The 6‐31G* and 6‐31G** basis sets previously introduced for first‐row atoms have been extended through the second‐row of the periodic table. Equilibrium geometries for one‐heavy‐atom hydrides calculated for the two‐basis sets and using Hartree–Fock wave functions are in good agreement both with each other and with the experimental data. HF/6‐31G* structures, obtained for two‐heavy‐atom hydrides and for a variety of hypervalent second‐row molecules, are also in excellent accord with experimental equilibrium geometries. No large deviations between calculated and experimental single bond lengths have been noted, in contrast to previous work on analogous first‐row compounds, where limiting Hartree–Fock distances were in error by up to a tenth of an angstrom. Equilibrium geometries calculated at the HF/6‐31G level are consistently in better agreement with the experimental data than are those previously obtained using the simple split‐valance 3‐21G basis set for both normal‐ and hypervalent compounds. Normal‐mode vibrational frequencies derived from 6‐31G* level calculations are consistently larger than the corresponding experimental values, typically by 10%–15%; they are of much more uniform quality than those obtained from the 3‐21G basis set. Hydrogenation energies calculated for normal‐ and hypervalent compounds are in moderate accord with experimental data, although in some instances large errors appear. Calculated energies relating to the stabilities of single and multiple bonds are in much better accord with the experimental energy differences.

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Self‐consistent molecular orbital methods. XXIII. A polarization‐type basis set for second‐row elements

A modified conjugate gradient algorithm for geometry optimization is outlined for use with ab initioMO methods. Since the computation time for analytical energy gradients is approximately the same as for the energy, the optimization algorithm evaluates and utilizes the gradients each time the energy is computed. The second derivative matrix, rather than its inverse, is updated employing the gradients. At each step, a one-dimensional minimization using a quartic polynomial is carried out, followed by an n-dimensional search using the second derivative matrix. By suitably controlling the number of negative eigenvalues of the second derivative matrix, the algorithm can also be used to locate transition structures. Representative timing data for optimizations of equilibrium geometries and transition structures are reported for ab initioSCF–MO calculations.

Optimization of equilibrium geometries and transition structures

We present an approach for deriving net atomic charges from ab initio quantum mechanical calculations using a least squares fit of the quantum mechanically calculated electrostatic potential to that of the partial charge model. Our computational approach is similar to those presented by Momany [J. Phys. Chem., 82, 592 (1978)], Smit, Derissen, and van Duijneveldt [Mol. Phys., 37, 521 (1979)], and Cox and Williams [J. Comput. Chem., 2, 304 (1981)], but differs in the approach to choosing the positions for evaluating the potential. In this article, we present applications to the molecules H2O, CH3OH, (CH3)2O, H2CO, NH3, (CH3O)2PO, deoxyribose, ribose, adenine, 9-CH3 adenine, thymine, 1-CH3 thymine, guanine, 9-CH3 guanine, cytosine, 1-CH3 cytosine, uracil, and 1-CH3 uracil. We also address the question of inclusion of “lone pairs,” their location and charge.

An approach to computing electrostatic charges for molecules

The IMOMM, IMOMO, and ONIOM methods have been proven to be powerful tools for the theoretical treatment of large molecular systems where different levels of theory are applied to different parts of a molecule. Within this framework we present a modified handling of the link atoms which are introduced to terminate the dangling bonds of the model system. Using this new scheme the definition of the combined energy gradient, the Hessian matrix, and the integration of higher derivatives of the energy with respect to nuclear coordinates and the electric field vector becomes straightforward. This allows for the first time the consistent combination of vibrational frequencies and the calculation of other molecular properties such as IR intensities, Raman intensities as well as dipole moments, polarizabilities, and hyperpolarizabilities. Test calculations for some typical as well as unusual examples and partitioning schemes are presented to demonstrate the power and limitations of the method and to provide guidelines for its applicability. Users of the method are strongly advised to test, calibrate and confirm for themselves the validity of the method combination and the model subsystem for the properties they want to calculate.

A new oniom implementation in gaussian98. part i. the calculation of energies, gradients, vibrational frequencies and electric field derivatives

Jaguar is an ab initio quantum chemical program that specializes in fast electronic structure predictions for molecular systems of medium and large size. Jaguar focuses on computational methods with reasonable computational scaling with the size of the system, such as density functional theory (DFT) and local second-order Moller–Plesset perturbation theory. The favorable scaling of the methods and the high efficiency of the program make it possible to conduct routine computations involving several thousand molecular orbitals. This performance is achieved through a utilization of the pseudospectral approximation and several levels of parallelization. The speed advantages are beneficial for applying Jaguar in biomolecular computational modeling. Additionally, owing to its superior wave function guess for transition-metal-containing systems, Jaguar finds applications in inorganic and bioinorganic chemistry. The emphasis on larger systems and transition metal elements paves the way toward developing Jaguar for its use in materials science modeling. The article describes the historical and new features of Jaguar, such as improved parallelization of many modules, innovations in ab initio pKa prediction, and new semiempirical corrections for nondynamic correlation errors in DFT. Jaguar applications in drug discovery, materials science, force field parameterization, and other areas of computational research are reviewed. Timing benchmarks and other results obtained from the most recent Jaguar code are provided. The article concludes with a discussion of challenges and directions for future development of the program. © 2013 Wiley Periodicals, Inc.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/qua.24481

Jaguar: A high-performance quantum chemistry software program with strengths in life and materials sciences

Three basis sets (minimal s–p, extended s–p, and minimal s–p with d functions on second row atoms) are used to calculate geometries and binding energies of 24 molecules containing second row atoms. d functions are found to be essential in the description of both properties for hypervalent molecules and to be important in the calculations of two‐heavy‐atom bond lengths even for molecules of normal valence.

Self‐consistent molecular orbital methods. XVII. Geometries and binding energies of second‐row molecules. A comparison of three basis sets

The energies of planar vs. tetrahedral geometries of tetracoordinate organic molecules have been surveyed by ab ini- tio molecular orbital calculations. Because of their 7~ acceptor and u donor character, electropositive substituents, especially lithium, are particularly effective in stabilizing the planar arrangements selectively. Multiple substitution by such metals and by three-membered rings provides further stabilization, and 1,l-dilithiocyclopropane (XVII) and 3,3-dilithiocyclopropene (XVIII), inter alia, are actually calculated (RHF/STO-3G theory) to be more stable planar than tetrahedral.

John B. Collins

Papers

Self‐consistent molecular orbital methods. XVII. Geometries and binding energies of second‐row molecules. A comparison of three basis sets

Stabilization of planar tetracoordinate carbon

Molecular orbital study of tetrahedral, planar, and pyramidal structures of the isoelectronic series BH4-, CH4, NH4+, AlH4-, SiH4, and PH4+

Molecular orbital theory of the electronic structure of molecules. 29. The interaction of molecular hydrogen with simple Lewis acids

Stabilization of planar tetracoordinate carbon