Revealing the Nature of Molecule–Electrode Contact in Tunneling Junctions Using Raw Data Heat Maps

Mechanistic
understanding of charge transport through molecular
tunnel junctions requires reproducible and statistically relevant
data sets. This challenge has been overcome by development of large
area junctions, especially those based on liquid-metal physi-sorbed
top-electrodes, such as eutectic gallium–indium. A challenge
with these junctions, however, is an inability to diagnose the quality
of contact between the top-electrode and the SAMs. Since tunneling
currents are dependent on the distance between the two electrodes,
we demonstrate that by analyzing all raw unfitted data derived from
a measurement using heat-maps, one can deduce the quality of contact
and other minor bias-dependent fluctuations in the charge transport
behavior. We demonstrate that the use of 3D plots would be challenging
to interpret, but adoption of heat maps clearly captures details on
junction quality irrespective of the total size of the data set or
molecules used. We propose representation of raw data, rather than
reliance on statistics, as proof of quality junctions.

对分子隧道结（molecular tunnel junctions）中电荷输运（charge transport）过程的机理认知，需依托可复现且具备统计相关性的数据集。此前，基于液态金属物理吸附顶电极（如共晶镓铟合金）的大面积结技术解决了该难题。然而这类结器件尚存一项挑战：无法诊断顶电极与自组装单分子层（Self-Assembled Monolayers, SAMs）之间的接触质量。由于隧穿电流（tunneling currents）与两电极间距紧密相关，本研究证实，通过热图（heat map）分析测量所得的全部未拟合原始数据，可推断出接触质量以及电荷输运行为中其他细微的偏置依赖涨落。研究表明，采用三维绘图（3D plots）难以实现有效解读，但热图法能够清晰捕捉结器件的质量细节，且不受数据集总规模或所用分子种类的限制。我们提出，应采用原始数据表征而非依赖统计方法，作为结器件质量合格的证明依据。