Dear all,

Does the "compute heat/flux" support charged pairwise potentials such as

Coulombics interaction?

Regards,

Ali Rajabpour

The compute heat/flux command authored by Reese, Philip, Vikas

was released today in a 6Jul09 patch.Steve

Hi Reese,

I'm also interested in code for heat flux.

I would really appreciate if you can send it to me.

German SamolyukHi Bill,

I have working, validated code for computing the heat flux and a

python script for computing the necessary autocorrelation and its

integration. This was developed by Vikas Varshney, Phillip Howell and

myself. I am cleaning it up and giving it to Steve P. in the next week

or so.

I can send you the cleaned up version and the correlation script at

the same time I send it to Steve if you would like.

Reese

WJ Evans wrote:

Hi Steve,

There are several advantages of the Green-Kubo (GK) method compared

to the

non-equilibrium method (NEMD). 1) Because GK simulations are done

with the

system in equilibrium, there is no imposed driving force and so the

system

is always in the linear-response regime. 2) The GK method can compute

the

entire heat flux tensor with one simulation. NEMD would require a

simulation

run for each component of the heat flux vector. There the GK method

lends

itself much easier to the study of anisotropic effects. 3) A key

advantage

to the GK method is that it is much less sensitive to finite model size

effects because a heat source and sink are not required. Hence the GK

method

can use much smaller models than the NEMD methods. For example, good

results

for diamond were obtained with only a 4000 atom model with a

dimension of

about 2.8 nm. The NEMD method would require a model comparable tot he

mean

free path length (174 nm).

Of course there are disadvantages of the GK method compared to the NEMD

method but I have only discussed the positive attributes of the GK

method.

A way to implement the GK in lammps would be beneficial to many

researchers.

I would be interested in obtaining a copy of any GK source code

additions to

lammps if anyone has been successful in implementing it.

Bill Evans

From: "Steve Plimpton" <[email protected]>

To: <[email protected]>

Sent: Tuesday, April 14, 2009 9:24 AM

Subject: [lammps-users] Fwd: Thermal Conductivity Calculation

usingGreen-Kubo Relations

From: Steve Plimpton <[email protected]>

Date: Tue, Apr 14, 2009 at 7:23 AM

Subject: Re: [lammps-users] Thermal Conductivity Calculation using

Green-Kubo Relations

To: German Samolyuk <[email protected]>

Cc: Mario Pinto <[email protected]>, [email protected]I don't think anyone has answered my question of how

is this different than the Muller-Plathe method. For

viscosity the MP method is almost always better than

the traditional NEMD way of computing it. I'm guessing

the same is true of MP for thermal conductivity versus

the GK method. MP will converge much more quickly

than GK b/c the induced temp profile in MP is stable, whereas the

induced heat flux in GK is a quantity with large fluctuations. In

viscosity it is the off-diagonal pressure component that fluctuates

widely

and MP avoids computing it at all.

I also disagree with the statement below that GK can easily

be implemented for many-body potentials. It would require

inserting new code in every such potential in LAMMPS (AIREBO,

Tersoff, MEAM, ReaxFF, etc). By contrast the MP method just

works with any potential without the need to alter the potential at all.

It also just works with long-range Coulombics.Are there other downsides to MP for thermal K that I am missing?

Steve

the coefficient of thermal conductivity for the system in thermal

quilibrium, according to Green-Kubo method, equals

k=1/(3*volume*k_B*T*T) \int^{\inf}_{0}<J(t)J(0)> dt

there <> means ensemble average.

What is good in this expression - it's calculated in thermal

equilibrium, not so good - the ensemble average should be

calculated. Usually it's done by slicing results of one long enough

calculations by overlapping in time samples separated by t_{shift}

long

enough for the samples to be independent.

So

good - thermal equilibrium, bad - long calculations to reach

convergence in <> calculations.

Usually it's good to have value of thermal conductivity calculated

by two methods.

The many-body potentials was not inserted yet, I don't think it's

something very difficult.

I think Asegun Henry did it for LAMMPS.

German

A conceptual question on this topic. I don't know the details of

Green-Kubo for thermal conductivity. But isn't it essentially the

inverse of the Muller-Plathe method encoded in fix

thermal/conductivity?

I.e. in one case you impose a temperature difference and tally the

heat flux that results. In the other case you exchange bits of heat

flux and monitor the temperature profile that results.

If the two methods are essentially equivalent, and the GK has the

various difficulties you mention, and what you've done doesn't look

like it would address many-body potentials, then why not just use

fix thermal/conductivity?

Steve

Hi all,

I was not sure if it's a good idea to all lammps users, because it

still in testing phase.

If you think it will be interesting to everybody I will do it.

I've attached slightly modified style.h file. I added compute_hf.h

to it

and compute_hf.cpp, computer_hf.h files. I've used

compute_group_group.cpp

as a prototype, as soon as it has cycle over pair in it.It should be compiled

make yes-dpd,

- it uses velocities of ghost atoms.

I've also attached input file for Ar computation with two

temperatures

(in comment).

the results could be compared with results presented in chapter 2.18

of S. Yip (ed.), Handbook of Materials Modeling, 763–771. c 2005

Springer. Printed in the Netherlands.

I've deleted first 1000 iterations and calculated averaged values

over

20000 samples with 50 steps shift.

Known problems:

1) It's working with pair potentials only,

2) I do no know how to include Coulomb interaction.I would really appreciate any comments and suggestions ...

Best,

GermanDear German,

I would be very grateful if you could share your code. Could you

please

it to me and also put it on the mailing list?Thanks!

Mario PintoI have some variant of code with calculation of j(t) - heat

flux, actually energy flux.

For the calculation of lambda in the few components systems. I

tested it on a linux cluster using 32 Xenon processors for Ar -

solid and liquid.

It looks like it's working OK. So I can share it. I will appreciate

any information of

mistakes in the code.But I do not know how to include Coulomb interactions in this code.

As I understand pair->single() returns only real space part of

coulomb interaction. How I can calculate rest of the sum which

is calculated in kspace?

Thanks,

German SamolyukLAMMPS doesn't store Fij anywhere, it is computed in the pair

potentials, summed to Fi and Fj and discarded. You could write

a fix that looped over the neighbor list, and called

pair->single()

on each pair, which will return Fij to use however you wish.

The single() method also computes Eij.

Steve

Dear All,

I would like to calculate the thermal conductivity of a simple

one

component LJ system using LAMMPS. The Green-Kubo relation to

calculate

thermal conductivity (lambda) is:

lambda = ( 1/(3*V*kB*T^2) ) * Integral( 0 to infinity){

<j(0)j(t)>}

dt

where

j(t) = sum (over i) {v ei} + 0.5* Sum (over i,j; i not eq j) {

(Fij

dot

vi)

rij }However, I have not been able to locate the variable, (if it

exists)

that

gives the force between a given pair of particles. This would be

required to

perform the above calculation.Please can you point me as to whether such a variable exists /

any

other way

I can get a handle to this quantity.

If not, could you please provide access to this variable in

the next

release

of LAMMPS? Similarly, a variable that gives the potential between

two

specified particles would also be helpful.Any suggestions in performing the above calculations are welcome.

Cheers!

Mario PintoPS: I have looked at the thermal/conductivity fix, but that works

only

for

particles of the same mass; However in the near future I would

like

to

carry

out computations for systems consisting of a mixture of

particles.