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ExcelAutomat 1.4: generation of supporting information

  • Jalal Z. A. Laloo , Nandini Savoo , Lydia Rhyman und Ponnadurai Ramasami EMAIL logo
Veröffentlicht/Copyright: 4. April 2022

Abstract

Quantum chemical computations generate output files with data. The processing of these data generates results which are presented in a target document, such as a manuscript or supporting information (SI). Several tools and techniques can be employed to facilitate the transfer of data which, otherwise, can be time-consuming with a large number of files. However, depending on the user’s technical knowledge or expertise with the software, additional time has to be invested to set up the software or use the tools. In addition, to the best of the authors’ knowledge, the tools currently available do not provide an option to transfer the data from the output files directly to the target document without the use of custom scripts. The ExcelAutomat tool (Laloo et al., J. Comput. Aided Mol. Des. 2017, 31, 667 and Laloo et al., J. Comp. Chem. 2019, 40, 3) is spreadsheet-based and was developed in-house to facilitate the steps involved in the processing of computational files. The tool was adapted to facilitate the generation of SI in an update of ExcelAutomat 1.4. A graphical user interface was designed where the options for the generation of SI can be defined. ExcelAutomat 1.4 is compatible with Microsoft Excel and the open-source LibreOffice Calc. The extensible tool supports various software packages and parameters by interfacing with the cclib library and through built-in codes. The tool provides a method to transfer data from output files directly to a Microsoft Word or LibreOffice Writer document and can reduce the number of steps, tools or technical knowledge needed to generate SI, especially for users who are familiar with Microsoft Excel or LibreOffice Calc.


Article note:

A collection of invited papers based on presentations at the Virtual Conference on Chemistry and its Applications (VCCA-2021) held on-line, 9–13 August 2021.



Corresponding author: Ponnadurai Ramasami, Computational Chemistry Group, Department of Chemistry, Faculty of Science, University of Mauritius, Réduit 80837, Mauritius; and Centre for Natural Product Research, Department of Chemical Sciences, University of Johannesburg, Doornfontein Campus, Johannesburg 2028, South Africa, e-mail:

Funding source: University of Mauritius

Acknowledgements

The authors acknowledge facilities from the University of Mauritius. NS acknowledges the Higher Education Commission of Mauritius.

  1. Research funding: This work was supported by funding from the University of Mauritius (RA016).

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Published Online: 2022-04-04
Published in Print: 2022-07-26

© 2022 IUPAC & De Gruyter. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. For more information, please visit: http://creativecommons.org/licenses/by-nc-nd/4.0/

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