Slow-Light-Enhanced Polarization Division Multiplexing Infrared Absorption Spectroscopy for On-Chip Wideband Multigas Detection in a 1D Photonic Crystal Waveguide.

Slow-light photonic crystal waveguide (PCW) gas sensors based on infrared absorption spectroscopy play a pivotal role in enhancing the on-chip interaction between light and gas molecules, thereby significantly boosting sensor sensitivity. However, two-dimensional (2D) PCWs are limited by their narrow mode bandwidth and susceptibility to polarization, which restricts their ability for multigas measurement. Due to quasi-TE and quasi-TM mode guiding characteristics in one-dimensional (1D) PCW, a novel slow-light-enhanced polarization division multiplexing infrared absorption spectroscopy was proposed for on-chip wideband multigas detection. The optimized 1D PCW gas sensor experimentally shows an impressive slow-light mode bandwidth exceeding 100 nm (TM, 1500-1550 nm; TE, 1610-1660 nm) with a group index ranging from 4 to 25 for the two polarizations. The achieved bandwidth in the 1D PCW is 2-3 times that of the reported quasi-TE polarized 2D PCWs. By targeting the absorption lines of different gas species, multigas detection can be realized by modulating the lasers and demodulating the absorption signals at different frequencies. As an example, we performed dual-gas measurements with the 1D PCW sensor operating in TE mode at 1.65 µm for methane (CH4) detection and in TM mode at 1.53 µm for acetylene (C2H2) detection. The 1 mm long sensor achieved a remarkable limit of detection (LoD) of 0.055% for CH4 with an averaging time of 17.6 s, while for C2H2, the LoD was 0.18%. This polarization multiplexing sensor shows great potential for on-chip gas measurement because of the slow-light enhancement in the light-gas interaction effect as well as the large slow-light bandwidth for multigas detection.

Macrophage membrane (MMs) camouflaged near-infrared (NIR) responsive bone defect area targeting nanocarrier delivery system (BTNDS) for rapid repair: promoting osteogenesis via phototherapy and modulating immunity.

Bone defects remain a significant challenge in clinical orthopedics, but no targeted medication can solve these problems. Inspired by inflammatory targeting properties of macrophages, inflammatory microenvironment of bone defects was exploited to develop a multifunctional nanocarrier capable of targeting bone defects and promoting bone regeneration. The avidin-modified black phosphorus nanosheets (BP-Avidin, BPAvi) were combined with biotin-modified Icaritin (ICT-Biotin, ICTBio) to synthesize Icaritin (ICT)-loaded black phosphorus nanosheets (BPICT). BPICT was then coated with macrophage membranes (MMs) to obtain MMs-camouflaged BPICT (M@BPICT). Herein, MMs allowed BPICT to target bone defects area, and BPICT accelerated the release of phosphate ions (PO43-) and ICT when exposed to NIR irradiation. PO43- recruited calcium ions (Ca2+) from the microenvironment to produce Ca3(PO4)2, and ICT increased the expression of osteogenesis-related proteins. Additionally, M@BPICT can decrease M1 polarization of macrophage and expression of pro-inflammatory factors to promote osteogenesis. According to the results, M@BPICT provided bone growth factor and bone repair material, modulated inflammatory microenvironment, and activated osteogenesis-related signaling pathways to promote bone regeneration. PTT could significantly enhance these effects. This strategy not only offers a solution to the challenging problem of drug-targeted delivery in bone defects but also expands the biomedical applications of MMs-camouflaged nanocarriers.

Exploring the Effect of Different Secondary Building Units as Lewis Acid Sites in MOF Materials for the CO2 Cycloaddition Reaction.

In order to explore the catalytic effect of different Lewis acid sites (LASs) in the CO2 cycloaddition reaction, different secondary building units and N-rich organic ligand 4,4',4″-s-triazine-1,3,5-triyltri-p-aminobenzoate were assembled to construct six reported MOF materials: [Cu3(tatab)2(H2O)3]·8DMF·9H2O (1), [Cu3(tatab)2(H2O)3]·7.5H2O (2), [Zn4O(tatab)2]·3H2O·17DMF (3), [In3O(tatab)2(H2O)3](NO3)·15DMA (4), [Zr6O4(OH)7(tatab)(Htatab)3(H2O)3]·xGuest (5), and [Zr6O4(OH)4(tatab)4(H2O)3]·xGuest (6) (DMF = N,N-dimethylformamide, and DMA = N,N-dimethylacetamide). Large pore sizes of compound 2 enhance the concentration of substrates, and the multi-active sites inside its framework synergistically promote the process of the CO2 cycloaddition reaction. Such advantages endow compound 2 with the best catalytic performance among the six compounds and surpass many of the reported MOF-based catalysts. Meanwhile, the comparison of the catalytic efficiency indicated that Cu-paddlewheel and Zn4O display better catalytic performances than In3O and Zr6 cluster. The experiments investigate the catalytic effects of LAS types and prove that it is feasible to improve CO2 fixation property by introducing multi-active sites into MOFs.

Improving Recognition Accuracy of Pesticides in Groundwater by Applying TrAdaBoost Transfer Learning Method.

Accurate and rapid prediction of pesticides in groundwater is important to protect human health. Thus, an electronic nose was used to recognize pesticides in groundwater. However, the e-nose response signals for pesticides are different in groundwater samples from various regions, so a prediction model built on one region's samples might be ineffective when tested in another. Moreover, the establishment of a new prediction model requires a large number of sample data, which will cost too much resources and time. To resolve this issue, this study introduced the TrAdaBoost transfer learning method to recognize the pesticide in groundwater using the e-nose. The main work was divided into two steps: (1) qualitatively checking the pesticide type and (2) semi-quantitatively predicting the pesticide concentration. The support vector machine integrated with the TrAdaBoost was adopted to complete these two steps, and the recognition rate can be 19.3% and 22.2% higher than that of methods without transfer learning. These results demonstrated the potential of the TrAdaBoost based on support vector machine approaches in recognizing the pesticide in groundwater when there were few samples in the target domain.

Sensitive chemical sensor array based on nanozymes for discrimination of metal ions and teas.

Tea, originating from China, is an important part of Chinese traditional culture. There are different qualities of and producing areas for tea on the market, therefore it is necessary to discriminate between teas in a fast and accurate way. In this study, a chemical sensor array based on nanozymes was developed to discriminate between different metal ions and teas. The indicators for the sensor array are three kinds of nanozymes mimicking laccase (Cu-ATP, Cu-ADP, Cu-AMP). The as-developed sensor array successfully discriminated 12 metal ions and the detection limit was as low as 0.01 µM. The as-developed sensor array was also able to discriminate tea samples. Different kinds of tea samples appeared in different areas in the canonical score plot with different response patterns. Furthermore, in a blind experiment, we successfully discriminated 12 samples with a 100% accuracy. This sensor array integrates chemistry and food science together, realizing the simultaneous detection of several kinds of teas using a sensitive method. The as-developed sensor array would have an application in the tea market and provide a fast and easy method to discriminate between teas.

Invalid phase values removal method for absolute phase recovery.

A novel approach is presented for more effectively removing invalid phase values in absolute phase recovery. The approach is based on a detailed study involving the types and cases of invalid phase values. Meanwhile, some commonalities of the existing removal algorithms also are thoroughly analyzed. It is well known that rough absolute phase and fringe order maps can very easily be obtained by temporal phase unwrapping techniques. After carefully analyzing the components and fringe order distribution of the rough fringe order map, the proposed method chiefly adopts an entirely new strategy to refine a pure fringe order map. The strategy consists of three parts: (1) the square of an image gradient, (2) subregion areas of the binary image, and (3) image decomposition and composition. In combination with the pure fringe order map and a removal criterion, the invalid phase values can be identified and filtered out from the rough absolute phase map. This new strategy not only gets rid of the limitations of traditional removal methods but also has a two-fold function. The paper also offers different metrics from the experiment to evaluate the quality of the final absolute phase. In contrast with other removal methods, experimental results have verified the feasibility, effectiveness, and superiority of the proposed method.

Flexible calibration of phase-to-height conversion in fringe projection profilometry.

A flexible new technique is presented to calibrate the monocular system of phase-based fringe projection profilometry, which is made of a camera, a projector, and a computer. The proposed algorithm mainly consists of a more flexible phase-to-height conversion model and a minimum norm solution, followed by a nonlinear optimization based on the maximum likelihood criterion. In the whole calibration procedure, this method only requires the camera to capture a few two-dimensional checkerboard target images and several deformed fringe images with at least three different orientations. The proposed technique neither subjects to certain limitations nor measures additional geometry parameters in advance. Also, no highly precise gauge blocks or extra reference phases are involved. In contrast with the existing methods, the proposed technique is easier to use and more flexible. Experiments have been performed to validate the performance of this technique.

Development an electronic nose to recognize pesticides in groundwater.

Timely detection of Groundwater pollution is essential to protect human health, especially for pesticide pollution. To solve this issue, we proposed a novel solution to realize the prediction of pesticide in groundwater by using the electronic nose (e-nose). The main work of this paper was divided into three steps: 1) checking whether sample was polluted by pesticides, 2) further predicting the pesticide type, brand and pollution degree when the sample was polluted by pesticides, and 3) optimizing the sensor array. Random forest was used to complete the first step, which had the best accuracy and sensitivity of 100 %. Support vector machine was applied to complete the second step, and the accuracy reaching 98.08 %. As for the third step, recursive feature elimination was used to optimize the sensor array. After optimization, the number of sensors was reduced from 26 to 8. In addition, the e-nose developed in this paper was compared with a commercial e-nose. The results showed that the cost of the developed e-nose was much lower than that of the commercial e-nose despite its slightly weaker prediction performance. Thus, this e-nose can be employed to recognize the pesticides in groundwater, and even can be integrated into the while drilling technology to realize the in-situ detection of groundwater.

A versatile upconversion-based multimode lateral flow platform for rapid and ultrasensitive detection of microRNA towards health monitoring.

MicroRNAs are small single-stranded RNA molecules associated with gene expression and immune response, suggesting their potential as biomarkers for health monitoring. Herein, we designed a novel upconversion-based multimode lateral flow assay (LFA) system to detect microRNAs in body fluids by simultaneously producing three unique signals within a detection strip. The core-shell Au-DTNB@Ag nanoparticles act as both the Raman reporters and acceptors, quenching fluorescence from upconversion nanoparticles (UCNPs, NaYF4: Yb3+, Er3+) via the Förster resonance energy transfer mechanism. Using microRNA-21 as a representative analyte, the LFA system offers remarkable detection range from 2 nM to 1 fM, comparable to outcomes from signal amplification methods, due to the successful single-layer self-assembly of UCNPs on the NC membrane, which greatly enhances both the convenience and sensitivity of the LFA technique. Additionally, our proprietary fluorescence-Raman detection platform simplifies result acquisition by reducing procedural intricacies. The biosensor, when evaluated with diverse bodily fluids, showed remarkable selectivity and sustained stability. Importantly, our LFA biosensor effectively identified periodontitis and lung cancer patients from healthy subjects in genuine samples, indicating significant potential for disease prediction, early diagnosis, and progression tracking. This system holds promise as a multifunctional tool for various biomarker assays.

The chemometrics analysis and integrated pharmacology approach to decipher the effect and mechanism between raw and processed cistanche tubulosa.

ETHNOPHARMACOLOGICAL RELEVANCE: Cistanche tubulosa (CT) is the dried fleshy stem with scaly leaves of Cistanche tubiflora (Schenk) Wight, which has the effects of tonifying the kidney-yang, benefiting the vital essence and blood, and moisturizing the intestines and laxatives. There are differences in the activity of CT before and after processing, but the mechanism of processing is not clear. AIM OF THE STUDY: The study aimed to compare the strength of action of CT before and after yellow-wine processing in the treatment of constipation and kidney yang deficiency and to identify the active ingredients responsible for the differences in activity before and after yellow-wine processing. MATERIALS AND METHODS: This study established the fingerprints of CT and PCT using HPLC to identify their shared components. Then efficacy of KYDS and FC were carried out to compare the differences between CT and PCT in terms of efficacy. Next, this study established the spectrum-effect relationship between the shared chemical components and the medical effects of CT and PCT using the gray correlation analysis and entropy methods. Ultimately, the activity of the analyzed chemical components was verified using the zebrafish model. RESULTS: CT was more effective than PCT in promoting intestinal peristalsis, regulating gastrointestinal hormone levels, and thus treating FC. PCT was more effective than CT in improving the level of hormone indexes of the hypothalamus-pituitary-target gland axis, replenishing blood, and enhancing immunity. Through the analysis of the spectrum-effect relationship, it was finally found that 5, 6, 12 (tubuloside A), and 13 (isoacteoside) might be more closely related to the activity of tonifying kidney yang, and peaks 9, 10, and 11 (acteoside) are more closely associated with the treatment of constipation, and peaks 3 (salidroside), 4, 1, 2 (geniposidic acid), and 8 (echinacoside) were associated with both kidney yang tonic and treatment of constipation. At the same time, an activity verification experiment showed that echinacoside, geniposidic acid, and salidroside were effective in the treatment of FC and KYDS, while acteoside was very effective in the treatment of FC, and tubuloside A was significant in supplementing the blood, which validated the spectrum-effect relationship analysis. CONCLUSION: This study proved that the raw CT had a better laxative effect, while the yellow-wine processed CT had a better kidney-yang tonic effect; moreover, spectrum-effect relationships were established to analyze the chemical components leading to changes in the activity of CT before and after yellow-wine processing.

CaMKII activates ASK1 to induce apoptosis of spinal astrocytes under oxygen-glucose deprivation.

Calcium/calmodulin-dependent protein kinase II (CaMKII) is a ubiquitous, structurally complex multifunctional protein serine/threonine kinase that plays an important role in cell apoptosis via linking the ER stress and mitochondrial apoptosis pathways. Recently, CaMKII has been correlated with apoptosis signal-regulating kinase 1 (ASK1) activity and the ASK1-dependent apoptosis pathway through the direct phosphorylation of Thr845 of ASK1. The specific role of CaMKII in hypoxia-reoxygenation (H/R)-induced spinal astrocyte apoptosis, however, remains unclear. In this study, we investigated the effects of CaMKIIγ (an isoform of CaMKII) on spinal astrocyte apoptosis using an in vitro oxygen-glucose deprivation (OGD/R) model which mimics hypoxic/ischemic conditions in vivo. OGD/R increased cell death and the activation of CaMKII. Deletion of CaMKIIγ results in the reduced activation of CaMKII and apoptosis in astrocytes under OGD/R conditions. Notably, the deletion of CaMKIIγ induced ASK1 phosphorylation at Thr845 in astrocytes. The activation of JNK and p38 and the downstream effect of ASK1 were also reduced. These data suggest that CaMKIIγ is required for the CaMKII-dependent regulation of ASK1, affecting the apoptosis of a biologically important cell type under spinal cord injury.

Development of an electronic nose to characterize water quality parameters and odor concentration of wastewater emitted from different phases in a wastewater treatment plant.

For public health consideration, it is important to ensure the wastewater discharged from wastewater treatment plant is within the regulatory limits. This problem can be effectively solved by improving the accuracy and rapid characterization of water quality parameters and odor concentration of wastewater. In this paper, we proposed a novel solution to realize the precisive analysis of water quality parameters and odor concentration of wastewater by the electronic nose device. The main work of this paper was divided into three steps: 1) recognizing wastewater samples qualitatively from different sampling points, 2) analyzing the correlation between electronic nose response signals and water quality parameters and odor concentration, and 3) predicting the odor concentration and water quality parameters quantitatively. Combined with different feature extraction methods, support vector machine and linear discriminant analysis were applied as classifiers to recognize samples at different sampling points, which reported the best recognition rate of 98.83%. Partial least squares regression was applied to complete the second step, and R2 was reaching 0.992. As for the third step, ridge regression was used to predict water quality parameters and odor concentration with the RMSE less than 0.9476. Thus, electronic noses can be applied to determine water quality parameters and odor concentrations in the effluent discharged from wastewater plants.

A Multi-Scale Tool Orientation Generation Method for Freeform Surface Machining with Bull-Nose Tool.

Free-form surface parts are widely used in industries, and they consist of intricate 3D surfaces such as molds, impellers, and turbine blades that possess complex geometrical contours and demand high precision. Proper tool orientation is crucial for ensuring the efficiency and accuracy of five-axis computer numerical control (CNC) machining. Multi-scale methods have received much attention and have been widely used in various fields. They have been proven to be instrumental and can obtain fruitful outcomes. Ongoing research on multi-scale tool orientation generation methods, which aim to acquire tool orientations that satisfy both macro- and micro-scale requirements, is significantly important for improving the machining quality of workpiece surfaces. This paper proposes a multi-scale tool orientation generation method that considers both the machining strip width and roughness scales. This method also ensures a smooth tool orientation and avoids interference in the machining process. First, the correlation between the tool orientation and rotational axis is analyzed, and feasible area calculation and tool orientation adjustment methods are introduced. Then, the paper introduces the calculation method for machining strip widths on the macro-scale and the roughness calculation method on the micro-scale. Besides, tool orientation adjustment methods for both scales are proposed. Next, a multi-scale tool orientation generation method is developed to generate tool orientations that meet the macro- and micro-scale requirements. Finally, to verify the effectiveness of the proposed multi-scale tool orientation generation method, it is applied to the machining of a free-form surface. Experimental verification results have shown that the tool orientation generated by the proposed method can obtain the expected machining strip width and roughness, meeting both macro- and micro-scale requirements. Therefore, this method has significant potential for engineering applications.

A preliminary screening system for diabetes based on in-car electronic nose.

Studies have found differences in the concentration of volatile organic compounds in the breath of diabetics and healthy people, prompting attention to the use of devices such as electronic noses to detect diabetes. In this study, we explored the design of a non-invasive diabetes preliminary screening system that uses a homemade electronic nose sensor array to detect respiratory gas markers. In the algorithm part, two feature extraction methods were adopted, gradient boosting method was used to select promising feature subset, and then particle swarm optimization algorithm was introduced to extract 24 most effective features, which reduces the number of sensors by 56% and saves the system cost. Respiratory samples were collected from 120 healthy subjects and 120 diabetic subjects to assess the system performance. Random forest algorithm was used to classify and predict electronic nose data, and the accuracy can reach 93.33%. Experimental results show that on the premise of ensuring accuracy, the system has low cost and small size after the number of sensors is optimized, and it is easy to install on in-car. It provides a more feasible method for the preliminary screening of diabetes on in-car and can be used as an assistant to the existing detection methods.

Numerical Modeling of the Effect of Cutting-Edge Radius on Cutting Force and Stress Concentration during Machining.

Cutting is the primary method of material removal, and the quality of machined parts depends on the geometry of cutting tools. In this paper, a new cutting force coefficient model is established, revealing the influence of cutting-edge radius on the cutting process. The effects of cutting-edge radius on the shear angle and cutting force components are analyzed by finite element simulations. A series of simulations is conducted, and the results show that with increased cutting-edge radius, the shear angle decreases nonlinearly, and the cutting force increases gradually. Additionally, the growth rate of the feed force caused by increasing the cutting-edge radius is higher than that of the tangential force. Furthermore, the stress concentration area of the machined surface extends from the surface to the subsurface as the cutting-edge radius increases. The results of this research show that changing the cutting edge affects the cutting force component, shear angle, and stress concentration range during the cutting process. These results provide a theoretical reference for predicting the residual stress in parts.

A New Approach of Modelling Bottom Edge Cutting in 4-Axis Rough Milling of Complex Parts and Its Application on Feed Rate Optimization.

Complex mechanical parts such as a blisk of aero-engines are commonly used in aerospace industry. These parts are complex in shape and their rough machining are conducted in 4-axis machine tools with end mills. The end mills are fully engaged into the workpiece material to be removed. Because of the complex cutter motion in 4-axis milling, the bottom edges of the end mills are involved in cutting with high possibility, resulting in an undesirable increase of cutting forces, tool deflection, and quick tool wear. To address this technical challenge, an analytical method is proposed to identify and evaluate the bottom edge cutting in 4-axis milling in this work. The motion of the cutter's tool tip with respect to the workpiece is analyzed and the equations are formulated based on a basic interpolation algorithm. An approach to identifying and evaluating the bottom edge cutting is proposed. The increment of the cutting forces caused by the bottom edge cutting is taken into consideration to precisely evaluate the overall cutting forces. A feed rate optimization model is then established to control the cutting forces. The simulation and the experiment of rough milling of a blisk verify that the bottom edge cutting can be identified and the cutting force can be controlled by optimizing the feed rates without losing much machining efficiency.

A multi-platform sensor for selective and sensitive H2S monitoring: Three-dimensional macroporous ZnO encapsulated by MOFs with small Pt nanoparticles.

The high-selectivity and high-sensitivity determination of trace concentrations of toxic gases is a major challenge when using semiconductor metal oxide (SMO) gas sensors in complicated real-world environments. In this study, by strategically combining a three-dimensional inverse opal (3DIO) macroporous ZnO substrate and a ZIF-8 outer filter membrane, two series of sensors with Pt NPs loaded at different locations are developed. In the optimal 3DIO ZnO@ZIF-8/Pt sensor, the existence of small Pt NPs in ZIF-8 cavities can effectively accelerate the absorption of H2S, capture electrons from the N site of ZIF-8, and donate the electron to the S site of H2S, as indicated by density functional theory simulations, leading to a significantly increased response to H2S. Together with the molecular-sieving effect that ZIF-8 exerts on gas molecules with larger kinetic diameters, the 3DIO ZnO@ZIF-8/Pt sensor exhibits a high response to H2S (118-5.5 ppm), a detection limit of 40 ppb, and importantly, a 59-fold higher selectivity to H2S against typical interference gases. In addition, the 3DIO ZnO@ZIF-8/Pt sensor is developed as a multi-platform sensor to evaluate trace concentrations of H2S in meat quality assessment, halitosis diagnosis, and automobile exhaust assessment.

Accurate Modeling of Working Normal Rake Angles and Working Inclination Angles of Active Cutting Edges and Application in Cutting Force Prediction.

The normal rake angle is an important geometric parameter of a turning tool, and it directly affects the accuracy of the cutting force prediction. In this study, an accurate model of the working normal rake angle (WNRA) and working inclination angle (WIA) is presented, including variation in the cutting velocity direction. The active cutting edge of the turning tool is discretized into differential elements. Based on the geometric size of the workpiece and the position of the differential elements, the cutting velocity direction of each differential element is calculated, and analytical expressions for the WNRA, WIA, and working side cutting edge angle are obtained for each differential element. The size of the workpiece is found to exert an effect on the WNRA and WIA of the turning tool. The WNRA and WIA are used to predict the cutting force. A good agreement between the predicted and experimental results from a series of turning experiments on GH4169 with different cutting parameters (cutting depth and feed rate) demonstrates that the proposed model is accurate and effective. This research provides theoretical guidelines for high-performance machining.

Traditional Sensory Evaluation and Bionic Electronic Nose as Innovative Tools for the Packaging Performance Evaluation of Chitosan Film.

Inspired by the natural epidermis of animals and plants with antioxidant and antibacterial properties, the aim of this research was to characterize and analyze the effects of the chitosan concentrations on properties of glycerol plasticized chitosan (GPC) film and to investigate the suitability of sensory evaluation and bionic electronic nose (b-electronic nose) detection to assess the freshness of ground beef packaged in the GPC film. The increase in chitosan concentration resulted in an increase in solubility value, total color differences and color intensity of chitosan films. The water vapor permeability (WVP) of the GPC films decreased with the increasing of the chitosan concentration and then increased at higher chitosan concentrations. Longer storage time led to poorer freshness of the ground beef and the GPC film could keep beef samples fresher and delay the deterioration of the beef. Both the traditional sensory evaluation and b-electronic nose technology were fit for evaluating the quality and shelf-life of ground beef, which could advantageously be applied in the future for analyzing other bionic food packaging materials.

Evaluation of conifer and broad-leaved barriers in intercepting particulate matters in a wind tunnel.

Fugitive dust is an important source of particulate matters (PM) emission in the air. Vegetation barriers (VBs) can be an effective way to mitigate PM from fugitive dust sources. It is meaningful to choose appropriate plants to establish VBs that can efficiently capture PM from various sources. This study was conducted to establish comparable and repeatable conditions to evaluate the capability of different VB species in mitigating PM emission from certain fugitive dust source. The airflow around two VBs and their PM interception mechanism was studied in a wind tunnel with simulated PM emission source of animal feeding operations. The species used for the two VBs were conifers represented by Pinus Sylvestris var. mongolica Litv. (PS) and the broad-leaved species represented by Syringa Oblate Lindl. (SOL). The results showed that the interception efficiency of the PS vegetation barrier was only slightly lower than that of SOL vegetation, while the PS had a lower effect on the wind speed at the similar leaf surface area. On the other hand, there were a large number of disordered "ridged" stripes on the microscopic structure of the hydrophilic leaves of SOL and PS, and a large amount of fine particles deposited on the leaves were observed, indicating that the microscopic geometric surface structure increased the deposition efficiency of the particles. These findings help to better understand the potential of tree species to reduce PM in environments. Implications: To evaluate the capability of different VB species in mitigating PM emission from certain fugitive dust source, airflow around the two VBs and their PM interception mechanisms were studied in wind tunnels with comparable and repeatable conditions. The results showed that the interception efficiency of the Pinus Sylvestris var. mongolica Litv. (PS) was only slightly lower than that of the Syringa Oblate Lindl. (SOL) vegetation, while the PS had a lowering effect on the wind speed at the same low leaf surface area. Microscopic analysis of leaves surface indicated that the microscopic characteristics increased the deposition efficiency of the particles.