Evidence map›Paper›PMID 36598507›Full record

ArticleIUCrJ2023

Modelling fine-sliced three dimensional electron diffraction data with dynamical Bloch-wave simulations.

Anton Cleverley, Richard Beanland

Abstract read
In one paragraph

Article in IUCrJ, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Electrons and X-rays for diffraction and imaging.Acta crystallographica. Section D, Structural biology · 2026
    Review
  2. Article
  3. Journal of applied crystallography · 2026
    Article
  4. Article
  5. Parameterized absorptive electron scattering factors.Acta crystallographica. Section A, Foundations and advances · 2024
    Article
  6. Modelling dynamical 3D electron diffraction intensities. II. The role of inelastic scattering.Acta crystallographica. Section A, Foundations and advances · 2024
    Article
  7. Modelling dynamical 3D electron diffraction intensities. I. A scattering cluster algorithm.Acta crystallographica. Section A, Foundations and advances · 2024
    Article
  8. Review
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

2 authors.

Anton CleverleyDepartment of Chemistry, University of Warwick, Coventry CV4 7AL, United Kingdom.ORCID 0000-0001-6076-8378
Richard BeanlandDepartment of Physics, University of Warwick, Coventry CV4 7AL, United Kingdom.ORCID 0000-0003-1749-4134

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent interest in structure solution and refinement using electron diffraction (ED) has been fuelled by its inherent advantages when applied to crystals of sub-micrometre size, as well as its better sensitivity to light elements. Currently, data are often processed with software written for X-ray diffraction, using the kinematic theory of diffraction to generate model intensities - despite the inherent differences in diffraction processes in ED. Here, dynamical Bloch-wave simulations are used to model continuous-rotation electron diffraction data, collected with a fine angular resolution (crystal orientations of ∼0.1°). This fine-sliced data allows a re-examination of the corrections applied to ED data. A new method is proposed for optimizing crystal orientation, and the angular range of the incident beam and the varying slew rate are taken into account. Observed integrated intensities are extracted and accurate comparisons are performed with simulations using rocking curves for a (110) lamella of silicon 185 nm thick. R

Indexed as

3D-ED3D electron diffractioncomputational modellingdynamical refinementdynamical simulations

Identifiers

PMID36598507
PMCPMC9812222

What OpenQuestion holds

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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.