Evidence map›Paper›PMID 41902102›Full record

ReviewSensors (Basel, Switzerland)2026

On the Use of Laser-Induced Graphene (LIG) in the Development of Chemoresistive Gas Sensors.

Alejandro Santos-Betancourt, Xavier Vilanova

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Alejandro Santos-BetancourtUniversitat Rovira i Virgili, Microsystems Nanotechnologies for Chemical Analysis (MINOS), Departament d'Enginyeria Electronica, Països Catalans, 26, 43007 Tarragona, Spain.ORCID 0000-0002-2849-5856
Xavier VilanovaUniversitat Rovira i Virgili, Microsystems Nanotechnologies for Chemical Analysis (MINOS), Departament d'Enginyeria Electronica, Països Catalans, 26, 43007 Tarragona, Spain.ORCID 0000-0002-6245-7933

Funding

Agencia Estatal de Investigación (FEDER) PID2022-142451OB-C21
6 · The paper itself

Abstract

In recent years, two-dimensional (2D) materials have attracted growing attention for their application in chemoresistive gas sensors. Among these materials, graphene stands out due to its exceptional electrical, mechanical, and chemical properties. A simple and low-cost method for producing graphene involves the use of a laser to induce its formation on carbon-rich substrates, such as polyimides. This technique, first introduced in 2014, has been successfully applied in the fabrication of various types of sensors, including pressure sensors, temperature sensors, biosensors, and gas sensors. For chemoresistive gas sensors, laser-induced graphene (LIG) has been used either as an electrode or as part of the nanocomposite forming the active sensing layer. Moreover, this technology has allowed the use of heating elements. Sensing performance, including sensitivity and selectivity, can be tailored by incorporating different materials into the nanocomposite, such as metallic nanoparticles, metal oxides, or conductive polymers. These modifications can be implemented using low-cost and scalable fabrication methods, making this approach highly suitable for the development of affordable and efficient gas sensors. In this contribution, we present a comprehensive overview of the contributions, reported from the proposal of LIG technology in 2014 to 2025, about the use of this fabrication process in the development of chemoresistive gas sensors.

Indexed as

laser-induced graphenelaser parametersLIGLIG as IDEsLIG-based gas sensorLIG combined with MOX/TMD/NP/polymersLIG in heaters

Identifiers

PMID41902102
PMCPMC13030825

What OpenQuestion holds

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LicenceCC BY
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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.