I’m giving my Statistical Thermodynamics Lectures this week. I have about 3.5 hours, which includes a double slot on Thursday. I hate double slots, and I suspect the students do too, but that’s another subject!

So, as with the Quantum Chemistry, it comes down to deciding what to cover and in how much detail. I start by trying to explain the importance of the subject – bridging the macroscopic and microscopic strands of Physical Chemistry, enabling the calculation of thermodynamic quantities etc. To be honest, I don’t know how much of an impact that statement makes to the students, because until you’ve seen the ‘bigger picture’ it’s hard to see the subject in this way. But I think it’s important, otherwise the subject is in danger as being viewed as ‘just a collection of equations’.

In the first lecture I start with the Boltzmann Distribution, which has been covered before, so hopefully it’s revision. That takes me straight into partition functions, and I try to eplain why they are useful and what information they give. I suspect if the person who taught this subject to me had done this at the time, it might have made more impact! I then go through translational, rotational and vibrational partition functions and give examples of calculations. Last year there were issues with units, and confusion between wavenumber and frequency, so I’ll spend a bit of time on that.

Lecture two is about using Statistical Thermodynamics to calculate thermodynamic properties. Starting with internal energy, we consider heat capacity, residual entropy, and finally entropy itself, using the Sackur-Tetrode equation, that celebrates its centenary this year. Heat capacity and residual entropy are good examples because there are experimental values to compare with. I show some example calculations, and try to stress that these have to be done in stages, because calculators can’t cope with the magnitude of some of the numbers involved.

I’ll consider lecture 3 in a separate post. It will need some thought for this year, because some of the material I’ve covered previously didn’t go down too well last year. Thankfully I have some time to sort this out!

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3.5 hours is not much time to put across Stat mech. I think that besides the applications using partition functions, a statistical interpretation of entropy is important.

Agreed. I do try to include the statistical interpretation of entropy in lecture 3, but find it hard to explain clearly. I’ll put my lecture on the web tomorrow, so if you have a moment to see how I do it and comment, I would appreciated it.