  Direct design of complex functional materials would revolutionize
technologies ranging from printable organs to novel clean energy devices.
However, even incremental steps towards designing functional materials have
proven challenging. If the material is constructed from highly complex
components, the design space of materials properties rapidly becomes too
computationally expensive to search. On the other hand, very simple components
such as uniform spherical particles are not powerful enough to capture rich
functional behavior. Here, we introduce a differentiable materials design model
with components that are simple enough to design yet powerful enough to capture
complex materials properties: rigid bodies composed of spherical particles with
directional interactions (patchy particles). We showcase the method with
self-assembly designs ranging from open lattices to self-limiting clusters, all
of which are notoriously challenging design goals to achieve using purely
isotropic particles. By directly optimizing over the location and interaction
of the patches on patchy particles using gradient descent, we dramatically
reduce the computation time for finding the optimal building blocks.
