Sniffing speeds up chemical detection by controlling air-flows near sensors

Spencer, Thomas L.; Clark, Adams; Fonollosa, Jordi; Virot, Emmanuel; Hu, David L.

doi:10.1038/s41467-021-21405-y

Cited by 17 publications

(10 citation statements)

References 61 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Section: Resultsmentioning

confidence: 99%

“…Overall, the sensor array was subjected to nearly 100 such gas concentration cycles over a period of 72 h. Under real sensing conditions, the gas composition generally changes more gradually. However, such an ON-OFF gas exchange protocol can be implemented in real sensors by flow modulation (sniffing [42,43] or by releasing the gases from a pre-concentrator). In terms of conductance, the overall response amplitudes (defined as the difference between the maximum and minimum values) of sensors S1, S3 and S4 to O 3 were comparable; the response of sensor S2 was 2.5 times smaller (Table 2).…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Semiquantitative Classification of Two Oxidizing Gases with Graphene-Based Gas Sensors

et al. 2022

View full text Add to dashboard Cite

Miniature and low-power gas sensing elements are urgently needed for a portable electronic nose, especially for outdoor pollution monitoring. Hereby we prepared chemiresistive sensors based on wide-area graphene (grown by chemical vapor deposition) placed on Si/Si3N4 substrates with interdigitated electrodes and built-in microheaters. Graphene of each sensor was individually functionalized with ultrathin oxide coating (CuO-MnO2, In2O3 or Sc2O3) by pulsed laser deposition. Over the course of 72 h, the heated sensors were exposed to randomly generated concentration cycles of 30 ppb NO2, 30 ppb O3, 60 ppb NO2, 60 ppb O3 and 30 ppb NO2 + 30 ppb O3 in synthetic air (21% O2, 50% relative humidity). While O3 completely dominated the response of sensors with CuO-MnO2 coating, the other sensors had comparable sensitivity to NO2 as well. Various response features (amplitude, response rate, and recovery rate) were considered as machine learning inputs. Using just the response amplitudes of two complementary sensors allowed us to distinguish these five gas environments with an accuracy of ~ 85%. Misclassification was mostly due to an overlap in the case of the 30 ppb O3, and 30 ppb O3 + 30 ppb NO2 responses, and was largely caused by the temporal drift of these responses. The addition of recovery rates to machine learning input variables enabled us to very clearly distinguish different gases and increase the overall accuracy to ~94%.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Semiquantitative Classification of Two Oxidizing Gases with Graphene-Based Gas Sensors

et al. 2022

View full text Add to dashboard Cite

show abstract

“…[37] Spencer et al compared the sniff strategy of different mammals and proposed a MOX sensor system using sniffs to speed up gas detection. [38] Furthermore, Ziyatdinov et al applied a mechanical ventilator to simulate the biological sniffs with a steady respiration frequency. [39] The MOX sensor array can more quickly identify the composition of acetone-ethanol binary mixtures by extracting high frequency features.…”

Section: Introductionmentioning

confidence: 99%

Sniffing Like a Wine Taster: Multiple Overlapping Sniffs (MOSS) Strategy Enhances Electronic Nose Odor Recognition Capability

Liu,

Na,

et al. 2023

Advanced Science

View full text Add to dashboard Cite

As highly promising devices for odor recognition, current electronic noses are still not comparable to human olfaction due to the significant disparity in the number of gas sensors versus human olfactory receptors. Inspired by the sniffing skills of wine tasters to achieve better odor perception, a multiple overlapping sniffs (MOSS) strategy is proposed in this study. The MOSS strategy involves rapid and continuous inhalation of odorants to stimulate the sensor array to generate feature‐rich temporal signals. Computational fluid dynamics simulations are performed to reveal the mechanism of complex dynamic flows affecting transient responses. The proposed strategy shows over 95% accuracy in the recognition experiments of three gaseous alkanes and six liquors. Results demonstrate that the MOSS strategy can accurately and easily recognize odors with a limited sensor number. The proposed strategy has potential applications in various odor recognition scenarios, such as medical diagnosis, food quality assessment, and environmental surveillance.

show abstract

“…Most of those with highly evolved olfactory systems have tortuous air pathways along the nasal cavity with long and curved turbinates that split and stretch the inhaled air's streamlines. The multiscale morphological structures and other biological features help capture tiny particles from the inhaled air onto the olfactory epithelium [17,18]. Airpath twists induce secondary flows, including the so-called Dean's pattern.…”

Section: Introductionmentioning

confidence: 99%

On the design of particle filters inspired by animal noses

Yuk

Chakraborty

Cheng

et al. 2022

J. R. Soc. Interface.

View full text Add to dashboard Cite

Passive filtering is a common strategy to reduce airborne disease transmission and particulate contaminants across scales spanning orders of magnitude. The engineering of high-performance filters with relatively low flow resistance but high virus- or particle-blocking efficiency is a non-trivial problem of paramount relevance, as evidenced in the variety of industrial filtration systems and face masks. Next-generation industrial filters and masks should retain sufficiently small droplets and aerosols while having low resistance. We introduce a novel 3D-printable particle filter inspired by animals’ complex nasal anatomy. Unlike standard random-media-based filters, the proposed concept relies on equally spaced channels with tortuous airflow paths. These two strategies induce distinct effects: a reduced resistance and a high likelihood of particle trapping by altering their trajectories with tortuous paths and induced local flow instability. The structures are tested for pressure drop and particle filtering efficiency over different airflow rates. We have also cross-validated the observed efficiency through numerical simulations. We found that the designed filters exhibit a lower pressure drop, compared to commercial masks and filters, while capturing particles bigger than approximately 10 μm. Our findings could facilitate a novel and scalable filter concept inspired by animal noses.

show abstract

Sniffing speeds up chemical detection by controlling air-flows near sensors

Cited by 17 publications

References 61 publications

Semiquantitative Classification of Two Oxidizing Gases with Graphene-Based Gas Sensors

Semiquantitative Classification of Two Oxidizing Gases with Graphene-Based Gas Sensors

Sniffing Like a Wine Taster: Multiple Overlapping Sniffs (MOSS) Strategy Enhances Electronic Nose Odor Recognition Capability

On the design of particle filters inspired by animal noses

Contact Info

Product

Resources

About