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A dog's nose differs from a human's in that air does not change direction but flows in a unidirectional path from inlet to outlet. Previous simulations showed that unidirectional flow through a dog’s complex nasal passageways creates stagnant zones of trapped air. We hypothesize that these zones give the dog a “physical memory,” which it may use to compare recent odors to past ones. In this study, we conducted experiments with our previously built Gaseous Recognition Oscillatory Machine Integrating Technology (GROMIT) and performed corresponding simulations in two dimensions. We compared three settings: a control setting that mimics the bidirectional flow of the human nose; a short-circuit setting where odors exit before reaching the sensors; and a unidirectional configuration using a dedicated inlet and outlet that mimics the dog’s nose. After exposure to odors, the sensors in the unidirectional setting showed the slowest return to their baseline level, indicative of memory effects. Simulations showed that both short-circuit and unidirectional flows created trapped recirculation zones, which slowed the release of odors from the chamber. In the future, memory effects such as the ones found here may improve the sensitivity and utility of electronic noses.

 

Abstract Most mammals sniff to detect odors, but little is known how the periodic inhale and exhale that make up a sniff helps to improve odor detection. In this combined experimental and theoretical study, we use fluid mechanics and machine olfaction to rationalize the benefits of sniffing at different rates. We design and build a bellows and sensor system to detect the change in current as a function of odor concentration. A fast sniff enables quick odor recognition, but too fast a sniff makes the amplitude of the signal comparable to noise. A slow sniff increases signal amplitude but delays its transmission. This trade-off may inspire the design of future devices that can actively modulate their sniffing frequency according to different odors.