Abstract
To obtain observable physical or molecular properties like ionization potential and fluo- rescent wavelength with quantum chemical (QC) computation, multi-step computation manip- ulated by a human is required. Hence, automating the multi-step computational process and making it a black box that can be handled by anybody, are important for effective database con- struction and fast realistic material design through the framework of black-box optimization where machine learning algorithms are introduced as a predictor. Here, we propose a python library, QCforever, to automate the computation of some molecular properties and chemical phenomena induced by molecules. This tool just requires a molecule file for providing its ob- servable properties, automating the computation process of molecular properties (for ionization potential, fluorescence, etc) and output analysis for providing their multi-values for evaluating a molecule. Incorporating the tool in black-box optimization, we can explore molecules that have properties we desired within the limitation of QC.
Supplementary materials
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Supporting Information
Description
SMILES string list of 100 molecules
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Supplementary weblinks
Title
python code of QCforever
Description
QCforever is a wrapper of Gaussian (https://gaussian.com). It is possible to evaluate a molecule with its multiple properties.
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