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Membrane technologies that enable the efficient purification of impaired water sources are needed to address growing water scarcity. However, state-of-the-art engineered membranes are constrained by a universal, deleterious trade-off where membranes with high water permeability lack selectivity. Current membranes also poorly remove low–molecular weight neutral solutes and are vulnerable to degradation from oxidants used in water treatment. We report a water desalination technology that uses applied pressure to drive vapor transport through membranes with an entrapped air layer. Since separation occurs due to a gas-liquid phase change, near-complete rejection of dissolved solutes including sodium chloride, boron, urea, andN-nitrosodimethylamine is observed. Membranes fabricated with sub-200-nm-thick air layers showed water permeabilities that exceed those of commercial membranes without sacrificing salt rejection. We also find the air-trapping membranes tolerate exposure to chlorine and ozone oxidants. The results advance our understanding of evaporation behavior and facilitate high-throughput ultraselective separations.

 

This work proposes to analyze the time-dependent characteristics of the physical attributes measured along pathlines derived from unsteady flows, which can be represented as a series of time activity curves (TAC). A new TAC-based unsteady flow visualization and analysis framework is proposed. The center of this framework is a new event-based distance metric (EDM) that compares the similarity of two TACs, from which a new spatio-temporal, hierarchical clustering of pathlines based on their physical attributes and an attribute-based pathline exploration are proposed. These techniques are integrated into a visual analytics system, which has been applied to a number of unsteady flow in 2D and 3D to demonstrate its utility. 

Most existing unsteady flow visualization techniques concentrate on the depiction of geometric patterns in flow, assuming the geometry information provides sufficient representation of the underlying physical characteristics, which is not always the case. To address this challenge, this work proposes to analyse the time‐dependent characteristics of the physical attributes measured along pathlines which can be represented as a series of time activity curves (TAC). We demonstrate that the temporal trends of these TACs can convey the relation between pathlines and certain well‐known flow features (e.g. vortices and shearing layers), which enables us to select pathlines that can effectively represent the physical characteristics of interest and their temporal behaviour in the unsteady flow. Inspired by this observation, a new TAC‐based unsteady flow visualization and analysis framework is proposed. The centre of this framework is a new similarity measure that compares the similarity of two TACs, from which a new spatio‐temporal, hierarchical clustering that classifies pathlines based on their physical attributes, and a TAC‐based pathline exploration and selection strategy are proposed. A visual analytic system incorporating the TAC‐based pathline clustering and exploration is developed, which also provides new visualizations to support the user exploration of unsteady flow using TACs. This visual analytic system is applied to a number of unsteady flow in 2D and 3D to demonstrate its utility. The new system successfully reveals the detailed structure of vortices, the relation between shear layer and vortex formation, and vortex breakdown, which are difficult to convey with conventional methods.

 

Gd chelates have occupied most of the market of magnetic resonance imaging (MRI) contrast agents for decades. However, there have been some problems (nephrotoxicity, non‐specificity, and lowr₁) that limit their applications. Herein, a wet‐chemical method is proposed for facile synthesis of poly(acrylic acid) (PAA) stabilized exceedingly small gadolinium oxide nanoparticles (ES‐GON‐PAA) with an excellent water dispersibility and a size smaller than 2.0 nm, which is a powerfulT₁‐weighted MRI contrast agent for diagnosis of diseases due to its remarkable relaxivities (r₁= 70.2 ± 1.8 mM⁻¹s⁻¹, andr₂/r₁= 1.02 ± 0.03, at 1.5 T). Ther₁is much higher and ther₂/r₁is lower than that of the commercial Gd chelates and reported gadolinium oxide nanoparticles (GONs). Further ES‐GON‐PAA is developed with conjugation of RGD2 (RGD dimer) (i.e., ES‐GON‐PAA@RGD2) forT₁‐weighted MRI of tumors that overexpress RGD receptors (i.e., integrinα_vβ₃). The maximum signal enhancement (ΔSNR) forT₁‐weighted MRI of tumors reaches up to 372 ± 56% at 2 h post‐injection of ES‐GON‐PAA@RGD2, which is much higher than commercial Gd‐chelates (<80%). Due to the high biocompatibility and high tumor accumulation, ES‐GON‐PAA@RGD2 with remarkable relaxivities is a promising and powerfulT₁‐weighted MRI contrast agent.