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Module-3 Ab Initio Molecular Dynamics March 25
18

Lecture March30

Feb 01, 2016

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Anubhav Vardhan

Molecular Modelling Lecture Notes
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Page 1: Lecture March30

Module-3

Ab Initio Molecular Dynamics

March 25

Page 2: Lecture March30

Bulk vs Finite System

~1023 atoms cannot be treated

computationally

~10 - 106 atoms can be usually treated computationallysuch boundary

effects should be avoided!

Page 3: Lecture March30

Periodic Boundary Conditions

if an atom goesout of the simulationbox, the same atom

should come into the box from the opposite

side

Page 4: Lecture March30
Page 5: Lecture March30

Minimum image convention:

longest distance

should not be larger than L/2

L

dx = xI � xJ

If |dx| > L/2, then

dx = dx� L sgn(dx)

dx

I

J

dx

O

If(x � L) thenx = x� L

If(x < 0) thenx = x+ L

wrapping the coordinates:correct distance:

J

Page 6: Lecture March30
Page 7: Lecture March30

Simulation of NVE Ensemble

Constant energy simulation (i.e. by solving the Hamilton’s equations of motion) in a constant volume

closed box (periodic/non-periodic)

A = hai =RdX a(X) �(H(X)� E)R

dX �(H(X)� E)

Ensemble average:

Page 8: Lecture March30

Home Work

• Write a working MD code for a two dimensional harmonic oscillator using Velocity Verlet Integrator (in any programing language)

Page 9: Lecture March30

Simulation of NVT Ensemble

Constant temperature simulation in a constant volume closed box (periodic/non-periodic)

systemsystem

Bath at T

• Hamilton’s equations of motion for the system, but with their momentum coupled to “bath

variables”• Total energy of the system will

no longer conserved• Bath+system energy is

conserved

Page 10: Lecture March30

A = hai =RdX a(X) exp(��H(X))R

dX exp(��H(X))

Fluctuations of a canonical ensemble should be captured in the simulations. For e.g. fluctuation in total energy

�2(E) = kBT2CV

Page 11: Lecture March30

Thermostat for NVT simulations

• Direct scaling of velocities:

T / R2I

Tt

T0=

R2I(t)

R20,I(t)

R0,I(t) = RI(t)

rT0

Tt

Usually, velocity scaling is used only in helping to equilibrate the system.

Scaling is often done if temperature goes beyond a window, or at some frequency (say every 50 MD steps); scaling

every time step doesn’t allow fluctuations, and thus leads to wrong ensemble!

req. velocity

current velocity

current temperature

req. temperature

Page 12: Lecture March30

Velocities are replaced by that from Maxwell-Boltzmann distribution (generated through Random numbers).

In a “Single particle” Andersen thermostat mode, thermostat is applied to a randomly picked single particle.

In “massive” Andersen thermostat mode every particle is coupled to the thermostat.

Thermostat is applied at a certain frequency (“collision frequency”) and not every MD step.

It can be proven that the correct canonical ensemble can be obtained by this thermostat; the thermostat disturbs

the dynamics (not good for computing diffusion const. etc.)

• Andersen Thermostat (system coupled to a stochastic bath)

Hans C. Andersen. J. Chem. Phys. 72, 2384 (1980)

Page 13: Lecture March30

• Langevin Thermostat

FI(t) = �rIU(RN )� �IMIRI(t) + gI

frictional coeff. Gaussian

random forcewith zero mean and

� =p2kBT0�IMI/�t

Brünger-Brooks-Karplus Integrator for the implementation of Lang. thermostat.

A. Brünger, C. L. Brooks III, M. Karplus, Chem. Phys. Letters, 1984, 105 (5) 495-500.

http://localscf.com/localscf.com/LangevinDynamics.aspx.html

Page 14: Lecture March30

• Berendsen Thermostat

Scaling velocity with �

�2 = 1 +�t

✓T0

T (t)� 1

timescale of heat transfer

(0.1-0.4 ps)

Scaled every time stepProper fluctuations of a canonical ensemble is not well

captured

Page 15: Lecture March30

Nose Hoover Chain Thermostat

RI =PI

MI

PI = FI �p⌘1

Q1PI

⌘j =p⌘j

Qj, j = 1, ·,M

p⌘1 =

"X

I

P2I

MI� dNkBT

#� p⌘2

Q2p⌘1

p⌘M =

"p2⌘M�1

QM�1� kBT

#

p⌘j =

"p2⌘j�1

Qj�1� kBT

#�

p⌘j+1

Qj+1p⌘j

Ref: 1 Martyna, Kein, Tuckermann (1992),

J. Chem. Phys. 97 2635

Page 16: Lecture March30

Q1 = dNkBT ⌧2

Qj = kBT ⌧2, j = 2, · · · ,M

⌧ � 20�t

Results in canonical ensemble distribution

Widely used today in molecular simulations.

Special integration scheme is required: RESPA Integrator (Martyna 1996)

Martyna et al., Mol. Phys. 87 , 1117 (1996)

Usually

Page 17: Lecture March30

Ab Initio MD: Born-Oppenheimer MD

HBOMD({RI}, {PI}) =NX

I=1

P2I

2MI+ Etot({RI})

=NX

I=1

P2I

2MI+

min{ }

nD

({ri}, {RI})�

Hel

({ri}, {RI})Eo

+NX

J>I

ZIZJ

RIJ

Page 18: Lecture March30

rRI

D |Hel| |

E=DrRI |Hel| |

E+D |rRI Hel| |

E+D |Hel|rRI |

E

6=D |rRI Hel| |

E

Basis set should be large enough!

Convergence of wave function and energy conservation:

Time step (fs)

Convergence (a.u.)

conservation (a.u./ps)

CPU time (s) for 1 ps

trajectory

0.25 10-6 10-6 16590

1 10-6 10-6 4130

2 10-6 6 x 10-6 2250

2 10-4 1 x 10-3 1060