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The increase in industrial production can lead to more complex emissions of O3 precursors, but the changes in the formation mechanism and source of O3 are still unclear. Taking Jincheng as the typical industrial city, an observation-based model (OBM) is explored to analyze the changes in O3 formation in 2022 and 2024. The results indicated that the concentration of NOx and VOCs in 2024 increased by 21.1% and 22.3%, respectively. And the concentrations of alkenes related to industrial processes increased significantly. RO2+NO is the main pathway for O3 formation (51.5~54.2%), while VOCs+OH· contributes most to the formation of RO2. VOC and NOx both play important roles in O3 formation, and the sensitivity of VOCs increased from 0.76 to 0.84 in 2022 and 2024, with alkenes increasing the most. Industrial processes and coal combustion are the important sources for O3 and its precursors, and the contribution of the industrial process increased significantly during 2022 and 2024. In summary, the increase in the industrial activity level has led to the increase in alkenes, which has a key impact on the formation of O3. Controlling the emission of alkene from the industrial process is the direction for the continuous control of O3 pollution in industrial cities.

The authors have immobilized nanowires made from zirconium glycerolate (ZrGly) on magnetite (Fe 3 O 4 ) nanoparticles by applying a solvothermal growth process using metal-glycerolate as a precursor. The structure and the dissolution-recrystallization mechanism of the resulting Fe 3 O 4 @ZrGly composite were investigated by attenuated total reflection-FTIR, energy-dispersive X-ray analysis, thermogravimetric analysis and solid-state cross polarization/magic angle spinning 13 C NMR spectroscopy. The interaction between the zirconium glycerolate in Fe 3 O 4 @ZrGly and cis -diols leads to efficient adsorption of riboncleosides which then can be quantified by HPLC with UV detection. The sorbent was successfully applied to the selective enrichment of adenosine, cytidine, uridine and guanosine from spiked human urine samples. The detection limit of the method is in the range from 1.7 to 19 ng·mL −1 of nucleosides in spiked human urine, with relative standard deviations of lower than 12.4% and recoveries ranging from 90.6 to 113%. Graphical abstract Fe 3 O 4 @ZrGly with high selectivity towards ribonucleosides was designed and applied for quantitation of urinary ribonucleosides.

Despite the various synthesis methods to obtain carbon dots (CDs), the bottom‐up methods are still the most widely administrated route to afford large‐scale and low‐cost synthesis. However, as CDs are developed with increasing reports involved in producing many CDs, the structure and property features have changed enormously compared with the first generation of CDs, raising classification concerns. To this end, a new classification of CDs, named carbonized polymer dots (CPDs), is summarized according to the analysis of structure and property features. Here, CPDs are revealed as an emerging class of CDs with distinctive polymer/carbon hybrid structures and properties. Furthermore, deep insights into the effects of synthesis on the structure/property features of CDs are provided. Herein, the synthesis methods of CDs are also summarized in detail, and the effects of synthesis conditions of the bottom‐up methods in terms of the structures and properties of CPDs are discussed and analyzed comprehensively. Insights into formation process and nucleation mechanism of CPDs are also offered. Finally, a perspective of the future development of CDs is proposed with critical insights into facilitating their potential in various application fields. The classification of carbon dots (CDs) is improved and carbonized polymer dots (CPDs) are revealed with distinctive polymer/carbon hybrid structures and properties, as a new classification of CDs. The synthesis methods of CDs and effects of synthesis on the structures and properties of CPDs are discussed. Furthermore, insights are offered into the nucleation mechanism and the future development of CPDs.

Lamellar calcite veins are prevalent in carbonate-rich, lacustrine dark shale. The formation mechanisms of these veins have been extensively debated, focusing on factors such as timing, depth, material source, and driving forces. This paper examines dark lacustrine shale lamellar calcite veins in the Paleogene strata of Dongying Depression, using various analytical techniques: petrography, isotope geochemistry, cathodoluminescence, inclusion thermometry, and electron probe micro-analysis. Two distinct types of calcite veins have been identified: granular calcite veins and sparry calcite veins. These two types differ significantly in color, grain structure, morphology, and inclusions. Through further investigation, it was observed that vein generation occurred from the shallow burial period to the maturation of organic matter, with a transition from granular calcite veins to sparry calcite veins. The granular calcite veins exhibit characteristics associated with the shallow burial period, including plastically deformed laminae and veins, the development of strawberry pyrite, the absence of oil and gas, weak fractionation in oxygen isotopes, and their contact relationship with sparry calcite veins. These granular calcite veins were likely influenced by the reduction of sulfate bacteria. On the other hand, sparry calcite veins with fibrous grains are antitaxial and closely linked to the evolution and maturation of organic matter. They contain oil and gas inclusions and show a distribution range of homogenization temperature between 90 °C and 120 °C and strong fractionation in oxygen isotopes, indicating formation during the hydrocarbon expulsion period. The carbon isotope analysis of the surrounding rocks and veins suggests that the material for vein formation originates from the shale itself, specifically authigenic micritic calcite modified by the action of methanogens. The opening of horizontal fractures and vein formation is likely driven by fluid overpressure resulting from undercompaction and hydrocarbon expulsion. Veins may form rapidly or through multi-stage composite processes. Early veins are predominantly formed in situ, while late veins are a result of continuous fluid migration and convergence. Furthermore, the veins continue to undergo modification even after formation. This study emphasizes that the formation of lamellar calcite veins in shale is a complex diagenetic process influenced by multiple factors: biology, organic matter, and inorganic processes, all operating at various stages throughout the shale's diagenetic history.

Hundreds of members have been synthesized and versatile applications have been promised for endofullerenes (EFs) in the past 30 y. However, the formation mechanism of EFs is still a long-standing puzzle to chemists, especially the mechanism of embedding clusters into charged carbon cages. Here, based on synthesis and structures of two representative vanadium–scandium–carbido/carbide EFs, VSc₂C@Ih (7)-C80 and VSc₂C₂@Ih (7)-C80, a reasonable mechanism—C₁ implantation (a carbon atom is implanted into carbon cage)—is proposed to interpret the evolution from VSc₂C carbido to VSc₂C₂ carbide cluster. Supported by theoretical calculations together with crystallographic characterization, the single electron on vanadium (V) in VSc₂C@Ih (7)-C80 is proved to facilitate the C₁ implantation. While the V=C double bond is identified for VSc₂C@Ih (7)-C80, after C₁ implantation the distance between V and C atoms in VSc₂C₂@Ih (7)-C80 falls into the range of single bond lengths as previously shown in typical V-based organometallic complexes. This work exemplifies in situ self-driven implantation of an outer carbon atom into a charged carbon cage, which is different from previous heterogeneous implantation of nonmetal atoms (Group-V or -VIII atoms) driven by high-energy ion bombardment or high-pressure offline, and the proposed C₁ implantation mechanism represents a heretofore unknown metal–carbon cluster encapsulation mechanism and can be the fundamental basis for EF family genesis.

Multicolor emissive carbon dots (M-CDs) have tremendous potential applications in manifold fields of bioimaging, biomedicine and light-emitting devices. Until now, it is still difficult to produce fluorescence tunable CDs with high quantum yield across the entire visible spectra. In this work, a type of M-CDs with concentration-tunable fluorescence and solvent-affected aggregation states was synthesized by solvothermal treatment of citric acid (CA) and 1-(2-pyridylazo)-2-naphthol (PAN) and the formation mechanism was monitored by different reaction time and raw material ratio. The fluorescence spectra of M-CDs in organic solvents can range from 350 to 750 nm by adjusting the concentration. M-CDs possess different aggregation states in water and organic solvents, accompanied by different fluorescence emission, which is attributed to the different surface states of various component CDs in M-CDs. Moreover, the obtained products can be uniformly dispersed into polymethylmethacrylate (PMMA) solutions as well as epoxy resins to fabricate transparent CDs/PMMA films and CDs/epoxy composites, which can effectively prevent the aggregation and produce multicolor and white light-emitting diodes (WLED). In addition, the prepared WLED with Commission Internationale de L’Eclairage (CIE) of (0.29, 0.31) by using M-CDs/epoxy resin as packages, demonstrating the M-CDs exhibit potential applications for light-emitting devices.

Medium and high internal phase Pickering emulsions stabilized by cellulose nanocrystals (CNCs) have been prepared and the effects of CNC concentration and type of oil phase on the properties of emulsions were studied. The maximum oil phase volume that can be stabilized by CNCs is 87% when the CNC concentration is 0.6 wt.%; this slightly decreases to 83% when the CNC concentration is increased to 1.2 wt.% or higher. In addition, the oil droplets stabilized with 0.6 wt.% CNC suspensions have a larger size than those stabilized with higher concentration CNC suspensions. As evidenced by the change in oil droplet morphology and size, two different emulsion formation mechanisms are proposed. For a CNC concentration of 0.6 wt.%, the extra oil added into the emulsion is accommodated by the expansion of oil droplet size, whereas for CNC concentrations of 1.2 wt.% and higher, the oil is stabilized mainly by the formation of new oil droplets.

Iron oxides are chemical compounds which have different polymorphic forms, including γ-Fe2O3 (maghemite), Fe3O4 (magnetite), and FeO (wustite). Among them, the most studied are γ-Fe2O3 and Fe3O4, as they possess extraordinary properties at the nanoscale (such as super paramagnetism, high specific surface area, biocompatible etc.), because at this size scale, the quantum effects affect matter behavior and optical, electrical and magnetic properties. Therefore, in the nanoscale, these materials become ideal for surface functionalization and modification in various applications such as separation techniques, magnetic sorting (cells and other biomolecules etc.), drug delivery, cancer hyperthermia, sensing etc., and also for increased surface area-to-volume ratio, which allows for excellent dispersibility in the solution form. The current methods used are partially and passively mixed reactants, and, thus, every reaction has a different proportion of all factors which causes further difficulties in reproducibility. Direct active and complete mixing and automated approaches could be solutions to this size- and shape-controlled synthesis, playing a key role in its exploitation for scientific or technological purposes. An ideal synthesis method should be able to allow reliable adjustment of parameters and control over the following: fluctuation in temperature; pH, stirring rate; particle distribution; size control; concentration; and control over nanoparticle shape and composition i.e., crystallinity, purity, and rapid screening. Iron oxide nanoparticle (IONP)-based available clinical applications are RNA/DNA extraction and detection of infectious bacteria and viruses. Such technologies are important at POC (point of care) diagnosis. IONPs can play a key role in these perspectives. Although there are various methods for synthesis of IONPs, one of the most crucial goals is to control size and properties with high reproducibility to accomplish successful applications. Using multiple characterization techniques to identify and confirm the oxide phase of iron can provide better characterization capability. It is very important to understand the in-depth IONP formation mechanism, enabling better control over parameters and overall reaction and, by extension, properties of IONPs. This work provides an in-depth overview of different properties, synthesis methods, and mechanisms of iron oxide nanoparticles (IONPs) formation, and the diverse range of their applications. Different characterization factors and strategies to confirm phase purity in the IONP synthesis field are reviewed. First, properties of IONPs and various synthesis routes with their merits and demerits are described. We also describe different synthesis strategies and formation mechanisms for IONPs such as for: wustite (FeO), hematite (α-Fe2O3), maghemite (ɤ-Fe2O3) and magnetite (Fe3O4). We also describe characterization of these nanoparticles and various applications in detail. In conclusion, we present a detailed overview on the properties, size-controlled synthesis, formation mechanisms and applications of IONPs.

[Purpose/Significance] A thorough understanding of algorithm aversion among social media users, encompassing its manifestations and underlying causes, is crucial in the algorithmic era. This understanding serves as the cornerstone for accurately capturing users' information needs and preferences, which are constantly evolving due to technological advances and changes in societal behaviors. By studying how users perceive, interact with, and respond to algorithmic recommendations and personalizations, researchers can gain insight into the effectiveness and limitations of current algorithmic technologies. These insights are invaluable for improving and optimizing algorithms to ensure that they not only meet user expectations, but also enhance their overall experience and satisfaction. Moreover, understanding algorithm aversion can help design more ethical and transparent algorithms, foster trust between users and technology, and ultimately promote the sustainable development of the digital economy. In addition, this research has broader implications for the fields of human-computer interaction, artificial intelligence, and social media studies. By exploring the psychological, social, and cultural factors that influence users' attitudes and behaviors towards algorithms, researchers can contribute to the development of more user-centered and socially responsible technologies. This, in turn, can lead to more inclusive and equitable digital environments, where everyone can benefit from the advances of technology. [Method/Process] This study employed a qualitative research approach, which is well suited for exploring complex and nuanced phenomena such as algorithm aversion among social media users. Qualitative research allows for the collection of rich, detailed, and contextually embedded data, enabling a deeper understanding of the subject matter. To accomplish this, the study included in-depth interviews with 26 respondents, who were selected for their active use of social media and their diverse experiences and perspectives on algorithmic recommendations and personalizations. The interviews were conducted using a semi-structured format that allowed for flexibility in the conversation while still addressing key research questions and themes. This approach allowed the researchers to gain detailed insights into the participants' attitudes, beliefs, and experiences with algorithms, as well as their perceptions of the consequences of algorithm aversion. A rigorous coding process was used to analyze the collected data. This involved breaking down the textual data into smaller, manageable units, or codes, which were then categorized and grouped based on common themes and patterns. The coding analysis focused on three main areas: the expression of algorithm aversion, the formation mechanisms of algorithm aversion, and the consequences of algorithm aversion for social media users. Drawing on qualitative research paradigms, the analysis resulted in the construction of a theoretical model analysis framework specifically tailored to algorithm aversion among social media users. This framework provides a structured way to understand the complex interplay between users' attitudes, beliefs, and behaviors towards algorithms, and the factors that influence these attitudes and behaviors. The framework also highlights key consequences of algorithm aversion, such as reduced trust in social media platforms, decreased engagement with algorithmic recommendations, and potential negative impacts on user experience and satisfaction. [Results/Conclusions] The results reveal three distinct forms of algorithm aversion among social media users: algorithmic interruption, algorithmic complaint, and algorithmic evasion. These forms have significant implications for individuals, organizations, and society. Additionally, the study identifies personal factors, algorithmic technology factors, and social environment factors as key drivers of algorithm aversion. A comprehensive framework for analyzing the formation mechanism of algorithm aversion, based on the concept of \"individual-algorithm-social environment,\" is extracted. Based on this framework, the study proposes research paths and coping strategies from three perspectives: theoretical research, technical research, and humanistic research. These recommendations aim to effectively address and mitigate algorithm aversion among social media users.

The electron butterfly distribution, characterized by pitch angles (PA) primarily at 45° and 135°, was rarely observed in Earth's magnetotail. Here using the high‐resolution measurements from Magnetospheric Multiscale mission, we present the observation of electron butterfly distribution in a contracting dipolarization front (DF), and propose a new physical mechanism to explain its formation. Specifically, we discover that the electron butterfly distribution only exhibited in the locally contracted DF and was observed above 1.7 keV. We infer that local contraction of the DF transformed its configuration from a magnetic bottle to an hourglass‐shaped magnetic structure, and the butterfly distribution was formed by the magnetic mirror effect of this magnetic hourglass. Additionally, the theoretically estimated loss cone of the magnetic hourglass fits well with the observations of electrons, validating our inference about the formation mechanism. These findings can improve our understanding of electron dynamics in Earth's magnetosphere. Plain Language Summary Examining the pitch‐angle (PA) distribution of electrons can help us understand the electron dynamic process in space. In this paper, we present the observation of electron butterfly distribution, characterized by PA primarily around 45° and 135°, in Earth's magnetotail. We find that the electron butterfly distribution was observed only above 1.7 keV, and exhibited in a locally contracting dipolarization front (DF). We propose a new formation mechanism for this distribution, and perform the theoretical calculations to validate it. Our findings can significantly improve the knowledge of electron dynamics in Earth's magnetosphere. Key Points The electron butterfly distribution was observed above 1.7 keV and only exhibited in the contracted dipolarization front (DF) The local contraction of the DF transformed its configuration from a magnetic bottle to an hourglass‐shaped magnetic structure The butterfly distribution is formed by the magnetic mirror effect of the hourglass‐shaped structure