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Gaussian 03:

Expanding the limits of Computational Chemistry

Gaussian 03 brings enhancements and performance boosts to existing methods along with new features applying electronic structure methods to previously inaccessible areas of investigation and types of molecules.

Gaussian 03 is the latest in the Gaussian series of electronic structure programs. Gaussian 03 is used by chemists, chemical engineers, biochemists, physicists and others for research in established and emerging areas of chemical interest.

Starting from the basic laws of quantum mechanics, Gaussian predicts the energies, molecular structures, and vibrational frequencies of molecular systems, along with numerous molecular properties derived from these basic computation types. It can be used to study molecules and reactions under a wide range of conditions, including both stable species and compounds which are difficult or impossible to observe experimentally such as short-lived intermediates and transition structures. This article introduces several of its new and enhanced features.

Traditionally, proteins and other large biological molecules have been out of the reach of electronic structure methods. However, Gaussian 03's ONIOM method overcomes these limitations. ONIOM first appeared in Gaussian 98, and several significant innovations in Gaussian 03 make it applicable to much larger molecules.

This computational technique models large molecules by defining two or three layers within the structure that are treated at different levels of accuracy. Calibration studies have demonstrated that the resulting predictions are essentially equivalent to those that would be produced by the high accuracy method.

The ONIOM facility in Gaussian 03 provides substantial performance gains for geometry optimizations via a quadratic coupled algorithm and the use of micro-iterations. In addition,  the program's option to include electronic embedding within ONIOM calculations enables both the steric and electrostatic properties of the entire molecule to be taken into account when modeling processes in the high accuracy layer (e.g., an enzyme's active site). These techniques yield molecular structures and properties results that are in very good agreement with experiment.

For example, researchers are currently studying excited states of bacteriorhodopsin (illustrated below) using an ONIOM(MO:MM) model, as a first step in understanding the means by which this species generates energy within a cell. In this two-layer approach, the active site is treated using an electronic structure method while the rest of the system is modeled with molecular mechanics. Electronic embedding, which includes the electrostatics of the protein environment within the QM calculation of the active site, is essential to accurate predictions of the molecule's UV-Visible spectrum.

Bacteriorhodopsin, set up for an ONIOM calculation (stylized). See T. Vreven and K. Morokuma, ¡°Investigation of the S₀¡æS₁ excitation in bacteriorhodopsin with the ONIOM(MO:MM) hybrid method,¡± Theor. Chem. Acc. (2003).

The ONIOM method is also applicable to large molecules in many other areas, including enzyme reactions, reaction mechanisms for organic systems, cluster models of surfaces and surface reactions, photochemical processes of organic species, substituent effects and reactivity of organic and organometallic compounds, and homogeneous catalysis.

Other new ONIOM related features in Gaussian 03:

• Customizable molecular mechanics force fields.
• Efficient ONIOM frequency calculations.
• ONIOM calculation of electric and magnetic properties.

Conformational analysis is a difficult problem when studying new compounds for which X-ray structures are not available. Magnetic shielding data in NMR spectra provides information about the connectivity between the various atoms within a molecule. Spin-spin coupling constants can aid in identifying specific conformations of molecules because they depend on the torsion angles with the molecular structure.

Gaussian 03 can predict spin-spin coupling constants in addition to the NMR shielding and chemical shifts available previously. Computing these constants for different conformations and then comparing predicted and observed spectra makes it possible to identify the specific conformations that were observed. In addition, the assignment of observed peaks to specific atoms is greatly facilitated.

Gaussian 03 expands the range of chemical systems that it can model to periodic systems such as polymers and crystals via its periodic boundary conditions (PBC) methods.  The PBC technique models these systems as repeating unit cells in order to determine the structure and bulk properties of the compound.

For example, Gaussian 03 can predict the equilibrium geometries and transition structures of polymers. It can also study polymer reactivity by predicting isomerization energies, reaction energetics, and so on, allowing the decomposition, degradation, and combustion of materials to be studied. Gaussian 03 can also model compounds' band gaps.

Other PBC capabilities in Gaussian 03:

• 2D PBC methods can be used to model surface chemistry, such as reactions on surfaces and catalysis. In addition, using Gaussian 03 allows you to study the same problem using a surface model and/or a cluster model, using the same basis set and Hartree-Fock or DFT theoretical method in both cases. Using Gaussian 03 enables you to choose the appropriate approach for the system you are studying, rather than being forced to frame the problem to fit the capabilities and limitations of a particular model.
• 3D PBC: The structures and available bulk properties of crystals and other three-dimensional periodic systems can be predicted.

Gaussian 03 can compute a very wide range of spectra and spectroscopic properties. These include:

• IR and Raman
• Pre-resonance Raman
• UV-Visible
• NMR
• Vibrational circular dichroism (VCD)
• Electronic circular dichroism (ECD)
• Optical rotary dispersion (ORD)
• Harmonic vibration-rotation coupling
• Anharmonic vibration and vibration-rotation coupling
• g tensors and other hyperfine spectra tensors

For example, Gaussian 03 computes many of the tensors which contribute to hyperfine spectra. These results are useful for making spectral assignments for observed peaks, something which is usually difficult to determine solely from the experimental data (see the example below). Using theoretical predictions to aid in interpreting and fitting observed results should make non-linear molecules as amenable to study as linear ones.

The observed (yellow) and computed (blue) hyperfine spectra for H₂ C₆ N (N=4-3). The predicted spectrum allows spectral assignments to be made for the observed peaks, a task which is often difficult or impossible from the experimental data alone due to spectral overlap. Experimental data provided by S. E. Novick, W. Chen, M. C. McCarthy and P. Thaddeus (article in preparation).

Molecular properties and chemical reactions often vary considerably between the gas phase and in solution. For example, low lying conformations can have quite different energies in the gas phase and in solution (and in different solvents), conformation equilibria can differ, and reactions can take significantly different paths.

Gaussian 03 offers the Polarizable Continuum Model (PCM) for modeling system in solution. This approach represents the solvent as a polarizable continuum and places the solute in a cavity within the solvent.

The PCM facility in Gaussian 03 includes many enhancement that significantly extend the range of problems which can be studied:

• Excitation energies and related properties of excited states can be calculated in the presence of a solvent (see the surfaces in the diagram below).
• NMR spectra and other magnetic properties.
• Vibrational frequencies, IR and Raman spectra, and other properties computed via analytic second derivatives of the energy.
• Polarizabilities and hyperpolarizabilities.
• General performance improvements.

(excited state-ground state)^solvated - (excited state-ground state)^{gas phase}

These surfaces represent the electron density difference between the ground state and the charge transfer excited state in paranitroaniline (the molecule is at the near right). The small surface at the top right shows the electron density difference in the gas phase, and the one to its left shows the difference in acetonitrile solution. Electron density moves from the green areas to the red areas in the excited state.

The larger surface below the small ones is the difference of these difference densities (solution minus gas phase), and it illustrates how the charge transfer from NH₂ to NO₂ from the ground state to the excited state is larger in solution than it is for the same gas phase transition. In addition, as the level diagrams indicate, the ordering of the lowest two excited states changes between the gas phase and in solution with acetonitrile (the yellow states have 0 oscillator strengths and are not observed in ordinary UV-Visible spectra).