[DFTB-Plus-User] Correct Way to Run MPI-enabled DFTB+ (Conda Installation)

[Ankur Gupta]

Dear Dr. Aradi,

I am already using the new geometry optimizers. I have tried all three
optimizers available (Rational, LBFGS, FIRE). It seems like the
optimization starts wandering when the max. gradient reaches around
1.00E-03. So, we probably need to decrease the step size when the maximum
gradient is around that value. I am currently working with simple periodic
organic molecules, with only two molecules in a unit cell, so I expect the
optimization to converge within 150 steps.

I have used GFN2-xTB (in the xTB code) for molecular optimizations of large
molecules and found it to be quite robust for a wide variety of cases.
However, since the xTB methods have not been parameterized for periodic
systems, I was wondering if that's the reason for their poor performance in
optimizing periodic systems.

Best,
Ankur

On Fri, Apr 29, 2022 at 2:36 AM Bálint Aradi <aradi at uni-bremen.de> wrote:

> Dear Ankur,
>
> > I have another question related to the usage of DFTB+. I am currently
> > trying to optimize periodic organic systems (containing around 60-110
> > atoms) using the GFN2-xTB method; however, it seems like the geometry
> > optimization is extremely slow in terms of gradient convergence. For
> > example, in around 300 geometry optimization steps, the gradient norm
> > dropped from 0.72 H/a0 to only 0.0005499 H/a0. Is there a way to speed
> > up the gradient convergence so that the geometry optimization finishes
> > in fewer steps?
>
> Use the new geometry optimizers (Driver = GeometryOptimization {}).
> Depending on the system, if the potential surface is very flat, it can
> be difficult to obtain the minimum.
>
> Best regards,
>
> Bálint
>
> --
> Dr. Bálint Aradi
> Bremen Center for Computational Materials Science, University of Bremen
> http://www.bccms.uni-bremen.de/cms/people/b-aradi/
>
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