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Title: Efficient optimization of natural resonance theory weightings and bond orders by gram‐based convex programming

We describe the formal algorithm and numerical applications of a novel convex quadratic programming (QP) strategy for performing the variational minimization that underlies natural resonance theory (NRT). The QP algorithm vastly improves the numerical efficiency, thoroughness, and accuracy of variational NRT description, which now allows uniform treatment ofallreference structures at the high level of detail previously reserved only for leading “reference” structures, with little or no user guidance. We illustrate overall QPNRT search strategy, program I/O, and numerical results for a specific application to adenine, and we summarize more extended results for a data set of 338 species from throughout the organic, bioorganic, and inorganic domain. The improved QP‐based implementation of NRT is a principal feature of the newly releasedNBO 7.0program version. © 2019 Wiley Periodicals, Inc.

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Award ID(s):
Author(s) / Creator(s):
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Publisher / Repository:
Wiley Blackwell (John Wiley & Sons)
Date Published:
Journal Name:
Journal of Computational Chemistry
Page Range / eLocation ID:
p. 2028-2035
Medium: X
Sponsoring Org:
National Science Foundation
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