Design Principles From Natural Olfaction for Electronic Noses
Abstract Natural olfactory systems possess remarkable sensitivity and precision beyond what is currently achievable by engineered gas sensors. Unlike their artificial counterparts, noses are capable of distinguishing scents associated with mixtures of volatile molecules in complex, typically fluctua...
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| Format: | Article |
| Language: | English |
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Wiley
2025-03-01
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| Series: | Advanced Science |
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| Online Access: | https://doi.org/10.1002/advs.202412669 |
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| author | Haritosh Patel Vicente Garrido Portilla Anna V. Shneidman Jacopo Movilli Jack Alvarenga Christophe Dupré Michael Aizenberg Venkatesh N. Murthy Alexander Tropsha Joanna Aizenberg |
| author_facet | Haritosh Patel Vicente Garrido Portilla Anna V. Shneidman Jacopo Movilli Jack Alvarenga Christophe Dupré Michael Aizenberg Venkatesh N. Murthy Alexander Tropsha Joanna Aizenberg |
| author_sort | Haritosh Patel |
| collection | DOAJ |
| description | Abstract Natural olfactory systems possess remarkable sensitivity and precision beyond what is currently achievable by engineered gas sensors. Unlike their artificial counterparts, noses are capable of distinguishing scents associated with mixtures of volatile molecules in complex, typically fluctuating environments and can adapt to changes. This perspective examines the multifaceted biological principles that provide olfactory systems their discriminatory prowess, and how these ideas can be ported to the design of electronic noses for substantial improvements in performance across metrics such as sensitivity and ability to speciate chemical mixtures. The topics examined herein include the fluid dynamics of odorants in natural channels; specificity and kinetics of odorant interactions with olfactory receptors and mucus linings; complex signal processing that spatiotemporally encodes physicochemical properties of odorants; active sampling techniques, like biological sniffing and nose repositioning; biological priming; and molecular chaperoning. Each of these components of natural olfactory systems are systmatically investigated, as to how they have been or can be applied to electronic noses. While not all artificial sensors can employ these strategies simultaneously, integrating a subset of bioinspired principles can address issues like sensitivity, drift, and poor selectivity, offering advancements in many sectors such as environmental monitoring, industrial safety, and disease diagnostics. |
| format | Article |
| id | doaj-art-708fbf8f2baa4efabdf5b1362bf9fe3c |
| institution | Kabale University |
| issn | 2198-3844 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advanced Science |
| spelling | doaj-art-708fbf8f2baa4efabdf5b1362bf9fe3c2025-08-20T03:41:59ZengWileyAdvanced Science2198-38442025-03-011212n/an/a10.1002/advs.202412669Design Principles From Natural Olfaction for Electronic NosesHaritosh Patel0Vicente Garrido Portilla1Anna V. Shneidman2Jacopo Movilli3Jack Alvarenga4Christophe Dupré5Michael Aizenberg6Venkatesh N. Murthy7Alexander Tropsha8Joanna Aizenberg9Harvard John A. Paulson School of Engineering and Applied Sciences Harvard University Boston MA 02134 USAHarvard John A. Paulson School of Engineering and Applied Sciences Harvard University Boston MA 02134 USAHarvard John A. Paulson School of Engineering and Applied Sciences Harvard University Boston MA 02134 USAHarvard John A. Paulson School of Engineering and Applied Sciences Harvard University Boston MA 02134 USAHarvard John A. Paulson School of Engineering and Applied Sciences Harvard University Boston MA 02134 USADepartment of Molecular & Cellular Biology Harvard University Cambridge MA 02138 USAHarvard John A. Paulson School of Engineering and Applied Sciences Harvard University Boston MA 02134 USADepartment of Molecular & Cellular Biology Harvard University Cambridge MA 02138 USADepartment of Chemistry The University of North Carolina at Chapel Hill Chapel Hill NC 27516 USAHarvard John A. Paulson School of Engineering and Applied Sciences Harvard University Boston MA 02134 USAAbstract Natural olfactory systems possess remarkable sensitivity and precision beyond what is currently achievable by engineered gas sensors. Unlike their artificial counterparts, noses are capable of distinguishing scents associated with mixtures of volatile molecules in complex, typically fluctuating environments and can adapt to changes. This perspective examines the multifaceted biological principles that provide olfactory systems their discriminatory prowess, and how these ideas can be ported to the design of electronic noses for substantial improvements in performance across metrics such as sensitivity and ability to speciate chemical mixtures. The topics examined herein include the fluid dynamics of odorants in natural channels; specificity and kinetics of odorant interactions with olfactory receptors and mucus linings; complex signal processing that spatiotemporally encodes physicochemical properties of odorants; active sampling techniques, like biological sniffing and nose repositioning; biological priming; and molecular chaperoning. Each of these components of natural olfactory systems are systmatically investigated, as to how they have been or can be applied to electronic noses. While not all artificial sensors can employ these strategies simultaneously, integrating a subset of bioinspired principles can address issues like sensitivity, drift, and poor selectivity, offering advancements in many sectors such as environmental monitoring, industrial safety, and disease diagnostics.https://doi.org/10.1002/advs.202412669adaptive mechanismsbioinspirationgas sensorsmachine learningmaterials science |
| spellingShingle | Haritosh Patel Vicente Garrido Portilla Anna V. Shneidman Jacopo Movilli Jack Alvarenga Christophe Dupré Michael Aizenberg Venkatesh N. Murthy Alexander Tropsha Joanna Aizenberg Design Principles From Natural Olfaction for Electronic Noses Advanced Science adaptive mechanisms bioinspiration gas sensors machine learning materials science |
| title | Design Principles From Natural Olfaction for Electronic Noses |
| title_full | Design Principles From Natural Olfaction for Electronic Noses |
| title_fullStr | Design Principles From Natural Olfaction for Electronic Noses |
| title_full_unstemmed | Design Principles From Natural Olfaction for Electronic Noses |
| title_short | Design Principles From Natural Olfaction for Electronic Noses |
| title_sort | design principles from natural olfaction for electronic noses |
| topic | adaptive mechanisms bioinspiration gas sensors machine learning materials science |
| url | https://doi.org/10.1002/advs.202412669 |
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