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dc.contributor.authorKalb, Daniel J.  Concept link
dc.contributor.authorOlson, Robert J.  Concept link
dc.contributor.authorSosik, Heidi M.  Concept link
dc.contributor.authorWoods, Travis A.  Concept link
dc.contributor.authorGraves, Steven W.  Concept link
dc.date.accessioned2018-12-06T16:19:06Z
dc.date.available2018-12-06T16:19:06Z
dc.date.issued2018-11-14
dc.identifier.citationPLoS One 13 (2018): e0207532en_US
dc.identifier.urihttps://hdl.handle.net/1912/10766
dc.description© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in PLoS One 13 (2018): e0207532, doi:10.1371/journal.pone.0207532.en_US
dc.description.abstractAcoustic standing waves can precisely focus flowing particles or cells into tightly positioned streams for interrogation or downstream separations. The efficiency of an acoustic standing wave device is dependent upon operating at a resonance frequency. Small changes in a system’s temperature and sample salinity can shift the device’s resonance condition, leading to poor focusing. Practical implementation of an acoustic standing wave system requires an automated resonance control system to adjust the standing wave frequency in response to environmental changes. Here we have developed a rigorous approach for quantifying the optimal acoustic focusing frequency at any given environmental condition. We have demonstrated our approach across a wide range of temperature and salinity conditions to provide a robust characterization of how the optimal acoustic focusing resonance frequency shifts across these conditions. To generalize these results, two microfluidic bulk acoustic standing wave systems (a steel capillary and an etched silicon wafer) were examined. Models of these temperature and salinity effects suggest that it is the speed of sound within the liquid sample that dominates the resonance frequency shift. Using these results, a simple reference table can be generated to predict the optimal resonance condition as a function of temperature and salinity. Additionally, we show that there is a local impedance minimum associated with the optimal system resonance. The integration of the environmental results for coarse frequency tuning followed by a local impedance characterization for fine frequency adjustments, yields a highly accurate method of resonance control. Such an approach works across a wide range of environmental conditions, is easy to automate, and could have a significant impact across a wide range of microfluidic acoustic standing wave systems.en_US
dc.description.sponsorshipThis research was supported by grants from the National Institute of General Medical Sciences of the National Institutes of Health under award number R21GM107805 and the NSF under award number (OCE-1130140 and OCE-1131134) to SWG, RJO, and HMS.en_US
dc.language.isoen_USen_US
dc.publisherPublic Library of Scienceen_US
dc.relation.urihttps://doi.org/10.1371/journal.pone.0207532
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleResonance control of acoustic focusing systems through an environmental reference table and impedance spectroscopyen_US
dc.typeArticleen_US
dc.identifier.doi10.1371/journal.pone.0207532


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Attribution 4.0 International
Except where otherwise noted, this item's license is described as Attribution 4.0 International