Evidence map›Paper›PMID 36282103›Full record

ArticleACS nano2022

Sensing Capabilities of Single Nanowires Studied with Correlative

Lilian M Vogl, Peter Schweizer, Peter Denninger, Gunther Richter, Erdmann Spiecker

Abstract read
In one paragraph

Article in ACS nano, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

5 authors.

Lilian M VoglInstitute of Micro- and Nanostructure Research (IMN), Center for Nanoanalysis and Electron Microscopy (CENEM), Interdisciplinary Center for Nanostructured Films (IZNF), Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany.
Peter SchweizerInstitute of Micro- and Nanostructure Research (IMN), Center for Nanoanalysis and Electron Microscopy (CENEM), Interdisciplinary Center for Nanostructured Films (IZNF), Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany.
Peter DenningerInstitute of Micro- and Nanostructure Research (IMN), Center for Nanoanalysis and Electron Microscopy (CENEM), Interdisciplinary Center for Nanostructured Films (IZNF), Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany.
Gunther RichterMax Planck Institute for Intelligent Systems, 70569 Stuttgart, Germany.
Erdmann SpieckerInstitute of Micro- and Nanostructure Research (IMN), Center for Nanoanalysis and Electron Microscopy (CENEM), Interdisciplinary Center for Nanostructured Films (IZNF), Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany.ORCID 0000-0002-2723-5227

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Modern devices based on modular designs require versatile and universal sensor components which provide an efficient, sensitive, and compact measurement unit. To improve the space capacity of devices, miniaturized building elements are needed, which implies a turning away from conventional microcantilevers toward nanoscale cantilevers. Nanowires can be seen as high-quality resonators and offer the opportunity to create sensing devices on small scales. To use such a one-dimensional nanostructure as a resonant cantilever, a precise characterization based on the fundamental properties is needed. We present a correlative electron and light microscopy approach to characterize the pressure and environment sensing capabilities of single nanowires by analyzing their resonance behavior

Indexed as

correlative in situ microscopynanowirequality factorresonancesensing

Identifiers

PMID36282103
PMCPMC9706674

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.