The effect of extracellular polymeric substances on MICP solidifying rare earth slags and stabilizing Th and U.

Microbially induced carbonate precipitation (MICP) has been used to cure rare earth slags (RES) containing radionuclides (e.g. Th and U) and heavy metals with favorable results. However, the role of microbial extracellular polymeric substances (EPS) in MICP curing RES remains unclear. In this study, the EPS of Lysinibacillus sphaericus K-1 was extracted for the experiments of adsorption, inducing calcium carbonate (CaCO3) precipitation and curing of RES. The role of EPS in in MICP curing RES and stabilizing radionuclides and heavy metals was analyzed by evaluating the concentration and morphological distribution of radionuclides and heavy metals, and the compressive strength of the cured body. The results indicate that the adsorption efficiencies of EPS for Th (IV), U (VI), Cu2+, Pb2+, Zn2+, and Cd2+ were 44.83%, 45.83%, 53.7%, 61.3%, 42.1%, and 77.85%, respectively. The addition of EPS solution resulted in the formation of nanoscale spherical particles on the microorganism surface, which could act as an accumulating skeleton to facilitate the formation of CaCO3. After adding 20 mL of EPS solution during the curing process (Treat group), the maximum unconfined compressive strength (UCS) of the cured body reached 1.922 MPa, which was 12.13% higher than the CK group. The contents of exchangeable Th (IV) and U (VI) in the cured bodies of the Treat group decreased by 3.35% and 4.93%, respectively, compared with the CK group. Therefore, EPS enhances the effect of MICP curing RES and reduces the potential environmental problems that may be caused by radionuclides and heavy metals during the long-term sequestration of RES.

Selection of optimal models for predicting growth stress in Artemisia desertorum by comparison of linear regression and multiple neural networks: Take the construction of a green mine in the Bayan Obo mine as an example.

In recent years, more and more countries are focusing on the control of mining sites and the surrounding ecological environment, and the new environmental concept of green mines has been proposed. By investigating the ecological background of a mine site, pollution and ecological imbalances in the mine can be predicted, managed or transformed. This study investigated the effects of rare earth elements on plant growth in the Baotou Bayan Obo Rare Earth Mine and evaluated soil contamination and subsequent remediation through the measured plant height. Using linear regression, BP(Back Propagation) neural networks, GA-BP(Genetic Algorithm- Back Propagation) neural networks, ELM(Extreme Learning Machine) and GA-ELM(Genetic Algorithm- Extreme Learning Machine) model prediction instruments, the different rare earth solution concentrations were set as input values and the heights of Artemisia desertorum, which as the model plant, were set as output values in the prediction. The results showed that the linear regression predicted the standard error of single La(III), Ce(III) solution and compound La(III) + Ce(III) solution for Artemisia desertorum growth stress was on the high side, 7.02%- 8.92%; the efficiency range of each group of models under BP neural network, GA-BP neural network and ELM neural network were 1.15%- 2.53%, 0.85%- 1.28%, 1.76%- 3.53%; while the efficiency range under GA-ELM neural network was 0.59%- 0.68%, with average error values and predicted values close to the true values. Among them, the MAPE of GA-ELM neural network are significantly lower than other models, and the error decreases with increasing concentration of the compound solution. So GA-ELM neural network can be used as an efficient, fast and reasonable optimal model for predicting the growth stress of Artemisia desertorum in Bayan Obo mining area. The experimental results can provide a theoretical basis for assessing the risk of soil rare earth contamination in the area, evaluating the expectation of later remediation, and provide a degree of new ideas for the construction of green mines.

Coordination-driven self-assembly of a molecular figure-eight knot and other topologically complex architectures.

Over the past decades, molecular knots and links have captivated the chemical community due to their promising mimicry properties in molecular machines and biomolecules and are being realized with increasing frequency with small molecules. Herein, we describe how to utilize stacking interactions and hydrogen-bonding patterns to form trefoil knots, figure-eight knots and [2]catenanes. A transformation can occur between the unique trefoil knot and its isomeric boat-shaped tetranuclear macrocycle by the complementary concentration effect. Remarkably, the realization and authentication of the molecular figure-eight knot with four crossings fills the blank about 41 knot in knot tables. The [2]catenane topology is obtained because the selective naphthalenediimide (NDI)-based ligand, which can engender favorable aromatic donor-acceptor π interactions due to its planar, electron-deficient aromatic surface. The stacking interactions and hydrogen-bond interactions play important roles in these self-assembly processes. The advantages provide an avenue for the generation of structurally and topologically complex supramolecular architectures.