The DOI matches its Crossref record; 342 of the 342 references it cites were found in a registry or an index.
Sensors for Volatile Organic Compounds
Abstract
This paper provides an overview of recent developments in the field of volatile organic compound (VOC) sensors, which are finding uses in healthcare, safety, environmental monitoring, food and agriculture, oil industry, and other fields. It starts by briefly explaining the basics of VOC sensing and reviewing the currently available and quickly progressing VOC sensing approaches. It then discusses the main trends in materials' design with special attention to nanostructuring and nanohybridization. Emerging sensing materials and strategies are highlighted and their involvement in the different types of sensing technologies is discussed, including optical, electrical, and gravimetric sensors. The review also provides detailed discussions about the main limitations of the field and offers potential solutions. The status of the field and suggestions of promising directions for future development are summarized.
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Cites
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Ultrastructural Characterization of the Lower Motor System in a Mouse Model of Krabbe Disease
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Double-slit photoelectron interference in strong-field ionization of the neon dimer
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Cited by
Wang, C., He, T., Zhou, H., Zhang, Z., & Lee, C. (2023) · Bioelectronic Medicine · doi:10.1186/s42234-023-00118-1 · Cited by 295
Perovskite materials for sensing applications: Recent advances and challenges
Bui, T. H., & Shin, J. H. (2023) · Microchemical Journal · doi:10.1016/j.microc.2023.108924 · Cited by 95
Azimzadeh, M., Khashayar, P., Mousazadeh, M., Daneshpour, M., Rostami, M., Goodlett, D. R., Manji, K., Fardindoost, S., Akbari, M., & Hoorfar, M. (2025) · Talanta · doi:10.1016/j.talanta.2025.127991 · Cited by 16
Metadata
- Authors
- Khatib, M., & Haick, H.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2022-05-05
- Volume
- 16
- Issue
- 5
- Pages
- 7080-7115
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W4229026135
- Cited by
- 533
- References
- 342
- FWCI
- 27.04
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
