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Upper-Year Materials Chemistry Computational Modeling Module for Organic Display Technologies
In undergraduate chemistry curricula that include computational modeling, students may gain first-hand experience in both introductory and advanced applications of this technique. However, although students can be exposed to the predictive power of computational work, its capabilities are often limi...
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Published in: | Journal of chemical education 2021-03, Vol.98 (3), p.805-811 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | In undergraduate chemistry curricula that include computational modeling, students may gain first-hand experience in both introductory and advanced applications of this technique. However, although students can be exposed to the predictive power of computational work, its capabilities are often limited to determining the intrinsic properties of the molecules being modeled, rather than potential applications of functional materials intended for devices. To address this disconnect, we have designed and implemented a computational module for upper-year undergraduate and graduate students within an organic materials chemistry course. The module is conducted over 7 weeks and is based on an increasingly important phenomenon in organic photochemistry known as thermally activated delayed fluorescence (TADF). TADF emitters are ideal for display technologies (organic light emitting diodes). Students connect molecular structure with predicted properties and function by performing computational modeling on known TADF emitters, before correlating their results with the experimental performance of the emitters. They also address potential limitations of density functional theory (DFT) that they have not encountered previously, attempt to rationalize outlying data points based on content presented in class, and summarize their calculations and conclusions in a communications-style manuscript. Overall, students learn how DFT can be used to inform molecular materials chemistry and engineering as well as identify some limitations of in silico design. |
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ISSN: | 0021-9584 1938-1328 |
DOI: | 10.1021/acs.jchemed.0c01325 |