Statistical Method to Optimize the Efficiency of Multi-Layer Polymer LEDs
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Statistical Method to Optimize the Efficiency of Multi-Layer Polymer LEDs Michele Cecchi1, David Braun2, Heather Smith3, and Linda Vanasupa1 1 Cal Poly State University, Materials Engineering Dept, San Luis Obispo, CA 2 Cal Poly State University, Electrical Engineering Dept, San Luis Obispo, CA 3 Cal Poly State University, Statistics Dept, San Luis Obispo, CA ABSTRACT Research and development of displays and image sensors based on semiconducting polymers require design of new polymer materials and evaluation of film properties. Optimizing device performance using a one-factor-at-a-time (OFAT) requires screening the effect of several process parameters, running numerous samples, and may consume more scarce new material than desired. This paper investigates the effects of Indium-tin oxide (ITO), alkoxy-poly(pphenylene vinylene) (OC1C10-PPV) and poly(3,4-ethylene dioxythiophene) (PEDOT) layer preparation on polymer LED brightness and power efficiency by performing and analyzing a two-cubed full-factorial design experiment with 3 replicated center points. Full-factorial design evaluates all main factors and all interactions. Design of experiments (DOE) showed that correct selection of ITO anneal temperature can significantly improve brightness. Atomic Force Microscopy (AFM) measurements affirm that the increased brightness correlates with a reduction in ITO average surface roughness.
INTRODUCTION The discovery of conjugated polymers has generated great interest in lightweight displays, large area image sensors, solar cells and inexpensive integrated circuits. Several companies are actively researching, developing, or producing polymer LEDs for displays and lighting applications. The purpose of this study is to identify important factors that influence device performance with the dual aims of optimizing the brightness and power efficiency of Ca/OC1C10PPV/PEDOT/ITO LEDs. This study takes advantage of statistical methods in an effort to enhance the efficiency of designing and performing the experiments. The design of experiments (DOE) technique assists with setting up initial experiments to screen process parameters with an efficient number of samples. For data analysis, the ANOVA (Analysis Of Variance) technique extracts statistically significant conclusions to help define an optimal process window. Specifically, this work applies DOE and ANOVA methods to understand how thermal treatments of the ITO, PEDOT, and OC1C10-PPV layers influence device brightness and power efficiency.
EXPERIMENTAL DESIGN Table I summarizes the process flow used to make two-layer polymer LEDs and test the influence of thermal treatments on device performance. Preparation of the Ca/OC1C10PPV/PEDOT/ITO devices began with ITO electrodes on 30 mm x 30 mm glass substrates patterned by Colorado Concept Coatings. After substrate cleaning as previously reported [1], the layer of as-received Bayer Baytron-P PEDOT is spin-coated and annealed in air. C4.5.1
Table I. Summary of the process treatments. Steps 1 2 3 4 5 6 7 8 9
Material ITO ITO ITO PEDOT P
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