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I asked this on Physics.SE and got recommended here.
More precisely, as a condensed matter theory PhD student, I am often overwhelmed by the wide variety of chemical formulas that experimentalists trot out for their results. I'm thinking about the cuprates, transition metal dichalcogenides, iron pnictides, SrRu with O$_3$, O$_4$, O$_7$, and many more.
Welcome to the club of academic migrants! I didn't take any university-level chemistry courses during my undergrad years (except a special topics course for graduate students called "bioelectronics" which one might say was more physics and biology than chemistry). I was much more interested in physics and biology (and math) than chemistry, so I pursued a double major and double minor with my majors being "BMath in Applied Math" and "BSc in Honours Science", with the minors being in Physics and Biology.
However, my PhD ended up being granted from a chemistry department, and in recent years I probably worked more in quantum chemistry than in any other field. I know exactly how it feels.
It might seem hypocritical for me to say this, because I personally didn't do this, but hindsight is 2020 (or in my case, maybe even 1970 since my early lack of interest in chemistry might even trace back to my family always talking about physics, math and biology but rarely chemistry). It sounds like you're a relatively new PhD student and will have to take graduate-level courses anyway, so I hope my advice (based on what I'd probably do if I could turn back time) will be useful for your academic career: I'd recommend taking the following chemistry courses if available: inorganic chemistry, transition metal chemistry, heavy-metal chemistry (involving lanthanides and actinides), solid-state chemistry. The following topics might also be of interest: quantum chemistry, computational chemistry (lab), main group chemistry.
For quite some time, I've wanted to audit some of those courses, but I can't do it during COVID and during an extremely busy teaching term. If you were to ask for my advice (considering that my background is similar to yours, as well as my career trajectory, except that I was in your shoes many years ago), I would say to take those courses as early as possible! A lot of (or almost all of?) applied materials physics is chemistry.
I'm grad student about to finish their PhD, so you may find my perspective valuable.
For reference, my undergrad degree was in physics and math, where I did big data analysis on high energy data gathered at CERN. I had some much earlier experience working in a condensed matter lab, yet gained very little (to no) chemistry experience. To date, I have never actually taken a condensed matter course -- and don't intend to. I likewise don't have any specialized training in chemistry, and never took a chemistry class.
Despite this, I feel that I've developed a strong enough understanding of the field to curate my own interest and pursue my own problems. This is in part due to a research mindset that I inherited from my supervisor, and in part due to my own personal preferences toward learning.
The mindset is as follows: Find some problem that interests you enough that you'll throw everything you got at it. Maybe you know nothing about the field -- no general knowledge, no specialized techniques, absolutely nothing. It's like staring out at an ocean -- and condensed matter is a vast ocean -- and not knowing how to pass the beach. Don't fret. Pursue your problem with as much zeal as your interest can muster. Learning everything related to this problem; and with time, effort, and some help, you'll find before you a tiny island of knowledge, deep in the scientific ocean.
Some people might say (and you might feel) that it is necessary to take a class about X, Y, and Z in order to even start doing proper research. But homework -- simple problems that have a clear answer in a book -- will only have you playing in the shallows. Yes, you should calculate and do problems, perhaps even from a book (or paper) if it helps, but always in pursuit of your problem.
These smaller problems orbiting your goal will form the beaches of this tiny island of knowledge. And it is that island which will define your unique perspective as a researcher, and allow you to see farther in the scientific ocean than you could if you stayed in the shallows. And with time, and more island forming research in the deep, you'll have an archipelago to call your own.
Essentially, what I mean by this bit of philosophical mumbo jumbo is: dive deep into an interesting problem. Your own efforts in solving the problem will provide you the ground-level knowledge needed to do other things in your field. And perhaps most importantly, it is the only way to actually learn how to research -- doing research.
This is definitely just my perspective, one which is informed by my experiences. No doubt I am on the extreme end of being class anti-oriented.
As a personal example, I started my theory career studying the Fe-based superconductors (pnictides and chalcogenides). In particular, I chose one material in that broader family -- FeSe -- and studied the hell out of it. Not only are many of the Fe-based superconductors electronically similar, in part owing to the similarities in their symmetries, but I find that the tools I learned translate to other unrelated materials as well.
In real materials, there are also many different types of measurement techniques and experiments: conductance, photoemission, scanning tunneling microscopy, to name a few. I find it can be overwhelming at times, especially when some critical new research in the field depends on a set of techniques which are entirely new to me. But it's in these novel moments that I find the chance to develop my best physics intuition. And a lot of the time, these many different measurements can be related to a few key concepts -- e.g density of states (DOS) shows up everywhere.
Lastly, as a new theory researcher you may consider exposing yourself to cutting-edge numerical methods, such as the Density Matrix Renormalization Group (DMRG), machine learning (ML), or Density Functional Theory (DFT). It's a bit of a myth that you need to invest your entire graduate career in order to learn these things, or that you won't have the opportunity to learn them if your supervisor isn't an expert. There are actually a number of readily accessible tools and codebases from which one can start: QuantumEspresso=DFT, ITensor=DMRG, and Keras/TensorFlow=ML are just a few that I've used.
These toolsets aren't just useful blackboxes either, but a fully functioning code that has the potential to teach you the method. It can be challenging to build up a codebase from scratch, as there a lot of new things to learn, and all the pieces have to fit just right in order for it to properly compute. But a fully functioning codebase can have pieces rewritten piece by piece, with the understanding that if it doesn't compute, then it's your piece that's bad. There are also tons of related workshops where you can learn from the pros.
This top-down approach to novel numerical methods is how industry teaches machine learning, since it's pedagogically faster, and allows one to get results while they learn. If you're supervisor talks about one of these techniques, but they themselves don't have experience coding them, then they'll likely be super impressed if you did. You might suddenly find yourself becoming extremely valuable to your research group.
Answering "How does a beginner condensed matter theorist working on real materials, get up to speed?" is not as easy as it could appear.
From my own experience, if you are a condensed matter theory PhD student and only focus on condensed matter, you will (should?) grow faster.
In my case, I am a physicist and also made my PhD in theoretical condensed matter physics (developing a phonon laser called SASER). But then, I moved to make a post-doc in an experimental semiconductor group (coming back to my undergrad / master main subject). After the first year, I come back to applying theory to the semiconductor devices studied in the group.
Then, I began to work as professor in my actual university. At the time (2006), the older researchers (all chemist and pharmacist) worked in inorganic chemistry developing materials and in organic chemistry in drug development for different diseases. In order to be inserted in that (new) research lines, I did a lot of individual studies and an organic chemistry course with one of the colleagues I was collaborating with. Certainly the latter "delayed" me a bit.
Now, I can move between condensed matter, structural biology and drug development. So, for me, it was a win-win path.
