Discussed at: https://news.ycombinator.com/item?id=36951815 (198 comments)
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.
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.
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.
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!