Achieving Efficient Multichannel Conductance in Through‐Space Conjugated Single‐Molecule Parallel Circuits

Shen, Pingchuan; Huang, Miao-Ling; Qian, Jingyu; Li, Jinshi; Ding, Siyang; Zhou, Xiao‐Shun; Xu, Bin; Zhao, Zujin; Tang, Ben Zhong

doi:10.1002/ange.202000061

Cited by 7 publications

(6 citation statements)

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“…In structure–property investigations of single molecule conductance, it is common to determine a single “most probable” conductance for each molecule by fitting the molecular peak in the 1D histogram. − ,,, The peak value is then identified as the molecular conductance, and it is often compared across different molecules or with first-principles calculations. However, because the molecular signal is necessarily convolved with a “background” signal due to traces in which no molecule was bound or in which the molecule detaches and reattaches multiples times (e.g., Figure a), molecular peaks in 1D histograms tend to have complex, asymmetric shapes (e.g., Figure d).…”

Section: Resultsmentioning

confidence: 99%

“…While such histograms usefully summarize the ensemble of single molecule conductance behaviors, they obscure likely meaningful differences within and among different molecular constructs that could be harnessed to advance a host of intriguing molecular electronics research directions. At present, 1D histograms are often used to determine a single “peak” or “most probable” conductance for a given molecule, − and 2D histograms have been used to separate molecular features that may correspond to distinct physical phenomena, such as different binding modes. ,− However, the broad features found in these histograms make it difficult to confidently separate features without introducing bias, and the complex “background” signature, composed of tunneling decay and broken molecular plateaus, makes it hard to robustly fit molecular peaks. These inter-related challenges have motivated several research groups to develop automated clustering and data-sorting methods for analyzing breaking traces − and related data. ,− Broadly speaking, the goal of these approaches is to partition a large data set of highly varied traces into separate groupings in order to improve the robustness of peak conductance measurements and/or to identify distinct junction behaviors.…”

Section: Introductionmentioning

confidence: 99%

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Unsupervised Segmentation-Based Machine Learning as an Advanced Analysis Tool for Single Molecule Break Junction Data

et al. 2020

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Improved understanding of charge-transport in single molecules is essential for harnessing the potential of molecules, e.g., as circuit components at the ultimate size limit. However, interpretation and analysis of the large, stochastic data sets produced by most quantum transport experiments remain an ongoing challenge to discovering much-needed structure–property relationships. Here, we introduce segment clustering, a novel unsupervised hypothesis generation tool for investigating single molecule break junction distance–conductance traces. In contrast to previous machine learning approaches for single molecule data, segment clustering identifies groupings of similar pieces of traces instead of entire traces. This offers a new and advantageous perspective into data set structure because it facilitates the identification of meaningful local trace behaviors that may otherwise be obscured by random fluctuations over longer distance scales. We illustrate the power and broad applicability of this approach with two case studies that address common challenges encountered in single molecule studies: First, segment clustering is used to extract primary molecular features from a varying background to increase the precision and robustness of conductance measurements, enabling small changes in conductance in response to molecular design to be identified with confidence. Second, segment clustering is applied to a known data mixture to qualitatively separate distinct molecular features in a rigorous and unbiased manner. These examples demonstrate two powerful ways in which segment clustering can aid in the development of structure–property relationships in molecular quantum transport, an outstanding challenge in the field of molecular electronics.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Unsupervised Segmentation-Based Machine Learning as an Advanced Analysis Tool for Single Molecule Break Junction Data

et al. 2020

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“…As the noise power does not completely scale as G 2.0 , it is possible that these folded molecules hold through-bond channel in addition to through-space channel for charge transport [62][63][64] . In order to validate this hypothesis and shed light on the transmission mechanism of these molecules, density functional theory (DFT) simulation is carried out using the ATK software package with nonequilibrium Green's functions (NEGF).…”

Section: General Characterizationmentioning

confidence: 99%

Mechanical single-molecule potentiometers with large switching factors from ortho-pentaphenylene foldamers

Shen

Zhen

et al. 2021

Nat Commun

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Molecular potentiometers that can indicate displacement-conductance relationship, and predict and control molecular conductance are of significant importance but rarely developed. Herein, single-molecule potentiometers are designed based on ortho-pentaphenylene. The ortho-pentaphenylene derivatives with anchoring groups adopt multiple folded conformers and undergo conformational interconversion in solutions. Solvent-sensitive multiple conductance originating from different conformers is recorded by scanning tunneling microscopy break junction technique. These pseudo-elastic folded molecules can be stretched and compressed by mechanical force along with a variable conductance by up to two orders of magnitude, providing an impressively higher switching factor (114) than the reported values (ca. 1~25). The multichannel conductance governed by through-space and through-bond conducting pathways is rationalized as the charge transport mechanism for the folded ortho-pentaphenylene derivatives. These findings shed light on exploring robust single-molecule potentiometers based on helical structures, and are conducive to fundamental understanding of charge transport in higher-order helical molecules.

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“…In previous work, we established a new class of hybrid conjugation system of tetraphenylethene (TPE)-cored foldamers, which employ TPE as a TBC core and fold a pair of aryl wings (fragments or chains) into a π-stacking TSC component. [46][47][48][49] Utilizing such a fantastic geometry, efficient luminescent materials, bipolar carrier transporting materials, 50 and multichannel single-molecular wires 51,52 have been successfully created. In addition, preliminary investigations on the structure-property correlation have been carried out.…”

Section: Introductionmentioning

confidence: 99%

Deciphering Benzene–Heterocycle Stacking Interaction Impact on the Electronic Structures and Photophysical Properties of Tetraphenylethene-Cored Foldamers

Zhuang

Shen

et al. 2022

CCS Chem

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Conjugation, as an essential chemical term used to describe electron delocalization, can be roughly grouped into two categories, through-bond conjugation (TBC) and through-space conjugation (TSC). A hybrid conjugation system integrating both TBC and TSC is rarely studied and utilized, for lack of a well-established model and difficulty of structure modification and property tuning, despite its theoretical significance and potential applications. Herein, various foldamers with a tetraphenylethene (TPE) core are employed as hybrid conjugation models to investigate structure-property correlation by introducing heterocycles of furan/thiophene into the π-stacking TSC component. For comparison, two kinds of TPE-cored foldamers with different stacking models, a benzene-heterocycle stacking model and a benzene-benzene stacking model, are designed. Combining experimental measurements and theoretical calculations, the impact of benzene-heterocycle interaction on the hybrid conjugation natures and photophysical properties has been studied systematically. The results reveal that the benzene-heterocycle stacking model can fabricate a hybrid conjugation nature with an improved TSC component to make a more dominant contribution to the electronic transition natures than the benzene-benzene stacking model, leading to the distinguishing photophysical behavior. This work provides valuable guidance for the design of new functional materials with hybrid conjugation systems.

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Achieving Efficient Multichannel Conductance in Through‐Space Conjugated Single‐Molecule Parallel Circuits

Cited by 7 publications

References 53 publications

Unsupervised Segmentation-Based Machine Learning as an Advanced Analysis Tool for Single Molecule Break Junction Data

Unsupervised Segmentation-Based Machine Learning as an Advanced Analysis Tool for Single Molecule Break Junction Data

Mechanical single-molecule potentiometers with large switching factors from ortho-pentaphenylene foldamers

Deciphering Benzene–Heterocycle Stacking Interaction Impact on the Electronic Structures and Photophysical Properties of Tetraphenylethene-Cored Foldamers

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