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dc.contributor.authorKannemann, Felix Oliver
dc.date.accessioned2013-03-27T19:22:44Z
dc.date.available2013-03-27T19:22:44Z
dc.date.issued2013-03-27
dc.identifier.urihttp://hdl.handle.net/10222/21434
dc.description.abstractDensity-functional theory has become an indispensible tool for studying matter on the atomic level, being routinely applied across diverse disciplines from solid-state physics to chemistry and molecular biology. Its failure to account for dispersion interactions has spurred intensive research over the past decade. In this thesis, a semilocal density-functional approximation including dispersion is developed by combining standard functionals for exchange and correlation with the nonempirical “exchange-hole dipole moment“ (XDM) dispersion model of Becke and Johnson. With a minimum of empiricism, the method accurately describes all types of noncovalent interactions, from the extremely weak dispersion forces in rare-gas systems to the hydrogen bonding and stacking interactions responsible for the structure and function of biological macromolecules such as DNA and proteins. The method is compatible with a wide variety of standard Gaussian basis sets, and is easily applied to any system that can be modeled with density-functional theory.en_US
dc.language.isoenen_US
dc.subjectDensity-functional theory, dispersion, noncovalent interactions, quantum chemistry, computational chemistry, electronic structure theoryen_US
dc.titleDevelopment And Benchmarking Of A Semilocal Density-Functional Approximation Including Dispersionen_US
dc.date.defence2013-02-22
dc.contributor.departmentDepartment of Chemistryen_US
dc.contributor.degreeDoctor of Philosophyen_US
dc.contributor.external-examinerAjit J. Thakkaren_US
dc.contributor.graduate-coordinatorMark Stradiottoen_US
dc.contributor.thesis-readerRussell J. Boyd, Donald F. Weaver, Josef W. Zwanzigeren_US
dc.contributor.thesis-supervisorAxel D. Beckeen_US
dc.contributor.ethics-approvalNot Applicableen_US
dc.contributor.manuscriptsYesen_US
dc.contributor.copyright-releaseYesen_US
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