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

 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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