摘要：
采用正交实验法优化制备Al-Fe-La除氟材料,研究按照不同Al/Fe/La摩尔比配制的除氟材料在不同水浴温度、不同pH值和不同结晶时间下的除氟性能,从而确定具备最佳除氟性能的Al-Fe-La金属复合氧化物制备方法.研究表明:所制备吸附剂的吸附效果受pH值的影响最大,受晶化时间的影响次之,受水浴温度和Al/Fe/La摩尔比的影响最小;其最佳吸附氟离子的实验条件组合为吸附剂配比浓度0.1 mol/L、水浴温度50℃、pH值10.5和晶化时间6 h.
摘要：
A metal-free environmentally-friendly and highly efficient photocatalyst is always desirable for photocatalytic remediation of antibiotic contamination. Herein, we firstly reported a novel g-C3N4/carbon dots nanosheets (C-CN-NS) nanocomposite photocatalyst which was prepared through a simple thermal oxidation etching process to remove a representative antibiotic sulfadiazine (SDZ). The degradation rate of SDZ by C-CN-NS500 (calcination temperature at 500 degrees C) was around 2.4 times larger than that of g-C3N4/carbon dots (C-CN) under visible light (lambda > 420 nm) irradiation. The valence band of C-CN-NS500 increased by 0.42 eV under the quantum confinement effect, which promoted the oxidation potential, in favor of the degradation of SDZ. Increased specific surface area, improved separation efficiency and prolonged contact time for C-CN-NS500 can also facilitate the degradation of SDZ. Experiments demonstrated that photo-induced hole (h(+)) has the strongest effect in photocatalytic degradation process, followed by O-center dot(2)-, and (OH)-O-center dot. The toxicity assessment showed that C-CN-NS500 nanocomposite has high biocompatibility and low toxicity. This work may provide a promising green photocatalyst for photocatalytic degradation of antibiotic contaminant.
摘要：
In recent years, water pollution has been attracted public attention being that its harm to human and ecology. Ferro-Manganese binary oxide (FMBO) with the characteristics of much active sites and high affinity to contaminants has been widely applied in wastewater treatment. This paper aims to review FMBO and its ramification, collectively named as FMBO-based materials to remove various pollutants from polluted water. Firstly, the synthesis methods of FMBO-based materials ware summarized and indicated that co-precipitation was the most common method. Secondly, the application of FMBO-based materials in water treatment was introduced emphatically. Thirdly, the influence factors refer to pH, coexisting ions and the physicochemical properties of FMBO-based materials ware also concluded. Moreover, the mechanisms including adsorption, redox and degradation were also discussed comprehensively and deeply. Finally, future researches on FMBO-based materials were also proposed such as toxicity of FMBO-based materials in practical environmental remediation, modifying potential waste by FMBO to realize the utilization of resources, composite catalytic system as to the synergistic mechanism, application in other refractory organic pollutants and application in soil remediation.
作者机构：
School of Architectural and Surveying and Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou, China;School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan, China;School of Municipal and Surveying Engineering, Hunan City University, Yiyang, China;Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Central South University, Changsha, China
摘要：
Parameters optimization is a research hotspot of SVM and has gained increasing interest from various research fields. Compared with other optimization algorithms, genetic-based evolutionary algorithms that have achieved optimization according to the laws of separation and free combination in genetics are gradually attracted much attention. Also, due to the characteristics of self-organization and self-adaptation, these algorithms often enable SVM to obtain appropriate parameters, so that the model can be applied to more applications. Additionally, many improvements have been proposed in the past two decades in order to allow the optimized SVM model to obtain better performance. This work focuses on reviewing the current state of genetic-based evolutionary algorithms used to optimize parameters of SVM and its variants. First, we introduce the principles of SVM and provide a survey on optimization methods of its parameters. Then we propose a taxonomy of improving genetic-based evolutionary algorithms according to code mechanism, parameters control, population structure, evolutionary strategy, operation mechanism, operators, and many other hybrid approaches. Furthermore, this paper analyzes and compares the advantages and disadvantages of the above algorithms explicitly, and provides their applicable scenarios as well. Finally, we highlight the existing problems of genetic-based evolutionary algorithms used for parameters optimization of SVM and prospect development trends of this field in the future.
摘要：
Zinc hydrometallurgy residue is one of the main sources of heavy metals in the environment. The chemical components and mineralogical characteristics of the reductive leaching residue was obtained by ICP-AES, XRD and SEM + EDS analysis. The results showed that the main heavy metals in the residue were Pb, Zn, Cd and As. Pb, Zn and Cd in the residue existed as PbSO4, ZnS and CdS, respectively. The three-step sequential extraction procedure study showed that Zn and Cd mainly existed as oxidizable form; Pb and As mainly existed as the residue form. The leaching toxicity results using sulfuric acid and nitric acid method showed that the leaching toxicity of Zn and Cd exceeded the reference values. The potential ecological risk assessment results of heavy metals of the residue showed that the sequence of the environmental activity and ecological risk was Cd > Zn > As > Pb. Cadmium contributed to the potential risk index more greatly than any other heavy metal in the residue and the contribution rate reached 98.9%, which showed that the cadmium in the reductive leaching residue threw the greatest threat to the ecological environment.
