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Programmatic conversion of crystal structures into 3D printable files using Jmol

Overview of attention for article published in Journal of Cheminformatics, November 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#3 of 370)
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

news
1 news outlet
blogs
2 blogs
twitter
60 tweeters
wikipedia
1 Wikipedia page
googleplus
2 Google+ users
reddit
1 Redditor
video
1 video uploader

Readers on

mendeley
13 Mendeley
citeulike
1 CiteULike
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Title
Programmatic conversion of crystal structures into 3D printable files using Jmol
Published in
Journal of Cheminformatics, November 2016
DOI 10.1186/s13321-016-0181-z
Pubmed ID
Authors

Vincent F. Scalfani, Antony J. Williams, Valery Tkachenko, Karen Karapetyan, Alexey Pshenichnov, Robert M. Hanson, Jahred M. Liddie, Jason E. Bara, Scalfani, Vincent F, Williams, Antony J, Tkachenko, Valery, Karapetyan, Karen, Pshenichnov, Alexey, Hanson, Robert M, Liddie, Jahred M, Bara, Jason E

Abstract

Three-dimensional (3D) printed crystal structures are useful for chemistry teaching and research. Current manual methods of converting crystal structures into 3D printable files are time-consuming and tedious. To overcome this limitation, we developed a programmatic method that allows for facile conversion of thousands of crystal structures directly into 3D printable files. A collection of over 30,000 crystal structures in crystallographic information file (CIF) format from the Crystallography Open Database (COD) were programmatically converted into 3D printable files (VRML format) using Jmol scripting. The resulting data file conversion of the 30,000 CIFs proceeded as expected, however some inconsistencies and unintended results were observed with co-crystallized structures, racemic mixtures, and structures with large counterions that led to 3D printable files not containing the desired chemical structure. Potential solutions to these challenges are considered and discussed. Further, a searchable Jmol 3D Print website was created that allows users to both discover the 3D file dataset created in this work and create custom 3D printable files for any structure in the COD. Over 30,000 crystal structures were programmatically converted into 3D printable files, allowing users to have quick access to a sizable collection of 3D printable crystal structures. Further, any crystal structure (>350,000) in the COD can now be conveniently converted into 3D printable file formats using the Jmol 3D Print website created in this work. The 3D Print website also allows users to convert their own CIFs into 3D printable files. 3D file data, scripts, and the Jmol 3D Print website are provided openly to the community in an effort to promote discovery and use of 3D printable crystal structures. The 3D file dataset and Jmol 3D Print website will find wide use with researchers and educators seeking to 3D print chemical structures, while the scripts will be useful for programmatically converting large database collections of crystal structures into 3D printable files.

Twitter Demographics

The data shown below were collected from the profiles of 60 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Denmark 1 8%
United States 1 8%
Unknown 11 85%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 31%
Student > Bachelor 3 23%
Researcher 2 15%
Student > Master 1 8%
Professor 1 8%
Other 2 15%
Readers by discipline Count As %
Chemistry 8 62%
Pharmacology, Toxicology and Pharmaceutical Science 1 8%
Biochemistry, Genetics and Molecular Biology 1 8%
Computer Science 1 8%
Agricultural and Biological Sciences 1 8%
Other 1 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 68. 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 24 May 2017.
All research outputs
#118,021
of 7,826,457 outputs
Outputs from Journal of Cheminformatics
#3
of 370 outputs
Outputs of similar age
#8,505
of 250,197 outputs
Outputs of similar age from Journal of Cheminformatics
#1
of 22 outputs
Altmetric has tracked 7,826,457 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 370 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has done particularly well, scoring higher than 99% 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 250,197 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.