Recently, I’ve been working to assign the relative configuration of some tricky diastereomers, which has led me to do a bit of a deep dive into the world of computational NMR prediction.

Python is an easy language to write, but it’s also very slow.

Eric Gilliam, whose work on the history of MIT I highlighted before, has a nice piece looking at Irving Langmuir’s time at the General Electric Research Laboratory and how applied science can lead to advances in basic research.

When thinking about science, I find it helpful to divide computations into two categories: models and oracles.

—Richard Hamming What’s the difference between science and engineering? Five years ago, I would have said something along the lines of “engineers study known unknowns, scientists study unknown unknowns” (with apologies to Donald Rumsfeld), or made a distinction between expanding the frontiers of knowledge (science) and settling already-explored territory (engineering). These thoughts seem broadly consistent with what others think.

Every year, our group participates in a “Paper of the Year” competition, where we each nominate five papers and then duke it out in a multi-hour debate.

For almost all Hartree–Fock-based computational methods, including density-functional theory, the rate-limiting step is calculating electron–electron repulsion.

While looking over papers from the past year, one theme in particular stood out to me: meta-optimization, or optimizing how we optimize things.

Note: old versions of this post lacked a discussion of S _N 2. I've added an appendix which remedies this. In “The Rate-Limiting Span,” I discussed how thinking in terms of the span from ground state to transition state, rather than in terms of elementary steps, can help prevent conceptual errors. Today, I want to illustrate why this is important in the context of a little H/D KIE puzzle.

Last January, I aimed to read 50 books in 2022. I got through 32, which is at least more than I read in 2021. There’s been a bit of discourse around whether setting numerical reading goals for oneself is worthwhile or counterproductive.

A technique that I’ve seen employed more and more in computational papers over the past few years is to calculate Boltzmann-weighted averages of some property over a conformational ensemble.