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Abstract As the tools of computational quantum chemistry have continued to mature, larger and more complex molecular systems have become amenable to computational study. However, studies of these complex systems often require the execution of enormous numbers of computations, which can be a tedious and error‐prone process if done manually. We have developed a suite of free, open‐source tools to facilitate the automation of quantum chemistry workflows. These tools are collected under the organization QChASM (Quantum Chemistry Automation and Structure Manipulation) and include functionality for building and manipulating complex molecular structures and performing routine tasks (AaronTools), a toolkit for automating TS optimizations and predictions of the outcomes of selective homogeneous catalytic reactions, and a plug‐in for UCSF ChimeraX that provides a graphical interface for building complex molecular structures and representing output from quantum chemistry computations. These tools are described below, with a focus on the recent Python implementation of AaronTools. This article is categorized under:Structure and Mechanism > Reaction Mechanisms and CatalysisSoftware > Quantum Chemistry
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Open Chemistry, JupyterLab , REST , and quantum chemistry
Abstract Quantum chemistry must evolve if it wants to fully leverage the benefits of the internet age, where the worldwide web offers a vast tapestry of tools that enable users to communicate and interact with complex data at the speed and convenience of a button press. The Open Chemistry project has developed an open‐source framework that offers an end‐to‐end solution for producing, sharing, and visualizing quantum chemical data interactively on the web using an array of modern tools and approaches. These tools build on some of the best open‐source community projects such as Jupyter for interactive online notebooks, coupled with 3D accelerated visualization, state‐of‐the‐art computational chemistry codes including NWChem and Psi4, and emerging machine learning and data mining tools such as ChemML and ANI. They offer flexible formats to import and export data, along with approaches to compare computational and experimental data.
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- Award ID(s):
- 1751161
- PAR ID:
- 10453965
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- International Journal of Quantum Chemistry
- Volume:
- 121
- Issue:
- 1
- ISSN:
- 0020-7608
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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