arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2007.03796cond-mat.mtrl-sci
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单层MoS2的近单位分子掺杂效率

Near Unity Molecular Doping Efficiency in Monolayer MoS2

Milad Yarali, Yiren Zhong, Serrae N. Reed, Juefan Wang, Kanchan A. Ulman, David J. Charboneau, Julia B. Curley, David J. Hynek, Joshua V. Pondick, Sajad Yazdani… 展开作者

Milad Yarali, Yiren Zhong, Serrae N. Reed, Juefan Wang, Kanchan A. Ulman, David J. Charboneau, Julia B. Curley, David J. Hynek, Joshua V. Pondick, Sajad Yazdani, Nilay Hazari, Su Ying Quek, Hailiang Wang, Judy J. Cha

摘要:

利用有机电子给体(OED)进行表面功能化是二维(2D)材料的有效掺杂策略,其可以实现超过常规电场门控可能的掺杂水平。虽然表面官能化的有效性已在许多2D系统中得到证实,但OED的掺杂效率在很大程度上尚未测量,这与其精确合成和定制的氧化还原电位形成鲜明对比。在这里,使用单层MoS 2作为模型系统和基于4,4-联吡啶(DMAP-OED)的有机还原剂作为强有机掺杂剂,我们确定DMAP-OED对MoS 2的掺杂效率在0.63至1.26电子/分子的范围内。我们还实现了最高的掺杂水平,迄今为止在单层二硫化钼表面功能化,并证明DMAP-OED是一个更强的掺杂剂比苄基紫精,这是以前最好的OED掺杂剂。掺杂效率的测量范围与从第一性原理计算预测的值很好地一致。本文的工作为合理设计高掺杂二维材料的有机电致发光器件提供了依据。

英文摘要:

Surface functionalization with organic electron donors (OEDs) is an effective doping strategy for two-dimensional (2D) materials, which can achieve doping levels beyond those possible with conventional electric field gating. While the effectiveness of surface functionalization has been demonstrated in many 2D systems, the doping efficiencies of OEDs have largely been unmeasured, which is in stark contrast to their precision syntheses and tailored redox potentials. Here, using monolayer MoS2 as a model system and an organic reductant based on 4,4-bipyridine (DMAP-OED) as a strong organic dopant, we establish that the doping efficiency of DMAP-OED to MoS2 is in the range of 0.63 to 1.26 electrons per molecule. We also achieve the highest doping level to date in monolayer MoS2 by surface functionalization and demonstrate that DMAP-OED is a stronger dopant than benzyl viologen, which was the previous best OED dopant. The measured range of the doping efficiency is in good agreement with the values predicted from first-principles calculations. Our work provides a basis for the rational design of OEDs for high-level doping of 2D materials.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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