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Free Energy and Entropy from MD

Goddard, William A., III (2021) Free Energy and Entropy from MD. In: Computational Materials, Chemistry, and Biochemistry: From Bold Initiatives to the Last Mile. Springer Series in Materials Science. No.284. Springer International Publishing , Cham, pp. 1089-1095. ISBN 978-3-030-18777-4. https://resolver.caltech.edu/CaltechAUTHORS:20210127-070905792

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Abstract

It is straightforward to predict electronic energy from QM and the potential energy from FF-based MD and more recently from QM-based MD. However, extracting entropy and free energy has been problematic. Generally, the accepted methodology, going back to Jack Kirkwood and Richard Tolman, is thermodynamic integration theory or free energy perturbation theory. These methods are rigorous for obtaining free energy differences if the perturbations are sufficiently slow that the system remains in equilibrium as system A morphs into B. This generally requires repeated equilibrium calculations during the MD, which makes it very expensive for large-scale (100,000 atom) systems. A major advance here is the validation of FEP technology by Bill Jorgensen and its implementation into an automatic module by Schodinger. To make entropy and free energy calculations practical for nanosecond reactive simulations of large systems with up to millions of atoms, Lin, Blanco, and I (LBG) developed the two-phase thermodynamics (2PT) method that is generally 1000’s of time faster than thermodynamic integration (TI) but equally accurate.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1007/978-3-030-18778-1_48DOIArticle
ORCID:
AuthorORCID
Goddard, William A., III0000-0003-0097-5716
Additional Information:© Springer Nature Switzerland AG 2021. First Online: 26 January 2021.
Other Numbering System:
Other Numbering System NameOther Numbering System ID
WAG1443
Series Name:Springer Series in Materials Science
Issue or Number:284
DOI:10.1007/978-3-030-18778-1_48
Record Number:CaltechAUTHORS:20210127-070905792
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20210127-070905792
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:107741
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:27 Jan 2021 19:08
Last Modified:16 Nov 2021 19:05

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