ALBERT

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.

Description: Acoustic 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.

Description: This 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.

Description: © The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Limnology and Oceanography: Methods 15 (2017): 867–874, doi:10.1002/lom3.10205.

Description: Imaging FlowCytobot, a submersible instrument that measures optical properties and captures images of nano- and microplankton-sized particles, has proved useful in plankton studies, but its sampling rate is limited by the ability of hydrodynamic focusing to accurately position flowing sample particles. We show that IFCB's sampling rate can be increased at least several-fold by implementing in-line acoustic focusing upstream of the flow cell. Particles are forced to the center of flow by acoustic standing waves created by a piezo-electric transducer bonded to the sample capillary and driven at the appropriate frequency. With the particles of interest confined to the center of the sample flow, the increased size of the sample core that accompanies increased sample flow rate no longer degrades image and signal quality as it otherwise would. Temperature affects the optimum frequency (through its effect on the speed of sound in water), so a relationship between sample temperature and optimum frequency for acoustic focusing was determined and utilized to control the transducer. The modified instrument's performance was evaluated through analyses of artificial particles, phytoplankton cultures, and natural seawater samples and through deployments in coastal waters. The results show that large cells, especially dinoflagellates, are acoustically focused extremely effectively (which could enable, for example, 〉 10-fold increased sampling rate of harmful algal bloom species, if smaller cells are ignored), while for nearly all cell types typically monitored by IFCB, threefold faster data accumulation was achieved without any compromises. Further increases are possible with more sophisticated software and/or a faster camera.

Description: NSF Grant Numbers: OCE-1130140 , OCE-1131134