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The fluidic memristor as a collective phenomenon in elastohydrodynamic networks
Alejandro Martínez-Calvo1,2, Matthew D Biviano3, Anneline H Christensen3
1Princeton Center for Theoretical Science, Princeton University, Princeton, NJ, 08544, USA.
Nature Communications
|April 10, 2024
Summary
Researchers developed a
Area of Science:
- Fluid dynamics
- Soft materials science
- Nonlinear systems
Background:
- Fluid flow networks are essential in both engineered and biological systems.
- Individual components of these networks often display nonlinear pressure-flow relationships.
- The collective behavior of these nonlinear elements remains poorly understood.
Purpose of the Study:
- To investigate the collective behavior of soft fluid flow networks.
- To understand networks with elements exhibiting negative differential resistance.
- To identify mechanisms governing the emergent properties of these networks.
Main Methods:
- Combined theoretical analysis, experimental validation, and numerical simulations.
- Focused on soft flow networks with nonlinear resistive elements.
- Investigated the impact of negative differential resistance on network behavior.
Main Results:
- A minimal network of nonlinear resistors, termed a 'fluidic memristor', was identified.
- This fluidic memristor exhibits history-dependent resistance.
- The network demonstrates characteristics analogous to hysteresis loops, enabling information storage.
Conclusions:
- Fluidic memristors represent a novel class of tunable resistors for fluidic systems.
- Insights gained can advance applications in soft robotics, biomedical engineering, and materials science.
- This work may also enhance understanding of physiological flow networks in plants and animals.
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