Behavior of uranium series in groundwater of the Wajid Formation, Wadi AdDawasir, Saudi Arabia

Neurocomputing Modelling of Hydrochemical and Physical Properties of Groundwater Coupled with Spatial Clustering, GIS, and Statistical Techniques

Groundwater (GW) is a critical freshwater resource for billions of individuals worldwide. Rapid anthropogenic exploitation has increasingly deteriorated GW quality and quantity. Reliable estimation of complex hydrochemical properties of GW is crucial for sustainable development. Real field and experimental studies in an agricultural area from the significant sandstone aquifers (Wajid Aquifer) were conducted. For the modelling purpose, three types of computational models, including the emerging Hammerstein–Wiener (HW), back propagation neural network (BPNN), and statistical multi-variate regression (MVR), were developed for the multi-station estimation of total dissolved solids (TDS) (mg/L) and total hardness (TH) (mg/L). A geographic information system (GIS) was used for the spatial variability assessment of 32 hydrochemical and physical properties of the GW aquifer. A comprehensive visualized literature review spanning several decades was conducted in order to gain an understanding of the existing research and debates relevant to a particular GW and artificial intelligence (AI) study. The experimental data, pre-processing, and feature selection were conducted to determine the most dominant variables for AI-based modelling. The estimation results were evaluated using determination coefficient (DC), mean bias error (MBE), mean square error (MSE), and root mean square error (RMSE). The outcomes proved that TDS (mg/L) and TH (mg/L) correlated more than 90% and 70–85% with Ca2+, Cl−, Br−, NO3−, and Fe, and Na+, SO42−, Mg2+, and F− combinations, respectively. HW-M1 justified promising among all the models with MBE = 1.41 × 10−11, 1.14 × 10−14, and MSE = 7.52 × 10−2, 3.88 × 10−11 for TDS (mg/L), TH (mg/L), respectively. The accuracy proved merit for the overall development of and practical estimation of hydrochemical variables (TDS, TH) (mg/L) and decision-making benchmarks.

Application Progress of Deinococcus radiodurans in Biological Treatment of Radioactive Uranium-Containing Wastewater

Radioactive uranium wastewater contains a large amount of radionuclide uranium and other heavy metal ions. The radioactive uranium wastewater discharged into the environment will not only pollute the natural environment, but also threat human health. Therefore, the treatment of radioactive uranium wastewater is a current research focus for many researchers. The treatment in radioactive uranium wastewater mainly includes physical, chemical and biological methods. At present, the using of biological treatment to treat uranium in radioactive uranium wastewater has been gradually shown its superiority and advantages. Deinococcus radiodurans is a famous microorganism with the most radiation resistant to ionizing radiation in the world, and can also resist various other extreme pressures. D. radiodurans can be directly used for the adsorption of uranium in radioactive waste water, and it can also transform other functional genes into D. radiodurans to construct genetically engineered bacteria, and then applied to the treatment of radioactive uranium containing wastewater. Radionuclides uranium in radioactive uranium-containing wastewater treated by D. radiodurans involves a lot of mechanisms. This article reviews currently the application of D. radiodurans that directly or construct genetically engineered bacteria in the treatment of radioactive uranium wastewater and discusses the mechanism of D. radiodurans in bioremediation of uranium. The application of constructing an engineered bacteria of D. radiodurans with powerful functions in uranium-containing wastewater is prospected.

Thin film nanocomposite membrane with triple-layer structure for enhanced water flux and antibacterial capacity

Triple-layered thin film composite (TFC) forward osmosis (FO) membranes prepared on interlayer-based supports have overcome the limitations of conventional porous substrates due to the formation of ultrathin and highly selective polyamide (PA) layers. However, mitigating the internal concentration polarization (ICP) and biofouling of TFC membranes remain a great challenge. Herein, we designed a novel triple-layered thin film nanocomposite (TFN) FO membrane with incorporation of silver (Ag) decorated graphene oxide quantum dots (GOQD) into PA layer via interfacial polymerization on a carbon nanotube (CNT) interlayer-based polyether sulfone substrate. By contrast with the TFC membranes, the newly developed GOQD/Ag incorporated triple-layered TFN membrane (TFN-GOQD/Ag) exhibited a great alleviation for ICP accompanied with a prominently enhanced water flux of 65.8 L·m^-2·h^-1 and decreased specific reverse salt flux of 1.4 g·m^-2·h^-1 by employing 1 M NaCl solution as draw solution. Moreover, the TFN-GOQD/Ag membrane possessed prominent antibacterial activity against both E. coli (99.8%) and S. aureus (97.3%). Noteworthy, the obtained TFN membrane demonstrated a controlled release of Ag⁺ along with long-term antibacterial potential and outstanding fouling resistance during the FO process. This work provides a new avenue to fabricate newly FO membranes with superior performance for water cleaning treatment.