研究领域
Physical Chemistry: Computational quantum mechanics emphasizing ab-initio electronic structure theory. Developing new methods for computational thermochemistry with applications to predictions of the absolute rates of chemical reactions.
My group develops improved theoretical methods for the calculation of molecular energies. We are particularly interested in methods applicable to transition states and potential energy surfaces for chemical reactions. Our work has included the integration of these methods into variational transition state theory and the prediction of absolute rates for chemical reactions. Our complete basis set (CBS) methods for molecular energies and our intrinsic reaction coordinate maximum energy (IRCMax) method for transition states are available in the computer program Gaussian 09TM.
The slow convergence of the correlation energy with the one-electron basis set expansion has provided the motivation for several attempts to extrapolate to the complete basis set limit. Our complete basis set extrapolations are based on the asymptotic convergence of pair natural orbital (PNO) expansions of the first-order wave function:
(1)
The essential idea is conveyed by a graph of eij(N) vs N-1, where the intercept is the CBS limit. Note that only certain closed-shell sets of pair natural orbitals (denoted by filled red circles in Figure 1) are useful for the extrapolation.
Figure 2. Comparison of CBS-APNO ZC-VTST calculated rate constants with experiment.
The accurate calculation of molecular energies requires convergence of both the one-particle (basis set) expansion and the n-particle (CI, perturbation, or coupled-cluster) expansion. However, the order-by-order contributions to chemical energies, and thus the number of significant figures required, generally decrease with increasing order of perturbation theory. The general approach for our CBS-n models is therefore to first determine the geometry and ZPE at a low level of theory, and then perform a high level single point electronic energy calculation at this geometry using large basis sets for the SCF calculation, medium basis sets for the MP2 calculation, and small basis sets for the higher-order calculations through order n. The components of each model have been selected to be balanced so that no single component dominates either the computer time or the error. Our sequence of CBS computational models are denoted CBS-4, ROCBS-QB3, and CBS-QCI/APNO. The RMS errors for a standard test set of 125 chemical energy differences are 2.5, 1.3, and 0.7 kcal/mol respectively.
The absolute rates of chemical reactions present a formidable challenge to theoretical predictions. The difficulty lies in the extreme sensitivity of the predicted rate constant to small errors in the activation energy. An error of only 1.4 kcal/mol leads to an error of an order-of-magnitude in the reaction rate at room temperature. Our IRCMax method reduces errors in transition state geometries by as much as a factor of five and errors in barrier heights by as much as a factor of ten.
More than sixty years ago, Eyring proposed the use of statistical mechanics to evaluate the absolute rate constant:
(2)
The challenge is to accurately determine all the quantities required to evaluate this equation. We employ an adaptation of Truhlar’s “zero curvature variational transition state theory” (ZC-VTST) to our CBS models through use of the IRCMax technique. Arrhenius plots for five hydrogen abstraction reactions are given in the Figure 2. The barrier heights for these reactions range from 1.3 kcal/mol (H2 + F) to 20.6 kcal/mol (H2O + H). We include temperatures from 250 K to 2500 K. The rate constants range from 10-18 up to 10-10 cm3/ molecule sec. If we include variations of the zero-point energy along the reaction path (i.e. variational transition state theory), all absolute rate constants obtained from our CBS-QCI/APNO model are within the uncertainty of the experiments. The dashed curves and open symbols for H2 + H, H2 + D, and D2 + H represent the least-squares fits of smooth curves to large experimental data sets in an attempt to reduce the noise level in the experimental data. The close agreement with theory suggests that this attempt was successful.
Our more recent work has included establishing rigorous complete basis set limits to provide benchmarks for the calibration of a new generation of more accurate CBS models (Figure 3), devising more efficient methods for optimizing Gaussian basis sets and using these methods to develop the nZaP family of basis sets, and developing a new density functional with physically correct dispersion terms.
The APF-D functional employs a spherical atom model (SAM) for instantaneous dipole – induced dipole interactions. This model is based on the interaction between two polarizable spherical shells:
(3)
which corrects the effective interatomic distance, RAB for the size of the atoms, rs(A) and rs(B). It is comparable in accuracy to including C6R–6, C8R–8, and C10R–10, terms in a point multipole expansion. The attraction between the hydrophobic side chains of amino acids plays an important role in protein folding. This new DFT describes these interactions within the currently known accuracy (Figure 4).
Dispersion forces can also play an important role in determining the relative energies of conformational and configurational isomers. For example, the cis-halopropenes are more stable than the trans-isomers, due in part to the dispersion attractions. Hartree-Fock calculations predict that only the cis-fluoropropene is more stable than the trans-isomer (Table 1). The B3LYP functional reduces the rms error by a factor of two and correctly predicts that all three cis-halopropenes are more stable than the trans-isomers. The M05-2X functional again cuts the errors in half, while the APF-D model reduces the errors well below the level of second-order many-body perturbation theory. The APF-D functional will provide a valuable new tool for structural studies.
近期论文
查看导师新发文章
(温馨提示:请注意重名现象,建议点开原文通过作者单位确认)
“A computational study of RXHn X-H bond dissociation enthalpies,” K.B. Wiberg, G.A. Petersson, J. Phys. Chem. A, A118, 2353 (2014).
“Aogacillins A and B produced by Simplicillium sp. FKI-5985: new circumventors of arbekacin resistance in MRSA,” K. Takata, M. Iwatsuki, T. Yamamoto, T. Shirahata, K. Nonaka, R. Masuma, Y. Hayakawa, H. Hanaki, Y. Kobayashi, G.A. Petersson, S. Omura, K. Shiomi, Org. Lett., 15, 4678 (2013).
“Evaluation of the heats of formation of corannulene and C60 by means of inexpensive theoretical procedures,” Frank Dobek, Duminda Ranasinghe, Kyle Throssell, George A. Petersson, J. Phys. Chem. A, 117, 4726 (2013).
“CCS(T)/CBS atomic and molecular benchmarks for H through Ar,” Duminda Ranasinghe, George A. Petersson, J. Chem. Phys., 138, 144104 (2013).
“Substituent Effects on O-H Bond Dissociation Enthalpies. A Computational Study,” Kenneth B. Wiberg, G. Barney Ellison, J. Michael McBride, and George A. Petersson, J. Phys. Chem., A117, 213 (2013).
“A Density Functional with Spherical Atom Dispersion Terms,” Amy Austin, George A. Petersson, Michael Frisch, Frank Dobek, Giovanni Scalmani, and Kyle Throssell, Journal of Chemical Theory and Computation, 8, 4989 (2012).
“A Computational Study of the Properties and Reactions of Small Molecules Containing O, S and Se,” Kenneth B. Wiberg, William F. Bailey, and George A. Petersson, Journal of Chemical Theory and Computation, 115, 12624 (2011).
“MP2/CBS atomic and molecular benchmarks for H through Ar,” Ericka C. Barnes, and George A. Petersson, J. Chem. Phys. 132, 114111 (2010).
“Spin unrestricted coupled-cluster and Brueckner-doubles variations of W1 theory,” Ericka C. Barnes, George A. Petersson, Michael J. Frisch, John A. Montgomery, Jr., and Jan Martin, Journal of Chemical Theory and Computation 5, 2687 (2009).
“Intramolecular nonbonded attractive interactions: 1-substituted propenes,” Kenneth B. Wiberg, Yi-gui Wang, George A. Petersson, and William F. Bailey, Journal of Chemical Theory and Computation 5, 1033 (2009).
“Uniformly Convergent n-tuple-z Augmented Polarized (nZaP) Basis Sets for Complete Basis Set Extrapolations. I. Self-consistent Field Energies,” Shijung Zhong, Ericka C. Barnes, and George A. Petersson, J. Chem. Phys. 129, 184116 (2008).
“The CCSD(T) Complete Basis Set Limit for Ne Revisited,” Ericka C. Barnes, George A. Petersson, David Feller, and Kirk A. Peterson, J. Chem. Phys. 129, 194115 (2008).
“A restricted-open-shell complete-basis-set model chemistry,” Geoffry P. F. Wood, Leo Radom, George A. Petersson, Ericka C. Barnes, Michael J. Frisch, and John A. Montgomery Jr,, J. Chem. Phys. 125, 94106 (2006).
“The Convergence of CASSCF-CISD Energies to the Completer Basis Set Limit,” George A. Petersson, David K. Malick, Michael J. Frisch, and Matthew Braunstein, J. Chem. Phys. 125, 44107, (2006).
“The Convergence of CASSCF Energies to the Completer Basis Set Limit,” George A. Petersson, David K. Malick, Michael J. Frisch, and Matthew Braunstein J. Chem. Phys 123, 74111, (2005).
“On the Optimization of Gaussian Basis sets,” G. A. Petersson, S. Zhong, J. A. Montgomery, Jr., and M. J. Frisch, J. Chem. Phys.118, 1101 (2003).
“An Overlap Criterion for Selection of Core Orbitals,” Amy J. Austin, Austin, Michael J. Frisch, J. A. Montgomery, Jr., and George A. Petersson, Theor. Chem. Acc. 107, 180-186 (2002).
“A Complete Basis Set Model Chemistry. VII. Use of the Minimum Population Localization Method,” J. A. Montgomery, Jr., M. J. Frisch, J. W. Ochterski, and G. A. Petersson, J. Chem. Phys.112, 6532 (2000).
“A Journey from Generalized Valence Bond Theory to the Full CI Complete Basis Set Limit,” G. A. Petersson and M. J. Frisch, J. Phys. Chem. 104, 2183 (2000).
“Perspective on “The Activated Complex in Chemical Reactions,” H. Eyring, J. Chem. Phys., 3, 107 (2000),” George A. Petersson, Theor. Chem. Acc., 103, 190 (2000).