Geometry optimization of clusters with translational and rotational coordinates

Wanted to share this with the community: I work with explicit water systems and with charge transfer complexes. Often I face an issue that with default tolerance parameters I either results in local minimum which still does not give me a good guess for TS geometry or for charge transfer complexes system oscillates continuously (over 500 iterations) around the final structure.

With some recommendations I became familiar with a paper and found that switching from internal coordinates to translational and rotational for such systems actually leads to a converged geometry optimization faster and with more fine tolerance. Authors made their code geomeTRIC available and it smoothly runs on macOS calling QChem for calculations.
I actually had issues running it when installed with pip or python setup.py install, but if installed using conda, it works great.

Hope it helps!

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I wasn’t aware that geomeTRIC could be run standalone, but I did know that it could be used as a geometry optimizer backend for QCEngine, which also supports Q-Chem as a driver.

I probably should have specified it more correctly. geomeTRIC is a code that uses Q-Chem as a back end. Same as pyGSM which refers to geomeTRIC and uses translational and rotational coordinates.