Hoang-Giang Nguyen

Reciprocity can halve what a mechanical network can learn

A passive, reciprocal, linear network driven by forces or currents and read at points it drives cannot be trained below an error floor computed from the target beforehand. The usual parameter count for such networks does not charge for Maxwell-Betti reciprocity. We prove that when such an elastic, resistor or flow netw...

Effect of defects on fracture and mechanical properties in Cu/Zr nanolayers