Abhishaike Mahajan recently wrote an excellent piece on how generative ML in chemistry is bottlenecked by synthesis (disclaimer: I gave some comments on the piece, so I may be biased).

I've been playing around with generating non-equilibrium conformations by molecular dynamics recently, and I've been thinking about how to best parse the outputs of a dynamics simulation.

Scientific software can be confusing, particularly when you're doing something that the software isn't primarily intended for.

Much molecular design today can be boiled down to “put the right functional groups in exactly the right places.” In catalysis, proper positioning of functional groups to complement developing charge or engage in other stabilizing non-covalent interactions with the transition state can lead to vast rate accelerations.

Pure mathematics has all sorts of unexpected connections to other fields, and chemistry is no exception.

Apologies for the long hiatus: we've had some health issues in the family, and startup life has been particularly overwhelming.

In Wednesday’s post, I wrote that “traditional physical organic chemistry is barely practiced today,” which attracted some controversy on X. Here are some responses:

In this post, I’m trying something new and embedding calculations on Rowan alongside the text.

(Previously: 2022) #1. Tony Fadell, Build #2. Giff Constable, Talking To Humans #3. Ben Horowitz, The Hard Thing About Doing Hard Things #4. Dale Carnegie, How To Win Friends And Influence People Sounds Machiavellian, but actually quite wholesome: a “dad book,” as my friend

“And I took the little scroll from the hand of the angel and ate it.

I took a pistol course in undergrad, and while I was a poor marksman I enjoyed the experience.