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The direct copolymerization of ethylene with polar monomers to produce functional polyolefins continues to be highly appealing due to its simple operation process and controllable product microstructure. Low-cost nickel catalysts have been extensively utilized in academia for the synthesis of polar polyethylenes. However, the development of high-temperature copolymerization catalysts suitable for industrial production conditions remains a significant challenge. Classified by the resultant copolymers, this review provides a comprehensive summary of the research progress in nickel complex catalyzed ethylene-polar monomer copolymerization at elevated temperatures in the past five years. The polymerization results of ethylene–methyl acrylate copolymers, ethylene-tert–butyl acrylate copolymers, ethylene–other fundamental polar monomer copolymers, and ethylene–special polar monomer copolymers are thoroughly summarized. The involved nickel catalysts include the phosphine-phenolate type, bisphosphine-monoxide type, phosphine-carbonyl type, phosphine-benzenamine type, and the phosphine-enolate type. The effective modulation of catalytic activity, molecular weight, molecular weight distribution, melting point, and polar monomer incorporation ratio by these catalysts is concluded and discussed. It reveals that the optimization of the catalyst system is mainly achieved through the methods of catalyst structure rational design, extra additive introduction, and single-site catalyst heterogenization. As a result, some outstanding catalysts are capable of producing polar polyethylenes that closely resemble commercial products. To achieve industrialization, it is essential to further emphasize the fundamental science of high-temperature copolymerization systems and the application performance of resultant polar polyethylenes. [ABSTRACT FROM AUTHOR]

Lysosome, the digestive organelle in eukaryotic cells, plays an important role in the degradation and recirculation of cellular products as well as in maintaining the stability of cellular metabolic microenvironment. Surface‐enhanced Raman scattering (SERS) is a molecular fingerprint technology with high detection sensitivity and photostability, suited for revealing various intracellular molecular information by inducing endocytosis of SERS‐active nanoparticles. However, it remains challenging to selectively extract the molecular information of specific organelles (e.g., lysosomes) from a high‐dimensional spectral set. Herein, we proposed a novel paradigm by combining label‐free SERS spectroscopy with confocal fluorescence imaging to investigate the digestion behavior of lysosomes in cells. The structural similarity algorithm was innovatively introduced and exhibited its effectiveness in screening out the wavenumbers in the SERS spectral set with high correlation with the metabolic behaviors of lysosomes. With comprehensive experiments on HeLa single cells, we captured the intracellular macromolecular digestion phenomenon and discovered the changing pattern of cellular SERS spectra after starvation‐induced autophagy, and analyzed the molecular information within the lysosomes in three‐dimensional space. [ABSTRACT FROM AUTHOR]

Simple Summary: The research of this paper can be applied in the compaction parameter prediction of soil-filling materials, which can significantly reduce the amount of laboratory work and improve the efficiency of optimizing design for soil resource utilization in engineering construction. Maximum Dry Density (MDD) and Optimum Moisture Content (OMC) are two important parameters of soil filling, which affect the soil stability and bearing capacity, and thus the reliability and durability of facilities such as highways and bridges. Therefore, it is important to make reasonable predictions of OMC and MDD. Four machine learning algorithms, namely, Support Vector Machine (SVM), Artificial Neural Network (ANN), Random Forest (RF), and Extreme Gradient Boosting Tree (XGBoost), are adopted in this paper to establish MDD and OMC prediction models. After training and testing, the best models of the four algorithms are compared. The results show that, as an ensemble learning algorithm, XGBoost is the best model for predicting MDD and OMC, with an R2 of 0.9234 for OMC, and an R2 of 0.9098 for MDD. Finally, the feature importance analysis concludes that the plastic limit (PL) and the liquid limit (LL) are the two features that affect OMC and MDD the most. The prediction of soil compaction parameters using machine learning models, especially ensemble learning, can significantly reduce the amount of laboratory work and improve the efficiency of optimizing design for soil resource utilization in engineering construction. [ABSTRACT FROM AUTHOR]

This study aims to optimize the sustainable utilization of excavated soil by incorporating it exclusively as a fine aggregate and cement in the formulation of soil-based controlled low-strength materials. The polycarboxylate superplasticizer was introduced to enhance flowability. Various factors, including the cement contents, initial water contents, and curing time, were systematically analyzed for their effects on the fresh properties, mechanical parameters, transverse relaxation time distribution, pore size distribution, porosity, and corrosivity of soil-based controlled low-strength materials. The results indicate that polycarboxylate superplasticizer effectively dispersed clay minerals and cement particles, enhancing the flowability. The unconfined compressive strength increased with the rising cement content and decreased with the increasing initial water content. Additionally, the transverse relaxation time distribution curves of the soil-based controlled low-strength materials exhibited two peaks. These curves shifted to smaller transverse relaxation time values with the increasing cement content, while gradually shifting to larger transverse relaxation time values with the increasing initial water content. An increase in the cement content resulted in higher volume percentages of small and mesopores, while extra-large pores and macropores decreased. The addition of the polycarboxylate superplasticizer had minimal impact on the pore volume percentage distribution. Furthermore, porosity experienced a decline with the rise in the cement content and curing time, in contrast to a notable increase with a higher initial water content. This investigation provides valuable insights into the engineering properties and microstructural characteristics of soil-based controlled low-strength materials, offering a foundation for sustainable waste management practices in geotechnical applications. [ABSTRACT FROM AUTHOR]

The emission of chlorinated pollutants is one of the main problems when recovering copper (Cu) via pyrolysis from waste enameled wires. This is mainly attributed to other wastes which possess high poly(vinyl chloride) content, such as electrical wires and cables, which are often recycled together with enameled copper wires. In this research, to control the chlorinated pollutants, copper(II) oxide (CuO) was chosen and demonstrated to be an efficient dechlorinating agent, and CuO did not introduce any impurities that influence the quality of the recovered Cu. The pyrolysis and co-pyrolysis of polyester enameled wires, PVC, and CuO were investigated, and special attention was paid to chlorinated compounds in released pyrolytic products. In particular, the co-pyrolysis of this ternary mixture was studied for the first time, and some new pyrolysis behaviors were discovered. For example, the results of Py-GC/MS analyses showed that the addition of CuO removed about 75% of the chloro-organic products, the main types of which were chloroaromatic compounds rather than the more toxic chloroesters. Moreover, pyrolysis gases were collected and characterized via ion chromatography, and the results showed that the chlorine content in the pyrolysis gases decreased by about 71%. TG analysis indicated that CuO only minimally affected the pyrolysis of polyester paint. However, through the chlorine fixation effect, CuO influenced the dechlorination and dehydrochlorination of PVC, as well as secondary reactions between HCl and pyrolysis products of polyester paint, therefore changing the products and behaviors of co-pyrolysis. Mechanism of reducing chlorine-containing pollutants and reaction mechanism of forming typical pyrolysis products closely correlated to the effects of CuO were also proposed, providing theoretical guidance for the recycling of waste enameled wires. [ABSTRACT FROM AUTHOR]