Evidence map›Paper›PMID 37723143›Full record

ArticleNature communications2023

Probing three-dimensional mesoscopic interfacial structures in a single view using multibeam X-ray coherent surface scattering and holography imaging.

Miaoqi Chu, Zhang Jiang, Michael Wojcik, Tao Sun, Michael Sprung, Jin Wang

Abstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Miaoqi ChuX-ray Science Division, Argonne National Laboratory, Lemont, IL, 60439, USA. mqichu@anl.gov.ORCID http://orcid.org/0000-0002-6465-1529
Zhang JiangX-ray Science Division, Argonne National Laboratory, Lemont, IL, 60439, USA.
Michael WojcikX-ray Science Division, Argonne National Laboratory, Lemont, IL, 60439, USA.
Tao SunX-ray Science Division, Argonne National Laboratory, Lemont, IL, 60439, USA.ORCID http://orcid.org/0000-0002-4881-9774
Michael SprungDeutsches Elektronen-Synchrotron (DESY), Notkestr. 85, 22607, Hamburg, Germany.ORCID http://orcid.org/0000-0003-2396-3304
Jin WangX-ray Science Division, Argonne National Laboratory, Lemont, IL, 60439, USA. wangj@anl.gov.ORCID http://orcid.org/0000-0001-9112-6538

Funding

DOE | LDRD | Argonne National Laboratory (ANL) 2017-073
6 · The paper itself

Abstract

Visualizing surface-supported and buried planar mesoscale structures, such as nanoelectronics, ultrathin-film quantum dots, photovoltaics, and heterogeneous catalysts, often requires high-resolution X-ray imaging and scattering. Here, we discovered that multibeam scattering in grazing-incident reflection geometry is sensitive to three-dimensional (3D) structures in a single view, which is difficult in conventional scattering or imaging approaches. We developed a 3D finite-element-based multibeam-scattering analysis to decode the heterogeneous electric-field distribution and to faithfully reproduce the complex scattering and surface features. This approach further leads to the demonstration of hard-X-ray Lloyd's mirror interference of scattering waves, resembling dark-field, high-contrast surface holography under the grazing-angle scattering conditions. A first-principles calculation of the single-view holographic images resolves the surface patterns' 3D morphology with nanometer resolutions, which is critical for ultrafine nanocircuit metrology. The holographic method and simulations pave the way for single-shot structural characterization for visualizing irreversible and morphology-transforming physical and chemical processes in situ or operando.

Identifiers

PMID37723143
PMCPMC10507109

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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.