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As a consequence of the large demand of face masks due to the COVID19 pandemic, cheap, fast and non-destructive tests that can verify in-line the variability of the filtration capacities, prove the potential disinfection and/or evaluate the performance of new filtering materials are needed. Using two different approaches based on air-coupled ultrasounds (0.15-1.6 MHz) with equivalent results, this work shows that each face mask presents a distinctive ultrasonic signature that enables the classification and the evaluation of their performance. Moreover, it is shown that the ultrasonic propagation through the face masks and the main filter layers takes place through the pore space and that low frequency response of the attenuation and the velocity is highly dispersive and is dominated by the interaction between the air in the pores and the fibers in the filters. Hence, the parameters that describe ultrasonic velocity, attenuation and dispersion can be related with their filtration efficiency and breathability. These techniques are fully contactless, non-invasive and fast.
Non-destructive test, SARS-CoV-2, Non-destructive tests, Textiles, Masks, COVID-19, Equipment Design, Materials Testing, Humans, Ultrasonics, Air-coupled ultrasound, Face masks
Non-destructive test, SARS-CoV-2, Non-destructive tests, Textiles, Masks, COVID-19, Equipment Design, Materials Testing, Humans, Ultrasonics, Air-coupled ultrasound, Face masks
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 8 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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| downloads | 99 |

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