Dataset Information

Electrically controlled cloud of bulk nanobubbles in water solutions.

ABSTRACT: Using different experimental techniques we visualize a cloud of gas in water that is produced electrochemically by the alternating polarity process. Liquid enriched with gas does not contain bubbles strongly scattering visible light but its refractive index changes significantly near the electrodes. The change of the refractive index is a collective effect of bulk nanobubbles with a diameter smaller than 200 nm. Any alternative explanation fails to explain the magnitude of the effect. Spatial structure of the cloud is investigated with the optical lever method. Its dynamics is visualised observing optical distortion of the electrode images or using differential interference contrast method. The cloud covers concentric electrodes, in a steady state it is roughly hemispherical with a size two times larger than the size of the electrode structure. When the electrical pulses are switched off the cloud disappears in less than one second. The total concentration of gases can reach very high value estimated as 3.5 × 1020 cm-3 that corresponds to an effective supersaturation of 500 and 150 for hydrogen and oxygen, respectively.

SUBMITTER: Postnikov AV

PROVIDER: S-EPMC5519201 | biostudies-other | 2017

REPOSITORIES: biostudies-other

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Electrically controlled cloud of bulk nanobubbles in water solutions.

Postnikov Alexander V AV Uvarov Ilia V IV Lokhanin Mikhail V MV Svetovoy Vitaly B VB

PloS one 20170720 7

Using different experimental techniques we visualize a cloud of gas in water that is produced electrochemically by the alternating polarity process. Liquid enriched with gas does not contain bubbles strongly scattering visible light but its refractive index changes significantly near the electrodes. The change of the refractive index is a collective effect of bulk nanobubbles with a diameter smaller than 200 nm. Any alternative explanation fails to explain the magnitude of the effect. Spatial st ...[more]

PMID: 28727812

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Project description:Aerosol-cloud interactions are the largest source of uncertainty in quantifying anthropogenic radiative forcing. The large uncertainty is, in part, due to the difficulty of predicting cloud microphysical parameters, such as the cloud droplet number concentration (N d). Even though rigorous first-principle approaches exist to calculate N d, the cloud and aerosol research community also relies on empirical approaches such as relating N d to aerosol mass concentration. Here we analyze relationships between N d and cloud water chemical composition, in addition to the effect of environmental factors on the degree of the relationships. Warm, marine, stratocumulus clouds off the California coast were sampled throughout four summer campaigns between 2011 and 2016. A total of 385 cloud water samples were collected and analyzed for 80 chemical species. Single- and multispecies log-log linear regressions were performed to predict N d using chemical composition. Single-species regressions reveal that the species that best predicts N d is total sulfate ( Radj2=0.40 ). Multispecies regressions reveal that adding more species does not necessarily produce a better model, as six or more species yield regressions that are statistically insignificant. A commonality among the multispecies regressions that produce the highest correlation with N d was that most included sulfate (either total or non-sea-salt), an ocean emissions tracer (such as sodium), and an organic tracer (such as oxalate). Binning the data according to turbulence, smoke influence, and in-cloud height allowed for examination of the effect of these environmental factors on the composition-N d correlation. Accounting for turbulence, quantified as the standard deviation of vertical wind speed, showed that the correlation between N d with both total sulfate and sodium increased at higher turbulence conditions, consistent with turbulence promoting the mixing between ocean surface and cloud base. Considering the influence of smoke significantly improved the correlation with N d for two biomass burning tracer species in the study region, specifically oxalate and iron. When binning by in-cloud height, non-sea-salt sulfate and sodium correlated best with N d at cloud top, whereas iron and oxalate correlated best with N d at cloud base.

Dataset Information

Electrically controlled cloud of bulk nanobubbles in water solutions.

Publications

Electrically controlled cloud of bulk nanobubbles in water solutions.

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