2019 Fiscal Year Final Research Report
Creation of an organic thin film deposition system by integration of information science
| Project/Area Number |
18K14126
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 29020:Thin film/surface and interfacial physical properties-related
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| Research Institution | Kyoto University |
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Principal Investigator |
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| Project Period (FY) |
2018-04-01 – 2020-03-31
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| Keywords | 有機薄膜 / 低速電子線回折 / 走査トンネル顕微鏡 / 低速電子線回折シミュレーション / ベイズ最適化 / 教師なし機械学習 / 薄膜構造の解明 |
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| Outline of Final Research Achievements |
Organic thin films on metallic substrates are widely used as charge transport layers in OLEDs (organic light emitting diodes) and other organic electronics.
In this project, we aimed to create a machine learning algorithm which can find the optimal deposition conditions for creating highly crystalline, small-molecule organic thin films. We succeeded to collect training data for this algorithm, and confirmed that it spans a wide range of thin film states (sub-monolayer to multilayer) using scanning tunneling microscopy. However, more training data is needed to run the optimization algorithm properly. In addition, we created a new computational method which can, in principle, determine the atomic structure of an organic thin film from low energy electron diffraction (LEED) data.
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| Free Research Field |
計算材料科学
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| Academic Significance and Societal Importance of the Research Achievements |
・By minimizing trial-and-error, the algorithm will reduce the time required to deposit high-quality small molecule thin films, and might accelerate the development of organic electronics based upon small-molecule films.
・Organic thin film structure might be elucidated with our computational method.
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