Evidence map›Paper›PMID 37681677›Full record

ArticleNano letters2023

Atmospheric-Pressure Mass Spectrometry by Single-Mode Nanoelectromechanical Systems.

Batuhan E Kaynak, Mohammed Alkhaled, Enise Kartal, Cenk Yanik, M Selim Hanay

Open access · hybridAbstract read
In one paragraph

Article in Nano letters, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.0field-weighted citation impact, top 13% of its field
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

4 citing papers in PubMed, 10 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Batuhan E KaynakDepartment of Mechanical Engineering, Bilkent University, 06800 Ankara, Turkey.ORCID 0000-0002-7306-4561
Mohammed AlkhaledDepartment of Mechanical Engineering, Bilkent University, 06800 Ankara, Turkey.ORCID 0000-0002-1744-3452
Enise KartalDepartment of Mechanical Engineering, Bilkent University, 06800 Ankara, Turkey.ORCID 0000-0002-9892-6076
Cenk YanikSUNUM, Sabancı University Nanotechnology Research and Application Center, 34956 Istanbul, Turkey.ORCID 0000-0001-5294-6744
M Selim HanayDepartment of Mechanical Engineering, Bilkent University, 06800 Ankara, Turkey.ORCID 0000-0002-1928-044X
Bilkent University · TRSabancı Üniversitesi · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Weighing particles above the megadalton mass range has been a persistent challenge in commercial mass spectrometry. Recently, nanoelectromechanical systems-based mass spectrometry (NEMS-MS) has shown remarkable performance in this mass range, especially with the advance of performing mass spectrometry under entirely atmospheric conditions. This advance reduces the overall complexity and cost while increasing the limit of detection. However, this technique required the tracking of two mechanical modes and the accurate knowledge of mode shapes that may deviate from their ideal values, especially due to air damping. Here, we used a NEMS architecture with a central platform, which enables the calculation of mass by single-mode measurements. Experiments were conducted using polystyrene and gold nanoparticles to demonstrate the successful acquisition of mass spectra using a single mode with an improved areal capture efficiency. This advance represents a step forward in NEMS-MS, bringing it closer to becoming a practical application for the mass sensing of nanoparticles.

Indexed as

atmospheric-pressure mass spectrometrynanoelectromechanical systemsnanoparticle mass measurementNEMS mass spectrometrypaddle NEMSsingle-mode sensing

Identifiers

PMID37681677
PMCPMC10540252
OpenAlexW4386531360

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.