Gaussian16

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Gaussian 16 is the latest version of the Gaussian series of electronic structure programs, used by chemists, chemical engineers, biochemists, physicists and other scientists worldwide. Gaussian 16 provides a wide-ranging suite of the most advanced modeling capabilities available. You can use it to investigate the real-world chemical problems that interest you, in all of their complexity, even on modest computer hardware.

What Sets Gaussian 16 Apart from Other Software?

•Gaussian 16 produces accurate, reliable and complete models without cutting corners.

•A wide variety of methods makes Gaussian 16 applicable to a broad range of chemical conditions, problem sizes and compounds.

•Gaussian 16 provides state-of-the-art performance in single CPU, multiprocessor and multicore, cluster/network and GPU computing environments.

•Setting up calculations is simple and straightforward, and even complex techniques are fully automated. The flexible, easy-to-use options give you               complete control over calculation details when needed.

•Calculation results are presented in natural and intuitive graphical form by GaussView 6.

Fundamental Capabilities

Starting from the fundamental laws of quantum mechanics, Gaussian 16 predicts the energies, molecular structures, vibrational frequencies and molecular properties of compounds and reactions in a wide variety of chemical environments. Gaussian 16’s models can be applied to both stable species and compounds which are difficult or impossible to observe experimentally, whether due to their nature (e.g., toxicity, combustibility, radioactivity) or their inherent fleeting nature (e.g., short-lived intermediates and transition structures).

With Gaussian 16, you can thoroughly investigate the chemical problems that interest you. For example, not only can you minimize molecular structures rapidly and reliably, you can also predict the structures of transition states, and verify that the predicted stationary points are in fact minima or transition structure (as appropriate). You can go on to compute the reaction path by following the intrinsic reaction coordinate (IRC) and determine which reactants and products are connected by a given transition structure. Once you have a complete picture of the potential energy surface, reaction energies and barriers can be accurately predicted. You can also predict a wide variety of chemical properties.

Gaussian 16 offers a wide range of methods for modeling compounds and chemical processes, including:

Molecular Properties in Gaussian 16

Antiferromagnetic coupling

Atomic charges

ΔG of solvation

Dipole moment

Electron affinities

Electron density

Electronic circular dichroism (ECD)

Electrostatic potential

Electrostatic potential-derived charges

Electronic transition band shape

High accuracy energies

Hyperfine coupling constants (anisotropic)

Hyperfine spectra tensors (including g tensors)

Ionization potentials

IR and Raman spectra*

Pre-resonance Raman spectra*

Resonance Raman spectra

Molecular orbitals

Multipole moments

NMR shielding and chemical shifts

NMR spin-spin coupling constants

Optical rotations (ORD)

Polarizabilities/hyperpolarizabilities

Raman optical activity (ROA)*

Thermochemical analysis

UV/Visible spectra

Vibration-rotation coupling

Vibrational circular dichroism (VCD)*

Vibronic (absorption and emission) spectra

*Harmonic approx. and including anharmonic effects

•Molecular mechanicsEGF: Amber, UFF, Dreiding

•Semi-empirical methodsEGF†: AM1, PM6, PM7, DFTB, among others

•Hartree-FockEGF

•Density functional (DFT) methodsEGF, with support for a plethora of published functionals; long-range and empirical dispersion corrections are available where defined

•Complete active space self-consistent field (CASSCF)EGF, including RAS support and conical intersection optimizations

•Møller-Plesset perturbation theory: MP2EGF, MP3EG, MP4(SDQ)EG, MP4(SDTQ)E, MP5E

•Coupled cluster: CCDEG, CCSDEG, CCSD(T)E

•Brueckner doubles: BDEG, BD(T)E

•Outer Valence Green’s Function (OVGF): ionization potentials and electron affinities

•High accuracy energy models: G1-G4, CBS series and W1 series, all with variants

•Excited state methods: TD-DFTEGF, EOM-CCSDEG and SAC-CIEG

EEnergies; GAnalytic gradients; FAnalytic frequencies; F†Reimplemented with analytic frequencies.

A wide range of Gaussian results can be examined with GaussView’s visualization capabilities:

•Molecule annotations and/or property-specific coloring: e.g., atomic charges, bond orders, NMR chemical shifts

•Plots, including NMR, vibrational and vibronic spectra

•Surfaces or contours: e.g., molecular orbitals, electron density, spin density. Properties such as the electrostatic potential can be visualized as a colorized density surface.

•Animations: e.g., normal modes, IRC paths, geometry optimizations

Binary Location:

/data/apps/Gaussian/g09

Version: Gaussian16

Job Script:

#!/bin/bash

#SBATCH --partition=long        # include the appropriate partition, node, ntasks, ntasks-pernode for the respective SLURM key

#SBATCH --ntasks=32

#SBATCH --cpus-per-task=1

#SBATCH --job-name=Gaussian

#SBATCH --output Gaussian.%J.out

#SBATCH --error Gaussian.%J.err

ulimit -s unlimited

export g16root=/data/apps

export GAUSS_SCRDIR=/scratch/$USER

. $g16root/g16/bsd/g16.profile

#Name of your input file ie H_SPE1.gjf

JobFile=force

# This creates a list of nodes that you job received to run on

LindaList=./nodes_linda.$SLURM_JOBID

touch $LindaList

# This creates a job file

JobName=./${JobFile}${SLURM_JOBID}.com

touch $JobName

# Create a list of hostnames and save it to the LindaList machine file

srun hostname -s | sort -u > $LindaList

# Tell linda to use ssh

export GAUSS_LFLAGS=' -opt "Tsnet.Node.lindarsharg: ssh"'

# Read the contents of the machine file and put it in the job file

workers="%LindaWorkers="$(cat $LindaList | tr "\n" "," | sed "s/,$//")

# Write that out to the job file

cat <(echo "${workers}") ./$JobFile.com > $JobName

g16 < ${JobFile}${SLURM_JOBID}.com > ${JobFile}.log

echo "Job Complete"