Reddit reviews Introduction to Computational Chemistry

Mitchandre has an excellent point. This program is called an REU or Research Experience for Undergrads, and most professors will really love having an eager undergraduate for the summer to learn more. I am a computational chemist pursuing my PhD at Georgia Tech with Dr. Sherrill, and I know that we are looking for REU students every summer. I have previously worked with Dr. Robert Harrison at the University of Tennessee/Oak Ridge National Labs and he also has REU students most summers.
Here is the REU program: http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=5517&from=fund
If you are just interested in learning some computational chemistry for yourself, a book that I have found to be extremely useful and basic enough to understand at any level is Introduction to Computational Chemistry by Frank Jensen: http://www.amazon.com/Introduction-Computational-Chemistry-Frank-Jensen/dp/0470011874/ref=sr_1_1?ie=UTF8&s=books&qid=1267759772&sr=8-1

If you really wanna try and get your feet wet, try applying for an REU with any professors you can contact, plus its a great way just to see a different part of the country for a summer! Good luck

Frank Jensen's Introduction to Computational Chemistry is, in my opinion, one of the best books out there for computational chemistry. Jensen's book does a great job introducing the concepts and equations in a way that doesn't feel like you need years of background in math and physics to understand. This book lived on my desk while I was in grad school. From what I've seen, most university libraries have a copy of it in their collection.

There are books out there that go into far more detail about the various methods and give detailed mathematical proofs, like Ira Levine's Quantum Chemistry, but those are very dense and, even as someone with a PhD in the field, intimidating.

By "expensive calculation", I meant DFT. A semiempirical method such as PM6, PM3, AM1, ZINDO, etc. is much, much quicker to run and can often get you a good starting geometry for a DFT calculation. You'll need to use your eyeballs for this part though.

You usually want the best basis set you can afford. In this case, you want it to include d and f angular momentum functions to properly describe the wavefunction at the cobalt. A small basis set like 3-21G will not work. However, 6-311+G(d,p) is too costly and may fail; even though it has higher angular momentum functions, the '+' means a set of diffuse functions has been added. This will result in orbitals that are quite large but "fuzzy", potentially causing false overlap of orbitals between atoms. It's important for many anions, but unnecessary here. Something intermediate like 6-31G(d) might be acceptable for a geometry.

If you want to learn more, I highly recommend this book, this book, and maybe most of all this book, depending on how much modeling you're required to do.

Hi,

I am currently a grad student in comp/theory.

A background in programming is not necessary, but you may find yourself wanting to get familiar with programming for data analysis. You should feel comfortable in the terminal to begin something like this (but I've seen people with almost no computer skills learn to run MD simulations within a few weeks of struggle).

The points I give below apply to most questions of this sort.

A good starting place is considering what do I want to simulate?
Consider the underlying physics. If you can write the formulas of what you want to observe with statistical mechanics consider molecular dynamics or monte carlo. If you require quantum mechanics use post Hartree-Fock or DFT.

Do you want to simply look at a change in structure? MD will work. Do you want to look at the process of polymerization? That requires bond formation which requires quantum mechanics. A note: SCF is not orthogonal to MD; there exists QM/MD origrams such as terachem but its sounds fairly impractical to apply to a polymer.

Lets say you wanted to observe the unfolding of a polymer w.r.t. temperature. This could be observed with molecular dynamics. Now you need to consider what program to use. I don't know your system but NAMD is a good starting place because it is fairly user friendly. If you'd like some reading suggestions I'd suggest skimming Jensen's comp chem Let me know if you have more questions

DISCLAIMER:
I am a QM guy specifically quantum Monte Carlo, but I work closely with NAMD users

http://www.amazon.com/Introduction-Computational-Chemistry-Frank-Jensen/dp/0470011874/ref=pd_bxgy_b_img_b

This is a good book. Also you should become familiar with programs like Gaussian (http://www.gaussian.com/) and BOSS (http://zarbi.chem.yale.edu/software.html)