Fine structure characterization of zero-valent iron nanoparticles for decontamination of nitrites and nitrates in wastewater and groundwater

The main objectives of the present study were to investigate the chemical reduction of nitrate or nitrite species by zero-valent iron nanoparticle (ZVIN) in aqueous solution and related reaction kinetics or mechanisms using fine structure characterization. This work also exemplifies the utilization of field emission-scanning electron microscope (FE–SEM), transmission electron microscopy (TEM), and x-ray diffraction (XRD) to reveal the speciation and possible reaction pathway in a very complex adsorption and redox reaction process. Experimentally, ZVIN of this study was prepared by sodium borohydride reduction method at room temperature and ambient pressure. The morphology of as-synthesized ZVIN shows that the nearly ball and ultrafine particles ranged of 20–50 nm were observed with FE–SEM or TEM analysis. The kinetic model of nitrites or nitrates reductive reaction by ZVIN is proposed as a pseudo first-order kinetic equation. The nitrite and nitrate removal efficiencies using ZVIN were found 65–83% and 51–68%, respectively, based on three different initial concentrations. Based on the XRD pattern analyses, it is found that the quantitative relationship between nitrite and Fe(III) or Fe(II) is similar to the one between nitrate and Fe(III) in the ZVIN study. The possible reason is due to the faster nitrite reduction by ZVIN. In fact, the occurrence of the relative faster nitrite reductive reaction suggested that the passivation of the ZVIN have a significant contribution to iron corrosion. The extended x-ray absorption fine structure (EXAFS) or x-ray absorption near edge structure (XANES) spectra show that the nitrites or nitrates reduce to N₂ or NH₃ while oxidizing the ZVIN to Fe₂O₃ or Fe₃O₄ electrochemically. It is also very clear that decontamination of nitrate or nitrite species in groundwater via the in-situ remediation with a ZVIN permeable reactive barrier would be environmentally attractive.     

4,5-二硝基咪唑的制备

以咪唑为原料,混酸为硝化剂,通氮气条件下,采用正加法、二次加料的方式:先滴加混酸(发烟硫酸20%和硝酸98%),硝化硫酸咪唑盐;再在反应液中滴加硝酸98%反应,合成出4,5-二硝基咪唑。对第二次反应所用的硝酸(98%)量、反应温度和反应时间进行了试验,得到了较佳的实验条件:第二次硝酸滴加量为1.6 mol(咪唑为1 mol),反应温度为90~95℃,反应时间为5~5.5 h。     

EDTA络合滴定法测定推进剂中铝含量

采用乙二胺四乙酸二钠(EDTA)络合-氟盐取代滴定法测定固体推进剂中的铝含量。向铝溶液中加入过量的EDTA溶液,使其与溶液中的铝离子完全络合,以二甲酚橙为指示剂,用铅的标准溶液回滴过量EDTA,加入氟化物并煮沸,释放出与铝等量的EDTA,再用铅的标准溶液滴定,由此计算铝的质量分数。该方法可用于分析火炸药、发射药、固体推进剂等中的铝含量,其相对标准偏差在0.1%~0.2%之间(n=6),准确度达98%以上。     

硝酸铯热分解性能研究

本文在TG-DTA分析的基础上,研究了硝酸铯的热分解特性,并且利用化学平衡计算软件CEA对硝酸铯在不同温度下热分解产生的自由电子密度和热分解需要的能量进行了计算,为利用硝酸铯作为增电子材料使用提供了理论依据.     

ADN/GUDN 双氧化剂对NEPE 固体推进剂燃烧性能的影响（英）

设计并制备了含N?脒基脲二硝酰胺盐（GUDN）和二硝酰胺铵（ADN）的硝酸酯增塑聚醚（ NEPE）固体推进剂样品,测试了推进剂的燃烧性能（燃速和压强指数）、燃烧火焰结构和燃烧波温度分布,并与不含GUDN和ADN的推进剂性能进行对比。结果表明,GUDN/ADN 双氧化剂对NEPE推进剂的燃烧性能有明显的影响,推进剂配方中添加ADN可提高推进剂的燃速和压强指数,含15%、20%和22.5%的ADN替换高氯酸铵（AP）可使推进剂在7.0MPa 下的燃速提高25.30%、36.76%和47.69%,GUDN使推进剂在7.0MPa下的燃速降低18.97% ,而压强指数在1~15MPa提高12.04%,而且在不同压力下含双氧化剂的NEPE推进剂的燃烧火焰结构呈多火焰结构,而且火焰的亮度随着压强的增大而变亮。     

分光光度法快速测定嘉陵江水体中硝酸盐氮

采用美国HACH公司最新推出的DR/5000紫外可见分光光度计,及其专用试剂测定水中硝酸盐氮含量。该法测定精密度好、灵敏度较高、准确度好,加标回收率近100%,操作简便、快速、试剂用量少。     

高温熔盐在太阳能热发电中的应用

高温熔盐蓄热技术是熔盐在新领域的又一应用,有着广阔的发展前景。本文介绍了高温熔盐的特性及常见熔盐的种类,比较其性能的优缺点,重点探讨了硝酸熔盐在太阳能热发电中的应用。通过实例的具体数据,对其应用的可行性进行了分析,结果表明硝酸熔盐更能减少发电系统成本,将是今后太阳能热发电中主要的蓄热和传热材料。     

Evaluation of nitrate removal effect on groundwater using artificial neural networks

Considering the non-linear,complex and multivariable process of biological denitrification,an activated sludge process was introduced to remove nitrate in groundwater with the aid of artificial neural networks (ANN) to evaluate the nitrate removal effect. The parameters such as COD,NH3-N,NO-3-N,NO-2-N,MLSS,DO,etc.,were used for input nodes,and COD,NH3-N,NO-3-N,NO-2-N were selected for output nodes. Experimental ANN training results show that ANN was able to predict the output water quality parameters very well. Most of relative errors of NO-3-N and COD were in the range of ±10% and ±5% respectively. The results predicted by ANN model of nitrate removal in groundwater produced good agreement with the experimental data. Though ANN model can optimize effect of the whole system,it cannot replace the water treatment process.     

钡盐改性常温锌钙系磷化液

通过扫描电镜及能谱仪(SEM EDS)扫描、氯化钠溶液腐蚀试验等方法研究了硝酸钡、SO24-对常温锌钙系磷化的影响。结果表明,磷化液中的SO24-会进入磷化膜,且不能通过水洗磷化膜清除,明显影响锌钙系磷化膜的性能,甚至引起磷化液报废;添加Ba2 ≤0.9g/L可有效除去磷化液中的SO24-;改变磷化膜的组成并提高磷化膜的耐蚀性能。