Student(s): Chiwon Yu
Project: Impact of Coasting Speed and Temperature On Organic Film Effect Transistor Performance | View Poster (PDF)
Major(s): Chemical Engineering
Advisor(s): Elsa Reichmnanis
Abstract
The effect of coating speed and temperature on organic field-effect transistors (OFETs) fabricated via blade coating was investigated. The organic polymer, poly[2,5-(2-octyldodecyl)-3,6-diketopyrrolopyrrole-alt-5,5-(2,5-di(thien-2-yl)thieno[3,2-b]thiophene)] (DPP-DTT), was dissolved in chlorobenzene (5 g/L) and blade-coated at temperatures ranging from room temperature (RT) to 100°C with coating speeds of 1, 3, and 5 mm/s. Charge mobility measurements revealed a linear decrease in mobility with increasing coating speed at RT, 40°C, and 100°C. However, at 60°C and 80°C, mobility showed the trend, decreasing at 3 mm/s but recovering at 5 mm/s. This behavior suggested a transition between different coating regimes, including evaporation and Landau-Levich regimes. At lower temperatures, mobility decline was likely due to insufficient solvent evaporation, leading to non-uniform film formation. In contrast, high temperatures (100°C) led to rapid solvent loss, which may hinder optimal polymer order. The trend observed at 60°C and 80°C suggested an interplay between solvent evaporation and fluid flow, which may influence the final film properties and charge transport. These findings highlighted the importance of optimizing coating parameters to improve OFET performance.
About Chiwon Yu
Chiwon Yu is a senior majoring in Chemical Engineering at Lehigh University. Born in South Korea, he immigrated to the United States after high school and began his academic journey at a community college before transferring to Lehigh. He was awarded the Alumni Experiential Learning Award in 2023 and 2024 for his research projects. Currently, he is conducting research in Dr. Reichmanis’ Lab, working with graduate student Myeongyeon Lee to fabricate high-performance Organic Field-Effect Transistors (OFETs). His research focuses on optimizing OFET performance by varying key factors such as solvent type and coating conditions. Additionally, he analyzes experimental and literature data using machine learning to identify the most influential parameters. Outside of academics, he enjoys playing video games and watching movies.