Effects of porosity and contaminant on evaporation from nanopores

Evaporation from nanopores, owing to its high mass/heat fluxes and high heat transfer coefficients, have found widespread applications in various industrial process, including electronics cooling, solar steam generation, membrane distillation and power generation. To further improve the performance of these nanopore-evaporation-associated processes, it is necessary to experimentally quantify the ultimate transport limit of evaporation from nanopores and understand its dependence on nanoscale confinement and operating conditions. This ultimate transport limit has now been widely accepted to be dictated by evaporation kinetics at the liquid-vapor interface, which is very difficult to quantify experimentally due to the ultra-small evaporation rates from single nanopores. To overcome this challenge, a new measurement approach based on a hybrid nanochannel-nanopore device design has been developed recently. This measurement approach can accurately measure evaporation rates/fluxes from single nanopore and has been used to investigate the effect of nanopore diameter on kinetic-limited evaporation flux. Although this study provides us new fundamental understanding about how nanoscale confinements change evaporation from nanopore, the effects of contaminant and pore porosity, which to some extent determines the practical performance of evaporation from nanopores, have remained elusive. Such lacking understanding has prevented us from developing optimized evaporative nanoporous structures for practical applications. This works aims to investigate the effects of porosity and contaminant on kinetic-limited evaporation flux by experimentally measuring kinetic-limited evaporation rates from nanopore arrays. A modified hybrid nanochannel-nanopore device design is used to achieve this goal. In this modified device design, a nanopore array is directly connected to a 2-D nanochannel and the total evaporation rate from the nanopore array is measured by tracking meniscus receding in the nanochannel during a drying/evaporation process. Using this modified device design, we measured the kinetic-limited evaporation rates from 3x3 nanopore arrays with different interval distances ranging from 200 nm to 1 μm. To facilitate comparison between different devices, the total evaporation rates were converted to evaporation fluxes based on the nanopore projected area. Our results showed that that porosity or nanopore interval distance has negligible effect on the kinetic-limited evaporation flux. We also performed evaporation experiment using water with impurity and studied the effect of contaminant on kinetic-limit evaporation flux. It was observed that the contaminants in water can significantly reduce the kinetic-limited evaporation flux in nanopores and the contaminant effect becomes much more obvious in smaller nanopore due to contaminant-accumulation-induced pore blockage

InGVIO: A Consistent Invariant Filter for Fast and High-Accuracy GNSS-Visual-Inertial Odometry

Combining Global Navigation Satellite System (GNSS) with visual and inertial sensors can give smooth pose estimation without drifting in geographical coordinates. The fusion system gradually degrades to Visual-Inertial Odometry (VIO) with the number of satellites decreasing, which guarantees robust global navigation in GNSS unfriendly environments. In this letter, we propose an open-sourced invariant filter-based platform, InGVIO, to tightly fuse monocular/stereo visual-inertial measurements, along with raw data from GNSS, i.e. pseudo ranges and Doppler shifts. InGVIO gives highly competitive results in terms of accuracy and computational load compared to current graph-based and `naive' EKF-based algorithms. Thanks to our proposed key-frame marginalization strategies, the baseline for triangulation is large although only a few cloned poses are kept. Besides, landmarks are anchored to a single cloned pose to fit the nonlinear log-error form of the invariant filter while achieving decoupled propagation with IMU states. Moreover, we exploit the infinitesimal symmetries of the system, which gives equivalent results for the pattern of degenerate motions and the structure of unobservable subspaces compared to our previous work using observability analysis. We show that the properly-chosen invariant error captures such symmetries and has intrinsic consistency properties. InGVIO is tested on both open datasets and our proposed fixed-wing datasets with variable levels of difficulty. The latter, to the best of our knowledge, are the first datasets open-sourced to the community on a fixed-wing aircraft with raw GNSS.Comment: 8 pages, 8 figures; manuscript will be submitted to IEEE RA-L for possible publicatio

N 2,N 2′-Bis(3-nitro­benzyl­idene)pyridine-2,6-dicarbohydrazide dimethyl­formamide disolvate trihydrate

In the title compound, C21H15N7O6·2C3H7NO·3H2O, the N 2,N 2′-bis­(3-nitro­benzyl­idene)pyridine-2,6-dicarbohydrazide and one water mol­ecule are located on a twofold rotation axis. The mol­ecules are connected by hydrogen bonds. One dimethylformamide molecule is disordered over two positions; the site occupancy factors are ca 0.8 and 0.2

Boosting Oxygen Reduction at Pt(111)|Proton Exchange Ionomer Interfaces through Tuning the Microenvironment Water Activity

A proton exchange ionomer is one of the most important components in membrane electrode assemblies (MEAs) of polymer electrolyte membrane fuel cells (PEMFCs). It acts as both a proton conductor and a binder for nanocatalysts and carbon supports. The structure and the wetting conditions of the MEAs have a great impact on the microenvironment at the three-phase interphases in the MEAs, which can significantly influence the electrode kinetics such as the oxygen reduction reaction (ORR) at the cathode. Herein, by using the Pt(111)|X ionomer interface as a model system (X = Nafion, Aciplex, D72), we find that higher drying temperature lowers the onset potential for sulfonate adsorption and reduces apparent ORR current, while the current wave for OHad formation drops and shifts positively. Surprisingly, the intrinsic ORR activity is higher after properly correcting the blocking effect of Pt active sites by sulfonate adsorption and the poly(tetrafluoroethylene) (PTFE) skeleton. These results are well explained by the reduced water activity at the interfaces induced by the ionomer/PTFE, according to the mixed potential effect. Implications for how to prepare MEAs with improved ORR activity are provided.This work was supported by the National Natural Science Foundation of China (Nos. 21972131, 22372154). E.H. gratefully acknowledges the International Professorship by USTC and financial support from the Ministerio de Ciencia e Innovación (Project PID2022-137350NB-I00)

Understanding User Behavior in Volumetric Video Watching: Dataset, Analysis and Prediction

Volumetric video emerges as a new attractive video paradigm in recent years since it provides an immersive and interactive 3D viewing experience with six degree-of-freedom (DoF). Unlike traditional 2D or panoramic videos, volumetric videos require dense point clouds, voxels, meshes, or huge neural models to depict volumetric scenes, which results in a prohibitively high bandwidth burden for video delivery. Users' behavior analysis, especially the viewport and gaze analysis, then plays a significant role in prioritizing the content streaming within users' viewport and degrading the remaining content to maximize user QoE with limited bandwidth. Although understanding user behavior is crucial, to the best of our best knowledge, there are no available 3D volumetric video viewing datasets containing fine-grained user interactivity features, not to mention further analysis and behavior prediction. In this paper, we for the first time release a volumetric video viewing behavior dataset, with a large scale, multiple dimensions, and diverse conditions. We conduct an in-depth analysis to understand user behaviors when viewing volumetric videos. Interesting findings on user viewport, gaze, and motion preference related to different videos and users are revealed. We finally design a transformer-based viewport prediction model that fuses the features of both gaze and motion, which is able to achieve high accuracy at various conditions. Our prediction model is expected to further benefit volumetric video streaming optimization. Our dataset, along with the corresponding visualization tools is accessible at https://cuhksz-inml.github.io/user-behavior-in-vv-watching/Comment: Accepted by ACM MM'2

Net volatilization of PAHs from the North Pacific to the Arctic Ocean observed by passive sampling

The North Pacific-Arctic Oceans are important compartments for semi-volatile organic compounds’ (SVOCs) global marine inventory, but whether they act as a “source or sink” remains controversial. To study the air-sea exchange and fate of SVOCs during their poleward long-range transport, low-altitude atmosphere and surface seawater were measured for polycyclic aromatic hydrocarbons (PAHs) by passive sampling from July to September in 2014. Gaseous PAH concentrations (0.67–13 ng m−3) were dominated by phenanthrene (Phe) and fluorene (Flu), which displayed an inverse correlation with latitude, as well as a significant linear relationship with partial pressure and inverse temperature. Concentrations of PAHs in seawater (1.8–16 ng L−1) showed regional characteristics, with higher levels near the East Asia and lower values in the Bering Strait. The potential impact from the East Asian monsoon was suggested for gaseous PAHs, which – similar to PAHs in surface seawater - were derived from combustion sources. In addition, the data implied net volatilization of PAHs from seawater into the air along the entire cruise; fluxes displayed a similar pattern to regional and monthly distribution of PAHs in seawater. Our results further emphasized that air-sea exchange is an important process for PAHs in the open marine environments