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Turbocharged molecular discovery of OLED emitters: From high-throughput quantum simulation to highly efficient TADF devices

机译:OLED发射器的涡轮增压分子发现:从高通量量子模拟到高效TADF装置

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摘要

Discovering new OLED emitters requires many experiments to synthesize candidates and test performance in devices. Large scale computer simulation can greatly speed this search process but the problem remains challenging enough that brute force application of massive computing power is not enough to successfully identify novel structures. We report a successful High Throughput Virtual Screening study that leveraged a range of methods to optimize the search process. The generation of candidate structures was constrained to contain combinatorial explosion. Simulations were tuned to the specific problem and calibrated with experimental results. Experimentalists and theorists actively collaborated such that experimental feedback was regularly utilized to update and shape the computational search. Supervised machine learning methods prioritized candidate structures prior to quantum chemistry simulation to prevent wasting compute on likely poor performers. With this combination of techniques, each multiplying the strength of the search, this effort managed to navigate an area of molecular space and identify hundreds of promising OLED candidate structures. An experimentally validated selection of this set shows emitters with external quantum efficiencies as high as 22%.
机译:发现新的OLED发射器需要进行许多实验,以合成候选物并测试设备的性能。大规模计算机仿真可以大大加快搜索过程的速度,但问题仍然具有挑战性,以至于大规模计算能力的强力应用不足以成功识别新颖的结构。我们报告了一项成功的高通量虚拟筛选研究,该研究利用了一系列方法来优化搜索过程。候选结构的生成被限制为包含组合爆炸。仿真针对特定问题进行了调整,并根据实验结果进行了校准。实验家和理论家积极合作,以便定期利用实验反馈来更新和调整计算搜索的范围。在量子化学模拟之前,受监督的机器学习方法优先考虑候选结构,以防止浪费可能的性能不佳的计算。借助这种技术组合,每种技术都使搜索的强度倍增,这项工作设法在分子空间的一个区域中导航并确定了数百种有前途的OLED候选结构。经过实验验证的该集合的选择显示出外部量子效率高达22%的发射器。

著录项

  • 来源
    《Organic light emitting materials and devices XX》|2016年|99410A.1-99410A.8|共8页
  • 会议地点 San Diego CA(US)
  • 作者单位

    Dept. of Chemistry and Chemical Biology, Harvard University, 12 Oxford St, Cambridge MA 02138;

    Dept. of Chemistry and Chemical Biology, Harvard University, 12 Oxford St, Cambridge MA 02138;

    Dept. of Chemistry and Chemical Biology, Harvard University, 12 Oxford St, Cambridge MA 02138;

    Department of Electrical Engineering and Computer Science, 77 Massachusetts Avenue,Massachusetts Institute of Technology, Cambridge, MA, 02139, USA;

    Department of Electrical Engineering and Computer Science, 77 Massachusetts Avenue,Massachusetts Institute of Technology, Cambridge, MA, 02139, USA;

    Department of Electrical Engineering and Computer Science, 77 Massachusetts Avenue,Massachusetts Institute of Technology, Cambridge, MA, 02139, USA;

    Department of Electrical Engineering and Computer Science, 77 Massachusetts Avenue,Massachusetts Institute of Technology, Cambridge, MA, 02139, USA;

    Dept. of Chemistry and Chemical Biology, Harvard University, 12 Oxford St, Cambridge MA 02138;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    TADF; DFT; high-throughput; simulation; machine-learning; emitter;

    机译:TADF; DFT;高通量模拟;机器学习发射器;

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