RESUMEN

Coffee rings formed by evaporation of analyte-containing droplets are widely observed in micropatterning, bio-arrays, and trace detection. The coffee-ring effect caused by contact line pinning significantly affects the detection uniformity and sensitivity. Here, we propose a simple and operable method to effectively suppress coffee rings through controllable nanoparticles aggregation by superhydrophobicity-enabled dynamic evaporation. The gold nanoparticles (AuNPs) deposition footprint formed after dynamic evaporation on an integrated superhydrophobic surface was reduced by ∼3 orders of magnitude compared to that of non-interventional evaporation. Detailed experiments, numerical simulations, and theoretical studies have revealed that substrate wettability, temperature and droplet motion behaviors play significant roles in suppressing coffee-ring effect. More critically, based on the force mechanism of AuNPs at the interface/contact line, universal mathematical models and regime maps were established to classify the different deposition modes for AuNPs under different evaporation conditions by introducing dimensionless parameter G, revealing the enrichment mechanism of AuNPs in droplets under superhydrophobicity-enabled dynamic evaporation. The accuracy of the theoretical model and enrichment mechanism was demonstrated through the single-molecule detection of rhodamine 6G with excellent sensitivity (10-17 M, enhancement factor ∼1013) and perfect uniformity (relative standard deviation ∼5.57 %), which provides a valuable guide for research and applications of nanoparticle aggregation.

RESUMEN

Infectious diseases have always been a seriously endanger for human life and health. A rapid, accurate and ultra-sensitive virus nucleic acid detection is still a challenge to deal with infectious diseases. Here, a RNA extraction-free reduced graphene oxide-based reverse transcription-loop-mediated isothermal amplification (EF-G-RT-LAMP) fluorescence assay was developed to achieve high-throughput, rapid and ultra-sensitive SARS-CoV-2 RNA detection. The whole detection process only took ∼36 min. The EF-G-RT-LAMP assay achieves a detection limit of 0.6 copies µL-1 with a wide dynamic range of aM-pM. A large number (up to 384) of samples can be detected simultaneously. Simulated detection of the COVID-19 pseudovirus and clinical samples in nasopharyngeal swabs demonstrated a high-throughput, rapid and ultra-sensitive practical detection capability of the EF-G-RT-LAMP assay. The results proved that the assay would be used as a rapid, easy-to-implement approach for epidemiologic diagnosis and could be extended to other nucleic acid detections.

Asunto(s)

Asunto(s)

RESUMEN

Protective forests are the ecological barriers of oases in arid sand areas and can effectively prevent and control wind and sand hazards. The structural characteristics of individual trees, as the basic unit of protective forests, are the key factors affecting the protective benefits. With the typical leafless tree species of Ulan Buh Desert oasis, i.e., Populus alba var. pyramidalis, Populus nigra var. thevestina, and Populus popularis, as the research objects, and by using the ground-based LiDAR and through computational fluid dynamics (CFD), we fully explored the structural characteristics of individual trees and their surrounding aerodynamic characteristics on the basis of real 3D models. We further established the relationship between structural parameters of individual trees and wind field index. The results showed that combining AdQSM and MeshLab to build tree models had high accuracy. The wind field around the individual trees could be roughly divided into six regions, including the attenuation zone of the windward side of the plant, the acceleration zone at the top of the plant, the eddy zone, the calm zone, the transition zone, and the recovery zone of leeward side of the plant. The pressure field around individual trees showed a gradual change of high pressure on the windward side to low pressure on the leeward side. Horizontally, in the range of 20% to 50% reduction in relative wind speed, the effective protection distances were 0.21H-1.51H, 0.20H-0.91H, and 0.25H-1.64H (H was the corresponding tree height) for P. alba var. pyramidalis, P. nigra var. thevestina, and P. popularis, corresponding to effective protection areas of 18-294, 15-227, and 18-261 m2, respectively. The maximum wind speed decay rate in the vertical direction was at 0.3H height for P. alba var. pyramidalis and P. popularis, and was reflected at 0.5H height for P. nigra var. thevestina. The correlation and stepwise regression analysis of the single tree structure parameters with the wind field indicators clearly indicated that optical porosity and volume porosity dominated the protection effect. Among the wind field factors, the best regression models related to the porous coefficient were screened for three factors, including diameter at breast height, tree surface area, and optical porosity. The regression variables screened for effective protection distance and effective protection area differed among the classes.

Asunto(s)

RESUMEN

We examined the growth decline and health status of farmland protective forest belt (Populus alba var. pyramidalis and Populus simonii shelterbelts) in Ulanbuh Desert Oasis by using airborne hyperspectral and ground-based LiDAR to collect the hyperspectral images and point cloud data of the whole forest belt respectively. Through correlation analysis and stepwise regression analysis, we constructed the evaluation model of the decline degree of farmland protection forest with the spectral differential value, vegetation index, and forest structure parameters as independent variables and the tree canopy dead branch index of the field survey as dependent variables. We further tested the accuracy of the model. The results showed that the evaluation accuracy of the decline degree of P. alba var. pyramidalis and P. simonii by LiDAR method was better than that by hyperspectral method, and that the evaluation accuracy of the combined LiDAR and hyperspectral method was the highest. Using the LiDAR method, hyperspectral method, the combined method, the optimal model of P. alba var. pyramidalis was all light gradient boosting machine model, with the overall classification accuracy being 0.75, 0.68, 0.80, and Kappa coefficient being 0.58, 0.43, 0.66, respectively. The optimal model of P. simonii was random forest model, random forest model, and multilayer perceptron model, with the overall classification accuracy being 0.76, 0.62, 0.81, and Kappa coefficient being 0.60, 0.34, 0.71, respectively. This research method could accurately check and monitor the decline of plantations.

Asunto(s)

RESUMEN

The solvent-free reactions of ß-enamino carbonyl compounds with 1-(pyridin-2-yl)-enones in the presence of manganese(iii) acetate dihydrate unexpectedly afforded 2-acyl-3-aryl-6,7-dihydro-4(5H)-benzofuran derivatives under mechanical milling conditions.