Evidence map›Paper›PMID 41305143›Full record

ReviewSensors (Basel, Switzerland)2025

Review of Hydrogen Sensors in Aerobic and Anaerobic Environments Coupled with Artificial Intelligence Tools.

Jordan Herbeck-Tazibt, Mohand A Djeziri, Tomas Fiorido, Jean-Luc Seguin

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2025. 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

4 authors.

Jordan Herbeck-TazibtCentre National de la Recherche Scientifique (CNRS) and Institut Matériaux Microélectronique Nanosciences de Provence (IM2NP), Aix-Marseille Université, Université de Toulon, 13397 Marseille, France.ORCID 0009-0006-6537-8671
Mohand A DjeziriCentre National de la Recherche Scientifique (CNRS) and Institut Matériaux Microélectronique Nanosciences de Provence (IM2NP), Aix-Marseille Université, Université de Toulon, 13397 Marseille, France.ORCID 0000-0002-1597-3193
Tomas FioridoCentre National de la Recherche Scientifique (CNRS) and Institut Matériaux Microélectronique Nanosciences de Provence (IM2NP), Aix-Marseille Université, Université de Toulon, 13397 Marseille, France.
Jean-Luc SeguinCentre National de la Recherche Scientifique (CNRS) and Institut Matériaux Microélectronique Nanosciences de Provence (IM2NP), Aix-Marseille Université, Université de Toulon, 13397 Marseille, France.ORCID 0000-0001-5305-3075

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hydrogen-based technologies are progressing in several areas, such as transportation and energy, especially regarding their use as a replacement for greenhouse gas-emitting fuels. However, hydrogen is known for its explosiveness and large-scale flammability; hence, there is a need to ensure it can be detected and measured without risk. Several types of hydrogen sensors are available on the market. Each sensor is suited to a specific environment and operating conditions. In recent years, Artificial Intelligence tools have been increasingly used to improve the design and performance of these sensors in terms of safety, reliability, sensitivity, speed, and selectivity. This paper provides a review of available hydrogen sensors, their fields of application, and the main directions explored by the scientific community for integrating Artificial Intelligence tools to improve their performance. A comparative analysis is presented based on criteria related to sensor technologies, data processing tools, and target performance. This review highlights the results achieved and the challenges that remain to be addressed in various application fields.

Indexed as

artificial intelligencehydrogen sensorsmaterialsmathematical algorithmmodelingphysics

Identifiers

PMID41305143
PMCPMC12656358

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.