Evidence map›Paper›PMID 38475065›Full record

ReviewSensors (Basel, Switzerland)2024

On-Chip Photonic Detection Techniques for Non-Invasive In Situ Characterizations at the Microfluidic Scale.

Tamar Kurdadze, Fabrice Lamadie, Karen A Nehme, Sébastien Teychené, Béatrice Biscans, Isaac Rodriguez-Ruiz

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2024. 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
–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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. 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

6 authors.

Tamar KurdadzeCEA, DES, ISEC, DMRC, Univ Montpellier, 30207 Bagnols-sur-Ceze, Marcoule, France.
Fabrice LamadieCEA, DES, ISEC, DMRC, Univ Montpellier, 30207 Bagnols-sur-Ceze, Marcoule, France.ORCID 0000-0002-1449-5986
Karen A NehmeLaboratoire de Génie Chimique, CNRS, UMR 5503, 4 Allée Emile Monso, 31432 Toulouse, France.
Sébastien TeychenéLaboratoire de Génie Chimique, CNRS, UMR 5503, 4 Allée Emile Monso, 31432 Toulouse, France.
Béatrice BiscansLaboratoire de Génie Chimique, CNRS, UMR 5503, 4 Allée Emile Monso, 31432 Toulouse, France.
Isaac Rodriguez-RuizLaboratoire de Génie Chimique, CNRS, UMR 5503, 4 Allée Emile Monso, 31432 Toulouse, France.ORCID 0000-0003-3949-3888

Funding

Atomic Energy and Alternative Energies Commission PRATA projectFrench National Centre for Scientific Research Internal funding for Master internship programmes
6 · The paper itself

Abstract

Microfluidics has emerged as a robust technology for diverse applications, ranging from bio-medical diagnostics to chemical analysis. Among the different characterization techniques that can be used to analyze samples at the microfluidic scale, the coupling of photonic detection techniques and on-chip configurations is particularly advantageous due to its non-invasive nature, which permits sensitive, real-time, high throughput, and rapid analyses, taking advantage of the microfluidic special environments and reduced sample volumes. Putting a special emphasis on integrated detection schemes, this review article explores the most relevant advances in the on-chip implementation of UV-vis, near-infrared, terahertz, and X-ray-based techniques for different characterizations, ranging from punctual spectroscopic or scattering-based measurements to different types of mapping/imaging. The principles of the techniques and their interest are discussed through their application to different systems.

Indexed as

analytical chemistrylab-on-a-chipmicrofluidicsphotonic detectionsensorsspectrometry

Identifiers

PMID38475065
PMCPMC10933925

What OpenQuestion holds

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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.