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Multi-scale modeling of early-stage morphology in solution-processed polycrystalline thin films
David L Patrick1, Cyrus Schaaf, Robell Morehouse
1Department of Chemistry, Western Washington University, 516 High St., Bellingham, WA 98225, USA. david.patrick@wwu.edu.
Physical Chemistry Chemical Physics : PCCP
|April 26, 2019
Summary
A new model accurately predicts film formation in solution-processed polycrystalline films. It captures nucleation, growth kinetics, and domain structure, matching experimental data for tetracene films.
Area of Science:
- Materials Science
- Chemical Engineering
- Physics
Background:
- Submonolayer polycrystalline films are crucial in various applications.
- Understanding nucleation and growth kinetics is key for controlling film properties.
- Solution-phase processing offers versatile fabrication methods.
Purpose of the Study:
- To develop a predictive model for early-stage nucleation, growth kinetics, and mesoscale domain structure in solution-processed submonolayer polycrystalline films.
- To combine stochastic nucleation with deterministic diffusion dynamics.
- To validate the model against experimental data.
Main Methods:
- A hybrid model integrating classical nucleation theory with a 2D diffusion equation.
- Numerical solution of the diffusion equation, treating nuclei as monomer sinks.
- Comparison with experimental measurements of solution-processed submonolayer tetracene films using vapor-liquid-solid deposition.
Main Results:
- Excellent agreement between model predictions and experimental observations.
- Accurate prediction of distinct induction, nucleation, and growth regimes.
- Precise matching of nucleation onset time, domain density, and domain spacing statistics.
- Detailed insights into the evolving monomer concentration landscape and derived rates.
Conclusions:
- The developed model provides a robust framework for understanding and predicting film formation in solution-processed submonolayer polycrystalline films.
- The model successfully captures key kinetic and structural characteristics, validating its predictive power.
- This work offers a valuable tool for optimizing fabrication processes and material design.
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