The regioselective hydrodifluoroalkylation of alkenes has been identified as a straightforward and highly atom-economical approach for synthesizing value-added difluoroalkylated molecules that have important applications in the pharmaceutical and agrochemical industries, as well as in the field of materials science. This is because olefins are structurally diverse raw materials that are inexpensive and easily obtainable from a wide range of sources. Recent years have witnessed significant progress in this field with the rapid development of visible-light catalysis and novel difluoroalkylating reagents. This article review summarizes the latest advances in the regioselective anti-Markovnikov and Markovnikov hydrodifluoroalkylation of various olefins, which provides an inspirational locale for researchers to engage. Herein, we supplement ideas for designing and developing new reactions, difluoroalkyl reagents, and catalytic strategies.
This work reports a one-step protocol for the synthesis of β-hydroxyamides via amino-carbonylation of epoxides using aromatic amines as the ammonia source instead of silylamine. The reaction was catalyzed by Co2(CO)8 modified with bidentate O-containing ligand L2, which was prepared by the oxidation of Xantphos [9,9-dimethyl-4,5-bis(diphenylphosphino)xanthene] by H2O2 as a diphosphine-dioxide. Under mild conditions (60 °C, CO 3.0 MPa, 6 h), L2-modified Co2(CO)8 efficiently catalyzed the amino-carbonylation of propylene oxide with aniline to generate 3-hydroxy-N-phenylbutanamide with the yield of 64%. The developed catalytic system exhibited fair stability and general substrate scope.
Pesticides are important tools to control crop diseases and pest hazards, guaranteeing the crop harvest. Natural products and their derivatives are major sources of novel pesticides and play indispensable roles in various fields, such as insecticide, fungicide, plant growth regulation, immune regulation and so on. In recent years, numerous fields of biotechnology have made great progress, like genomics, proteomics and structural biology. And thus, the identification of pesticide targets based on natural products and the creation of novel pesticide molecules based on target structures developed rapidly. The concept, rational design, received more attention in pesticide creation. In this article, the discovery of active natural products based on existed targets or novel targets verifying by natural products were demonstrated by several cases, and the subsequent progress in the development of new pesticides were also discussed. The cases explained the important role of natural products in bridging new targets and novel pesticides.
As the main component of greenhouse gases, CO2 represents an inexpensive and readily available renewable C1 synthon. In the past few decades, great efforts have been made toward the development of chemical processes that use CO2 as a promising fossil fuel alternative for C1 feedstocks for the production of industrially attractive chemicals. This could provide access to materials of commercial interest from an abundant, nontoxic, renewable, and low-cost carbon source, thus offering interesting opportunities for the chemical industry, organic synthesis, and so on. Considering the importance of chiral heterocycles in organic synthesis and drug development, the development of highly stereoselective and efficient catalytic asymmetric reactions using CO2 as a C1 synthon for these chiral heterocycles has received considerable attention. Successful examples for chiral lactones, carbonates, and carbamates have already been demonstrated. In this paper, we summarize the recent advances in this field.
This study developed a one-step spraying method using an aqueous solution of SiO2 particles to prepare SiO2/PET fabrics with saturated and uniform structural colors. The color brightness and uniformity were significantly improved by optimizing the treatment temperature, pH of the colloidal solution, and by introducing a small amount of ethanol. This method would promote the applications of structural colored fabrics because using water would reduce both environmental pollution and production cost.
As essential signaling molecules in biological systems, carbohydrates are involved in several vital physiological and pathological processes via specific recognition by receptors. Hence, nanomaterials comprising carbohydrates are crucial for deciphering and regulating biological processes. A non-covalent assembly process can conveniently yield carbohydrate-based nanomaterials owing to the unique merits of simplicity and controllability of the process. This review summarizes the construction and application of glyco-based functional materials through host-guest interactions and coordination-driven self-assembly processes. Additionally, their potential challenges and future directions are highlighted with the aim of improving understanding on carbohydrate-related physiological and pathological processes.
Sulfate ionic liquids, a new type of ionic liquid, are formed by the combination of sulfate anions and organic cations. Sulfate ionic liquids are important because of their unique characteristics, such as a lack of halogen ions, extremely low vapor pressure, high thermal stability, a high viscosity index, low isothermal compressibility, selective solubility, and good biocompatibility. In this paper, the recent progress in sulfate ionic liquids is reviewed, with focus on one-step and two-step synthetic methods. The physicochemical parameters, such as the density, viscosity, refractive index, surface tension, isothermal compression coefficient, and sound conduction, are summarized, and the effects of the physicochemical properties of sulfate ionic liquids, such as the length of the alkyl chains with anionic and cationic groups, are discussed. The sulfate ionic liquids discussed in this review could be used in various fields as new environmentally friendly solvents, extractants, catalysts, lubricating materials, gas absorption materials, and to separate or dope composite materials.
In this study, the electron-deficient pyridinium group and the naphthalene fluorophore were simultaneously introduced to a bipyridyl-containing Zr(Ⅳ) metal-organic framework (MOF) by the N-alkylation post-synthetic modification. The obtained ionic MOF, Zr-bpy-MNap, is nonluminous in the pristine state but shows selective fluorescence turn-on responses to some solvents and ammonia. Test papers were prepared using the MOF for the identification of solvents and detection of ammonia in air. The fluorescence turn-on response is considered to be due to complex host-guest interactions and solvation effects. The MOF is non-fluorescent due to the quenching effects of the host-guest communications between the bromide ion and the framework. On exposure to some solvents or ammonia, the quenching mechanisms are weakened or destroyed by the solvation of bromide or host-guest interactions between ammonia and the framework, resulting in fluorescence turn-on responses. The fluorescence originates from the charge-transfer transition between the naphthyl group and the electron-deficient framework.
The design of efficient and stable supported metal catalysts to prevent metal species from sintering into large nanoparticles under harsh preparation and reaction conditions is key for various important processes, including the conversion of C1 resources and dehydrogenation of low carbon alkanes to C2 and C3 olefins. Zeolites with uniform subnano micropores and various three-dimensional crystalline structures have been proven as ideal supports for preparing highly efficient and stable metal catalysts via encapsulating subnanometric metal clusters within their pores, cages, and channels. Interactions between metal clusters and the zeolite skeleton can regulate their geometric and electronic structure. The development of zeolite-confined subnanometric cluster catalysts aims to take advantage of this joint confinement effect and induce synergy between guest metal species and active sites in host zeolite frameworks. This can further improve the catalytic activity of resultant composite catalysts, for applications in multiple catalytic reaction processes . In this review, typical preparation methods of zeolite-confined subnanometric clusters and their catalytic applications in selective hydrogenation of CO2 and alkynes, hydrogen generation by formic acid decomposition and ammonia borane hydrolysis, and propane dehydrogenation to propene are discussed.
A promising chemical looping-oxidative coupling of methane (CL-OCM) oxygen-carrier catalyst, Na2WO4/Mn7SiO12-SiO2, was obtained by adding extra Mn2O3 to Mn2O3-Na2WO4/SiO2 and in-situ activating in the reaction stream. After experiencing an induction period, the oxygen-carrier phase transformed from Mn2O3 to Mn7SiO12 in association with an improvement in C2-C3 selectivity but decreased CH4 conversion. The Na2WO4/Mn7SiO12-SiO2 oxygen-carrier catalysts could also be obtained by directly calcining the Na2WO4/Mn2O3-SiO2 precursor at 800 ℃ in air. At 750 ℃ and a CH4 residence time of 12 s, the catalyst achieved 12% (or 7%) CH4 conversion and 81.5% (or 90.0%) C2-C3 selectivity using a mCat/mCH4 weight ratio of 27 (or 13.5). Notably, only C3H6 was detected as C3 products, whose selectivity was about 5%. The CL-OCM reaction proceeded selectively through the redox cycle mode of Mn7SiO12 $ \leftrightarrow $ [MnSiO3 + MnWO4]. The lattice-oxygen mobility in Mn7SiO12 was much weaker than that in Mn2O3, which improved C2-C3 selectivity but decreased CH4 conversion. Our findings provide guidance for the exploration of more advanced catalytic oxygen-carrier catalysts toward efficient CL-OCM process.
Methyl glyoxylate is widely used in organic synthesis and chemical production. The application of traditional preparation methods is limited by high cost, low efficiency, and significant environmental pollution. During the coal to ethylene glycol process, methyl glycolate is produced as an intermediate product of the hydrogenation of dimethyl oxalate (DMO) to ethylene glycol. Methyl glycolate can be selectively obtained from DMO via hydrogenation, and therefore, has the potential to serve as raw material for methyl glyoxylate. However, only few studies have considered this process. Herein , the applications, traditional preparation methods, and state-of-the-art research progress of methyl glycolate oxidation are reviewed. Recent research on selective oxidation of related alcohols (such as ethanol) to aldehydes and ketones is also summarized.
The selective hydrogenation of cinnamaldehyde is an important model reaction for investigating the relationship between catalyst structures and regioselectivity. In recent years, researchers have designed and synthesized a series of better-performing, supported Pt-based catalysts for the selective hydrogenation of cinnamaldehyde, based on electronic, synergistic, and geometric effects to improve the selectivity. In this mini-review, we aim to summarize the recent progress in different supported Pt-based catalysts for the selective hydrogenation of cinnamaldehyde and discuss the performance of these supported catalysts to provide ideas for the design of novel better-performing Pt-based catalysts.
To improve the catalytic performance of copper-based catalysts in the electroreduction of CO2, nitrotriacetic acid (NTA) was used as an additive to prepare copper-based catalysts having a three-dimensional structure by applying electrodeposition. The prepared catalysts exhibited excellent selectivity and activity for the electroreduction of CO2 to multi-carbon (C2+) products. At –1.26 V vs. RHE, the faradaic efficiency of C2H4 and C2+ products over the Cu-0.5/CP electrode reached 44.0% and 61.6%, respectively, and the total current density reached 12.3 mA·cm–2. In addition, Pd- and Zn-based catalysts were prepared by employing electrodeposition; the results showed that their selectivity for CO was significantly improved, proving that NTA has a certain universality in the preparation of electrocatalysts by using electrodeposition.
The efficient fixation and utilization of CO2 under mild conditions is one of the key components of green carbon science. The electrocatalytic coupling of CO2 and organic compounds can produce value-added chemicals, which is beneficial to sustainable development. In this review, we summarize the current methods of synthesizing carboxylic acids, organic carbonates, carbamates, and other chemicals via electrocatalytic CO2 coupling with organic compounds. We also present the latest research progress and opportunities in this field, such as asymmetric electrocarboxylation to construct chiral molecules, electrochemical ring-opening carboxylation, electrochemical N-methylation, electrocarboxylation with non-sacrificial anodes, and paired electrosynthesis.
To achieve the national strategy of carbon neutralization, the electroreduction of carbon dioxide into usable reagents via renewable energy has caused widespread concern in the scientific community. Cu-based electrocatalysts can reduce carbon dioxide to high value-added multi carbon products, but the catalytic mechanism still needs to be studied to improve its selectivity and efficiency. Depending on the state of the Cu, Cu-based catalysts can be divided into Cu alloy/composite catalysts, single-atom, oriented crystalline, and oxidized Cu-based catalysts. This paper introduced the common preparation methods, structural characteristics, effect of electro catalytic reduction of carbon dioxide, and possible catalytic mechanism of the four types of Cu-based catalysts mentioned above.
Bio-based 2,5-furandicarboxylic acid (FDCA) is expected to partially replace petroleum-based terephthalic acid (PTA) for the synthesis of high-performance polymer materials. This review article summarizes the latest achievements on the various synthesis routes of FDCA from 5-hydroxymethylfurfural (HMF), furoic acid, furan, diglycolic acid, hexaric acid, 2,5-dimethylfuran, and 2-methylfuran. In particular, the direct oxidation, heterogeneous thermal catalytic oxidation, photoelectric catalytic oxidation of HMF and furoic acid carboxylation, disproportionation, carbonylation, and other routes to synthesize FDCA are reviewed in detail. Based on the comparative analysis of the advantages and disadvantages of each route, the HMF route and the furoic acid route are considered the most promising candidates for the large-scale production of FDCA. Further exploration and future research should be carried out to improve the catalytic production and separation efficiency of FDCA, simplify the reaction process, and reduce production wastes.
Plastics are widely used in daily life owing to their light weight, portability, and affordability. However, post-consumer-waste plastics do not degrade easily in the natural environment, making plastic pollution a new global environmental issue. Thus, exploration in the field of plastic degradation has increased in recent years. To promote the treatment of plastic waste and provide a scientific reference for environmental protection and sustainable development, this study describes the current state of plastic pollution. It also systematically summarizes various research fields of plastic degradation and presents the development prospect of photocatalysis and bio-based plastics in the future.
The simple rule of base-pairing of nucleic acids enables nucleic acid structures to be designed via powerful energy-based prediction tools. Thus, nucleic acid structures have attracted considerable attention owing to their ability to fold into a variety of synthetic structures. However, the lack of chemical diversity of nucleic acid bases makes nucleic acid structures less functionally diverse than proteins, thereby limiting their practical applications. This review focuses on the underlying technology of nucleic acid molecular engineering, especially on the studies of nucleic acid structures and their molecular interactions. As nucleic acid structures are fully spatially addressable, a diversity of particles could be linked to designated positions on the surface of nucleic acid structures. Additionally, the intermolecular reaction kinetics of nucleic acids could be continuously fine-tuned by rational design of nucleic acid sequences. This review also summarizes the development of synthetic molecular networks, dynamic molecular machines, and nucleic acid-based biomaterials, as well as the application of these as green biomedical devices in biomolecular recognition, cell surface engineering, and biocatalysis.
Photothermal therapy has attracted attention as a novel cancer treatment with high specificity, minimal invasiveness, and low toxicity. In this study, a facile, effective, and green method was developed to prepare a novel supramolecular photothermal material. Grinding a commercial dye, dibenzotetrathiafulvalene (DBTTF, with absorption <400 nm) with cucurbit[8]uril (CB[8]) in air with a small amount of water leads to the oxidation of DBTTF to radical cations. Furthermore, DBTTF dimerizes, assembles into the cavity of CB[8], and forms a ternary supramolecular complex with strong absorption in the visible and near-infrared regions, where the longest absorption wavelength exceeds 1000 nm. The photothermal conversion efficiency of the supramolecular system is 18.7%. The system exhibits good photothermal stability and biocompatibility, and has been successfully applied in the photothermal ablation of live tumor cells. This supramolecular material has potential applications in photothermal therapy and other photothermal conversion fields.
A graph is called a two-degree graph if its vertices have only two distinct degrees. A two-degree tree of order at least three have two degrees, $ 1 $ and $ d $ for some $ d\geqslant 2; $ such a tree is called a $ (1,d) $ -tree. Given a positive integer $ n, $ we determine: (1) the possible values of $ d $ such that there exists a $ (1,d) $ -tree of order $ n; $ (2) the values of $ d $ such that there exists a unique $ (1,d) $ -tree of order $ n $ , and (3) the maximum diameter of two-degree trees of order $ n. $ The results provide a new example showing that the behavior of graphs may sometimes be determined by number theoretic properties.
In this paper, we consider the inverse problem of quadratic eigenvalue for a Hermitian R-antisymmetric matrix. By using the matrix block method, singular value decomposition, vector straightening, and the Moore-Penrose inverse, we prove the existence of a Hermitian R-antisymmetric solution. In addition, we provide the general expression for a Hermitian R-antisymmetric solution, and discuss the best approximation thereof. Finally, an example is offered to validate the theory.
In this paper, we introduce the notion of strongly Gorenstein weak flat modules, and we subsequently provide homological characterizations of strongly Gorenstein weak flat modules. It is shown that a Gorenstein weak flat module is a summand of a strongly Gorenstein weak flat module.
The complete convergence of sequences of random variables under sublinear expectation was studied. Using the properties of extended negatively dependent (ND) sequences, under the condition that the $ \lambda $ -order Choquet integrals of the random variable are finite, the complete convergence of the weighted sums for extended ND sequences under a sublinear expectation was proved. The results generalize and improve the results of independent sequences in the classical probability space.
The dynamical behavior of a class of second-order semilinear singularly perturbed Neumann boundary value problems with a turning point are studied. Firstly, we establish sufficient conditions for the exchange of stabilities near the turning point. By correcting the regularized equation of the degenerate problem, the accuracy of the asymptotic solution to the original problem is improved. Secondly, the Nagumo theorem is used to prove the existence of a smooth solution. Finally, a specific example is used to verify the validity of the results.
This paper considers a Neumann boundary value problem of a singularly perturbed delay reaction-diffusion equation with a nonlinear reactive term. By using the boundary layer function method, contrast structure theory, and contraction mapping principle, the asymptotic expansion of the solution is constructed, and the existence of a uniformly valid solution is proven. Finally, an example is presented to show the effectiveness of our result.
The precision (inverse covariance) matrix generated by the periodic vector autoregressive model is a sparse block tridiagonal matrix. Based on this precision matrix, a new block trace function is proposed for testing the equality of block traces of two precision matrices, the asymptotic behavior under the null hypothesis is investigated. Numerical experiments show that the proposed testing procedure has both appropriate size and good power.
In real-world scenarios, various events in the news are not only too nuanced and complex to distinguish, but also involve multiple entities. To address these problems, previous event-centric methods are designed to detect events first and then extract arguments, relying on imperfect performance for event trigger detection; this process, however, is unfit to deal with the sheer volume of news in the real world. Given that the performance of named entity recognition (NER) is satisfactory, we shift our perspective from an event-centric to a target-centric view. This paper proposes a new task: target-dependent event detection (TDED), which aims to extract target entities and detect their corresponding events. We also propose a semantic and syntactic aware approach to support thousands of target entity extractions first and subsequently the detection of dozens of event types; this approach can be applied to data from massive corporations. Experimental results on a real-world Chinese financial dataset demonstrated that our model outperformed previous methods, particularly in complex scenarios.
In the era of big data and with the continuous expansion of data, there are significant challenges with efficient access to data. Hence, designing an efficient index structure is of great significance. ALEX (updatable adaptive learned index) is a learned index that uses a machine learning model to replace the traditional B-tree index structure. Although it offers good time and space performance, it suffers from frequent page faults. In order to solve this problem and further improve the performance of ALEX, a memory pre-allocation strategy based on huge pages is proposed, on the basis of ALEX, that can help reduce the rate of memory page faults and improve the overall performance of ALEX. In the memory allocation phase, the pre-allocation strategy is adopted, and the memory free phase adopts a delayed release strategy. Experiments on the Longitudes dataset show that this strategy offers good performance.
Traditional virtual terrain modeling commonly uses a procedural generation method based on manual design, which cannot be used for competent simulation modeling tasks that need to restore real environments, such as in military applications. In this paper, we proposed a landscape simulation modeling method based on remote sensing images. The core of our proposed method is a landscape blended texture generation network (LBTG-Net); this method uses a blended texture generator (BTG) to generate landscape blended textures with the supervision of a style discriminator (SD) and multi-stage classification loss. Then, we procedurally build the complete virtual environment based on the blended texture generated by LBTG-Net. Our method has two main features: (1) accurate land-cover classification ability of remote sensing image inputs; and (2) high quality landscape blended texture outputs to guarantee virtual landscape modeling quality. We used multispectral image data from the Sentinel-2 satellite as the experimental dataset. The experimental results showed that our method offered high performance under mainstream land-cover classification evaluating indicators and can accurately reproduce the environmental distribution of input remote sensing images while completing high-quality virtual terrain simulation modeling.
In this paper, we propose a method for fast splicing of three-dimensional point clouds based on the lock pin model on a container terminal using high overlapping views. This experiment first uses an Azure Kinect depth camera to collect scene point clouds, and subsequently preprocesses the point cloud. The target point cloud is thus obtained. For lock pins with slightly different views, the sample consensus initial algorithm (SAC-IA) is used on the basis of the classic iterative closest point (ICP) algorithm to determine the overlapping position relationship of the two point clouds. In the overall splicing process, the relative size of the bounding box area projected by the lock pin in the z-direction of the camera is adopted to estimate the general shape of the lock pin; the relative size of the bounding box area is also used to select an appropriate number of point cloud views with high overlap in order to ensure the accuracy of registration and reduce processing time by comparing the difference between the area of adjacent views. The experimental results show that the proposed method has a lower relative registration error for the lock pin, and can quickly establish a workpiece model suitable for type matching.
The popularity of positioning devices has generated a large volume of vehicle driving data, making it possible to use historical data to predict the driving time of vehicles. Vehicle driving data consists of two parts: the sequence of road segments that the vehicle travels through, the departure time, the total length of the path, and other external information. The questions of how to extract sequence features in road segments and how to effectively fuse sequence features with external features become the key issues in predicting the travel time. To solve the aforementioned problems, a transformer-based travel time prediction model is proposed, which consists of two parts: a road segment sequence processing module and a feature fusion module. First, the road segment sequence processing module uses the self-attention mechanism to process the road segment sequence and extract the road segment sequence features. The model can not only fully consider the spatiotemporal correlation of road speeds between each road segment and other road segments, but also ensures the parallel input of data into the model, avoiding the low efficiency problem caused by sequential input of data when using recurrent neural networks. The feature fusion module fuses the road segment sequence features with external information, such as departure time, and obtains the predicted travel time. On this basis, the number of road segments connected by the intersection is determined by the upstream and downstream intersection features of the road segment, and the input model is combined with the road segment characteristics to further improve the prediction accuracy of the driving time. Comparative experiments with mainstream prediction methods on real data sets show that the model improves prediction accuracy and training speed, reflecting the effectiveness of the proposed method.
With the development of the Internet of Things, a large number of sensor devices can be connected to a network. Anomaly detection of data generated by these devices is related to the stability of system services. A time series database is a database system optimized for time series data. As an important component of a monitoring system, time series databases are responsible for storing and querying continuous streams of time series data. The current time series database, however, cannot fully utilize system computing resources and cannot meet the latency requirements when coping with queries from multiple data sources. To address these drawbacks, we redesigned the query execution model of a time series database based on the well-known InfluxDB, and we proposed InfluxDB-PP (parallel processing) as a method to address the aforementioned problems. The experimental results show that InfluxDB-PP reduces query latency by about 85.7% compared to InfluxDB for real-time anomaly data query scenarios.
With the continuous development of industrial intelligent inspection technology, the equipment element state recognition system based on digital image processing is widely used. In order to improve the accuracy of power distribution cabinet(PDC) equipment element state recognition in a distribution room, a ResNet(residual networks)-based equipment element state recognition method is proposed. Firstly, the data acquisition system is set up and the data set is constructed. Then, for the PDC image, the preset device component target area is cropped to generate the device component image. For device component images, a ResNet-based component state recognition model was constructed and trained, and the trained model was used to identify component states. Taking the data set for power distribution cabinet equipment element in substation distribution rooms as the research object, a network of single prediction heads is adopted as the component with complex features, and the network of multiple prediction heads is adopted as the component with simple features. Then, the compact and pruning model compression method is used to reduce the number of parameters and the calculation amount under the condition of less accuracy loss. Finally, the architecture design of the inspection system is introduced. A JetSon Nano edge terminal is used as the running hardware of the algorithm module to reduce the communication cost.
With the continuous development of China’s electric power system, the security and reliability of power supply directly affects regional production output and people’s economic life. As an important part of the power dispatch system, traditional fault locations rely on the cumulative experience and manual judgment of dispatchers. Faced with increasing demands, fault locations that rely solely on the traditional method are likely to result in an increase in misjudgment rates and pose a threat to the stable operation of the power system. This paper proposes a Boolean equation based on Kirchhoff’s law and the grid fault location algorithm to address this challenge. The fault location issue can effectively be converted to Boolean linear mixed programming problems and combined with simulated annealing algorithms. When these genetic algorithms are applied to the idea of a network and realized in the grid for fast positioning of small faults, the scheduling error rate can be reduced and the time difference from fault occurrence to fault isolation and fault processing can be shortened; in turn, this saves human resources and improves scheduling efficiency.
Cricket fighting is a traditional Chinese game that has lasted for more than 1000 years. Before competitions, Xishuai grass (stimulant grass) is commonly used to hit a cricket’s head and antennae to prepare the insects for battle. In “Flora of China” and flora of Chinese provinces, Xishuai grass is referenced as the Chinese common name of Eleusine indica (L.) Gaertn. In “Flora of Beijing” and “Flora of Hebei”, Xishuai grass is referenced as the Chinese common name of the genus Eleusine. In this paper, however, we demonstrate that Xishuai grass should actually be Digitaria spp. Given the mistakes in the above flora references, this paper aims to clarify the correct classification for future reference.
In this study, the MS2 phages were used as an indicator microorganism to test the function of seven disinfectants with different components: hydrogen peroxide, ethanol, fermented lactic acid disinfectant, iodine disinfectant, quaternary ammonium disinfectant, chlorine-containing disinfectant, and peracetic acid disinfectant. Our results showed that the virus disinfection rate varied notably between the selected disinfectants. The iodine disinfectant exhibited the strongest disinfection effect, followed by the quaternary ammonium salt disinfectant and the peracetic acid disinfectant, while the disinfection effects of hydrogen peroxide, ethanol, and fermentation lactic acid disinfectant were inadequate. The test results provide a reference for the efficient utilization of various disinfectants to eliminate harmful microorganisms in the environment.
Aluminum (Al) used for hydrogen generation and aqueous contaminant removal has been widely studied given its abundance and low redox potential; the reduction ability of Al, moreover, is restricted by the passive surface oxide film on Al particles. In addition to common Al surface treatment methods, such as acid/alkali washing, alloying, and mechanical ball-milling, Al surface modification technology arising in recent years has also been confirmed as an efficient Al activation method given its economical cost and benign manufacturing process. In this study, the merits and disadvantages of surface modification relative to other Al surface treatment methods were highlighted by reviewing existing research on the application of Al surface modification in hydrogen generation and aqueous contaminant removal. In addition, the paper presents an outlook on Al surface modification technology used for hydrogen generation and aqueous contaminant removal to promote the study of related processes.
The development of city-scale vegetation maps is helpful for vegetation management and conservation. Vegetation classification systems in China mainly consider natural vegetation and most classification systems operate at the national or provincial scale, making them unsuitable for city-scale classification. Until now, the lack of a classification system designed specifically for urban vegetation has limited the studies on urban vegetation. Based on the origin, disturbance, and function, our classification system divides urban vegetation into natural, secondary, and cultivated vegetations. Based on the function, cultivated vegetation is further divided into artificial forest land, landscape green land , and urban agricultural vegetations. Based on the Classification System of China’s Vegetation in 1980 and the three newly proposed preliminary guideline documents for classification of natural vegetation, we establish a new urban vegetation classification system. We applied the principles of this new urban system in Shanghai and other areas in China, to further refine the system and ensure it has both academic and practical values. This work provides the theoretical basis for compiling information about urban vegetation and provides technical support for the recognition, protection, construction, and management of urban vegetation.
中国综合性科技类核心期刊(北大核心)
