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Prediction and synthesis of a family of atomic laminate phases with Kagomé-like and in-plane chemical ordering

Overview of attention for article published in Science Advances, July 2017
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  • Good Attention Score compared to outputs of the same age (67th percentile)

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Citations

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Title
Prediction and synthesis of a family of atomic laminate phases with Kagomé-like and in-plane chemical ordering
Published in
Science Advances, July 2017
DOI 10.1126/sciadv.1700642
Pubmed ID
Authors

Martin Dahlqvist, Jun Lu, Rahele Meshkian, Quanzheng Tao, Lars Hultman, Johanna Rosen

Abstract

The enigma of MAX phases and their hybrids prevails. We probe transition metal (M) alloying in MAX phases for metal size, electronegativity, and electron configuration, and discover ordering in these MAX hybrids, namely, (V2/3Zr1/3)2AlC and (Mo2/3Y1/3)2AlC. Predictive theory and verifying materials synthesis, including a judicious choice of alloying M from groups III to VI and periods 4 and 5, indicate a potentially large family of thermodynamically stable phases, with Kagomé-like and in-plane chemical ordering, and with incorporation of elements previously not known for MAX phases, including the common Y. We propose the structure to be monoclinic C2/c. As an extension of the work, we suggest a matching set of novel MXenes, from selective etching of the A-element. The demonstrated structural design on simultaneous two-dimensional (2D) and 3D atomic levels expands the property tuning potential of functional materials.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 146 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 146 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 39 27%
Researcher 20 14%
Student > Master 16 11%
Student > Bachelor 6 4%
Student > Doctoral Student 5 3%
Other 20 14%
Unknown 40 27%
Readers by discipline Count As %
Materials Science 47 32%
Engineering 16 11%
Physics and Astronomy 13 9%
Chemistry 11 8%
Chemical Engineering 4 3%
Other 8 5%
Unknown 47 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 21 April 2023.
All research outputs
#7,050,597
of 25,382,440 outputs
Outputs from Science Advances
#9,790
of 12,215 outputs
Outputs of similar age
#103,393
of 325,062 outputs
Outputs of similar age from Science Advances
#181
of 223 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 12,215 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 120.3. This one is in the 19th percentile – i.e., 19% 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 325,062 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.
We're also able to compare this research output to 223 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.