Search

Carbon capture and storage (CCS) and carbon capture and utilization (CCU) are two kinds of strategies to reduce the CO2 concentration in the atmosphere, which is emitted from the burning of fossil fuels and leads to the greenhouse effect. With the unique properties of ionic liquids (ILs), such as low vapor pressures, tunable structures, high solubilities, and high thermal and chemical stabilities, they could be used as solvents and catalysts for CO2 capture and conversion into value-added chemicals. In this critical review, we mainly focus our attention on the tuning IL-based catalysts for CO2 conversion into quinazoline-2,4(1H,3H)-diones from o-aminobenzonitriles during this decade (2012~2022). Due to the importance of basicity and nucleophilicity of catalysts, kinds of ILs with basic anions such as [OH], carboxylates, aprotic heterocyclic anions, etc., for conversion CO2 and o-aminobenzonitriles into quinazoline-2,4(1H,3H)-diones via different catalytic mechanisms, including amino preferential activation, CO2 preferential activation, and simultaneous amino and CO2 activation, are investigated systematically. Finally, future directions and prospects for CO2 conversion by IL-based catalysts are outlined. This review is benefit for academic researchers to obtain an overall understanding of the synthesis of quinazoline-2,4(1H,3H)-diones from CO2 and o-aminobenzonitriles by IL-based catalysts. This work will also open a door to develop novel IL-based catalysts for the conversion of other acid gases such as SO2 and H2S.

The study of the aerodynamics of a flight vehicle under Martian air conditions is experimentally difficult due to its characteristics such as low air density and temperature, making the vehicle operate at an ultra-low Reynolds number, which in turn introduces a complex flow field. In this paper, to find a proper computational fluid dynamics (CFD) method with which to better understand the aerodynamics of rotor-type aircraft under Martian air conditions, the aerodynamic performance of a rotor with rectangular blades under ultra-low density Martian air conditions is studied. A simulation scheme using a large eddy simulation solver and sliding meshing technology is established, and the method is verified based on experimental results from a Mars Air Simulator (MAS). In addition, the influence of the test bench and chamber is investigated through flow field analysis. The results show that the established method can predict lift in a very accurate manner, but that the torque prediction is not so promising. The study also determines that the fixture and the chamber wall of an MAS has little influence on the prediction of aerodynamic performance due to the quickly decreasing of flow speed and dissipation of vortexes. The test bench has about 5% influence on lift prediction, possibly due to the ground effect of the bench. In addition, simulation under actual Martian air conditions shows that the results agree well with the MAS experiment’s results, indicating that the temperature difference has little influence on the lift performance, and therefore that the MAS is a good tool for the lift prediction of Martian helicopters.

The heating and impact of arc and droplet acting on the weld pool lead to the transfer of mass, heat, and momentum, which affects the dynamic behavior of the weld pool and the microstructure in the P-GMAW process. In this paper, an image processing program is used to extract the dynamic behavior characteristics of the droplet transition and the weld pool in high-speed photography. The influence of the current waveform on the arc pressure and the impact of the droplet is quantitatively analyzed with different parameters. The dynamic behavior of the weld pool and the microstructure under different current waveform conditions are further studied. The internal relation of current waveform parameters to weld pool behavior and weld microstructure was expounded. The results show that the droplet impact is positively correlated with the pulse peak current. The rectangular wave pulse has a more significant droplet impact than the exponential wave with the same waveform parameters. The impact of droplet transition on the weld pool enhances the convective intensity of the weld pool. It slows down the cooling rate of the solidified weld microstructure below the tail of the weld pool, increasing the grain size of the weld microstructure.

Multichannel communication has great potential in environments with unknown interference patterns. However, existing link quality metrics and models are generally established and verified under a single-channel scenario, which does not consider the impacts of radio interference and channel change. Therefore, it is hard to directly judge whether these metrics and models are still valid under a multichannel scenario. This paper empirically analyzes the applicability of popular link quality metrics and models in multiple channels with different interference levels. Results show that the link quality estimation (LQE) capability of traditional metrics will be affected by the interference level of the channel, which makes the conclusions obtained under a single-channel scenario no longer valid. Meanwhile, traditional LQE models are basically not adaptive to radio interference and channel change. They are only valid for channels with similar interference under which they are modeled. If these models are directly used under a multichannel scenario, the link quality will be overestimated inevitably. In other words, traditional LQE metrics and models cannot be directly used in the multichannel scenario. It is necessary to deeply analyze the statistical characteristics of popular link quality metrics in multiple typical channels and design channel and interference adaptive metrics and models to support effective multichannel communication.

In this work, we designed and implemented a wearable body temperature monitoring device, which was constructed by a graphene-enhanced polydimethylsiloxane patch and a temperature measurement chip. The body temperature patch adopts a completely flexible solution in combination with near field communication component, which provides the advantages of passive wireless, overall flexibility, and being comfortable to wear. The whole device can be bent and stretched in conformal contact with skin. In order to improve the temperature conduction ability of the patch and make the patch data more accurate, we adopted graphene nanoplates to improve the thermal conductivity of polydimethylsiloxane patch with a significant thermal conductivity increase of 23.8%. With the combination of hollow sandwich structure and small dimension. it will reduce the uncomfortable situation of wearing the device for extended periods and can be served to monitor the human body temperature for a long time. Ultimately, this device is combined with a reading software for analyzing and processing on a smart mobile terminal. The real-time and past temperature range can be a pre-warning; meanwhile, the historical data can be traced and analyzed. Therefore, this device can be utilized in multiple human body temperature measurement scenarios and complex public health situations.

Salinization is considered a threat to agricultural soil and decreases crop yield worldwide. Nitrification and denitrification are the core processes of soil N-cycle. However, the response of nitrifiers and denitrifiers to salinity in agricultural soils remains ambiguous. The study aimed to explore the effect of salinity on nitrifiers and denitrifiers communities in agricultural soils along a naturally occurring salinity gradient. The effects of salinity on the abundance, composition, and interactions of nitrifiers and denitrifiers in surface soils were investigated. The abundance of nitrifiers significantly decreased in response to the increase in salinity. Ammonia-oxidizing archaea (AOA) were more susceptible to salinity elevation than ammonia-oxidizing bacteria (AOB). Nitrospira and Nitrobacter showed a similar trend to the salinity gradient, but the relative abundance of Nitrobacter was increased in the saline soils. High salinity decreased the abundance of napA and nirK, but had no significant effect on other marker genes for denitrification. Besides electrical conductivity, total sulfur (TS)+available potassium (AK) and TN+TS+C/N+total phosphorus (TP)+AK significantly explained the variation in denitrifier and nitrifier communities. We also found that high salinity decreased the connections between different N functional genes. These results implied the alteration of the nitrogen cycling community by high salinity mainly through decreasing AOA, NOB, and some denitrifiers with nitrate or nitrite reduction potentials and weakening the connectivity between nitrogen cycling drivers.

One of the main methods for link quality prediction is to predict the physical layer parameters first, and then evaluate the link quality based on the mapping models between such parameters and packet reception ratio (PRR). However, existing methods often ignore the temporal correlations of physical layer parameter series and rarely consider the influence of link fluctuations, which lead to more errors under moderate and sudden changed links with larger fluctuations. In view of these problems, this paper proposes a more effective link quality prediction method RNN-LQI, which adopts Recurrent Neural Network (RNN) to predict the Link Quality Indicator (LQI) series, and then evaluates the link quality according to the fitting model of LQI and PRR. This method accurately mines the inner relationship among LQI series with the help of short-term memory characteristics of RNN and effectively deals with link fluctuations by taking advantage of the higher resolution of LQI in the transitional region. Compared with similar methods, RNN-LQI proves to be better under different link qualities. Especially under moderate and sudden changed links with larger fluctuations, the prediction error reduces at least by 14.51% and 13.37%, respectively. Therefore, the proposed method is more suitable for low power wireless links with more fluctuations.