An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
The past decades have witnessed intensive research on the biological effects of graphene-based nanomaterials (GBNs) and the application of GBNs in different fields. The published literature shows that GBNs exhibit inhibitory effects on almost all microorganisms under pure culture conditions, and that this inhibitory effect is influenced by the microbial species, the GBN’s physicochemical properties, the GBN’s concentration, treatment time, and experimental surroundings. In addition, microorganisms exist in the soil in the form of microbial communities. Considering the complex interactions between different soil components, different microbial communities, and GBNs in the soil environment, the effects of GBNs on soil microbial communities are undoubtedly intertwined. Since bacteria and fungi are major players in terrestrial biogeochemistry, this review focuses on the antibacterial and antifungal performance of GBNs, their antimicrobial mechanisms and influencing factors, as well as the impact of this effect on soil microbial communities. This review will provide a better understanding of the effects of GBNs on microorganisms at both the individual and population scales, thus providing an ecologically safe reference for the release of GBNs to different soil environments.
A quantitative description of aerobic waste degradation is important in evaluating landfill waste stability and economic management. This research aimed to develop a coupling model to predict the degree of aerobic waste degradation. On the basis of the first-order kinetic equation and the law of conservation of mass, we first developed the coupling model of aerobic waste degradation that considered temperature, initial moisture content and air injection volume to simulate and predict the chemical oxygen demand in the leachate. Three different laboratory experiments on aerobic waste degradation were simulated to test the model applicability. Parameter sensitivity analyses were conducted to evaluate the reliability of parameters. The coupling model can simulate aerobic waste degradation, and the obtained simulation agreed with the corresponding results of the experiment. Comparison of the experiment and simulation demonstrated that the coupling model is a new approach to predict aerobic waste degradation and can be considered as the basis for selecting the economic air injection volume and appropriate management in the future.
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