Litcius/Paper detail

Transient learning degrees of freedom for introducing function in materials

Varda F. Hagh, Sidney R. Nagel, Andrea J. Liu, M. Lisa Manning, Eric I. Corwin

2022Proceedings of the National Academy of Sciences38 citationsDOIOpen Access PDF

Abstract

SignificanceMany protocols used in material design and training have a common theme: they introduce new degrees of freedom, often by relaxing away existing constraints, and then evolve these degrees of freedom based on a rule that leads the material to a desired state at which point these new degrees of freedom are frozen out. By creating a unifying framework for these protocols, we can now understand that some protocols work better than others because the choice of new degrees of freedom matters. For instance, introducing particle sizes as degrees of freedom to the minimization of a jammed particle packing can lead to a highly stable state, whereas particle stiffnesses do not have nearly the same impact.

Topics & Concepts

Transient (computer programming)Degrees of freedom (physics and chemistry)Function (biology)Computer scienceControl theory (sociology)Materials sciencePhysicsArtificial intelligenceCell biologyBiologyThermodynamicsOperating systemControl (management)Force Microscopy Techniques and ApplicationsMaterial Dynamics and PropertiesMechanical and Optical Resonators