Simultaneous Aggregation and Height Bifurcation of Colloidal Particles near Electrodes in Oscillatory Electric Fields

Micrometer-scale particles suspended in NaCl solutions aggregate laterally near the electrode upon application of a low-frequency (∼100 Hz) field, but the same particles suspended in NaOH solutions are instead observed to separate laterally. The underlying mechanism for the electrolyte dependence remains obscure. Recent work by Woehl et al. (PRX, 2015) revealed that, contrary to previous reports, particles suspended in NaOH solutions indeed aggregate under some conditions while simultaneously exhibiting a distinct bifurcation in average height above the electrode. Here we elaborate on this observation by demonstrating the existence of a critical frequency (∼25 Hz) below which particles in NaOH aggregate laterally and above which they separate. The results indicate that the current demarcation of electrolytes as either aggregating or separating is misleading and that the key role of the electrolyte instead is to set the magnitude of a critical frequency at which particles transition between the two behaviors

Influence of Electrolyte Concentration on the Aggregation of Colloidal Particles near Electrodes in Oscillatory Fields

Micron-scale particles suspended in various aqueous electrolytes have been widely observed to aggregate near electrodes in response to oscillatory electric fields, a phenomenon believed to result from electrically induced flows around the particles. Previous work has focused on elucidating the effects of the applied field strength, frequency, and electrolyte type on the aggregation rate of particles, with less attention paid to the ionic strength. Here we demonstrate that an applied field causes micron-scale particles in aqueous NaCl to rapidly aggregate over a wide range of ionic strengths, but with significant differences in aggregation morphology. Optical microscopy observations reveal that at higher ionic strengths (∼1 mM) particles arrange as hexagonally closed-packed (HCP) crystals, but at lower ionic strengths (∼0.05 mM) the particles arrange in randomly closed-packed (RCP) structures. We interpret this behavior in terms of two complementary effects: an increased particle diffusivity at lower ionic strengths due to increased particle height over the electrode and the existence of a deep secondary minimum in the particle pair interaction potential at higher ionic strength that traps particles in close proximity to one another. The results suggest that electrically induced crystallization will readily occur only over a narrow range of ionic strengths

Effect of ambient humidity and temperature on transmission probability.

<p>The predicted probability of transmission at varied temperatures versus (A, C) relative humidity and (B, D) absolute humidity for the pulmonary (A–B) and NPTB (C–D) deposition efficiencies at 10 cm and 30 cm downstream, respectively. The experimental observations by Lowen <i>et al. </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0037088#pone.0037088-Lowen2" target="_blank">[4]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0037088#pone.0037088-Lowen3" target="_blank">[5]</a> are shown as discrete points. Blue circles: T = 5°C; gray triangles: T = 20°C; red squares: T = 30°C.</p

Guinea pig viral growth kinetics of rPan99 and Tx91.

<p>The measurements by Mubareka <i>et al. </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0037088#pone.0037088-Mubareka1" target="_blank">[6]</a> of the influenza concentration observed in nasal titers obtained from inoculated guinea pigs infected with rPan99 and Tx91. Black circles: rPan99; purple squares: Tx91. Dashed lines are fits to a numerical model for influenza viral dynamics <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0037088#pone.0037088-Baccam1" target="_blank">[18]</a>.</p

A Comprehensive Breath Plume Model for Disease Transmission via Expiratory Aerosols

<div><p>The peak in influenza incidence during wintertime in temperate regions represents a longstanding, unresolved scientific question. One hypothesis is that the efficacy of airborne transmission via aerosols is increased at lower humidities and temperatures, conditions that prevail in wintertime. Recent work with a guinea pig model by Lowen <em>et al.</em> indicated that humidity and temperature do modulate airborne influenza virus transmission, and several investigators have interpreted the observed humidity dependence in terms of airborne virus survivability. This interpretation, however, neglects two key observations: the effect of ambient temperature on the viral growth kinetics within the animals, and the strong influence of the background airflow on transmission. Here we provide a comprehensive theoretical framework for assessing the probability of disease transmission via expiratory aerosols between test animals in laboratory conditions. The spread of aerosols emitted from an infected animal is modeled using dispersion theory for a homogeneous turbulent airflow. The concentration and size distribution of the evaporating droplets in the resulting “Gaussian breath plume” are calculated as functions of position, humidity, and temperature. The overall transmission probability is modeled with a combination of the time-dependent viral concentration in the infected animal and the probability of droplet inhalation by the exposed animal downstream. We demonstrate that the breath plume model is broadly consistent with the results of Lowen <em>et al.,</em> without invoking airborne virus survivability. The results also suggest that, at least for guinea pigs, variation in viral kinetics within the infected animals is the dominant factor explaining the increased transmission probability observed at lower temperatures.</p> </div

Probability of transmission at different positions.

<p>Contour plots of the probability of transmission as a function of position downstream from an infected animal located at the origin for the pulmonary (A–F) and NPTB (G–L) deposition efficiencies. Red denotes high probability of transmission, blue denotes low probability. (A–C, G–I) Fixed relative humidity and varying temperature. (D–F, J–L) Fixed temperature and varying relative humidity. Note that the transmission probability depends strongly on temperature but more weakly on humidity.</p

Guinea pig viral growth kinetics at different temperatures.

<p>The measurements by Lowen <i>et al. </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0037088#pone.0037088-Lowen2" target="_blank">[4]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0037088#pone.0037088-Lowen3" target="_blank">[5]</a> of the influenza concentration observed in nasal titers obtained from inoculated guinea pigs maintained at different temperatures. Blue circles: T = 5°C; red squares: T = 30°C. Dashed lines are fits to a numerical model for influenza viral dynamics <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0037088#pone.0037088-Baccam1" target="_blank">[18]</a>; solid lines are analytical estimates given by Equation 1.</p

Droplet Conductivity Strongly Influences Bump and Crater Formation on Electrodes during Charge Transfer

Aqueous droplets acquire charge when they contact electrodes in high voltage electric fields, but the exact mechanism of charge transfer is not understood. Recent work by Elton et al. revealed that electrodes are physically pitted during charge transfer with aqueous droplets. The pits are believed to result when a dielectric breakdown arc occurs as a droplet approaches the electrode and the associated high current density transiently locally melts the electrode, leaving distinct crater-like deformations on the electrode surface. Here we show that the droplet conductivity strongly modulates the pitting morphology but has little effect on the amount of charge transferred. Electron and atomic force microscopy shows that deionized water droplets yield no observable deformations, but as the salt concentration in the droplet increases above 10^–3 M, the deformations become increasingly large. The observed intensity of the flash of light released during the dielectric breakdown arc also increases with droplet conductivity. Surprisingly, despite the large difference in pitting morphology and corresponding arc intensity, droplets of any conductivity acquire similar amounts of charge. These results suggest that the energy transferred during dielectric breakdown is primarily responsible for electrode pitting rather than the total amount of energy released during charge transfer

Droplet Conductivity Strongly Influences Bump and Crater Formation on Electrodes during Charge Transfer

Aqueous droplets acquire charge when they contact electrodes in high voltage electric fields, but the exact mechanism of charge transfer is not understood. Recent work by Elton et al. revealed that electrodes are physically pitted during charge transfer with aqueous droplets. The pits are believed to result when a dielectric breakdown arc occurs as a droplet approaches the electrode and the associated high current density transiently locally melts the electrode, leaving distinct crater-like deformations on the electrode surface. Here we show that the droplet conductivity strongly modulates the pitting morphology but has little effect on the amount of charge transferred. Electron and atomic force microscopy shows that deionized water droplets yield no observable deformations, but as the salt concentration in the droplet increases above 10^–3 M, the deformations become increasingly large. The observed intensity of the flash of light released during the dielectric breakdown arc also increases with droplet conductivity. Surprisingly, despite the large difference in pitting morphology and corresponding arc intensity, droplets of any conductivity acquire similar amounts of charge. These results suggest that the energy transferred during dielectric breakdown is primarily responsible for electrode pitting rather than the total amount of energy released during charge transfer

Droplet size evolution and deposition efficiencies.

<p>(A) Aerosol size versus time for droplets in air at 50% RH. Solid lines, <i>a₀</i> = 5 µm; dotted lines, <i>a₀</i> = 15 µm. Blue curves: T = 5°C; red curves: T = 30°C. (B) The deposition efficiency of a unit-density particle of radius <i>a</i> depositing in the pulmonary (P) and nasopharyngeal-tracheobronchial (NPTB) regions of a guinea pig. Purple: Pulmonary; black: NPTB. Reproduced from Schreider <i>et al. </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0037088#pone.0037088-Schreider1" target="_blank">[34]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0037088#pone.0037088-Schreider2" target="_blank">[35]</a>.</p