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We report a new, autonomous Lab-on-Chip (LOC) microfluidic pH sensor with a 6000 m depth capability, ten times the depth capability of the state of the art autonomous spectrophotometric sensor. The pH is determined spectrophotometrically using purified meta-Cresol Purple indicator dye offering high precision (<0.001 pH unit measurement reproducibility), high frequency (every 8 min) measurements on the total proton scale from the surface to the deep ocean (to 600 bar). The sensor requires low power (3 W during continuous operation or ∼1300 J per measurement) and low reagent volume (∼3 μL per measurement) and generates small waste volume (∼2 mL per measurement) which can be retained during deployments. The performance of the LOC pH sensor was demonstrated on fixed and moving platforms over varying environmental salinity, temperature, and pressure conditions. Measurement accuracy was +0.003 ± 0.022 pH units (n = 47) by comparison with validation seawater sample measurements in coastal waters. The combined standard uncertainty of the sensor in situ pH T measurements was estimated to be ≤0.009 pH units at pH 8.5, ≤ 0.010 pH units at pH 8.0, and ≤0.014 pH units at pH 7.5. Integrated on autonomous platforms, this novel sensor opens new frontiers for pH observations, especially within the largest and most understudied ecosystem on the planet, the deep ocean.

Using molecular dynamics simulations, we investigate the fate of a nanoparticle deposited on a solid surface as a liquid-liquid interface moves past it, depending on the wetting of the solid by the two liquids and the magnitude of the driving force. Interfacial pinning is observed below a critical value of the driving force. Above the critical driving force for pinning and for large contact angle value we observe stick-slip motion, with intermittent interfacial pinning and particle sliding at the interface. At low contact angles we observe that particle rolling precedes detachment, which indicates the importance of dynamic effects not present in static models. The findings in this work indicate that particle mobilization and removal efficiencies originating in dynamic liquid-liquid interfaces can be significantly underestimated by static models.

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