I’m interested to know if anyone has any recommended resources on DFT or DDFT (the simulation method used here) for someone with good applied math knowledge but who is not a physicist.<p>I have a decent working knowledge of stat mech from knowing about dynamical systems and information theory, but I am not a physicist. I’ve come across (classical) DFT before, but the tutorial papers I’ve come across get weighed down by a lot of physics jargon and notation that I don’t understand and they describe it in terms of certain physical systems that obfuscate whether I can adapt the method to problems I am interested (I think the answer is yes in my case but if I was confident I wouldn’t be asking). I could just rederive (classical) D or DDFT for my stochastic process, and that is likely the best way to learn it, but having a resource that is written more from the perspective of dynamical systems than a physicist would speed the process up quite a bit!
What’s really interesting to me as a non-scientist, is that the process of creating this is widely used in at least two different industries.<p>In silicon it’s called doping, and it’s pretty much the foundation of modern thin and strong glass used in everything from smartphones to car windshields.