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PyADF - A scripting framework for multiscale quantum chemistry.

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Title: PyADF - A scripting framework for multiscale quantum chemistry.
Authors: Jacob, Christoph R.1, Beyhan, S. Maya2, Bulo, Rosa E.2, Gomes, André Severo Pereira3, Götz, Andreas W.4, Kiewisch, Karin2, Sikkema, Jetze2, Visscher, Lucas2
Source: Journal of Computational Chemistry. Jul2011, Vol. 32 Issue 10, p2328-2338. 11p. 7 Diagrams.
Subjects: Quantum chemistry, Python programming language, Simulation methods & models, Quantum theory, Workflow software, Object-oriented programming languages
Abstract: Applications of quantum chemistry have evolved from single or a few calculations to more complicated workflows, in which a series of interrelated computational tasks is performed. In particular multiscale simulations, which combine different levels of accuracy, typically require a large number of individual calculations that depend on each other. Consequently, there is a need to automate such workflows. For this purpose we have developed P YA DF, a scripting framework for quantum chemistry. P YA DF handles all steps necessary in a typical workflow in quantum chemistry and is easily extensible due to its object-oriented implementation in the Python programming language. We give an overview of the capabilities of P YA DF and illustrate its usefulness in quantum-chemical multiscale simulations with a number of examples taken from recent applications. © 2011 Wiley Periodicals, Inc. J Comput Chem, 2011 [ABSTRACT FROM AUTHOR]
Copyright of Journal of Computational Chemistry is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 63808140
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PubType: Academic Journal
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  Data: <searchLink fieldCode="DE" term="%22Quantum+chemistry%22">Quantum chemistry</searchLink><br /><searchLink fieldCode="DE" term="%22Python+programming+language%22">Python programming language</searchLink><br /><searchLink fieldCode="DE" term="%22Simulation+methods+%26+models%22">Simulation methods & models</searchLink><br /><searchLink fieldCode="DE" term="%22Quantum+theory%22">Quantum theory</searchLink><br /><searchLink fieldCode="DE" term="%22Workflow+software%22">Workflow software</searchLink><br /><searchLink fieldCode="DE" term="%22Object-oriented+programming+languages%22">Object-oriented programming languages</searchLink>
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  Data: Applications of quantum chemistry have evolved from single or a few calculations to more complicated workflows, in which a series of interrelated computational tasks is performed. In particular multiscale simulations, which combine different levels of accuracy, typically require a large number of individual calculations that depend on each other. Consequently, there is a need to automate such workflows. For this purpose we have developed P YA DF, a scripting framework for quantum chemistry. P YA DF handles all steps necessary in a typical workflow in quantum chemistry and is easily extensible due to its object-oriented implementation in the Python programming language. We give an overview of the capabilities of P YA DF and illustrate its usefulness in quantum-chemical multiscale simulations with a number of examples taken from recent applications. © 2011 Wiley Periodicals, Inc. J Comput Chem, 2011 [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Computational Chemistry is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Jul2011
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