Percolation in Networks of Liquid Diodes.

Area of Science:

• Surface science and fluid dynamics
• Materials science and engineering
• Network theory

Background:

• Liquid diodes enable directional spontaneous liquid flow, crucial for natural processes like water uptake and feeding.
• Existing large-scale directional liquid networks are rare and limited in size.

Purpose of the Study:

• To simulate, design, and 3D print large-scale liquid diode networks.
• To establish guidelines for structural and wettability properties for directional liquid transport.
• To apply percolation theory to understand network connectivity and fluid transport thresholds.

Main Methods:

• Computational simulation and 3D printing of multi-unit cell liquid diode networks.
• Experimental investigation of liquid transport in uni- and bidirectional pathways.
• Application of percolation theory to analyze network connectivity and predict fluid behavior.

Main Results:

• Successful creation of large liquid diode networks with hundreds of unit cells.
• Development of structural and wettability guidelines for predictable directional liquid transport.
• Experimental validation of theoretical models for directed percolation and accurate prediction of network permeability and liquid state.

Conclusions:

• 3D printable liquid diode networks can achieve predictable, spontaneous directional liquid transport at large scales.
• Percolation theory effectively models fluid flow thresholds in these networks.
• The developed guidelines are promising for creating advanced structures for controlled liquid movement.