Dissipative Particle Dynamics. Molecular Dynamics, why slow? MD solves Newton’s equations of motion for atoms/molecules: Why MD is slow?

Slides:



Advertisements
Similar presentations
Time averages and ensemble averages
Advertisements

Continuum Simulation Monday, 9/30/2002. Class Progress Visualization: abstract concept (stress,2D, 3D), mechanical field Stochastic simulations: random.
Simulazione di Biomolecole: metodi e applicazioni giorgio colombo
Statistical mechanics
Formulation of an algorithm to implement Lowe-Andersen thermostat in parallel molecular simulation package, LAMMPS Prathyusha K. R. and P. B. Sunil Kumar.
Biological fluid mechanics at the micro‐ and nanoscale Lecture 7: Atomistic Modelling Classical Molecular Dynamics Simulations of Driven Systems Anne Tanguy.
Advanced Molecular Dynamics Velocity scaling Andersen Thermostat Hamiltonian & Lagrangian Appendix A Nose-Hoover thermostat.
Molecular Dynamics at Constant Temperature and Pressure Section 6.7 in M.M.
Transfer FAS UAS SAINT-PETERSBURG STATE UNIVERSITY COMPUTATIONAL PHYSICS Introduction Physical basis Molecular dynamics Temperature and thermostat Numerical.
Lecture 13: Conformational Sampling: MC and MD Dr. Ronald M. Levy Contributions from Mike Andrec and Daniel Weinstock Statistical Thermodynamics.
Molecular Dynamics. Basic Idea Solve Newton’s equations of motion Choose a force field (specified by a potential V) appropriate for the given system under.
Survey of Molecular Dynamics Simulations By Will Welch For Jan Kubelka CHEM 4560/5560 Fall, 2014 University of Wyoming.
An Introduction to Multiscale Modeling Scientific Computing and Numerical Analysis Seminar CAAM 699.
Incorporating Solvent Effects Into Molecular Dynamics: Potentials of Mean Force (PMF) and Stochastic Dynamics Eva ZurekSection 6.8 of M.M.
Statistical Models of Solvation Eva Zurek Chemistry Final Presentation.
1Notes. 2 Building implicit surfaces  Simplest examples: a plane, a sphere  Can do unions and intersections with min and max  This works great for.
Course Outline 1.MATLAB tutorial 2.Motion of systems that can be idealized as particles Description of motion; Newton’s laws; Calculating forces required.
CE 400 Honors Seminar Molecular Simulation Prof. Kofke Department of Chemical Engineering University at Buffalo, State University of New York Class 3.
1 MECH 221 FLUID MECHANICS (Fall 06/07) Tutorial 6 FLUID KINETMATICS.
Symmetry. Phase Continuity Phase density is conserved by Liouville’s theorem.  Distribution function D  Points as ensemble members Consider as a fluid.
Two Approaches to Multiphysics Modeling Sun, Yongqi FAU Erlangen-Nürnberg.
Motion near an equilibrium position can be approximated by SHM
1 CE 530 Molecular Simulation Lecture 2 David A. Kofke Department of Chemical Engineering SUNY Buffalo
Joo Chul Yoon with Prof. Scott T. Dunham Electrical Engineering University of Washington Molecular Dynamics Simulations.
Mechanical Energy and Simple Harmonic Oscillator 8.01 Week 09D
Motion of a mass at the end of a spring Differential equation for simple harmonic oscillation Amplitude, period, frequency and angular frequency Energetics.
Statistical Mechanics of Proteins
Computational Science jsusciencesimulation Principles of Scientific Simulation Spring Semester 2005 Geoffrey Fox Community.
Monte-Carlo simulations of the structure of complex liquids with various interaction potentials Alja ž Godec Advisers: prof. dr. Janko Jamnik and doc.
Free energies and phase transitions. Condition for phase coexistence in a one-component system:
Javier Junquera Molecular dynamics in the microcanonical (NVE) ensemble: the Verlet algorithm.
Molecular Dynamics A brief overview. 2 Notes - Websites "A Molecular Dynamics Primer", F. Ercolessi
Periodic Motion and Theory of Oscillations m 0 X Restoring force F x = -kx is a linear function of displacement x from equilibrium position x=0. Harmonic.
20 B Week II Chapters 9 -10) Macroscopic Pressure Microscopic pressure( the kinetic theory of gases: no potential energy) Real Gases: van der Waals Equation.
Namas Chandra Introduction to Mechanical engineering Hibbler Chapter 1-1 EML 3004C CHAPTER ONE General Principles.
Statistical Mechanics and Multi-Scale Simulation Methods ChBE
Ch 24 pages Lecture 9 – Flexible macromolecules.
Study of Pentacene clustering MAE 715 Project Report By: Krishna Iyengar.
FLUID PROPERTIES Independent variables SCALARS VECTORS TENSORS.
Advanced Molecular Dynamics Velocity scaling Andersen Thermostat Hamiltonian & Lagrangian Appendix A Nose-Hoover thermostat.
7. Lecture SS 2005Optimization, Energy Landscapes, Protein Folding1 V7: Diffusional association of proteins and Brownian dynamics simulations Brownian.
2. Brownian Motion 1.Historical Background 2.Characteristic Scales Of Brownian Motion 3.Random Walk 4.Brownian Motion, Random Force And Friction: The Langevin.
Molecular Modelling - Lecture 2 Techniques for Conformational Sampling Uses CHARMM force field Written in C++
200 Physics Concepts from Delores Gende Website
Interacting Molecules in a Dense Fluid
Course 2 – Mathematical Tools and Unit Conversion Used in Thermodynamic Problem Solving.
Molecular dynamics (2) Langevin dynamics NVT and NPT ensembles
Properties of Gases.
Work Readings: Chapter 11.
Monatomic Crystals.
Fokker-Planck Equation and its Related Topics
1 Statistical Mechanics and Multi- Scale Simulation Methods ChBE Prof. C. Heath Turner Lecture 17 Some materials adapted from Prof. Keith E. Gubbins:
Conservation of Energy
Chapter 1: Survey of Elementary Principles
Central Force Umiatin,M.Si. The aim : to evaluate characteristic of motion under central force field.
Computational Physics (Lecture 18) PHY4061. Molecular dynamics simulations Most physical systems are collections of interacting objects. – a drop of water.
PHY Statistical Mechanics 12:00* - 1:45 PM TR Olin 107
Diffusion over potential barriers with colored noise
Simulation Study of Phase Transition of Diblock Copolymers
Dynamical correlations & transport coefficients
Density, ρ, is the mass per unit volume of a material.
Hamiltonian Mechanics
Liquids & Aqueous solutions
Molecular Dynamics.
Dynamical correlations & transport coefficients
Advanced Molecular Dynamics
Molecular Mechanics Molecular Dynamics.
Electric Potential.
Continuum Simulation Monday, 9/30/2002.
Presentation transcript:

Dissipative Particle Dynamics

Molecular Dynamics, why slow? MD solves Newton’s equations of motion for atoms/molecules: Why MD is slow?

Length, Time, & Energy Scales Look at typical scales of carbon-based molecules: length 1 Å, mass 12 amu, spring constant k = 20 eV/Å 2 with a Hamiltonian What is the associated equation of motion and time scale?

Hamilton’s Equations From We get dp/dt = - k x, dx/dt = p/m Or The solution is a harmonic oscillation x(t)=Acos[ (2  t+δ)/T ] with time period

Time Scale We use the units conversion factors: 1 eV = 1.6 x joule 1 amu = 1.66 x kg 1 Å = meter 1 milli sec = sec 1 μs = sec 1 nano sec = sec 1 pico sec = sec 1 femto sec = sec

How to increase the time scale of MD? Increase mass m, instead of simulating a single atom, we simulate a lump of them. Decrease the interaction strength k, we make the interaction softer.

Lennard-Jones vs Soft Pair Potential LJ Linear soft repulsion r V(r)

Brownian/Langevin Dynamics -  p is a dissipative (frictional) force, R(t) is random force with zero average and δ-function correlated in time (white noise). Bold face for vectors.

How to solve an equation with random forces? Where  is independent Gaussian random variable with zero mean and variance 2  mk B T h. (Why?)

Statistical Ensembles Micro-canonical ensemble: fixed particle number, volume, and energy (N, V, E) Canonical ensemble: fixed particle number, volume, and temperature (N, V, T). Langevin dynamics implements a canonical ensemble.

Dissipative Particle Method The dissipative particle dynamics was first proposed by Hoogerbrugge and Koelman (1992) for simulating hydrodynamic behavior. It was further improved by Groot and Warren (1997). It is a molecular dynamics with pair forces of three types.

DPD equations The forces are pair-wise additive, with conservative force F C, dissipative force F D, and stochastic force F R.

Conservative Force V(r) = (1/2) a (r –r c ) 2, r < r c = 0, r ≥ r c Where r is distance between two given particles. What is the form of the force acting on particle i from particle j ?

Dissipative Force and Random Force

Velocity-Verlet Algorithm What value to take? Order of accuracy?

Application of DPD method Coarse-grained description for solutions (e.g., water), simulating polymers (e.g., DNAs) in solution. Complex fluids at hydrodynamic time scales. Suspension of hard objects (spheres, rods, etc) in fluids.

Smoothed Particle Hydrodynamics A typical class of methods where continuum field equations (such as hydrodynamic equations) are simulated using the concept of particles. The traditional methods was to solve the partial differential equations on a regular grids (in space and time).