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.
Gaussion 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 shortlived intermediates and transition structures.
Investigating the Reactivity and Spectra of Large Molecules
Traditionally, proteins and other large biological molecules have been out of the reach of electronic structure methods. However, Gaussian’s ONIOM method overcomes these limitations. ONIOM first appeared in Gaussian 98, and several significant innovations in Gaussian 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 provides substantial performance gains for geometry optimizations via a quadratic coupled algorithm and the use of microiterations. 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.
New Features in Gaussian 09
Gaussian 09 offers new features and performance enhancements which will enable you to model molecular systems of increasing size, with more accuracy, and/or under a broader range of real world conditions.

Model Reactions of Very Large Systems with ONIOM
The ONIOM facility includes electronic embedding for MO:MM calculations whereby the electrostatic properties of the MM region are into account during computations on the QM region, and a fast, reliable optimization algorithm that takes the coupling between atoms in the model system and those only in the MM layer into account and uses microiterations for the MM layer between traditional optimization steps on the real system. Gaussian 09 provides many additional enhancements to the ONIOM facility, including the following:

Transition state optimizations.

Much faster IRC calculations.

Frequency calculations including electronic embedding.

Calculations in solution.

General performance enhancements.

Fully customizable MM force fields.

New implementations of AM1, PM3, PM3MM, PM6 and
PDDG semiempirical methods with true analytic gradients
and frequencies (parameters also fully customizable).

Study Excited States in the Gas Phase and in Solution
Gaussian 09 includes many new features intended for studying excited state systems, reactions and processes:

Analytic timedependent DFT (TDDFT) gradients.

The EOMCCSD method.

Statespecific solvation excitations and deexcitations.

FranckCondon and HerzbergTeller analysis (and FCHT).

Full support for CIS and TDDFT calculations in solution (equilibrium and nonequilibrium).
Many More New Features:

Significantly enhanced solvation features: In addition to the excited state features mentioned above, the SCRF facility also includes a new implementation incorporating a continuous surface charge formalism that ensures continuity, smoothness and robustness of the reaction field, and which also has continuous derivatives with respect to atomic positions and external perturbing fields. This results in faster, more reliable optimizations (taking no more steps than the gas phase) and accurate frequency calculations in solution.

Analytic gradients for the Brueckner Doubles (BD) method.

Additional spectra prediction: analytic DFT first hyperpolarizabilities and numeric second hyperpolarizabilities, analytic static and dynamic Raman intensities, analytic dynamic ROA intensities, improved anharmonic frequency calculations.

Population analysis of individual orbitals.

Fragmentbased initial guess and population analysis.

Ease of use features: reliable restarts of many more calculation types, fragment definitions within molecule specifications, freezing atoms by type, fragment, ONIOM layer and/or residue, selecting/sorting normal modes of interest during a frequency calculation, saving/reading postSCF amplitudes, saving/reading normal modes.

Many new DFT functionals, including ones incorporating long range corrections, empirical dispersion, and double hybrids.

Substantial performance improvements throughout the program, including optimizations for large molecules, frequency calculations on large molecules (as much as 16x in parallel), IRC calculations (~3x faster), and optical rotations (~2x faster).
SpinSpin Coupling
Determining Conformations via SpinSpin Coupling Constants
Conformational analysis is a difficult problem when studying new compounds for which Xray structures are not available. Magnetic shielding data in NMR spectra provides information about the connectivity between the various atoms within a molecule. Spinspin coupling constants can aid in identifying specific conformations of molecules because they depend on the torsion angles with the molecular structure.
Gaussian can predict spinspin 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.
Studying Periodic Systems
Gaussian 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 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 can also model compounds’ band gaps.
Modeling Solvent Effects
Modeling Solvent Effects on Reactions and Molecular Properties
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 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.
Computation Features
Gaussian can compute a very wide range of spectra and spectroscopic properties. These include:

IR and Raman

Preresonance Raman

UVVisible

NMR

Vibrational circular dichroism (VCD)

Electronic circular dichroism (ECD)

Optical rotary dispersion (ORD)

Harmonic vibrationrotation coupling

Anharmonic vibration and vibrationrotation coupling

g tensors and other hyperfine spectra tensors