Evidence map›Paper›PMID 31683973›Full record

ArticleSensors (Basel, Switzerland)2019

Cantilever-Droplet-Based Sensing of Magnetic Particle Concentrations in Liquids.

Wilson Ombati Nyang'au, Andi Setiono, Maik Bertke, Harald Bosse, Erwin Peiner

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Tailored Microcantilever Optimization for Multifrequency Force Microscopy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023
    Article
  2. Article
  3. Article
  4. A Flexible PI/Si/SiOSensors (Basel, Switzerland) · 2021
    Article
  5. Article
  6. Article
  7. Nanomaterials for Healthcare Biosensing Applications.Sensors (Basel, Switzerland) · 2019
    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

5 authors.

Wilson Ombati Nyang'auInstitute of Semiconductor Technology (IHT) and Laboratory of Emerging Nanometrology (LENA), Technische Universität Braunschweig, 38106 Braunschweig, Germany. wilombat@tu-braunschweig.de.
Andi SetionoInstitute of Semiconductor Technology (IHT) and Laboratory of Emerging Nanometrology (LENA), Technische Universität Braunschweig, 38106 Braunschweig, Germany. a.setiono@tu-braunschweig.de.
Maik BertkeInstitute of Semiconductor Technology (IHT) and Laboratory of Emerging Nanometrology (LENA), Technische Universität Braunschweig, 38106 Braunschweig, Germany. m.bertke@tu-braunschweig.de.
Harald BossePrecision Engineering Division, Physikalisch-Technische Bundesanstalt (PTB), 38116 Braunschweig, Germany. Harald.Bosse@ptb.de.
Erwin PeinerInstitute of Semiconductor Technology (IHT) and Laboratory of Emerging Nanometrology (LENA), Technische Universität Braunschweig, 38106 Braunschweig, Germany. e.peiner@tu-braunschweig.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cantilever-based sensors have attracted considerable attention in the recent past due to their enormous and endless potential and possibilities coupled with their dynamic and unprecedented sensitivity in sensing applications. In this paper, we present a technique that involves depositing and vaporizing (at ambient conditions) a particle-laden water droplet onto a defined sensing area on in-house fabricated and commercial-based silicon microcantilever sensors. This process entailed the optimization of dispensing pressure and time to generate and realize a small water droplet volume (

Indexed as

adsorptionconcentrationdropletmagnetic polystyrene particlesmassmicrocantileverresonant frequency

Identifiers

PMID31683973
PMCPMC6864853

What OpenQuestion holds

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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.