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The Chinese Loess Plateau has undergone extensive revegetation to restore degraded land and enhance carbon sequestration. However, soil organic carbon (SOC) sequestrated in the soil profiles of deep-rooted plants has not been fully studied. Here, we investigated the SOC within a 0–23 m profile in farmlands and apple orchards converted from farmlands with different ages (A5, <5 years; A10, ~10 years; A15, ~15 years; A20, >20 years) and the controlling factors on three loess tablelands (Changwu, Qingyang, and Luochuan). The results show that SOC stocks among farmlands and orchards showed no significant difference (p = 0.88); however, SOC stocks showed a trend with tree ages, i.e., a decrease for A5 and A10 but an increase for A15 and A20. For the vertical variability, the SOC stock was the highest within 0–1 m, regardless of the standing age; however, the SOC stock in this layer only accounted for 8.8% of the total SOC stock (97.93 ± 9.18 kg m−2). Climate accounted for 82% of the variations and controlled the changes in SOC in the 0–1 m range, while soil texture dominated the SOC in the soil below 1 m, accounting for 57% of the SOC variations. The variations in SOC in the thick, unsaturated zones provide implications for future land use management and the sustainability of apple orchards in arid regions. [ABSTRACT FROM AUTHOR]

With the rapid development of cloud storage and cloud computing technology, users tend to store data in the cloud for more convenient services. In order to ensure the integrity of cloud data, scholars have proposed cloud data integrity verification schemes to protect users' data security. The storage environment of the Internet of Things, in terms of big data and medical big data, demonstrates a stronger demand for data integrity verification schemes, but at the same time, the comprehensive function of data integrity verification schemes is required to be higher. Existing data integrity verification schemes are mostly applied in the cloud storage environment but cannot successfully be applied to the environment of the Internet of Things in the context of big data storage and medical big data storage. To solve this problem when combined with the characteristics and requirements of Internet of Things data storage and medical data storage, we designed an SM2-based offline/online efficient data integrity verification scheme. The resulting scheme uses the SM4 block cryptography algorithm to protect the privacy of the data content and uses a dynamic hash table to realize the dynamic updating of data. Based on the SM2 signature algorithm, the scheme can also realize offline tag generation and batch audits, reducing the computational burden of users. In security proof and efficiency analysis, the scheme has proven to be safe and efficient and can be used in a variety of application scenarios. [ABSTRACT FROM AUTHOR]

In recent years, the development of computer technology has promoted the informatization and intelligentization of hospital management systems and thus produced a large amount of medical data. These medical data are valuable resources for research. We can obtain inducers and unknown symptoms that can help discover diseases and make earlier diagnoses. Hypertensive disorder in pregnancy (HDP) is a common obstetric complication in pregnant women, which has severe adverse effects on the life safety of pregnant women and fetuses. However, the early and mid-term symptoms of HDP are not obvious, and there is no effective solution for it except for terminating the pregnancy. Therefore, detecting and preventing HDP is of great importance. This study aims at the preprocessing of pregnancy examination data, which serves as a part of HDP prediction. We found that the problem of missing data has a large impact on HDP prediction. Unlike general data, pregnancy examination data have high dimension and a high missing rate, are in a time series, and often have many non-linear relations. Current methods are not able to process the data effectively. To this end, we propose an improved bi-LSTM-based missing value imputation approach. It combines traditional machine learning and bidirectional LSTM to deal with missing data of pregnancy examination data. Our missing value imputation method obtains a good effect and improves the accuracy of the later prediction of HDP using examination data. [ABSTRACT FROM AUTHOR]

Designing the electronic structures of the van der Waals (vdW) heterostructures to obtain high-efficiency solar cells showed a fascinating prospect. In this work, we screened the potential of vdW heterostructures for solar cell application by combining the group III–VI MXA (M = Al, Ga, In and XA = S, Se, Te) and elementary group VI XB (XB = Se, Te) monolayers based on first-principle calculations. The results highlight that InSe/Te vdW heterostructure presents type-II electronic band structure feature with a band gap of 0.88 eV, where tellurene and InSe monolayer are as absorber and window layer, respectively. Interestingly, tellurene has a 1.14 eV direct band gap to produce the photoexcited electron easily. Furthermore, InSe/Te vdW heterostructure shows remarkably light absorption capacities and distinguished maximum power conversion efficiency (PCE) up to 13.39%. Our present study will inspire researchers to design vdW heterostructures for solar cell application in a purposeful way. [ABSTRACT FROM AUTHOR]

CNT-AlSi10Mg composites fabricated by SLM have drawn a lot attention in structural application due to its excellent strength, elasticity and thermal conductivities. A planetary ball milling method was used to prepare the carbon nanotube (CNT)-AlSi10Mg powders, and the CNT-AlSi10Mg composites were fabricated by selective laser melting (SLM). The density, microstructure and mechanical properties of CNT-AlSi10Mg composites were studied. The density of the test samples increased at first and then decreased with increasing scan speed. When the laser scan speed was 800 mm/s, the test sample exhibited the highest density. The hardness increased by approximately 26%, and the tensile strength increased by approximately 13% compared to those values exhibited by the unreinforced AlSi10Mg. The grains of CNT-AlSi10Mg composite are finer than that in the AlSi10Mg. The CNTs were distributed along the grain boundaries of AlSi10Mg. Some of the CNTs reacted with Al element and transformed into Al4C3 during SLM, while some of the CNTs still maintained their tubular structure. The combination of CNTs and Al4C3 has a significant improvement in mechanical properties of the composites through fine grain strengthening, second phase strengthening, and load transfer strengthening. [ABSTRACT FROM AUTHOR]

A composite coating with enhanced mechanical properties including high hardness and excellent wear resistance was produced by laser cladding of mixed Ni45 and high-carbon ferrochrome powders on an ASTM 1045 steel substrate. Different quantities, ranging from 10 to 50 wt.% of high-carbon ferrochrome powder were added to the Ni45 powder to investigate the effect of mixture content on the cladding performance. The microstructure of the coatings were examined using scanning electron microscope, and the wear resistance was compared using a wear tester apparatus among the different cases. The results showed that the microstructure of the coating with 30 wt.% high-carbon ferrochrome content was mainly fine solid solution phase. With the increase of high-carbon ferrochrome content to 40 wt.% and above, cracks appeared on the cladding surface due to a large amount of chromium carbides formed during the process. The microhardness was enhanced remarkably by laser cladding the composite coating on the 1045 substrate, with 2.4 times higher than the hardness of the substrate when 30 wt.% high-carbon ferrochrome content was added. The best wear performance was achieved when the high-carbon ferrochrome content was 30 wt.%, demonstrating the smallest surface roughness and depth of wear marks. With further increased high-carbon ferrochrome content, microcracking and delamination were observed on the worn surfaces. [ABSTRACT FROM AUTHOR]

Local patch-based methods of object detection and pose estimation are promising. However, to the best of the authors' knowledge, traditional red-green-blue and depth (RGB-D) patches contain scene interference (foreground occlusion and background clutter) and have little rotation invariance. To solve these problems, a new edge patch is proposed and experimented with in this study. The edge patch is a local sampling RGB-D patch centered at the edge pixel of the depth image. According to the normal direction of the depth edge, the edge patch is sampled along a canonical orientation, making it rotation invariant. Through a process of depth detection, scene interference is eliminated from the edge patch, which improves the robustness. The framework of the edge patch-based method is described, and the method was evaluated on three public datasets. Compared with existing methods, the proposed method achieved a higher average F1-score (0.956) on the Tejani dataset and a better average detection rate (62%) on the Occlusion dataset, even in situations of serious scene interference. These results showed that the proposed method has higher detection accuracy and stronger robustness. [ABSTRACT FROM AUTHOR]

To autonomously move and operate objects in cluttered indoor environments, a service robot requires the ability of 3D scene perception. Though 3D object detection can provide an object-level environmental description to fill this gap, a robot always encounters incomplete object observation, recurring detections of the same object, error in detection, or intersection between objects when conducting detection continuously in a cluttered room. To solve these problems, we propose a two-stage 3D object detection algorithm which is to fuse multiple views of 3D object point clouds in the first stage and to eliminate unreasonable and intersection detections in the second stage. For each view, the robot performs a 2D object semantic segmentation and obtains 3D object point clouds. Then, an unsupervised segmentation method called Locally Convex Connected Patches (LCCP) is utilized to segment the object accurately from the background. Subsequently, the Manhattan Frame estimation is implemented to calculate the main orientation of the object and subsequently, the 3D object bounding box can be obtained. To deal with the detected objects in multiple views, we construct an object database and propose an object fusion criterion to maintain it automatically. Thus, the same object observed in multi-view is fused together and a more accurate bounding box can be calculated. Finally, we propose an object filtering approach based on prior knowledge to remove incorrect and intersecting objects in the object dataset. Experiments are carried out on both SceneNN dataset and a real indoor environment to verify the stability and accuracy of 3D semantic segmentation and bounding box detection of the object with multi-view fusion. [ABSTRACT FROM AUTHOR]

Changes in the elasticity modulus of an epoxy molding compound (EMC), an electronic packaging polymer, under high-temperature air storage conditions, are discussed in this study. The elasticity modulus of EMC had two different compositions (different filling contents) under different temperatures (175, 200, and 225 °C) and aging times (100, 500, and 1500 h), which were analyzed by using dynamic mechanic analysis technology. The results revealed that the elasticity modulus increased in the thermal aging process, with an increase in the temperature and the aging time. The increments of the glassy and rubbery states were similar. However, the growing rate was significantly different, and the growth of the rubbery state was significantly higher than that of the glassy state. The filling content influenced the degree of aging of the materials significantly. At a low filling content, long-term aging under high temperatures completely changed the material structure, and the mechanical properties of the polymer were reduced. [ABSTRACT FROM AUTHOR]

Environmental perception is a vital feature for service robots when working in an indoor environment for a long time. The general 3D reconstruction is a low-level geometric information description that cannot convey semantics. In contrast, higher level perception similar to humans requires more abstract concepts, such as objects and scenes. Moreover, the 2D object detection based on images always fails to provide the actual position and size of an object, which is quite important for a robot's operation. In this paper, we focus on the 3D object detection to regress the object's category, 3D size, and spatial position through a convolutional neural network (CNN). We propose a multi-channel CNN for 3D object detection, which fuses three input channels including RGB, depth, and bird's eye view (BEV) images. We also propose a method to generate 3D proposals based on 2D ones in the RGB image and semantic prior. Training and test are conducted on the modified NYU V2 dataset and SUN RGB-D dataset in order to verify the effectiveness of the algorithm. We also carry out the actual experiments in a service robot to utilize the proposed 3D object detection method to enhance the environmental perception of the robot. [ABSTRACT FROM AUTHOR]

A feasible approach was developed for the synthesis of ordered mesoporous SBA-15-type materials using coal fly ash (CFA) as raw material. In the proposed approach, CFA was, firstly, activated by subcritical water with the addition of NaOH, which allowed an efficient extraction of silicon species from CFA under strong acidic conditions at near room temperature. Subsequently, in the synthesis system, using silicon extraction solution as the silicon precursor, the introduction of anhydrous ethanol as a co-solvent effectively inhibited the polymerization of silanol species and promoted their collaborative self-assembly with surfactant molecules by enhancing the hydrogen bond interactions. The resultant SBA-15 material had a high purity, high specific surface area (1014 m2/g) and pore volume (1.08 cm3/g), and a highly ordered mesostructure, and, therefore, exhibited an excellent removal efficiency (90.5%) and adsorption capacity (160.8 mg/g) for methylene blue (MB) from simulated wastewater. Additionally, the generation of surface acid sites from the homogenous incorporation of Al atoms onto the mesoporous walls of SBA-15 combined with the perfect retention of the ordered mesostructure endowed the obtained Al-SBA-15 material with a further boost in the removal performance of MB. The MB removal efficiency can reach ~100%, along with a maximum adsorption capacity of 190.1 mg/g. [ABSTRACT FROM AUTHOR]

Three ground-based radars in the Pearl River Delta successfully observed Typhoon Higos (2020), which traveled over the offshore area in the South China Sea. During the observation period, the stratiform region of the outer rainband of HIGOS became active while swirling inward, merging into an unclosed eyewall and spreading outward, but its structure was asymmetric between upwind and downwind. To understand the dynamic mechanism of the asymmetry of the stratiform region in detail, the refined wind speed distributions in the inner core of Higos was retrieved by using the radar observation data and a three-dimensional, variational, direct, data assimilation, Dual-Doppler analysis (DDA). In addition, an Observing System Simulation Experiment (OSSE) was conducted with the numerical simulations by the Weather Research and Forecasting (WRF) model and numerical emulations by Cloud Resolving Model Radar SIMulator (CR-SIM) software to validate the retrieved data. From the OSSE, the emulated retrieved data were comparable with the WRF-out data. The analysis shows that the dynamic mechanisms are different between upwind and downwind in the stratiform rainband. In the former, the inflow sinks in the middle troposphere. In addition, there is an inflow in the lower troposphere, with an outflow aloft the inflow. In the latter, however, the stratiform rainband is primarily influenced by outflow from inside the rainband and inflow from outside the monsoon-related southwesterly winds. The vertical velocity characteristics in the stratiform rainband downwind also differ from those upwind. The upwind updraft was distinct in the middle troposphere, whereas the downwind updraft was caused by the convergence of the outflow from inside the stratiform rainband and the monsoon-related southwesterly inflow in the lower troposphere. [ABSTRACT FROM AUTHOR]

To reveal the influence of acid sites with different spatial locations of USY zeolite with different micro-/mesoporous structures and Si/Al ratio, catalytic cracking of methylcyclohexane on the zeolites is employed to study the synergism effects of acid sites and porous structures ("active region") in the hierarchical USY zeolites. The results showed that the hierarchical USY zeolites have increased numbers of accessibly strong Brønsted acid sites and greatly enhanced diffusion ability due to the hierarchical pore-structure, resulting in mainly monomolecular protolytic scission in cracking reactions and less bimolecular hydrogen transfer. The isomerization reaction is from intramolecular transalkylation and the isomerics are the intermediates of the cracking reaction. The protolytic cracking that occurs in hierarchical high-silica USY-zeolites follows the Haag-Dessau cracking. [ABSTRACT FROM AUTHOR]

The traditional CNN for 6D robot relocalization which outputs pose estimations does not interpret whether the model is making sensible predictions or just guessing at random. We found that convnet representations trained on classification problems generalize well to other tasks. Thus, we propose a multi-task CNN for robot relocalization, which can simultaneously perform pose regression and scene recognition. Scene recognition determines whether the input image belongs to the current scene in which the robot is located, not only reducing the error of relocalization but also making us understand with what confidence we can trust the prediction. Meanwhile, we found that when there is a large visual difference between testing images and training images, the pose precision becomes low. Based on this, we present the dual-level image-similarity strategy (DLISS), which consists of two levels: initial level and iteration-level. The initial level performs feature vector clustering in the training set and feature vector acquisition in testing images. The iteration level, namely, the PSO-based image-block selection algorithm, can select the testing images which are the most similar to training images based on the initial level, enabling us to gain higher pose accuracy in testing set. Our method considers both the accuracy and the robustness of relocalization, and it can operate indoors and outdoors in real time, taking at most 27 ms per frame to compute. Finally, we used the Microsoft 7Scenes dataset and the Cambridge Landmarks dataset to evaluate our method. It can obtain approximately 0.33 m and 7.51 ∘ accuracy on 7Scenes dataset, and get approximately 1.44 m and 4.83 ∘ accuracy on the Cambridge Landmarks dataset. Compared with PoseNet, our CNN reduced the average positional error by 25% and the average angular error by 27.79% on 7Scenes dataset, and reduced the average positional error by 40% and the average angular error by 28.55% on the Cambridge Landmarks dataset. We show that our multi-task CNN can localize from high-level features and is robust to images which are not in the current scene. Furthermore, we show that our multi-task CNN gets higher accuracy of relocalization by using testing images obtained by DLISS. [ABSTRACT FROM AUTHOR]

Hierarchically porous ZSM-5 was prepared by utilizing a two-step crystallization procedure with carbon–silica composites as precursors. The hierarchically porous zeolites obtained a regular mesoporous structure with aluminum incorporated into the carbon–silica composite frameworks. The carbon–silica composite zeolites were characterized by XRD, TEM, SEM, and nitrogen adsorption/desorption. As-prepared hierarchical zeolites were used in the 1,3,5-triisopropylbenzene (TIPB) cracking reaction and exhibited significantly high TIPB conversion, while the accessibility factors were also determined. [ABSTRACT FROM AUTHOR]

Based on the magneto-mechanical effect, the influence of crack size on stress evaluated with metal magnetic memory (MMM) technology was discussed in this paper. Based on equivalent theory, the regular rectangular grooves, with different widths and depths, were precut in the surface of an experimental sample for simulating surface crack, and a three dimensional electrically controlled displacement system was used to collect the Hp(y) signal of the sample under different stresses, and the fracture morphology was observed by using scanning electron microscopy (SEM). The results show that the influence of detection line on Hp(y) signal can be ignored; as stress increases, the Hp(y) signal turns counterclockwise around zero-crossing point and its mutation, corresponding to the location of groove, becomes distinct gradually. When groove depth is constant, the magnetic intensity gradient changes in the form of quadratic polynomial as groove width increases, and when the groove width is the same, the magnetic intensity gradient is a linear function of groove depth. When stress reaches the yield strength of the material, the magnetic intensity gradient decreases gradually as stress increases further, and the orientation of magnetic domain is seen as the main reason for that result. At last, the experimental results are discussed based on the piezomagnetic effect and leakage magnetic field theory of finite depth slit model, and the change of magnetic domain orientation is considered to be the main reason. [ABSTRACT FROM AUTHOR]

One of the challenging problems in robot navigation is efficient and safe planning in a highly dynamic environment, where the robot is required to understand pedestrian patterns in the environment, such as train station. The rapid movement of pedestrians makes the robot more difficult to solve the collision problem. In this paper, we propose a navigation probability map to solve the pedestrians' rapid movement problem based on the influencer recognition model (IRM). The influencer recognition model (IRM) is a data-driven model to infer a distribution over possible causes of pedestrian's turning. With this model, we can obtain a navigation probability map by analyzing the changes in the effective pedestrian trajectory. Finally, we combined navigation probability map and artificial potential field (APF) method to propose a robot navigation method and verified it on our data-set, which is an unobstructed, overlooked pedestrians' data-set collected by us. [ABSTRACT FROM AUTHOR]

Three industrially modified Y zeolites with a hierarchical structure were characterized by XRD, N2 adsorption–desorption, SEM, TEM, 27Al-/29Si-NMR, in situ pyridine-FTIR, and NH3-TPD techniques. The industrial hydrocracking catalyst of light diesel oil was prepared by kneading and extruding the mixture of 10 wt.% industrially modified zeolite, commercial alumina, nickel nitrate, and molybdenum oxide. The small amount of hierarchical Y zeolite in the hydrocracking catalyst plays a key role, resulting in selective hydrogenation of naphthalene and further ring-opening activity. The mesoporous structure of the zeolites provided an effective interface and improved the accessibility of acid sites to bulky reactants. [ABSTRACT FROM AUTHOR]

Ordered mesoporous Zr-Al composite oxide materials (denoted as OMZA-x) with different Zr contents have been synthesized by a solvent evaporation-inducing self-assembly procedure associated with a thermal treatment at 100 °C. A cooperative co-assembly process of amphiphilic triblock copolymer F127 molecules and inorganic hydroxyl species originated from the hydrolysis of Zr and Al precursors was proposed to explain the synthesis of OMZA-x. Compared to ordered mesoporous alumina prepared without introducing Zr species, the resultant OMZA-x exhibited a much more ordered mesostructure combined with a distinct increase in the pore volume and specific surface area. The highly homogenous doping of Zr into the mesopore walls together with the formation of Zr-O-Al bonds can effectively enhance the thermal and hydrothermal stability of OMZA-x. For instance, the ordered mesostructure and excellent textural properties of OMZA-6 prepared with the optimum atomic ratio of Al to Zr of 6 could be well maintained even after a high-temperature treatment at 1000 °C for 1 h or a hydrothermal treatment at 100 °C for 6 h. [ABSTRACT FROM AUTHOR]

Systematic periodic density functional theory computations including dispersion correction (DFT-D) were carried out to determine the preferred location site of Zr atoms in sodalite (SOD) and CHA-type topology frameworks, including alumino-phosphate-34 (AlPO-34) and silico-alumino-phosphate-34 (SAPO-34), and to determine the relative stability and Brönsted acidity of Zr-substituted forms of SOD, AlPO-34, and SAPO-34. Mono and multiple Zr atom substitutions were considered. The Zr substitution causes obvious structural distortion because of the larger atomic radius of Zr than that of Si, however, Zr-substituted forms of zeolites are found to be more stable than pristine zeolites. Our results demonstrate that in the most stable configurations, the preferred favorable substitutions of Zr in substituted SOD have Zr located at the neighboring sites of the Al-substituted site. However, in the AlPO-34 and SAPO-34 frameworks, the Zr atoms are more easily distributed in a dispersed form, rather than being centralized. Brönsted acidity of substituted zeolites strongly depends on Zr content. For SOD, substitution of Zr atoms reduces Brönsted acidity. However, for Zr-substituted forms of AlPO-34 and SAPO-34, Brönsted acidity of the Zr-O(H)-Al acid sites are, at first, reduced and, then, the presence of Zr atoms substantially increased Brönsted acidity of the Zr-O(H)-Al acid site. The results in the SAPO-34-Zr indicate that more Zr atoms substantially increase Brönsted acidity of the Si-O(H)-Al acid site. It is suggested that substituted heteroatoms play an important role in regulating and controlling structural stability and Brönsted acidity of zeolites. [ABSTRACT FROM AUTHOR]

Pd nanoparticles (NPs) supported on amine-functionalized layered double hydroxides (LDHs) (Pd/NH2-LDH-NS) were successfully obtained by implanting aminopropyltriethoxysilane (APTS) on MgAl LDH nanosheets (LDH-NS), followed by impregnating [Pd(NH3)4]Cl2 and reduction with NaBH4. The physicochemical characteristics of the obtained Pd/NH2-LDH-NS were characterized by X-ray diffraction (XRD), Fourier transform infrared (FT-IR),, N2 adsorption–desorption, inductive coupled plasma (ICP), transmission electron microscopy (TEM) and X-ray photoelectron spectroscopy(XPS), and their catalytic performance was tested in the selective oxidation of benzyl alcohol with molecular oxygen under solvent-free and base-free conditions. The results showed that the implanted –NH2 groups can promote the dispersion of the supported Pd NPs via complexation of the implanted –NH2 groups to Pd NPs, and they can increase the surface basicity of the catalysts, thus enhancing the catalytic activity and selectivity to benzylaldehyde. Pd/NH2-LDH-NS exhibited enhanced catalytic activity (31.6%) and selectivity (>98%) compared to the corresponding Pd/LDH-NS, Pd/LDH, Pd/SiO2, and Pd/Al2O3. Moreover, Pd/NH2-LDH-NS was remarkably stable and could be reused at least four times without a significant loss in activity and selectivity. [ABSTRACT FROM AUTHOR]

CO is a toxic gas discharged as a byproduct in tail gases from different industrial flue gases, which needs to be taken care of urgently. In this study, a CuCl/AC adsorbent was made by a facile route of physically mixing CuCl2 and Cu(HCOO)2 powder with activated carbon (AC), followed by heating at 533 K under vacuum. The samples were characterized by X-ray powder diffraction (XRD), inductively coupled plasma optical emission spectrometry (ICP-OES), N2 adsorption/desorption, and scanning electron microscopy (SEM). It was shown that Cu(II) can be completely reduced to Cu(I), and the monolayer dispersion threshold of CuCl on AC support is 4 mmol·g−1 AC. The adsorption isotherms of CO, CO2, CH4, and N2 on CuCl/AC adsorbents were measured by the volumetric method, and the CO/CO2, CO/CH4, and CO/N2 selectivities of the adsorbents were predicted using ideal adsorbed solution theory (IAST). The obtained adsorbent displayed a high CO adsorption capacity, high CO/N2, CO/CH4, and CO/CO2 selectivities, excellent ad/desorption cycle performance, rapid adsorption rate, and appropriate isosteric heat of adsorption, which made it a promising adsorbent for CO separation and purification. [ABSTRACT FROM AUTHOR]

The recent development of SERS substrates based on irregular nanostructures for directly molecule recognition has aroused increasing attention. By combining the irregular flake-like nanostructures of mantis wings, high SERS performance of Ag nanofilms, and the chemical stability of Au nanoparticles (NPs), an ultra-sensitive and flexible SERS substrate based on Au NPs functionalized Ag nanofilms-mantis wings (Au-Ag-M.w.) hybrid system is successfully fabricated. When 4-aminothiophenol is selected as the probe molecule, the limit of detection (LOD) is as low as 10−13 M and the relative standard deviation (RSD) is lower than 7.15%. This novel SERS platform exhibits high SERS performance in terms of sensitivity, reproducibility and practicability mainly because there are high-density and multi-level "hot spots" in the appropriate nanogaps. Meanwhile, it also systematically compares the differences of the SERS performance of Cu and Ag decorated M.w. hybrids and how these differences can alter their response. Moreover, the proposed substrate is employed to rapidly detect the pesticide residues on apple peels and the LOD for cypermethrin is estimated at 10−10 mg/mL. Therefore, this novel SERS substrate has great potential in rapid sampling of pesticide residues on real samples and expands the investigation to other natural materials for fabricating various SERS platforms. [ABSTRACT FROM AUTHOR]

To improve the catalytic performance of zeolite catalysts in reactions involving bulky molecules, a series of mesoporous Beta zeolite were prepared using organic functionalized fumed silica as the silicon source, which were thoroughly characterized in terms of porosity and acidity. The peaks in X-ray diffraction (XRD) patterns showed broadening, and the external surface area and mesoporosity increased progressively when the content of organic functionalization increased. An infrared (IR) spectroscopy study of adsorbed probe molecules, including pyridine (Py-IR), 2,6-ditertbutylpyridine (DTBPy-IR) and pivalonitrile (Pn-IR), showed that the improvement of mesoporosity increased the accessibility of acidic sites. In the catalytic benzylation of naphthalene with benzyl chloride (BC) over the mesoporous Beta zeolite catalysts, the conversion of BC was significantly increased when the accessibility of Brönsted acid sites improved. The increase of mesoporosity not only improved the diffusion ability of the reactants and products, but also increased the accessibility of acid sites, which greatly enhanced the activity of the mesoporous Beta zeolite catalysts. It is highlighted that the interdependence of mesoporosity, acid type, acid concentration, and strength of the mesoporous Beta zeolites on the catalytic performance in the benzylation of naphthalene with BC was comprehensively studied. [ABSTRACT FROM AUTHOR]

A hierarchical zeolite Beta has been prepared by a feasible one-pot and one-step method, which is suitable for application in industrial production. The synthesis is a simple hydrothermal process with low-cost raw materials, without adding alcohol or adding seeds, and without aging, recrystallization, and other complex steps. The hierarchical zeolite Beta is a uniform nanocrystal (20–50 nm) aggregation with high external surface area (300 m2/g) and mesoporous volume (0.50 cm3/g), with the mesoporous structure composed of intercrystal and intracrystal pores. As an acid catalyst in benzylation of naphthalene with benzyl chloride, the hierarchical zeolite Beta has shown high activity in the bulky molecule reaction due to its introduction of mesostructure. [ABSTRACT FROM AUTHOR]