[ProllyInfamous]

The only undergraduate class I had to repeat (because I failed its outdated-ness) was a 1hour lab for physical chemistry, which was taught by a geriatric whom still expected us to use decades-outdated "scientific software" [still DOS prompts, in mid-2000s?!?!] to perform calculations in support of since-disproven theories (mostly: his).

His class had a similar $$self$-$published$$ "book" [a packet of stapled 10lb paper] which hadn't been updated since his thesis, some sixty years earlier (literally 80+, now). Required turn-ins carried serialized imprints!

RIP when he died that summer and next year I retook the same class, with much more ease / better instruction.

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Dr. Shithead's wife was actually responsible for my entire scholarship, sweet-as-pie, and we'd often joke about her husband's "reputation" – he's so gentle with me, but I know who he is.

Both are longdead, now – thanks Drs. T-s!

[StableAlkyne]

> decades-outdated "scientific software" [still DOS prompts, in mid-2000s?!?!] to perform calculations in support of since-disproven theories (mostly: his).

Most computational chemistry is still done on the command line using decades old codes.

Gaussian is from the 70s, and it's still a major workhorse for small molecules. CP2K is from 2000 and is still popular for solid state.

It's actually a big barrier to entry in the field, because in addition to learning theory, you also have to know the Linux command line and whatnot

[ProllyInfamous]

Around the same time, decades ago (and until recently), my father (a post-tension concrete expert, P.E.), was still using an early 1980s DOS program to design 8- & 9-figure government facilities.

I guess the span deflection/moment/&c calculations don't really change much (i.e. get fancy) on brutalist state buildings. But he did grow up hand-drafting blueprints (I remember the ink/smell from my childhood) and did have a regular 3D/CAD technologist for fancier designs (he despised architects' more-esoteric "Vision").

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Wouldn't much of modern chemistry rapidly be integrating/upgrading within python environments (e.g. AlphaFold) on much-faster equipment? I know a few PhDs that are blown away by recent advances in dissertation-level output from machines — in days vs. entire graduate programs – and even walked the graduation stage with (now-Nobel Laureate) John, an Alphafold co-publisher... obviously his perspective is unique/polar.