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In the post epidemic era, the movement and distribution of pathogenic airflow and droplets produced by cough in the building space have been widely studied. Due to the limitations of research methods, there are few detailed research data on the temporal and spatial distribution of boundary conditions during cough, which is the basis of research and the key boundary conditions of computer simulation. Previous experiments have obtained cough airflow velocity distribution away from the mouth. This study aims to infer detailed data at mouth for CFD boundary conditions based on these experimental data. This is the first part of the research. Based on experiments, the types of parameters contained in the boundary conditions near the mouth during coughing are discussed. The main parameters are determined, including the maximum velocity of the mouth air flow, and the distribution function of the ejected air flow, among others, and the approximate value range. Different parameter combinations are used as boundary conditions for simulation, and with various combinations, database of conditions are obtained. Preliminary machine learning is performed on these databases, and boundary condition data consistent with experimental results are inferred. The study demonstrates that when the velocity distribution of the air flow at mouth satisfies the normal distribution function on the central vertical two-dimensional profile, the maximum velocity of the mouth air flow is 15m/s. Part 2 will use the complex neural network model to fit and infer more accurate boundary condition. The findings of this study can provide more accurate boundary conditions for simulating pathogenic airflow, as well as a supplementary database for epidemiological research.

In the post-epidemic era, the trajectory of pathogenic airflows and droplets generated by coughing have been widely studied. However, owing to the limitations of measurement methods, there is a lack of detailed data on their spatiotemporal distribution at the mouth during coughing, which are the basis of research and the critical boundary conditions for computational simulation. Previous experiments have determined the velocity distribution of coughing airflow in spaces located far from the mouth. This study aims to collect detailed data at the mouth for use as the Computational Fluid Dynamics (CFD) boundary conditions from the experimental data. In Part I of this study, the critical parameters that describe the boundary conditions at the mouth for CFD simulation were obtained. Based on these parameters, this part infers the detailed temporal and spatial distribution velocity data of the coughing airflow at the mouth using a neural network. We performed CFD simulation on the prediction results with V=10.76 and M=4, and got FAC2=0.56 compared with the experimental values. The results obtained provided a generic detailed boundary condition for coughing airflow at the mouth and appropriate machine-learning parameters. This study can provide more accurate boundary conditions for simulating the propagation of pathogenic airflow and a supplementary database for epidemic prevention research.

Molybdenum disulfide (MoS2), a typical two-dimensional transition metal dichalcogenides, is a promising candidate for electrochemical water splitting catalysis due to its ultrahigh special area and highly exposed active edge sites. The main challenges restricted the wider application for MoS2-based nanomaterials are the complex preparation process and the high overpotential. Here, we design a novel and facile sealed vessel to synthesize vertical oriented MoS2 nanosheets electrocatalyst with vast exposed edges. Benefiting from the unique vertically-oriented structural and compositional characteristics, the MoS2 nanosheets with 10-20 layers exhibits superior hydrogen evolution reaction (HER) performance with a small overpotential of 135.2 mV at a current density of 10 mA∙cm-2 and low Tafel slope of 82.5 mV∙dec-1 as well as extraordinary catalytic stability over 5000 cycles. Importantly, the sealed vessel reactor system may open up a versatile and potential synthetic way to construct various morphologies and structure of metal dichalcogenides for high-performance energy storage and conversions devices.

Arsenic is a kind of protoplasmic poison, which exists widely in the natural environment. Consuming too much arsenic can cause a number of health problems. Manganese oxide plays an important role in arsenic pollution removal technology. In this paper, arsenic hazard and its treatment methods and the application of manganese oxides in arsenic pollution treatment are summarized, and the prospect of research on arsenic pollution treatment by manganese oxides is put forward.

Soil heavy metal pollution is an important environmental problem threatening people’s health and sustainable economic development. Phytoremediation has become an important technology for the treatment of heavy metal contaminated soil with the characteristics of economy and environmental protection. This paper mainly analyzed the role of microbial community in heavy metal contaminated soil remediation process. Bacterias mainly strengthen the remediation effect of plants on heavy metal contaminated soil in two ways: first, bacterias have adsorption effect on heavy metals and reduce the toxicity of heavy metals to plants in soil; Two is to secrete organic acids and nutrients needed for plant growth to promote the absorption of heavy metals by hyperaccumulators.

As high theoretical capacity and excellent electrical conductivity, Co9S8 as a promising electrode material in lithium-ion batteries (LIBs) has attracted wide attention. In the present work, a simple vaporpressured induced route is developed for fabricating spherical-like Co9S8/N, S-codoped carbon nanocomposites (Co9S8/NSC), in which Co9S8 nanoparticles with an average size of 100 nm are encapsulated into N, S-codoped carbon matrix, by pyrolysis of mixture of cobalt isooctanoate dissolved into dimethylformamide and thiourea in a sealed vessel for the first time. As anode for LIBs, the Co9S8/NSC shows an excellent reversible capacity, a superior rate performance, and a long cycling stability. For example, a high capacity of 975.3 mA h g-1 can be achieved after 100 cycles at 0.1 A g-1. When cycled at 1 A g-1, it also maintains a high specific capacity of 791.5 mA h g-1 after 1000 cycles. Besides, it also shows a superior rate performance (329.8 mAh g-1 at 20 A g-1). Such superior performances may arise from its structural advantages that the smaller Co9S8 nanoparticles encapsulated into N, S-codoped carbon could enhance active sites, electrical conductivity, and structural stability.

Soil heavy metal pollution has become an environmental problem that has attracted worldwide attention. Nanomaterials have the advantages of large specific surface area, strong adsorption capacity and high reactivity, making nanomaterials remediation technology an excellent application prospect in contaminated soil remediation. This article introduces the main classification of nanomaterials, summarizes the mechanism of nanomaterials to remove heavy metals, and the combination technology of nanomaterials. It provides a scientific reference for the further development of this field.

In recent years, heavy metal pollution in soil has become a serious problem. Remediation technologies have been developed, such as physical remediation, chemical remediation, microbial remediation and other technologies. Among them, phytoremediation has been widely used in practice. In this paper, the present situation of heavy metal pollution in soil in China, the research progress of remediation technology of heavy metal contaminated soil and the remediation of heavy metal contaminated soil by hyperaccumulators are reviewed, to help with follow-up research in this area.