What’s New in Gaussian 16

Gaussian 16 offers new features and a wide array of performance improvements which make the modeling of molecular systems even larger than before easier. Excited states have been greatly improved in this release, offering a very large number of new features over previous releases.

TD-DFT Methods

The TD-DFT method is now available for widely-used functions. Analytic second derivatives are available for:

  • Frequency predictions.
  • Practical TS optimization & IRC calculations.

Gaussian 16 allows you to study chemistry on excited state potential energy surfaces. For example:


Fluorescence cycle (simplified):

  • Excitation to excited state S1.
  • Proton transfer reaction on S1PES.
  • Relaxation back to S0.

EOMCC Method

  • Using the EOMCC method in Gaussian 16 allows you to obtain Analytic gradients from Geometry optimization calculations.
  • Solvation interaction models.

Anharmonic Vibrational Spectroscopy

With the new Anharmonic Vibrational Spectroscopy features, Gaussian 16 can predict combination and overtone bands.

  • Computes additional terms which relax both parts of the double harmonic approximation.

In Gaussian 09, you could only compute the IR Spectra. In Gaussian 16, this has expanded to VCD and ROA Spectrum.

Anharmonic VIbrational Spectroscopy

Vibronic Spectroscopy

Gaussian 16 can now predict vibronic spectra.

Vibronic Spectroscopy

An example of Vibronic Spectroscopy is band assignment for S1←S0OPA spectrum of anisole, which is seen below.

S1←S0OPA spectrum

Gaussian 16 can also overlap data of Vibrational Modes using a Duschinsky Matrix.

Duschinsky Matrix

Other New Capabilities

  • Functionals: M08 family, PW6B95 family.
  • PM7 semi-empirical method.
  • Adamocharge transfer diagnostic for excited state transfer.
  • General internal coordinates.

Performance Enhancements

Support for GPUs


  • Optimized memory algorithm to avoid I/O during CCSD iterations.
  • Enhancements to GEDIIS optimization algorithm.
  • CASSCF improvements for active spaces ≥(10,10).
  • Core correlation energies for W1 compound model.
  • Improvements to low level of OVGF compound model.
  • Parellel speedups for systems with a large number of cores.

Last update: 30 December 2016