Achieving predictable biomimetic crystallization using sequence-defined synthetic molecules in mild conditions represents a long-standing challenge in materials synthesis. Herein we report a ...

This letter investigates the universal approximation capabilities of Hamiltonian Deep Neural Networks (HDNNs) that arise from the discretization of Hamiltonian Neural Ordinary Differential Equations.

These results strengthen Sweldens earlier analysis and confirm that the approximation power of biorthogonal and (semi-)orthogonal wavelet expansions is essentially the same. Finally, we compare the ...

This study reports a design of a variety of nanostructured films of 2D oxide nanosheets. We systematically examined the deposition of perovskite-type Ca2Nb3O10– nanosheets by spin-coating their ...

This map can be expanded to capture every way you can adjust a material. Each adjustable knob, or parameter, adds a new dimension you can move in on the map. Imagine tracking how quickly the arrow ...