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Capacitive deionization is an electrochemical ion removal technique that has broad application prospects for the efficient desalination of brackish water. The current research mainly focuses on the improvement of the electrode material performance and device structure for capacitive deionization. However, the capacitive deionization process is subject to the coupling effect of multiple physical parameters inside the porous electrode, the dominant order and optimization of multiple physical parameters in the capacitive deionization process are needed to be further investigated. In this study, the ion transport in porous electrode of the capacitive deionization is investigated via numerical simulation and physical similarity analysis. Fourteen dimensional physical parameters involved in ion transport are unified into eight dimensionless parameters based on the nondimensionalization of Navier–Stokes and Poisson–Nernst–Planck equations, and the dimensionless parameters are summarized into four categories, including ion adsorption capability, ion transport characteristics, ion motion driving force, and ion adsorption equilibrium time. Analysis based on the numerical models with an irregular porous electrode structure shows that the dimensionless parameters can explain a series of similar physical phenomena in the capacitive deionization processes. Moreover, a parametric sensibility analysis is performed to reveal that the concentration and velocity of inlet solution are dominant factors for optimizing the salt adsorption capacity per unit area and the average salt removal rate. In addition, the inlet solution concentration and electrode potential are critical factors for improving the removal efficiency. The physical similarity and parametric sensitivity analysis in this study provide theoretical guidance for performance improvement in the practical application of capacitive deionization. [ABSTRACT FROM AUTHOR]

We developed a high-frequency submersible sub-bottom profiler (HF-SSBP) instrument for taking deep-sea sediment measurement. In order to evaluate the reliability of profile data, a laboratory calibration method (LCM) was developed using illuminated acrylic standard boards in anechoic tank to form multi-layer reflections and evaluate the errors of the HF-SSBP. Two layer reflections induced by single boards in different thicknesses and ranges were performed and recorded, after which four layer reflections induced by two boards with an adjusted water crack were set and logged. The results showed that the HF-SSBP resolution was 44.9 mm in acrylic and its equivalent in the sediment was 28.5 mm. The absolute measure error was 7 mm with an acrylic board thickness of 100 mm, and the maximum measure error was 3.5 mm in different water thicknesses. As a test and application, deep-sea sediment measurement of the HF-SSBP was launched and compared with in situ sampling cores in the same site. The measurement thickness for sections A and B are 39.4 cm and 23.2 cm, respectively, corresponding to the sampling core of 39.8 cm and 23.7 cm. The two results are close as we expected. This work demonstrates the reliability and accuracy of the HF-SSBP measurement, thus providing a good choice for deep-sea submergence vehicles to carry this sonar instrument to obtain high-resolution stratum in deep-sea surficial sediments. [ABSTRACT FROM AUTHOR]

Porous flow fields distribute fuel and oxygen for the electrochemical reactions of proton exchange membrane (PEM) fuel cells through their pore network instead of conventional flow channels. This type of flow fields has showed great promises in enhancing reactant supply, heat removal, and electrical conduction, reducing the concentration performance loss and improving operational stability for fuel cells. This review presents the research and development progress of porous flow fields with insights for next-generation PEM fuel cells of high power density (e.g., ∼9.0 kW L–1). Materials, fabrication methods, fundamentals, and fuel cell performance associated with porous flow fields are discussed in depth. Major challenges are described and explained, along with several future directions, including separated gas/liquid flow configurations, integrated porous structure, full morphology modeling, data-driven methods, and artificial intelligence-assisted design/optimization. [ABSTRACT FROM AUTHOR]