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Polarized Molecular Orbital Model Chemistry 3. The PMO Method Extended to Organic Chemistry.


ABSTRACT: The polarized molecular orbital (PMO) method, a neglect-of-diatomic-differential-overlap (NDDO) semiempirical molecular orbital method previously parameterized for systems composed of O and H, is here extended to carbon. We modified the formalism and optimized all the parameters in the PMO Hamiltonian by using a genetic algorithm and a database containing both electrostatic and energetic properties; the new parameter set is called PMO2. The quality of the resulting predictions is compared to results obtained by previous NDDO semiempirical molecular orbital methods, both including and excluding dispersion terms. We also compare the PMO2 properties to SCC-DFTB calculations. Within the class of semiempirical molecular orbital methods, the PMO2 method is found to be especially accurate for polarizabilities, atomization energies, proton transfer energies, noncovalent complexation energies, and chemical reaction barrier heights and to have good across-the-board accuracy for a range of other properties, including dipole moments, partial atomic charges, and molecular geometries.

SUBMITTER: Isegawa M 

PROVIDER: S-EPMC3658842 | biostudies-literature | 2013 Jan

REPOSITORIES: biostudies-literature

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Polarized Molecular Orbital Model Chemistry 3. The PMO Method Extended to Organic Chemistry.

Isegawa Miho M   Fiedler Luke L   Leverentz Hannah R HR   Wang Yingjie Y   Nachimuthu Santhanamoorthi S   Gao Jiali J   Truhlar Donald G DG  

Journal of chemical theory and computation 20130101 1


The polarized molecular orbital (PMO) method, a neglect-of-diatomic-differential-overlap (NDDO) semiempirical molecular orbital method previously parameterized for systems composed of O and H, is here extended to carbon. We modified the formalism and optimized all the parameters in the PMO Hamiltonian by using a genetic algorithm and a database containing both electrostatic and energetic properties; the new parameter set is called PMO2. The quality of the resulting predictions is compared to res  ...[more]

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