Tag Archives: Chemistry

Stochastic chemical kinetics – things randomly bumping into each other

In this blog post I describe the advantages of taking a stochastic view of chemical systems based on the work of D. T. Gillespie and subsequent publications. Gillespie presented his formalism for considering stochastic chemical kinetics, now referred to as the Gillespie Algorithm, in two papers published in 1976 and 1977 (Gillespie, D. T. J. Comp. Phys. 1976, Gillespie D. T. J. Phys. Chem. 1977) – if you want to see the full derivation for the Gillespie Algorithm along with many examples I recommend giving them both a read.

The essential question of chemical kinetics as stated by Gillespie is:

“If a fixed volume V contains a spatially uniform mixture of N chemical species which can inter-react through M specified chemical reaction channels, then given the numbers of molecules of each species present at some initial time, what will these molecular population levels be at any later time?”

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My experience with (semi-)automating organic synthesis in the lab

After three years of not touching a single bit of glassware, I have recently donned on the white coat and stepped back into the Chemistry lab. I am doing this for my PhD project to make some of the follow-up compounds that my pipeline suggests. However, this time there is a slight difference – I am doing reactions with the aid of a liquid handler robot, the Opentrons. This is the first encounter that I have with (semi-)automated synthesis and definitely a very exciting opportunity! (Thanks to my industrial sponsor, Diamond Light Source!)

A picture of the Opentrons machine I have been using to do some organic reactions. Picture taken from https://opentrons.com/robots.

Opentrons is primarily used by biologists and their goal is to make a platform to easily share protocols and reproduce each other’s work (I think we can all agree how nice this would be!). They provide a very easy to use API, wishing it to be accessible to any bench scientist with basic computer skills. From my experience so far, this has been the case as I found it extremely easy to pick up and write my own protocols for chemical reactions. Here is the command that will: (1) pick up a new pipette tip; (2) transfer a volume from source1 to destination1; (3) drop the pipette tip in the trash; (4) pick up a new pipette tip; (5) transfer a volume from source2 to destination2; (5) drop the pipette tip in the trash.

pipette.transfer(volume, [source1, source2], [destination1, destination2], new_tip=’always')

But of course not everything is plain sailing – there are many challenges you will encounter by using an automated pipette. The robot is a liquid handler – it cannot handle solids so either the solids need to be pre-weighed and/or made into solution beforehand. Further difficulties lie within the properties of the solvent it is handling, for example:

  • Dripping – low boiling point solvents tend to drip more.
  • Viscosity of liquids causes issues with not drawing up the correct amount of liquid – more viscous liquids require longer times to aspirate and if aspiration is too quick then air pockets may be drawn up.

Here is a GIF I made of a dry run I was doing with the robot (sorry for the slight shake, this was recorded on my phone in the lab… See their website for professional footage of the robot!)

My (shaky) footage of a dry run I was performing with the Opentrons.