Exploring the Depths of Gaussian

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Apologies for my recent lack of posts, but I’ve been away this week at Imperial College London for the NSCCS Gaussian Workshop for Beginners.

I thought I knew a little bit about Gaussian before it started, but this course really was an eye-opener! I studied a small amount of computational chemistry during my undergraduate degree, so I was familiar with the basics of the theory, but definitely needed to refresh myself on a lot of it.

Luckily, the NSCCS provided us with real experts in Gaussian, with two speakers coming from California to share their wisdom, with Professor Hrant Hratchian having worked for Gaussian previously and written part of the code.

We were led through lectures which boggled our minds a little at first, but they were made more clear through the later hands on sessions. It felt good to try out the software for ourselves, and carry out some very basic calculations, but we often ran out of time and couldn’t complete some of the exercises. Nevertheless, I feel confident I could carry out some of these simple calculations on my own compounds after this training.

What really surprised me was how easily you can calculate spectra and molecular orbitals using the software. IR spectra are simple to obtain, and you can visualise the vibrations using animations on GaussView – a really helpful programme that guides you through the entire process from inputting your molecule to reading off the results.

NMR spectra can also be calculated, although these calculations do take more time. This would be invaluable to my research, and I’m confident it would be worth the computational expense.

We were also told how to investigate transition states, account for solvation effects and carry out calculations on very large molecules without the huge corresponding cost.

Of course, these calculations only work well if you choose the right level of theory for your system, and this is the first bridge I’ll have to cross if my dip into computational chemistry is to be a success.

However, my first impression of the Gaussian package is that, if I can figure out how to make it work for me, it could prove very useful for my research, and I’m looking forward to giving it a try.

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