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Conceptual DFT Descriptors of Amino Acids with Potential Corrosion Inhibition Properties Calculated with the Latest Minnesota Density Functionals

Overview of attention for article published in Frontiers in Chemistry, March 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

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Title
Conceptual DFT Descriptors of Amino Acids with Potential Corrosion Inhibition Properties Calculated with the Latest Minnesota Density Functionals
Published in
Frontiers in Chemistry, March 2017
DOI 10.3389/fchem.2017.00016
Pubmed ID
Authors

Juan Frau, Daniel Glossman-Mitnik

Abstract

Amino acids and peptides have the potential to perform as corrosion inhibitors. The chemical reactivity descriptors that arise from Conceptual DFT for the twenty natural amino acids have been calculated by using the latest Minnesota family of density functionals. In order to verify the validity of the calculation of the descriptors directly from the HOMO and LUMO, a comparison has been performed with those obtained through ΔSCF results. Moreover, the active sites for nucleophilic and electrophilic attacks have been identified through Fukui function indices, the dual descriptor Δf(r) and the electrophilic and nucleophilic Parr functions. The results could be of interest as a starting point for the study of large peptides where the calculation of the radical cation and anion of each system may be computationally harder and costly.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 49 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 27%
Researcher 8 16%
Student > Doctoral Student 4 8%
Student > Master 4 8%
Student > Postgraduate 3 6%
Other 4 8%
Unknown 13 27%
Readers by discipline Count As %
Chemistry 22 45%
Physics and Astronomy 3 6%
Materials Science 3 6%
Medicine and Dentistry 1 2%
Chemical Engineering 1 2%
Other 2 4%
Unknown 17 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 15 October 2020.
All research outputs
#4,106,392
of 22,959,818 outputs
Outputs from Frontiers in Chemistry
#259
of 5,985 outputs
Outputs of similar age
#73,793
of 308,425 outputs
Outputs of similar age from Frontiers in Chemistry
#6
of 25 outputs
Altmetric has tracked 22,959,818 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,985 research outputs from this source. They receive a mean Attention Score of 2.0. This one has done particularly well, scoring higher than 95% of its peers.
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 308,425 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.