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New Insights into Single-Molecule Junctions Using a Robust, Unsupervised Approach to Data Collection and Analysis

Overview of attention for article published in Journal of the American Chemical Society, July 2015
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Title
New Insights into Single-Molecule Junctions Using a Robust, Unsupervised Approach to Data Collection and Analysis
Published in
Journal of the American Chemical Society, July 2015
DOI 10.1021/jacs.5b05693
Pubmed ID
Authors

Michael S. Inkpen, Mario Lemmer, Nathan Fitzpatrick, David C. Milan, Richard J. Nichols, Nicholas J. Long, Tim Albrecht

Abstract

We have applied a new, robust and unsupervised approach to data collection, sorting and analysis that provides fresh insights into the nature of single-molecule junctions. Automation of tunneling current-distance (I(s)) spectroscopy facilitates the collection of very large datasets (up to 100,000 traces for a single experiment), enabling comprehensive statistical interrogations with respect to underlying tunneling characteristics, noise and junction formation probability (JFP). We frequently observe unusual low-to-high through-molecule conductance features with increasing electrode separation, in addition to numerous other 'plateau' shapes which may be related to changes in interfacial or molecular bridge structure. Furthermore, for the first time we use the JFP to characterize the homogeneity of functionalized surfaces at the nanoscale.

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
United States 1 1%
Unknown 73 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 33%
Researcher 15 20%
Student > Master 9 12%
Student > Bachelor 4 5%
Professor 4 5%
Other 12 16%
Unknown 6 8%
Readers by discipline Count As %
Chemistry 37 49%
Physics and Astronomy 14 19%
Materials Science 9 12%
Agricultural and Biological Sciences 2 3%
Engineering 2 3%
Other 2 3%
Unknown 9 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 August 2015.
All research outputs
#20,284,384
of 22,818,766 outputs
Outputs from Journal of the American Chemical Society
#60,154
of 61,996 outputs
Outputs of similar age
#219,839
of 263,145 outputs
Outputs of similar age from Journal of the American Chemical Society
#429
of 479 outputs
Altmetric has tracked 22,818,766 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 61,996 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 263,145 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 479 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.