Studying Crystal Growth Kinetics via Monte Carlo Simulation
Research Mentor(s)
Patrick, David L.
Description
Polycrystalline thin films of the organic semiconductor tetracene prepared using an approach called organic vapor-liquid-solid (OVLS) deposition have been studied via kinetic Monte Carlo (KMC) simulation. Understanding and controlling crystallization in such systems is important for applications such as solar cells, flexible displays, and lighting applications. We use KMC simulations to investigate the main kinetic parameters affecting the crystal growth. These simulations are compared to experimental data, and parameter values such as the relative monomer sticking probabilities on different crystal faces are determined. This poster describes the simulation algorithm develop for these studies, as well as initial results.
Document Type
Event
Start Date
17-5-2017 12:00 PM
End Date
17-5-2017 3:00 PM
Department
Chemistry
Genre/Form
student projects; posters
Subjects – Topical (LCSH)
Crystal growth--Computer simulation; Crystal growth--Mathematical models; Molecules--Models
Type
Image
Rights
Copying of this document in whole or in part is allowable only for scholarly purposes. It is understood, however, that any copying or publication of this documentation for commercial purposes, or for financial gain, shall not be allowed without the author's written permission.
Language
English
Format
application/pdf
Studying Crystal Growth Kinetics via Monte Carlo Simulation
Polycrystalline thin films of the organic semiconductor tetracene prepared using an approach called organic vapor-liquid-solid (OVLS) deposition have been studied via kinetic Monte Carlo (KMC) simulation. Understanding and controlling crystallization in such systems is important for applications such as solar cells, flexible displays, and lighting applications. We use KMC simulations to investigate the main kinetic parameters affecting the crystal growth. These simulations are compared to experimental data, and parameter values such as the relative monomer sticking probabilities on different crystal faces are determined. This poster describes the simulation algorithm develop for these studies, as well as initial results.