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Hybrid Nanomaterials Based on Graphene and Gold Nanoclusters for Efficient Electrocatalytic Reduction of Oxygen

Overview of attention for article published in Discover Nano, July 2016
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  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

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Citations

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12 Dimensions

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11 Mendeley
Title
Hybrid Nanomaterials Based on Graphene and Gold Nanoclusters for Efficient Electrocatalytic Reduction of Oxygen
Published in
Discover Nano, July 2016
DOI 10.1186/s11671-016-1552-0
Pubmed ID
Authors

Changhong Wang, Na Li, Qiannan Wang, Zhenghua Tang

Abstract

Nanocomposites based on gold nanoclusters (AuNCs) with polyvinyl pyrrolidone as ligand and reduced graphene oxide (RGO) have been prepared and employed as efficient electrocatalysts for oxygen reduction reaction (ORR). AuNCs were synthesized through a wet chemical approach and then loaded onto the RGO. The as-prepared hybrid materials were pyrolyzed to remove the organic ligands. The composites were characterized by transmission electron microscopy (TEM), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS) as well as other techniques. Electrochemical tests demonstrated that the hybrid materials exhibited effective ORR activity in alkaline media. Among a series of samples tested, the pyrolyzed sample with 50 % AuNCs mass loading exhibited the best activity, superior than AuNCs alone, RGO alone, and the others, in terms of onset potential and kinetic current density as well as durability. The method here may provide a generic approach to prepare supported noble metal nanoclusters with excellent reactivity and robust stability for ORR.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users 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 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 36%
Professor > Associate Professor 1 9%
Researcher 1 9%
Student > Master 1 9%
Unknown 4 36%
Readers by discipline Count As %
Chemistry 3 27%
Energy 1 9%
Physics and Astronomy 1 9%
Materials Science 1 9%
Engineering 1 9%
Other 0 0%
Unknown 4 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 20 July 2016.
All research outputs
#15,090,466
of 25,371,288 outputs
Outputs from Discover Nano
#471
of 1,146 outputs
Outputs of similar age
#209,997
of 377,256 outputs
Outputs of similar age from Discover Nano
#12
of 31 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,146 research outputs from this source. They receive a mean Attention Score of 3.5. This one has gotten more attention than average, scoring higher than 58% 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 377,256 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.