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Computational chemistry is a branch of chemistry that uses computer simulation to assist in solving chemical problems. It uses methods of theoretical chemistry, incorporated into computer programs, to calculate the structures and properties of molecules, groups of molecules, and solids. It is essential because, apart from relatively recent results concerning the hydrogen molecular ion, the quantum many-body problem cannot be solved analytically, much less in closed form. While computational results normally complement the information obtained by chemical experiments, it can in some cases predict hitherto unobserved chemical phenomena. It is widely used in the design of new drugs and materials.
Theoretical chemistry is the branch of chemistry which develops theoretical generalizations that are part of the theoretical arsenal of modern chemistry: for example, the concepts of chemical bonding, chemical reaction, valence, the surface of potential energy, molecular orbitals, orbital interactions, and molecule activation.
In computational physics and chemistry, the Hartree–Fock (HF) method is a method of approximation for the determination of the wave function and the energy of a quantum many-body system in a stationary state.
Gaussian is a general purpose computational chemistry software package initially released in 1970 by John Pople and his research group at Carnegie Mellon University as Gaussian 70. It has been continuously updated since then. The name originates from Pople's use of Gaussian orbitals to speed up molecular electronic structure calculations as opposed to using Slater-type orbitals, a choice made to improve performance on the limited computing capacities of then-current computer hardware for Hartree–Fock calculations. The current version of the program is Gaussian 16. Originally available through the Quantum Chemistry Program Exchange, it was later licensed out of Carnegie Mellon University, and since 1987 has been developed and licensed by Gaussian, Inc.
In molecular physics, the Pariser–Parr–Pople method applies semi-empirical quantum mechanical methods to the quantitative prediction of electronic structures and spectra, in molecules of interest in the field of organic chemistry. Previous methods existed—such as the Hückel method which led to Hückel's rule—but were limited in their scope, application and complexity, as is the Extended Hückel method.
The extended Hückel method is a semiempirical quantum chemistry method, developed by Roald Hoffmann since 1963. It is based on the Hückel method but, while the original Hückel method only considers pi orbitals, the extended method also includes the sigma orbitals.
Electronic correlation is the interaction between electrons in the electronic structure of a quantum system. The correlation energy is a measure of how much the movement of one electron is influenced by the presence of all other electrons.
MNDO, or Modified Neglect of Diatomic Overlap is a semi-empirical method for the quantum calculation of molecular electronic structure in computational chemistry. It is based on the Neglect of Diatomic Differential Overlap integral approximation. Similarly, this method replaced the earlier MINDO method. It is part of the MOPAC program and was developed in the group of Michael Dewar. It is also part of the AMPAC, GAMESS (US), PC GAMESS, GAMESS (UK), Gaussian, ORCA and CP2K programs.
Austin Model 1, or AM1, is a semi-empirical method for the quantum calculation of molecular electronic structure in computational chemistry. It is based on the Neglect of Differential Diatomic Overlap integral approximation. Specifically, it is a generalization of the modified neglect of differential diatomic overlap approximation. Related methods are PM3 and the older MINDO.
PM3, or Parametric Method 3, is a semi-empirical method for the quantum calculation of molecular electronic structure in computational chemistry. It is based on the Neglect of Differential Diatomic Overlap integral approximation.
CNDO is the abbreviation for Complete Neglect of Differential Overlap, one of the first semi empirical methods in quantum chemistry. It uses two approximations:
PQS is a general purpose quantum chemistry program. Its roots go back to the first ab initio gradient program developed in Professor Peter Pulay's group but now it is developed and distributed commercially by Parallel Quantum Solutions. There is a reduction in cost for academic users and a site license. Its strong points are geometry optimization, NMR chemical shift calculations, and large MP2 calculations, and high parallel efficiency on computing clusters. It includes many other capabilities including Density functional theory, the semiempirical methods, MINDO/3, MNDO, AM1 and PM3, Molecular mechanics using the SYBYL 5.0 Force Field, the quantum mechanics/molecular mechanics mixed method using the ONIOM method, natural bond orbital (NBO) analysis and COSMO solvation models. Recently, a highly efficient parallel CCSD(T) code for closed shell systems has been developed. This code includes many other post Hartree–Fock methods: MP2, MP3, MP4, CISD, CEPA, QCISD and so on.
Michael James Steuart Dewar was an American theoretical chemist.
In computational chemistry, NDDO is a formalism that was first introduced by John Pople and it is now the basis of most successful semiempirical methods. While INDO added all one-centre two electron integrals to the CNDO/2 formalism, NDDO adds all two centre integrals for repulsion between a charge distribution on one centre and a charge distribution on another centre. Otherwise the zero-differential overlap approximation is used.
AMPAC is a general-purpose semiempirical quantum chemistry program. It is marketed by Semichem, Inc. and was developed originally by Michael Dewar and his group.
Zero differential overlap is an approximation in computational molecular orbital theory that is the central technique of semi-empirical methods in quantum chemistry. When computers were first used to calculate bonding in molecules, it was only possible to calculate diatomic molecules. As computers advanced, it became possible to study larger molecules, but the use of this approximation has always allowed the study of even larger molecules. Currently semi-empirical methods can be applied to molecules as large as whole proteins. The approximation involves ignoring certain integrals, usually two-electron repulsion integrals. If the number of orbitals used in the calculation is N, the number of two-electron repulsion integrals scales as N4. After the approximation is applied the number of such integrals scales as N2, a much smaller number, simplifying the calculation.
Spartan is a molecular modelling and computational chemistry application from Wavefunction. It contains code for molecular mechanics, semi-empirical methods, ab initio models, density functional models, post-Hartree–Fock models, and thermochemical recipes including G3(MP2) and T1. Quantum chemistry calculations in Spartan are powered by Q-Chem.
Semi-empirical quantum chemistry methods are based on the Hartree–Fock formalism, but make many approximations and obtain some parameters from empirical data. They are very important in computational chemistry for treating large molecules where the full Hartree–Fock method without the approximations is too expensive. The use of empirical parameters appears to allow some inclusion of electron correlation effects into the methods.
Ab initio quantum chemistry methods are computational chemistry methods based on quantum chemistry. The term ab initio was first used in quantum chemistry by Robert Parr and coworkers, including David Craig in a semiempirical study on the excited states of benzene. The background is described by Parr. Ab initio means "from first principles" or "from the beginning", implying that the only inputs into an ab initio calculation are physical constants. Ab initio quantum chemistry methods attempt to solve the electronic Schrödinger equation given the positions of the nuclei and the number of electrons in order to yield useful information such as electron densities, energies and other properties of the system. The ability to run these calculations has enabled theoretical chemists to solve a range of problems and their importance is highlighted by the awarding of the Nobel prize to John Pople and Walter Kohn.
PyQuante is an open-source (BSD) suite of programs for developing quantum chemistry methods using Gaussian type orbital (GTO) basis sets. The program is written in the Python programming language, but has "rate-determining" modules written in C for speed, and also uses and requires the NumPy linear algebra extensions to Python. The resulting code, though not as fast as other quantum chemistry programs, is much easier to understand and modify. The goal of this software is not necessarily to provide a working quantum chemistry program but rather to provide a set of tools so that scientists can construct their own quantum chemistry programs without going through the tedium of having to write every low-level routine. PyQuante 1.6.3 is the latest stable version of the program.
References
- ↑ Dewar, Michael J.S.; Jie, Caoxian; Yu, Jianguo (1993). "SAM1; the first of a new series of general purpose quantum mechanical molecular models". Tetrahedron. 49 (23): 5003–5038. doi:10.1016/S0040-4020(01)81868-8.
- 1 2 Holder, Andrew J.; Dennington II, Roy D.; Jie, Caoxian (1994-01-17). "Addendum to SAM1 results previously published". Tetrahedron. 50 (3): 627–638. doi:10.1016/S0040-4020(01)80782-1.
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