Evidence map›Paper›PMID 34123235›Full record

ArticleChemical science2020

Understanding the geometric diversity of inorganic and hybrid frameworks through structural coarse-graining.

Thomas C Nicholas, Andrew L Goodwin, Volker L Deringer

Abstract read
In one paragraph

Article in Chemical science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Coarse-grainedChemical communications (Cambridge, England) · 2023
    Article
  4. Review
  5. Visualization and Quantification of Geometric Diversity in Metal-Organic Frameworks.Chemistry of materials : a publication of the American Chemical Society · 2021
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Thomas C NicholasDepartment of Chemistry, Inorganic Chemistry Laboratory, University of Oxford Oxford OX1 3QR UK volker.deringer@chem.ox.ac.uk.ORCID https://orcid.org/0000-0003-1333-0052
Andrew L GoodwinDepartment of Chemistry, Inorganic Chemistry Laboratory, University of Oxford Oxford OX1 3QR UK volker.deringer@chem.ox.ac.uk.ORCID https://orcid.org/0000-0001-9231-3749
Volker L DeringerDepartment of Chemistry, Inorganic Chemistry Laboratory, University of Oxford Oxford OX1 3QR UK volker.deringer@chem.ox.ac.uk.ORCID https://orcid.org/0000-0001-6873-0278

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Much of our understanding of complex structures is based on simplification: for example, metal-organic frameworks are often discussed in the context of "nodes" and "linkers", allowing for a qualitative comparison with simpler inorganic structures. Here we show how such an understanding can be obtained in a systematic and quantitative framework, combining atom-density based similarity (kernel) functions and unsupervised machine learning with the long-standing idea of "coarse-graining" atomic structure. We demonstrate how the latter enables a comparison of vastly different chemical systems, and we use it to create a unified, two-dimensional structure map of experimentally known tetrahedral AB

Identifiers

PMID34123235
PMCPMC8162807

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.