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Patterning of Microorganisms and Microparticles through Sequential Capillarity-assisted Assembly

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Surface-directed spinodal decomposition on chemically patterned substrates.

Prasenjit Das^1,2, Prabhat K Jaiswal³, Sanjay Puri²

¹Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot 76100, Israel.

Physical Review. E

|August 16, 2020

Summary

This summary is machine-generated.

Surface-directed spinodal decomposition (SDSD) involves phase separation and wetting at surfaces. This study numerically investigates SDSD on patterned substrates, observing a crossover from surface-registry to phase-separation regimes near the surface.

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Area of Science:

Materials Science
Physical Chemistry
Surface Science

Background:

Surface-directed spinodal decomposition (SDSD) is a critical phenomenon combining phase separation and surface wetting.
Understanding SDSD is vital for numerous scientific and technological applications.
Chemically patterned substrates offer a route to control interfacial dynamics.

Purpose of the Study:

To numerically investigate surface-directed spinodal decomposition (SDSD) on chemically patterned substrates.
To analyze the dynamical crossover between surface-registry and phase-separation regimes.
To elucidate the influence of surface patterns on SDSD dynamics.

Main Methods:

Numerical simulations of SDSD on chemically patterned substrates.
Analysis using layerwise correlation functions.
Characterization via structure factors and domain length scales.

Main Results:

Observation of a dynamical crossover from a surface-registry to a phase-separation regime in surface-proximal layers.
Demonstration that simulation results are applicable to arbitrary surface patterns, not just simple ones.
Detailed study of the crossover dynamics using various analytical tools.

Conclusions:

Surface patterns significantly influence the dynamics of spinodal decomposition near interfaces.
The observed crossover mechanism provides fundamental insights into interfacial phenomena.
This research contributes to the predictive understanding and control of phase separation on patterned surfaces.