QCforever: A Quantum Chemistry Wrapper for Everyone to Use in Black-Box Optimization.

Journal: Journal of chemical information and modeling
Published Date:

Abstract

To obtain observable physical or molecular properties such as ionization potential and fluorescent wavelength with quantum chemical (QC) computation, multi-step computation manipulated 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 construction 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 observable 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 computation.

Authors

  • Masato Sumita
    RIKEN Center for Advanced Intelligence Project, Tokyo 103-0027, Japan.
  • Kei Terayama
    Graduate School of Medical Life Science, Yokohama City University, Yokohama, Kanagawa 230-0045, Japan.
  • Ryo Tamura
    Research and Services Division of Materials Data and Integrated System , National Institute for Materials Science , 1-2-1 Sengen , Tsukuba , Ibaraki 305-0047 , Japan.
  • Koji Tsuda
    Graduate School of Frontier Sciences, The University of Tokyo Kashiwa Chiba 277-8561 Japan.