Machine learning-enabled graphene-based electronic olfaction sensors and their olfactory performance assessment
- DOI
- 10.1063/5.0132177
- Published
- 2023-05-15
- Container
- Applied Physics Reviews
- Publisher
- AIP Publishing
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1063/5.0132177,
title = {Machine learning-enabled graphene-based electronic olfaction sensors and their olfactory performance assessment},
author = {Shirong Huang and Alexander Croy and Antonie Louise Bierling and Vyacheslav Khavrus and Luis Antonio Panes-Ruiz and Arezoo Dianat and Bergoi Ibarlucea and Gianaurelio Cuniberti},
year = {2023},
journal = {Applied Physics Reviews},
doi = {10.1063/5.0132177},
url = {https://doi.org/10.1063/5.0132177}
}RIS
TY - JOUR TI - Machine learning-enabled graphene-based electronic olfaction sensors and their olfactory performance assessment AU - Shirong Huang AU - Alexander Croy AU - Antonie Louise Bierling AU - Vyacheslav Khavrus AU - Luis Antonio Panes-Ruiz AU - Arezoo Dianat AU - Bergoi Ibarlucea AU - Gianaurelio Cuniberti PY - 2023 JO - Applied Physics Reviews DO - 10.1063/5.0132177 UR - https://doi.org/10.1063/5.0132177 ER -
APA
Huang, S., Croy, A., Bierling, A. L., Khavrus, V., Panes-Ruiz, L. A., Dianat, A., Ibarlucea, B., & Cuniberti, G. (2023). Machine learning-enabled graphene-based electronic olfaction sensors and their olfactory performance assessment. Applied Physics Reviews. https://doi.org/10.1063/5.0132177
Source records
- crossref · retrieved 2026-09-24T19:49:30.843Z