Evidence map›Paper›PMID 32012875›Full record

ArticleSensors (Basel, Switzerland)2020

Evaluation of Silica Nanofluids in Static and Dynamic Conditions by an Optical Fiber Sensor.

Marco César Prado Soares, Matheus Santos Rodrigues, Egont Alexandre Schenkel, Gabriel Perli, Willian Hideak Arita Silva, Matheus Kauê Gomes, Eric Fujiwara, Carlos Kenichi Suzuki

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Marco César Prado SoaresLaboratory of Photonic Materials and Devices, School of Mechanical Engineering, University of Campinas, São Paulo 13083-860, Brazil.ORCID 0000-0002-5219-5124
Matheus Santos RodriguesLaboratory of Photonic Materials and Devices, School of Mechanical Engineering, University of Campinas, São Paulo 13083-860, Brazil.ORCID 0000-0002-7808-1811
Egont Alexandre SchenkelLaboratory of Photonic Materials and Devices, School of Mechanical Engineering, University of Campinas, São Paulo 13083-860, Brazil.
Gabriel PerliLaboratory of Photonic Materials and Devices, School of Mechanical Engineering, University of Campinas, São Paulo 13083-860, Brazil.
Willian Hideak Arita SilvaLaboratory of Photonic Materials and Devices, School of Mechanical Engineering, University of Campinas, São Paulo 13083-860, Brazil.
Matheus Kauê GomesLaboratory of Photonic Materials and Devices, School of Mechanical Engineering, University of Campinas, São Paulo 13083-860, Brazil.
Eric FujiwaraLaboratory of Photonic Materials and Devices, School of Mechanical Engineering, University of Campinas, São Paulo 13083-860, Brazil.ORCID 0000-0001-8169-9738
Carlos Kenichi SuzukiLaboratory of Photonic Materials and Devices, School of Mechanical Engineering, University of Campinas, São Paulo 13083-860, Brazil.

Funding

Conselho Nacional de Desenvolvimento Científico e Tecnológico Code 001Coordenação de Aperfeiçoamento de Pessoal de Nível Superior Code 001Fundação de Amparo à Pesquisa do Estado de São Paulo 2017/20445-8
6 · The paper itself

Abstract

This work presents an optical fiber dynamic light scattering sensor capable of simultaneously assessing concentration and flow speed of nanofluids. Silica nanoparticles (189 nm) in water were tested, yielding a sensitivity of 0.78288 × 10³ s

Indexed as

concentration measurementflow speed measurementoptical fiber sensorsilica nanofluid

Identifiers

PMID32012875
PMCPMC7039219

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.