# CCL:G: Interaction of QC software components via text files

*From*: Susi Lehtola <susi.lehtola_-_alumni.helsinki.fi>
*Subject*: CCL:G: Interaction of QC software components via text
files
*Date*: Thu, 27 Sep 2018 11:46:41 +0300

Sent to CCL by: Susi Lehtola [susi.lehtola#,#alumni.helsinki.fi]
On 9/26/18 8:34 PM, Grigoriy Zhurko reg_zhurko/achemcraftprog.com wrote:

Sent to CCL by: Grigoriy Zhurko [reg_zhurko-x-chemcraftprog.com]
I suppose it is well-known that the geometry optimization in Gaussian is
sometimes accompanied with serious problems, and the users have to invent their
own ways of solving them. Besides that, the energy of the final (optimized)
geometry computed with Gaussian is often slightly higher than the energy of the
penultimate (previous) step. This is usually not a big problem, but this is
slightly annoying (unless you use my program Chemcraft) ).
My question is, whether it is possible to implement a third-party algorithm
of geometry optimization, which implies invoking the Gaussian by a third-party
program. I mean that the third-party program generates a Gaussian input file
(.gjf) with single point and gradient computation, then Gaussian processes this
job and generates the output file, then the program reads and parses this output
file, then it predicts the coordinates of the next step and runs Gaussian again,
etc. until the energy minimum is reached.
If such an approach is possible, I will probably try to implement the
following things:
- geometry optimization and frequencies computation with CCSD(T)/CBS, or even
a composite method like FPD;
- performing several computations with different DFT functionals at same
geometry, and passing their results into a neural network to obtain a very
accurate energy.
So, is this possible to implement such interaction of a third-party program
with Gaussian (preferably the Windows version), or other QC codes?
Grigoriy Zhuko

The freely available open source PySCF program
https://github.com/sunqm/pyscf

`that has recently become extremely popular with theorists due to its
``elegance and simplicity for developing new methods supports a wide
``variety of both ab initio as well as dft methods, and employs the
``pyberny library for geometry optimizations.
` https://github.com/azag0/pyberny

`If PySCF does not fulfill your needs, you might find pyberny
``interesting. pyberny does not have a wrapper to Gaussian, so you would
``have to implement it yourself, but you can probably look to the
existing
``MOPAC interface in pyberny and the interface in PySCF for inspiration.
`

`The likewise freely available open source Psi4 program also has a
``variety of ab initio and DFT methods implemented, and also supports a
``variety of CBS extrapolations for energies and geometry optimizations
``out of the box.
` --
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Mr. Susi Lehtola, PhD Junior Fellow, Adjunct Professor
susi.lehtola{:}alumni.helsinki.fi University of Helsinki
http://www.helsinki.fi/~jzlehtol Finland
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Susi Lehtola, dosentti, FT tutkijatohtori
susi.lehtola{:}alumni.helsinki.fi Helsingin yliopisto
http://www.helsinki.fi/~jzlehtol
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