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Accelerated discovery of stable lead-free hybrid organic-inorganic perovskites via machine learning

Overview of attention for article published in Nature Communications, August 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

Mentioned by

news
1 news outlet
blogs
2 blogs
twitter
1 X user

Citations

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470 Dimensions

Readers on

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456 Mendeley
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Title
Accelerated discovery of stable lead-free hybrid organic-inorganic perovskites via machine learning
Published in
Nature Communications, August 2018
DOI 10.1038/s41467-018-05761-w
Pubmed ID
Authors

Shuaihua Lu, Qionghua Zhou, Yixin Ouyang, Yilv Guo, Qiang Li, Jinlan Wang

Abstract

Rapidly discovering functional materials remains an open challenge because the traditional trial-and-error methods are usually inefficient especially when thousands of candidates are treated. Here, we develop a target-driven method to predict undiscovered hybrid organic-inorganic perovskites (HOIPs) for photovoltaics. This strategy, combining machine learning techniques and density functional theory calculations, aims to quickly screen the HOIPs based on bandgap and solve the problems of toxicity and poor environmental stability in HOIPs. Successfully, six orthorhombic lead-free HOIPs with proper bandgap for solar cells and room temperature thermal stability are screened out from 5158 unexplored HOIPs and two of them stand out with direct bandgaps in the visible region and excellent environmental stability. Essentially, a close structure-property relationship mapping the HOIPs bandgap is established. Our method can achieve high accuracy in a flash and be applicable to a broad class of functional material design.

X Demographics

X Demographics

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 456 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 456 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 76 17%
Researcher 59 13%
Student > Master 49 11%
Student > Bachelor 29 6%
Professor > Associate Professor 16 4%
Other 62 14%
Unknown 165 36%
Readers by discipline Count As %
Materials Science 80 18%
Chemistry 53 12%
Engineering 40 9%
Physics and Astronomy 32 7%
Computer Science 12 3%
Other 53 12%
Unknown 186 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 20. 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 28 February 2023.
All research outputs
#1,679,907
of 23,873,907 outputs
Outputs from Nature Communications
#22,277
of 49,912 outputs
Outputs of similar age
#36,174
of 335,906 outputs
Outputs of similar age from Nature Communications
#649
of 1,419 outputs
Altmetric has tracked 23,873,907 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 49,912 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 56.2. This one has gotten more attention than average, scoring higher than 55% 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 335,906 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 89% of its contemporaries.
We're also able to compare this research output to 1,419 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 54% of its contemporaries.