Evidence map›Paper›PMID 39091019›Full record

ArticleApplied spectroscopy2024

Feasibility of a Fiber-Dispersive Raman Spectrometer for Biomarker Detection.

Mariia Sidorova, Sergey G Pavlov, Ute Böttger, Mickael Baqué, Alexei D Semenov, Heinz-Wilhelm Hübers

Abstract read
In one paragraph

Article in Applied spectroscopy, 2024. 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

6 authors.

Mariia SidorovaHumboldt-Universität zu Berlin, Department of Physics, Berlin, Germany.ORCID 0000-0002-9082-442X
Sergey G PavlovGerman Aerospace Center (DLR), Institute of Optical Sensor Systems, Berlin, Germany.ORCID 0000-0002-7670-5694
Ute BöttgerGerman Aerospace Center (DLR), Institute of Planetary Research, Berlin, Germany.
Mickael BaquéGerman Aerospace Center (DLR), Institute of Planetary Research, Berlin, Germany.ORCID 0000-0002-6696-6030
Alexei D SemenovGerman Aerospace Center (DLR), Institute of Optical Sensor Systems, Berlin, Germany.
Heinz-Wilhelm HübersHumboldt-Universität zu Berlin, Department of Physics, Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Raman spectroscopy is among the top analytical techniques for ultra-low-dense organic matter, crucial to the search for life and analysis of celestial body surfaces in space exploration missions. Achieving the ultimate sensitivity of in-situ Raman spectroscopy necessitates a breakthrough in detecting inelastically scattered light. Single-photon detectors (SPDs) operating in photon counting mode, which can differentiate between Raman and luminescence responses, are promising candidates for the challenging scientific requirements. Since large SPD arrays are not yet commercially available, a dispersive element can be adapted to a single-pixel detector. By exploiting chromatic dispersion in optical fibers and picosecond-pulsed excitation, we delay the arrivals of different spectral components onto a single-pixel SPD. This method also separates weak Raman signals from stronger luminescence through correlated time-domain measurements. We study the impact of fiber properties and the excitation wavelength of a pulsed laser on the spectral resolution of the fiber-dispersive Raman spectrometer (FDRS). Additionally, we demonstrate the FDRS's potential for studying biomarkers and discuss its feasibility for analyzing inclusions in ice matrices.

Indexed as

biomarkersFiber-dispersive Raman spectrometerice matricessuperconducting nanowire single-photon detector

Identifiers

PMID39091019
PMCPMC11492548

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Registered trials

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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.