污泥基吸附剂对亚甲基蓝和环丙沙星的吸附性能研究

亚甲基蓝和环丙沙星是水体中2种污染物, 对生态环境有潜在危害. 本文以市政剩余活性污泥为原料, 氯化锌为活化剂热解制备污泥基吸附剂, 研究盐酸酸洗浓度、氯化锌浓度、热解温度、热解时间等对污泥基吸附剂吸附水中亚甲基蓝和环丙沙星性能的影响. 结果表明 (1)污泥基吸附剂对亚甲基蓝的吸附性能随盐酸酸洗浓度的增大而增加, 对环丙沙星的吸附性能则随盐酸酸洗浓度的增大呈先降后增趋势, 两者均在1.500mol·L-1盐酸浓度下取得最优值. (2)污泥基吸附剂对亚甲基蓝和环丙沙星的吸附性能随氯化锌浓度和热解温度的增加呈先升后降趋势, 在氯化锌浓度为4.0mol·L-1、热解温度为500℃时有最优值; 随着热解时间的延长, 污泥基吸附剂对亚甲基蓝和环丙沙星的吸附性能分别在500℃热解70min和80min时有最优值. (3)污泥基吸附剂的最佳制备条件为 氯化锌4.0mol·L-1活化2h、500℃热解70min和80min、1.500mol·L-1盐酸酸洗; 以此制得的污泥基吸附剂对亚甲基蓝和环丙沙星的去除率分别为97.7%和96.4%, 平衡吸附量分别为97.9mg·g-1和3.9mg·g-1, 且污泥基吸附剂对亚甲基蓝和环丙沙星的吸附过程均符合准二级动力学方程.     

New Palladium – ZrO2 Nano-Architectures from Thermal Transformation of UiO-66-NH2 for Carbonylative Suzuki and Hydrogenation Reactions

The new nanocomposites, Pd/C/ZrO₂, PdO/ZrO_2, and Pd/PdO/ZrO₂, were prepared by thermal conversion of Pd@UiO-66-Zr−NH₂ (MOF) in nitrogen or air atmosphere. The presence of Pd nanoparticles, uniformly distributed on the ZrO₂ or C/ZrO₂ matrix, was evidenced by transmission electron microscopy, scanning electron microscopy (SEM), Raman and X-ray Photoelectron Spectroscopy (XPS) methods. All pyrolysed composites retained the shape of the MOF template. They catalyze carbonylative Suzuki coupling under 1 atm CO with an efficiency significantly higher than the original Pd@UiO-66-Zr−NH₂. The most active PdO/ZrO₂ composite, formed benzophenone with TOF up to 1600 h⁻¹, while by using Pd@UiO-66-Zr−NH₂, much lower TOF values, 51–95 h⁻¹, were achieved. After the reaction, PdO/ZrO₂ was recovered with the same composition and catalytic activity. Very good results were also obtained in the transfer hydrogenation of benzophenones to alcohols with Pd/C/ZrO₂ and PdO/ZrO₂ catalysts under microwave irradiation.     

Influence of oxygen on soot formation during acetylene pyrolysis

Kinetic modeling of pyrolysis of acetylene diluted with argon showed a strong influence of small additives of oxygen on the routes of formation of soot nuclei. The influence of oxygen on various channels of formation and consumption of propargyl radicals C₃H₃, which are important precursors of soot formation, as well as the fundamental possibility of controlling the process of soot formation and its properties are considered.     

Fast Cysteine Bioconjugation Chemistry

Cysteine bioconjugation serves as a powerful tool in biological research and has been widely used for chemical modification of proteins, constructing antibody-drug conjugates, and enabling cell imaging studies. Cysteine conjugation reactions with fast kinetics and exquisite selectivity have been under heavy pursuit as they would allow clean protein modification with just stoichiometric amounts of reagents, which minimizes side reactions, simplifies purification and broadens functional group tolerance. In this concept, we summarize the recent advances in fast cysteine bioconjugation, and discuss the mechanism and chemical principles that underlie the high efficiencies of the newly developed cysteine reactive reagents.     

纳米线组装叶片状三氧化钼的合成及其对三乙胺的气敏性能

通过溶剂热法制备了由一维纳米线自组装的叶状三氧化钼纳米材料，借助X射线衍射（XRD）、场发射扫描电子显微镜（FESEM）、透射电子显微镜（TEM）、高分辨透射电镜（HRTEM）、紫外-可见漫反射光谱（UV-Vis DRS）、热重-示差扫描量热（TG-DSC）、氮气吸附（N₂-sorption）等技术对材料进行了系统的组成和结构表征。结果表明，一维纳米线表面具有粗糙结构，且由一维纳米线组装的叶片状三氧化钼属畸变八面体中的正交晶系，其主要暴露的结晶面是（021）。此叶片状三氧化钼气敏材料在300℃的最佳工作温度下，对2.25 g·m^-3的三乙胺表现出优异的选择性、超高的灵敏度和较快的响应时间（5 s），甚至在浓度为4.5 mg·m^-3的检测标准下响应值仍可达到12.4。基于以上结构表征和性能测试结果，对叶片状三氧化钼的形成及三乙胺敏感机理进行了初步探讨分析。     

铅基堆超临界CO2复合循环发电系统热力学分析

本文对比了再压缩超临界CO2 (S-CO2)循环、蒸汽朗肯循环、He布雷顿循环分别应用于铅基堆的最优热学性能,明确了S-CO2循环与铅基堆结合较传统循环的热力学优势。为进一步提高再压缩S-CO2循环的效率,以跨临界CO2 (T-CO2)循环为底循环构建了再压缩S-CO2/T-CO2复合循环,探讨了不同顶循环透平入口温度、压力和压缩机入口温度条件下系统性能的变化规律,对比了S-CO2/T-CO2复合循环和S-CO2循环的热学性能。结果表明:铅基堆再压缩S-CO2循环发电系统较传统循环形式具有更高的热效率;构建的S-CO2/T-CO2复合循环能够有效提高S-CO2循环的效率,在所研究参数范围内,S-CO2/T-CO2复合循环的热效率和效率比S-CO2循环分别最大可提高约4.8%和8.3%;再压缩S-CO2循环和S-CO2/T-CO2复合循环热学性能随顶循环关键参数变化规律具有一致性。     

Predicting polycyclic aromatic hydrocarbon formation with an automatically generated mechanism for acetylene pyrolysis

Using Reaction Mechanism Generator (RMG), we have automatically constructed a detailed mechanism for acetylene pyrolysis, which predicts formation of polycyclic aromatic hydrocarbons (PAHs) up to pyrene. To improve the data available for formation pathways from naphthalene to pyrene, new high‐pressure limit reaction rate coefficients and species thermochemistry were calculated using a combination of electronic structure data from the literature and new quantum calculations. Pressure‐dependent kinetics for the CH potential energy surface calculated by Zádor et al. were incorporated to ensure accurate pathways for acetylene initiation reactions. After adding these new data into the RMG database, a pressure‐dependent mechanism was generated in a single RMG simulation which captures chemistry from C to C. In general, the RMG‐generated model accurately predicts major species profiles in comparison to plug‐flow reactor data from the literature. The primary shortcoming of the model is that formation of anthracene, phenanthrene, and pyrene are underpredicted, and PAHs beyond pyrene are not captured. Reaction path analysis was performed for the RMG model to identify key pathways. Notable conclusions include the importance of accounting for the acetone impurity in acetylene in accurately predicting formation of odd‐carbon species, the remarkably low contribution of acetylene dimerization to vinylacetylene or diacetylene, and the dominance of the hydrogen abstraction CH addition (HACA) mechanism in the formation pathways to all PAH species in the model. This work demonstrates the improved ability of RMG to model PAH formation, while highlighting the need for more kinetics data for elementary reaction pathways to larger PAHs.     

A model for crack formation during active solid pyrolysis of a char-forming solid: crack patterns; surface area generation; volatile mass efflux

A model is developed for the formation and propagation of cracks in a material sample that is heated at its top surface, pyrolyses, and then thermally degrades to form char. In this work the sample is heated uniformly over its entire top surface by a hypothetical flame (a heat source). The pyrolysis mechanism is described by a one-step overall reaction that is dependent nonlinearly on the temperature (Arrhenius form). Stresses develop in response to the thermal degradation of the material by means of a shrinkage strain caused by local mass loss during pyrolysis. When the principal stress exceeds a prescribed threshold value, the material forms a local crack. Cracks are found to generally originate at the surface in response to heating, but occasionally they form in the bulk, away from ever-changing material boundaries. The resulting cracks evolve and form patterns whose characteristics are described. Quantities examined in detail are: the crack spacing in the pyrolysis zone; the crack length evolution; the formation and nature of crack loops which are defined as individual cracks that have joined to form loops that are disconnected from the remaining material; the formation of enhanced pyrolysis area; and the impact of all of the former quantities on mass flux. It is determined that the mass flux from the sample can be greatly enhanced over its nominal (non-cracking) counterpart. The mass efflux profile qualitatively resembles those observed in Cone Calorimeter tests.     

Review on the Use of Artificial Intelligence to Predict Fire Performance of Construction Materials and Their Flame Retardancy

The evaluation and interpretation of the behavior of construction materials under fire conditions have been complicated. Over the last few years, artificial intelligence (AI) has emerged as a reliable method to tackle this engineering problem. This review summarizes existing studies that applied AI to predict the fire performance of different construction materials (e.g., concrete, steel, timber, and composites). The prediction of the flame retardancy of some structural components such as beams, columns, slabs, and connections by utilizing AI-based models is also discussed. The end of this review offers insights on the advantages, existing challenges, and recommendations for the development of AI techniques used to evaluate the fire performance of construction materials and their flame retardancy. This review offers a comprehensive overview to researchers in the fields of fire engineering and material science, and it encourages them to explore and consider the use of AI in future research projects.