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Versatility of Protocols for Resistance Training and Assessment Using Static and Dynamic Ladders in Animal Models

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Learning to learn by using nonequilibrium training protocols for adaptable materials.

Martin J Falk¹, Jiayi Wu¹, Ayanna Matthews²

¹Department of Physics, The University of Chicago, Chicago, IL 60637.

Proceedings of the National Academy of Sciences of the United States of America

|June 26, 2023

Summary

This summary is machine-generated.

Synthetic materials can be trained for adaptability, performing multiple functions by switching targets. This strategy enables materials like elastic networks and heteropolymers to adapt with minimal design changes, revealing physical principles of adaptability.

Keywords:

adaptability disordered materials inverse design materials training

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Area of Science:

Materials Science
Computational Science
Biophysics

Background:

Biological systems evolve adaptability to thrive in changing environments.
Environmentally responsive materials offer potential for synthetic adaptability.
High-dimensional inverse problems in materials design present challenges for achieving multiple functionalities.

Purpose of the Study:

To develop a training strategy for synthetic materials to achieve adaptability.
To demonstrate the ability of materials to perform incompatible functionalities with minimal parameter changes.
To explore the physical principles underlying material adaptability.

Main Methods:

Utilizing high-dimensional inverse problems for materials design.
Employing a target-switching algorithm to train material adaptability.
Simulating adaptable elastic networks and heteropolymer folding pathways.

Main Results:

Successfully trained materials to switch between incompatible functionalities.
Achieved functional switching with minimal changes in design parameters.
Identified physical principles like nucleation-controlled folding enabling adaptability.

Conclusions:

A novel training strategy enables synthetic materials to exhibit adaptive behaviors.
Minimal design parameter changes can unlock diverse functionalities in materials.
The approach provides insights into physical mechanisms governing material adaptability.