformatics Mar. Why Proteins Fold? (Parts of this presentation are based on work of Ashok Kolaskar) CS490B: Introduction to Bioinformatics Mar. 25, 2002 Molecular Dynamics: Introduction At physiological conditions, the

More information

ICCP Project 2 - Advanced Monte Carlo Methods Choose one of the three options below

ICCP Project 2 - Advanced Monte Carlo Methods Choose one of the three options below ICCP Project 2 - Advanced Monte Carlo Methods Choose one of the three options below Introduction In statistical physics Monte Carlo methods are considered to have started in the Manhattan project (1940

More information

Adaptive resolution molecular-dynamics simulation: Changing the degrees of freedom on the fly

Adaptive resolution molecular-dynamics simulation: Changing the degrees of freedom on the fly THE JOURNAL OF CHEMICAL PHYSICS 123, 224106 2005 Adaptive resolution molecular-dynamics simulation: Changing the degrees of freedom on the fly Matej Praprotnik, a Luigi Delle Site, and Kurt Kremer b Max-Planck-Institut

More information

Universal Repulsive Contribution to the. Solvent-Induced Interaction Between Sizable, Curved Hydrophobes: Supporting Information

Universal Repulsive Contribution to the. Solvent-Induced Interaction Between Sizable, Curved Hydrophobes: Supporting Information Universal Repulsive Contribution to the Solvent-Induced Interaction Between Sizable, Curved Hydrophobes: Supporting Information B. Shadrack Jabes, Dusan Bratko, and Alenka Luzar Department of Chemistry,

More information

Structural and dynamical properties of Polyethylenimine in explicit water at different protonation states: A Molecular Dynamics Study

Structural and dynamical properties of Polyethylenimine in explicit water at different protonation states: A Molecular Dynamics Study This journal is The Royal Society of Chemistry Structural and dynamical properties of Polyethylenimine in explicit water at different protonation states: A Molecular Dynamics Study Chandan Kumar Choudhury

More information

Speeding up path integral simulations

Speeding up path integral simulations Speeding up path integral simulations Thomas Markland and David Manolopoulos Department of Chemistry University of Oxford Funded by the US Office of Naval Research and the UK EPSRC Outline 1. Ring polymer

More information

Effects of interaction between nanopore and polymer on translocation time

Effects of interaction between nanopore and polymer on translocation time Effects of interaction between nanopore and polymer on translocation time Mohammadreza Niknam Hamidabad and Rouhollah Haji Abdolvahab Physics Department, Iran University of Science and Technology (IUST),

More information

CARBON 2004 Providence, Rhode Island. Adsorption of Flexible n-butane and n-hexane on Graphitized Thermal Carbon Black and in Slit Pores

CARBON 2004 Providence, Rhode Island. Adsorption of Flexible n-butane and n-hexane on Graphitized Thermal Carbon Black and in Slit Pores CARBON Providence, Rhode Island Adsorption of Flexible n-butane and n-hexane on Graphitized Thermal Carbon Black and in Slit Pores D. D. Do* and H. D. Do, University of Queensland, St. Lucia, Qld 7, Australia

More information

Advantages of a Finite Extensible Nonlinear Elastic Potential in Lattice Boltzmann Simulations

Advantages of a Finite Extensible Nonlinear Elastic Potential in Lattice Boltzmann Simulations The Hilltop Review Volume 7 Issue 1 Winter 2014 Article 10 December 2014 Advantages of a Finite Extensible Nonlinear Elastic Potential in Lattice Boltzmann Simulations Tai-Hsien Wu Western Michigan University

More information

PH 548 Atomistic Simulation Techniques

PH 548 Atomistic Simulation Techniques PH 548 Atomistic Simulation Techniques Lectures: Lab: 2-0-2-6 Tuesday 12-1 PM Thursday 12-1 PM Monday 2-5 PM P. K. Padmanabhan PH548: Two Excellent Books How to do it? 1 2 F 12 F 23 3 F i = F ij j i F

More information

Charge equilibration

Charge equilibration Charge equilibration Taylor expansion of energy of atom A @E E A (Q) =E A0 + Q A + 1 @Q A 0 2 Q2 A @ 2 E @Q 2 A 0 +... The corresponding energy of cation/anion and neutral atom E A (+1) = E A0 + @E @Q

More information

Hydrogels in charged solvents

Hydrogels in charged solvents Hydrogels in charged solvents Peter Košovan, Christian Holm, Tobias Richter 27. May 2013 Institute for Computational Physics Pfaffenwaldring 27 D-70569 Stuttgart Germany Tobias Richter (ICP, Stuttgart)

More information

Department of Chemical Engineering University of California, Santa Barbara Spring Exercise 2. Due: Thursday, 4/19/09

Department of Chemical Engineering University of California, Santa Barbara Spring Exercise 2. Due: Thursday, 4/19/09 Department of Chemical Engineering ChE 210D University of California, Santa Barbara Spring 2012 Exercise 2 Due: Thursday, 4/19/09 Objective: To learn how to compile Fortran libraries for Python, and to

More information

Directed Assembly of Functionalized Nanoparticles with Amphiphilic Diblock Copolymers. Contents

Directed Assembly of Functionalized Nanoparticles with Amphiphilic Diblock Copolymers. Contents Electronic Supplementary Material (ESI) for Physical Chemistry Chemical Physics. This journal is the Owner Societies 2017 Electronic Supplementary Information for Directed Assembly of Functionalized Nanoparticles

More information

Supporting Information Soft Nanoparticles: Nano Ionic Networks of Associated Ionic Polymers

Supporting Information Soft Nanoparticles: Nano Ionic Networks of Associated Ionic Polymers Electronic Supplementary Material (ESI) for Nanoscale. This journal is The Royal Society of Chemistry 2016 Supporting Information Soft Nanoparticles: Nano Ionic Networks of Associated Ionic Polymers Dipak

More information

Conformational Searching using MacroModel and ConfGen. John Shelley Schrödinger Fellow

Conformational Searching using MacroModel and ConfGen. John Shelley Schrödinger Fellow Conformational Searching using MacroModel and ConfGen John Shelley Schrödinger Fellow Overview Types of conformational searching applications MacroModel s conformation generation procedure General features

More information

Scientific Computing II

Scientific Computing II Scientific Computing II Molecular Dynamics Simulation Michael Bader SCCS Summer Term 2015 Molecular Dynamics Simulation, Summer Term 2015 1 Continuum Mechanics for Fluid Mechanics? Molecular Dynamics the

More information

Equilibrium sampling of self-associating polymer solutions: A parallel selective tempering approach

Equilibrium sampling of self-associating polymer solutions: A parallel selective tempering approach THE JOURNAL OF CHEMICAL PHYSICS 123, 124912 2005 Equilibrium sampling of self-associating polymer solutions: A parallel selective tempering approach Chakravarthy Ayyagari, a Dmitry Bedrov, and Grant D.

More information

Accelerating Rosetta with OpenMM. Peter Eastman. RosettaCon, August 5, 2010

Accelerating Rosetta with OpenMM. Peter Eastman. RosettaCon, August 5, 2010 Accelerating Rosetta with OpenMM Peter Eastman RosettaCon, August 5, 2010 What is OpenMM? OpenMM is a library for molecular modeling on high performance architectures. Performance 600 500 502 400 ns/day

More information

Advanced Molecular Dynamics

Advanced Molecular Dynamics Advanced Molecular Dynamics Introduction May 2, 2017 Who am I? I am an associate professor at Theoretical Physics Topics I work on: Algorithms for (parallel) molecular simulations including GPU acceleration

More information

Molecular Dynamics Simulation of Nanometric Machining Under Realistic Cutting Conditions Using LAMMPS

Molecular Dynamics Simulation of Nanometric Machining Under Realistic Cutting Conditions Using LAMMPS Molecular Dynamics Simulation of Nanometric Machining Under Realistic Cutting Conditions Using LAMMPS Rapeepan Promyoo Thesis Presentation Advisor: Dr. Hazim El-Mounayri Department of Mechanical Engineering

More information

Supplementary Information for: Controlling Cellular Uptake of Nanoparticles with ph-sensitive Polymers

Supplementary Information for: Controlling Cellular Uptake of Nanoparticles with ph-sensitive Polymers Supplementary Information for: Controlling Cellular Uptake of Nanoparticles with ph-sensitive Polymers Hong-ming Ding 1 & Yu-qiang Ma 1,2, 1 National Laboratory of Solid State Microstructures and Department

More information

EAM. ReaxFF. PROBLEM B Fracture of a single crystal of silicon

EAM. ReaxFF. PROBLEM B Fracture of a single crystal of silicon PROBLEM B Fracture of a single crystal of silicon This problem set utilizes a new simulation method based on Computational Materials Design Facility (CMDF) to model fracture in a brittle material, silicon.

More information

Atomistic Modeling of Small-Angle Scattering Data Using SASSIE-web

Atomistic Modeling of Small-Angle Scattering Data Using SASSIE-web Course Introduction Atomistic Modeling of Small-Angle Scattering Data Using SASSIE-web September 21-23, 2016 Advanced Photon Source Argonne National Laboratory, Argonne, IL ccpsas.org Scatters & Simulators

More information

Effect of equilibration on primitive path analyses of entangled polymers

Effect of equilibration on primitive path analyses of entangled polymers PHYSICAL REVIEW E 72, 061802 2005 Effect of equilibration on primitive path analyses of entangled polymers Robert S. Hoy* and Mark O. Robbins Department of Physics and Astronomy, Johns Hopkins University,

More information

Virtual material Design

Virtual material Design Fraunhofer Institute for Algorithms and Scientific Computing SCAI Virtual material Design Foto: viastore systems 1 virtual Material Design Many of the challenges of the 21st century such as the development

More information

A Study of the Thermal Properties of a One. Dimensional Lennard-Jones System

A Study of the Thermal Properties of a One. Dimensional Lennard-Jones System A Study of the Thermal Properties of a One Dimensional Lennard-Jones System Abstract In this study, the behavior of a one dimensional (1D) Lennard-Jones (LJ) system is simulated. As part of this research,

More information

Advanced Molecular Molecular Dynamics

Advanced Molecular Molecular Dynamics Advanced Molecular Molecular Dynamics Technical details May 12, 2014 Integration of harmonic oscillator r m period = 2 k k and the temperature T determine the sampling of x (here T is related with v 0

More information

Tutorial on Probabilistic Programming with PyMC3

Tutorial on Probabilistic Programming with PyMC3 185.A83 Machine Learning for Health Informatics 2017S, VU, 2.0 h, 3.0 ECTS Tutorial 02-04.04.2017 Tutorial on Probabilistic Programming with PyMC3 florian.endel@tuwien.ac.at http://hci-kdd.org/machine-learning-for-health-informatics-course

More information

MOLECULAR MODELING IN BIOLOGY (BIO 3356) SYLLABUS

MOLECULAR MODELING IN BIOLOGY (BIO 3356) SYLLABUS New York City College of Technology School of Arts and Sciences Department of Biological Sciences MOLECULAR MODELING IN BIOLOGY (BIO 3356) SYLLABUS Course Information Course Title: Molecular Modeling in

More information

arxiv: v1 [cond-mat.stat-mech] 6 Jan 2014

arxiv: v1 [cond-mat.stat-mech] 6 Jan 2014 arxiv:1401.1181v1 [cond-mat.stat-mech] 6 Jan 2014 Determination of Forces from a Potential in Molecular Dynamics (note) Bernard Monasse Mines-ParisTech, Cemef bernard.monasse@mines-paristech.fr January

More information

Parallel Utility for Modeling of Molecular Aggregation

Parallel Utility for Modeling of Molecular Aggregation Parallel Utility for Modeling of Molecular Aggregation Peter Spijker, Bart Markvoort and Peter Hilbers BioModeling and bioinformatics Eindhoven University of Technology Eindhoven,The Netherlands p.spijker@pumma.nl

More information

2008 Biowerkzeug Ltd.

2008 Biowerkzeug Ltd. 2008 Biowerkzeug Ltd. 1 Contents Summary...3 1 Simulation...4 1.1 Setup...4 1.2 Output...4 2 Settings...5 3 Analysis...9 3.1 Setup...9 3.2 Input options...9 3.3 Descriptions...10 Please note that we cannot

More information

Systematic Coarse-Graining and Concurrent Multiresolution Simulation of Molecular Liquids

Systematic Coarse-Graining and Concurrent Multiresolution Simulation of Molecular Liquids Systematic Coarse-Graining and Concurrent Multiresolution Simulation of Molecular Liquids Cameron F. Abrams Department of Chemical and Biological Engineering Drexel University Philadelphia, PA USA 9 June

More information

2D Clausius Clapeyron equation

2D Clausius Clapeyron equation 2D Clausius Clapeyron equation 1/14 Aim: Verify the Clausius Clapeyron equation by simulations of a 2D model of matter Model: 8-4 type potential ( Lennard-Jones in 2D) u(r) = 1 r 8 1 r 4 Hard attractive

More information

Computer simulation methods (2) Dr. Vania Calandrini

Computer simulation methods (2) Dr. Vania Calandrini Computer simulation methods (2) Dr. Vania Calandrini in the previous lecture: time average versus ensemble average MC versus MD simulations equipartition theorem (=> computing T) virial theorem (=> computing

More information

Biomolecular modeling II

Biomolecular modeling II 2015, December 16 System boundary and the solvent Biomolecule in solution typical MD simulations molecular system in aqueous solution task make the system as small as possible (reduce cost) straightforward

More information

Bioengineering 215. An Introduction to Molecular Dynamics for Biomolecules

Bioengineering 215. An Introduction to Molecular Dynamics for Biomolecules Bioengineering 215 An Introduction to Molecular Dynamics for Biomolecules David Parker May 18, 2007 ntroduction A principal tool to study biological molecules is molecular dynamics simulations (MD). MD

More information

Course Introduction. SASSIE CCP-SAS Workshop. January 23-25, ISIS Neutron and Muon Source Rutherford Appleton Laboratory UK

Course Introduction. SASSIE CCP-SAS Workshop. January 23-25, ISIS Neutron and Muon Source Rutherford Appleton Laboratory UK Course Introduction SASSIE CCP-SAS Workshop January 23-25, 2017 ISIS Neutron and Muon Source Rutherford Appleton Laboratory UK ccpsas.org Scatters & Simulators Develop a community of users and developers

More information

arxiv: v2 [cond-mat.mtrl-sci] 6 Jul 2017

arxiv: v2 [cond-mat.mtrl-sci] 6 Jul 2017 ATK-ForceField: A New Generation Molecular Dynamics Software Package arxiv:1701.02495v2 [cond-mat.mtrl-sci] 6 Jul 2017 1. Introduction Julian Schneider 1, Jan Hamaekers 2, Samuel T. Chill 1, Søren Smidstrup

More information

2D Clausius Clapeyron equation

2D Clausius Clapeyron equation 2D Clausius Clapeyron equation 1/14 Aim: Verify the Clausius Clapeyron equation by simulations of a 2D model of matter Model: 8-4 type potential ( Lennard-Jones in 2D) u(r) = 1 r 8 1 r 4 Hard attractive

More information

Structuring of hydrophobic and hydrophilic polymers at interfaces Stephen Donaldson ChE 210D Final Project Abstract

Structuring of hydrophobic and hydrophilic polymers at interfaces Stephen Donaldson ChE 210D Final Project Abstract Structuring of hydrophobic and hydrophilic polymers at interfaces Stephen Donaldson ChE 210D Final Project Abstract In this work, a simplified Lennard-Jones (LJ) sphere model is used to simulate the aggregation,

More information

Origins of Mechanical and Rheological Properties of Polymer Nanocomposites. Venkat Ganesan

Origins of Mechanical and Rheological Properties of Polymer Nanocomposites. Venkat Ganesan Department of Chemical Engineering University of Texas@Austin Origins of Mechanical and Rheological Properties of Polymer Nanocomposites Venkat Ganesan $$$: NSF DMR, Welch Foundation Megha Surve, Victor

More information

Overview. For this we will use the Q program ( for carrying out EVB calculations.

Overview. For this we will use the Q program (  for carrying out EVB calculations. EVB Tutorial: S N 2 Reaction in Gas Phase and Solution Overview The objective of this tutorial is to give a glimpse into the main features of the Empirical Valence Bond (EVB) method. We will study a simple

More information

Assignment 2 Atomic-Level Molecular Modeling

Assignment 2 Atomic-Level Molecular Modeling Assignment 2 Atomic-Level Molecular Modeling CS/BIOE/CME/BIOPHYS/BIOMEDIN 279 Due: November 3, 2016 at 3:00 PM The goal of this assignment is to understand the biological and computational aspects of macromolecular

More information

Reactive potentials and applications

Reactive potentials and applications 1.021, 3.021, 10.333, 22.00 Introduction to Modeling and Simulation Spring 2011 Part I Continuum and particle methods Reactive potentials and applications Lecture 8 Markus J. Buehler Laboratory for Atomistic

More information

Computational Methods for Nonlinear Systems

Computational Methods for Nonlinear Systems Computational Methods for Nonlinear Systems Cornell Physics 682 / CIS 629 James P. Sethna Christopher R. Myers Computational Methods for Nonlinear Systems Graduate computational science laboratory course

More information

Molecular Dynamics Simulations

Molecular Dynamics Simulations Molecular Dynamics Simulations Dr. Kasra Momeni www.knanosys.com Outline Long-range Interactions Ewald Sum Fast Multipole Method Spherically Truncated Coulombic Potential Speeding up Calculations SPaSM

More information

Analysis of the simulation

Analysis of the simulation Analysis of the simulation Marcus Elstner and Tomáš Kubař January 7, 2014 Thermodynamic properties time averages of thermodynamic quantites correspond to ensemble averages (ergodic theorem) some quantities

More information

Winmostar tutorial LAMMPS Polymer modeling V X-Ability Co,. Ltd. 2017/7/6

Winmostar tutorial LAMMPS Polymer modeling V X-Ability Co,. Ltd. 2017/7/6 Winmostar tutorial LAMMPS Polymer modeling V7.021 X-Ability Co,. Ltd. question@winmostar.com 2017/7/6 Contents Configure I. Register a monomer II. Define a polymer III. Build a simulation cell IV. Execute

More information

Amorphous Polymers: Polymer Conformation Laboratory 1: Module 1

Amorphous Polymers: Polymer Conformation Laboratory 1: Module 1 D E P A R T M E N T O F M A T E R I A L S S C I E N C E A N D E N G I N E E R I N G M A S S A C H U S E T T S I N S T I T U T E O F T E C H N O L O G Y 3.014 Materials Laboratory Fall 2008 Amorphous Polymers:

More information

An Implicit Divalent Counterion Force Field for RNA Molecular Dynamics

An Implicit Divalent Counterion Force Field for RNA Molecular Dynamics An Implicit Divalent Counterion Force Field for RNA Molecular Dynamics Paul S. Henke 1 1, 2, a and Chi H. Mak 1 Department of Chemistry and 2 Center of Applied Mathematical Sciences, University of Southern

More information

Molecular Dynamics Simulation of a Nanoconfined Water Film

Molecular Dynamics Simulation of a Nanoconfined Water Film Molecular Dynamics Simulation of a Nanoconfined Water Film Kyle Lindquist, Shu-Han Chao May 7, 2013 1 Introduction The behavior of water confined in nano-scale environment is of interest in many applications.

More information

LAMMPS Performance Benchmark on VSC-1 and VSC-2

LAMMPS Performance Benchmark on VSC-1 and VSC-2 LAMMPS Performance Benchmark on VSC-1 and VSC-2 Daniel Tunega and Roland Šolc Institute of Soil Research, University of Natural Resources and Life Sciences VSC meeting, Neusiedl am See, February 27-28,

More information

All-atom Molecular Mechanics. Trent E. Balius AMS 535 / CHE /27/2010

All-atom Molecular Mechanics. Trent E. Balius AMS 535 / CHE /27/2010 All-atom Molecular Mechanics Trent E. Balius AMS 535 / CHE 535 09/27/2010 Outline Molecular models Molecular mechanics Force Fields Potential energy function functional form parameters and parameterization

More information

Controlled healing of graphene nanopore

Controlled healing of graphene nanopore Controlled healing of graphene nanopore Konstantin Zakharchenko Alexander Balatsky Zakharchenko K.V., Balatsky A.V. Controlled healing of graphene nanopore. Carbon (80), December 2014, pp. 12 18. http://dx.doi.org/10.1016/j.carbon.2014.07.085

More information

Ab initio molecular dynamics. Simone Piccinin CNR-IOM DEMOCRITOS Trieste, Italy. Bangalore, 04 September 2014

Ab initio molecular dynamics. Simone Piccinin CNR-IOM DEMOCRITOS Trieste, Italy. Bangalore, 04 September 2014 Ab initio molecular dynamics Simone Piccinin CNR-IOM DEMOCRITOS Trieste, Italy Bangalore, 04 September 2014 What is MD? 1) Liquid 4) Dye/TiO2/electrolyte 2) Liquids 3) Solvated protein 5) Solid to liquid

More information

First steps toward the construction of a hyperphase diagram that covers different classes of short polymer chains

First steps toward the construction of a hyperphase diagram that covers different classes of short polymer chains Cent. Eur. J. Phys. 12(6) 2014 421-426 DOI: 10.2478/s11534-014-0461-z Central European Journal of Physics First steps toward the construction of a hyperphase diagram that covers different classes of short

More information

PHASE TRANSITIONS IN SOFT MATTER SYSTEMS

PHASE TRANSITIONS IN SOFT MATTER SYSTEMS OUTLINE: Topic D. PHASE TRANSITIONS IN SOFT MATTER SYSTEMS Definition of a phase Classification of phase transitions Thermodynamics of mixing (gases, polymers, etc.) Mean-field approaches in the spirit

More information

Morphology of Supported Polymer Electrolyte. Ultra-thin Films: a Numerical Study. Supporting Information

Morphology of Supported Polymer Electrolyte. Ultra-thin Films: a Numerical Study. Supporting Information Morphology of Supported Polymer Electrolyte Ultra-thin Films: a Numerical Study Supporting Information Daiane Damasceno Borges,, Gerard Gebel, Alejandro A. Franco, Kourosh Malek, and Stefano Mossa, Univ.

More information

Part 2: Molecular Dynamics. Literature History Practical Issues

Part 2: Molecular Dynamics. Literature History Practical Issues Part 2: Molecular Dynamics Literature History Practical Issues 1 Literature A. K. Hartmann Big Practical Guide to Computer Simulations (World Scientific, 2015) M. P. Allen and D.J. Tildesley Computer Simulations

More information

Computation of non-bonded interactions: Part 1

Computation of non-bonded interactions: Part 1 Computation of non-bonded interactions: Part 1 Computation of non-local (non-bonded) interactions in the potential function E p non-local scales with the number of atoms as N. For the large molecular systems

More information

Supplementary Information for Atomistic Simulation of Spinodal Phase Separation Preceding Polymer Crystallization

Supplementary Information for Atomistic Simulation of Spinodal Phase Separation Preceding Polymer Crystallization Supplementary Information for Atomistic Simulation of Spinodal Phase Separation Preceding Polymer Crystallization Richard H. Gee * Naida Lacevic and Laurence E. Fried University of California Lawrence

More information

Citation for published version (APA): Sok, R. M. (1994). Permeation of small molecules across a polymer membrane: a computer simulation study s.n.

Citation for published version (APA): Sok, R. M. (1994). Permeation of small molecules across a polymer membrane: a computer simulation study s.n. University of Groningen Permeation of small molecules across a polymer membrane Sok, Robert artin PRTANT NTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from

More information

Deformation of Elastomeric Networks: Relation between Molecular Level Deformation and Classical Statistical Mechanics Models of Rubber Elasticity

Deformation of Elastomeric Networks: Relation between Molecular Level Deformation and Classical Statistical Mechanics Models of Rubber Elasticity Deformation of Elastomeric Networks: Relation between Molecular Level Deformation and Classical Statistical Mechanics Models of Rubber Elasticity J. S. Bergström and M. C. Boyce Department of Mechanical

More information

Distribution of chains in polymer brushes produced by a grafting from mechanism

Distribution of chains in polymer brushes produced by a grafting from mechanism SUPPLEMENTARY INFORMATION Distribution of chains in polymer brushes produced by a grafting from mechanism Andre Martinez, Jan-Michael Y. Carrillo, Andrey V. Dobrynin,, * and Douglas H. Adamson, * Department

More information

Winmostar tutorial LAMMPS Polymer Annealing V X-Ability Co., Ltd. 2018/01/15

Winmostar tutorial LAMMPS Polymer Annealing V X-Ability Co., Ltd. 2018/01/15 Winmostar tutorial LAMMPS Polymer Annealing V8.007 X-Ability Co., Ltd. question@winmostar.com 2018/01/15 Summary In this tutorial we will calculate glass transition temperature from the cooling process

More information

Modeling Biological Systems Opportunities for Computer Scientists

Modeling Biological Systems Opportunities for Computer Scientists Modeling Biological Systems Opportunities for Computer Scientists Filip Jagodzinski RBO Tutorial Series 25 June 2007 Computer Science Robotics & Biology Laboratory Protein: πρώτα, "prota, of Primary Importance

More information

Supporting Information

Supporting Information Projection of atomistic simulation data for the dynamics of entangled polymers onto the tube theory: Calculation of the segment survival probability function and comparison with modern tube models Pavlos

More information

Can a continuum solvent model reproduce the free energy landscape of a β-hairpin folding in water?

Can a continuum solvent model reproduce the free energy landscape of a β-hairpin folding in water? Can a continuum solvent model reproduce the free energy landscape of a β-hairpin folding in water? Ruhong Zhou 1 and Bruce J. Berne 2 1 IBM Thomas J. Watson Research Center; and 2 Department of Chemistry,

More information

Contents Why use NEURON ( 5-10 mins) Basics of NEURON (20-25 mins) Exercises (45 mins) Wrap Up (10 mins)

Contents Why use NEURON ( 5-10 mins) Basics of NEURON (20-25 mins) Exercises (45 mins) Wrap Up (10 mins) Contents Why use NEURON ( 5-10 mins) 3 Basics of NEURON (20-25 mins) 8 Exercises (45 mins) 27 Wrap Up (10 mins) 28 (Many thanks to David Sterratt (Uni of Edinburgh) for allowing the use of his tutorials

More information

Shear Properties and Wrinkling Behaviors of Finite Sized Graphene

Shear Properties and Wrinkling Behaviors of Finite Sized Graphene Shear Properties and Wrinkling Behaviors of Finite Sized Graphene Kyoungmin Min, Namjung Kim and Ravi Bhadauria May 10, 2010 Abstract In this project, we investigate the shear properties of finite sized

More information