It's, in practice, applied gradient-based optimization on a geometrically-defined objective, which means if you squint hard enough it's machine learning.
(I am a crystallographer turned machine learning engineer.)
Many bits of physics start out as "did geometry". Will this particular idea pan out? Probably not. Should it be the subject of popular press at this stage? Probably not. But it's worth having scientists explore the possibilities. The paper might be interesting to specialists, once published, https://journals.aps.org/prl/accepted/33074Yb3Ufa1478fd33b04...
A decade ago I would have agreed with you. But then I discovered the topic of five-symmetries and my absolute favorite non-toxic non-stick pans are coated with that alloy (not long ago deemed impossible) that has the five way symmetry.
So the practical applications are not far behind for these "only 2D" crystals.
adw|2 years ago
(I am a crystallographer turned machine learning engineer.)
p1mrx|2 years ago
jacobolus|2 years ago
peterlada|2 years ago
So the practical applications are not far behind for these "only 2D" crystals.