5 citations · 6 across the 5 of their papers we have counts for
8 papers · 1 filter
Training precise stress patterns
Daniel Hexner
We introduce a training rule that enables a network composed of springs and dashpots to learn precise stress patterns. Our goal is to control the tensions on a fraction of "target"…
Adaptable materials via retraining
Daniel Hexner
Elastic metamaterials are often designed for a single permanent function. We explore the possibility of altering a material's function repeatedly through a self-organization, "trai…
Training nonlinear elastic functions: nonmonotonic, sequence dependent and bifurcating
Daniel Hexner
The elastic behavior of materials operating in the linear regime is constrained, by definition, to operations that are linear in the imposed deformation. Though the nonlinear regim…
Supervised learning in physical networks: From machine learning to learning machines
Menachem Stern, Daniel Hexner, Jason W. Rocks +1
Materials and machines are often designed with particular goals in mind, so that they exhibit desired responses to given forces or constraints. Here we explore an alternative appro…
Effect of aging on the non-linear elasticity and memory formation in materials
Daniel Hexner, Nidhi Pashine, Andrea J. Liu +1
Disordered solids often change their elastic response as they slowly age. Using experiments and simulations, we study how aging disordered planar networks under an applied stress a…
Directed aging, memory and Nature's greed
Nidhi Pashine, Daniel Hexner, Andrea J. Liu +1
Disordered materials are often out of equilibrium and evolve very slowly. This allows a memory of the imposed strains or preparation conditions to be encoded in the material. Here…