Zeolite-like molecular sieves show high potential in solid desiccant dehumidification cooling systems. They are recognized for remarkable moisture adsorption capacity and regeneration performance, characterized by their Sshaped adsorption isotherms. As a new type of zeolite-like molecular sieves, AlPO4-LTA has been reported with superior equilibrium moisture uptake, but its dynamic dehumidification characteristics in practical dehumidification systems still lack. In this study, to explore the application potential of AlPO4-LTA, the material was synthesized through ionothermal method, followed by an examination of its features and moisture adsorption characteristics, focusing extensively on the dynamics of moisture adsorption and desorption. Moreover, the practical dehumidification characteristics of AlPO4-LTA coated dehumidifier were investigated by a validated mathematical model. Observations confirmed that the AlPO4-LTA possessed a uniform structure, a high specific surface area, and a narrow pore size distribution. The equilibrium moisture adsorption uptake can reach 0.42 kg & sdot;kg-1 in adsorption isotherm of 30 degrees C. The adsorption/desorption kinetics coefficients kads/kdesof the AlPO4- LTA coatings determined by the linear driving force (LDF) model were on the magnitude of 0.001-0.01 s-1. Numerical results revealed the moisture removal capacity (MRC) and dehumidification coefficient of performance (DCOP) of AlPO4-LTA coated dehumidifier can reach 8.58 g & sdot;kg-1 and 0.17 at regeneration temperature of 75 degrees C, respectively, which were 1.8 and 1.1 times over those conventional AlPOs (including FAM-Z01 and EMM8) coated dehumidifiers.

N-doped TiO2/carbon 2 /carbon composites (N-TiPC) have shown excellent photodegradation performances to the organic contaminants but are limited by the multistage preparation (i.e., preparation of porous carbon, preparation of Ndoped TiO2 , 2 , and loading of N-doped TiO2 2 on porous carbon). Here, we develop a handy way by combining the Pickering emulsion-gel template route and chelation reaction of polysaccharides. The N-TiPC is obtained by calcinating pectin/DL-serine L-serine hydrazide hydrochloride (SHH)-Ti4+ 4 + chelate and is further described by modern characterization techniques. The results show that the N atom is successfully doped into the TiO2 2 lattice, and the bandgap value of N-TiPC is reduced to 2.3 eV. Moreover, the particle size of N-TiPC remains about 10 nm. The configurations of the composites are simulated using DFT calculation. The photocatalytic experiments show that N-TiPC has a high removal efficiency for methylene blue (MB) and oxytetracycline hydrochloride (OTC-HCL). The removal ratios of MB (20 mg/L, 50 mL) and OTC-HCL (30 mg/L, 50 mL) are 99.41 % and 78.29 %, respectively. The cyclic experiments show that the photocatalyst has good stability. Overall, this study provides a handy way to form N-TiPC with enhanced photodegradation performances. It can also be promoted to other macromolecules such as cellulose and its derivatives, sodium alginate, chitosan, lignin, etc.

Solid desiccant dehumidification systems offer an effective and energy-efficient alternative for deeply dehumidifying air. Desiccant coated heat exchangers (DCHEs), a type of solid desiccant dehumidification system, have garnered attention due to their ability to eliminate adsorption heat and thereby enhance dehumidification capacity, unlike desiccant wheels that perform adiabatic dehumidification. This study introduces a silica gel coated cross-flow DCHE equipped with a circulating blowing loop for deep dehumidification applications. A twodimensional numerical model is developed to simulate deep dehumidification behavior of the DCHE. Parametric analysis is performed to explore the dehumidification characteristics under various conditions, setting different volume fractions omega of blowing loop air. Results indicate that the DCHE can effectively reduce the moisture content of humid air to a deep dehumidification threshold of 6.2 g/kg. Additionally, dehumidification capacity can be increased by incorporating a circulating blowing loop. The influence of process air velocity, cooling air velocity, process air humidity ratio, regeneration air temperature and air channel length on the dehumidification performance are analyzed, focusing on metrics such as minimum outlet air humidity ratio Ya1,ad,out min, effective deep dehumidification time teff, moisture removal capacity MRC and dehumidification coefficient of performance DCOP. It is determined that the regeneration air temperature should be raised to 80 degrees C to ensure deep dehumidification, and an air channel length of 0.2 m is optimal.

Chemical looping gasification (CLG) technology is promising for renewable energy, efficiently transforming biomass into high-quality syngas with minimal tar and pollutants. In this study, we examined the CLG characteristics of soy protein (SP), a model compound present in kitchen waste (KW), using two different oxygen carriers (OCs): Cu-Fe and Ni-Fe. The study revealed that enhancing the carbon conversion ratio (eta c) could be effectively achieved by increasing the oxygen equivalent coefficient (alpha) and the steam content. Consequently, the optimal gasification performance was attained when the Cu-Fe and Ni-Fe OCs were operated at the alpha values of 0.3 and 0.4, and steam contents of 30 % and 40 %, respectively. After ten cycles of chemical looping, both OCs retained their robust oxidation activity, ensuring that the eta cremained consistent throughout the ten cycles. Under optimized experimental conditions, the CLG characteristics of KW were successfully determined. Notably, the eta cof KW was substantially enhanced, doubling in comparison to previous levels. The Cu-Fe OC emerged as a more suitable candidate for the CLG of KW due to its lower cost and non-toxic nature. This study provides important theoretical support and practical insights for the harmless treatment and resource utilization of KW.

N-doped TiO2/carbon composites (N-TiPC) have shown excellent photodegradation performances to the organic contaminants but are limited by the multistage preparation (i.e., preparation of porous carbon, preparation of N-doped TiO2, and loading of N-doped TiO2 on porous carbon). Here, we develop a handy way by combining the Pickering emulsion-gel template route and chelation reaction of polysaccharides. The N-TiPC is obtained by calcinating pectin/Dl-serine hydrazide hydrochloride (SHH)-Ti4+ chelate and is further described by modern characterization techniques. The results show that the N atom is successfully doped into the TiO2 lattice, and the bandgap value of N-TiPC is reduced to 2.3 eV. Moreover, the particle size of N-TiPC remains about 10 nm. The configurations of the composites are simulated using DFT calculation. The photocatalytic experiments show that N-TiPC has a high removal efficiency for methylene blue (MB) and oxytetracycline hydrochloride (OTC-HCL). The removal ratios of MB (20 mg/L, 50 mL) and OTC-HCL (30 mg/L, 50 mL) are 99.41 % and 78.29 %, respectively. The cyclic experiments show that the photocatalyst has good stability. Overall, this study provides a handy way to form N-TiPC with enhanced photodegradation performances. It can also be promoted to other macromolecules such as cellulose and its derivatives, sodium alginate, chitosan, lignin, etc.

Researchers are already becoming willing to get involved in bismuth oxysulfide (Bi2O2S), a new two-dimensional optoelectronic material with a lengthy carrier lifetime and a unique loose structure. In this work, the Bi2O2S nanosheets are produced by room temperature chemical synthesis and built a Bi2O2S nanosheets flexible photodetector based on deionized water solid-state electrolytes. Photoelectrochemical tests showed that the photodetector based on deionized water solid-state electrolyte had excellent photoresponse performance under 0 V, and its photocurrent density was 0.55 μA/cm2 when the optical power was 75 mW/cm2. In addition, the photodetector exhibited superb stability. After cycling the “on–off” behavior for 1000 s, the photocurrent slightly decreased 8% than initial state. At a bending angle of 30°, the photocurrent density was about 91% of the original state, but when the bending angle is 60°, the photocurrent density was about 76% of the original state, which may be caused by the small cracks formed during the bending process. The results showed that the flexible photodetector based on Bi2O2S nanosheets had decent stability and mechanical flexibility, and were safer and more environmentally friendly than traditional detectors, providing a workable option for the flexible photodetector’s construction.

Tellurium (Te) is a kind of multifunctional material attracting a great deal of interest. Herein, we described a substrate-free solution process to produce Te nanosheets (Te NSs) and build photodetectors (PDs) of photoelectrochemical (PEC) type based on them. The PDs are self-powered according to the photocurrent density about 0.28 µA cm −2 and the photo responsivity of 3.37 µA W −1 when the optical power is 80.2 mW cm −2 without any extrinsic voltage. They exhibit excellent photo-response switching behaviors with high responsivity (15.8 µA W −1 ) and rapid response time (~ 227 ms of the rise time and ~ 293 ms of the fall time) at 0.6 V potential, as well as great long-term stability and durability (storage in ethanol for 1 month). Simultaneously, we measured the photoelectric response after heating the solution to explore the effect of the solution temperature on the photoelectric properties of Te NSs. At a temperature of 70℃, the enhancement was leveraged to promote the photo-response to 14.3 µA W −1 . This work paved the way for developing higher performance PDs.

Clouds play an important role in the Earth’s climate system; however, various observational methods describe clouds differently, leading to cloud products being described with different characteristics, and affecting our understanding of cloud effects. To address this problem, this study integrates different cloud products into the transfer-learning procedure of a deep-learning model and determines the cloud effective radius (CER), cloud optical thickness (COT), and cloud top height (CTH) from Himawari-8 thermal infrared measurements. The retrieval results were independently evaluated against the moderate-resolution imaging spectroradiometer science products and further compared with Himawari-8 operational products during the day. The root mean squared errors (RMSEs) of the model for the CER, COT, and CTH were $4.490~\mu \text{m}$ , 11.198, and 1.904 km, respectively, which are lower than those of Himawari-8 operational products (RMSE: $11.172~\mu \text{m}$ , 14.755, and 2.860 km). Moreover, validation results against active sensors show that the model performs slightly better during the day than at night, and both are generally better than the Himawari-8 operational product. Overall, the model maintains stable performance during both day and night, and its accuracy is higher than that of Himawari-8 operational products.

Forward radiative transfer (RT) models are essential for atmospheric applications such as remote sensing and weather and climate models, where computational efficiency becomes equally as important as accuracy for high-resolution hyperspectral measurements that need rigorous RT simulations for thousands of channels. This study introduces a fast and accurate RT model for the hyperspectral infrared (HIR) sounder based on principal component analysis (PCA) or machine learning (i.e., neural network, NN). The Geosynchronous Interferometric Infrared Sounder (GIIRS), the first HIR sounder onboard the geostationary Fengyun-4 satellites, is considered to be a candidate example for model development and validation. Our method uses either PCA or NN (PCA/NN) twice for the atmospheric transmittance and radiance, respectively, to reduce the number of independent but similar simulations to accelerate RT simulations; thereby, it is referred to as a multi-domain compression model. The first PCA/NN gives monochromatic gas transmittance in both spectral and atmospheric pressure domains for each gas independently. The second PCA/NN is performed in the traditional spectral radiance domain. Meanwhile, a new method is introduced to choose representative variables for the PCA/NN scheme developments. The model is three orders of magnitude faster than the standard line-by-line-based simulations with averaged brightness temperature difference (BTD) less than 0.1 K, and the compressions based on PCA or NN methods result in comparable efficiency and accuracy. Our fast model not only avoids an excessively complicated transmittance scheme by using PCA/NN but is also highly flexible for hyperspectral instruments with similar spectral ranges simply by updating the corresponding spectral response functions.

Titanium dioxide/carbon (TiO2/C) composites are generally prepared from fossil resources, which contradicts carbon neutrality science and economics. This study used sawdust as the feedstock to make TiO2/C binary composites that were further used to photodegrade methylene blue (MB) under simulated sunlight irradiation. The composites were characterized by SEM, FT-IR, XRD, XPS, TG-DT G, UV-vis, and N2 adsorption-desorption. Carbon primarily existed in the outer layer of the composite, significantly enhancing sensitization. The direct band gap of the TiO2/C-550 composite was 2.7 eV. As a result, the visible light absorption of TiO2 widened, and the charge recombination rate decreased. The degradation ratio of MB aqueous solution reached nearly 100% within 30 min in the presence of TiO2/C-550 composites. Moreover, TiO2/C-550 still maintained about 95% photodegradation efficiency after 5 cycles. Meanwhile, the dominant role of center dot O2-produced in the reaction has been confirmed through free radical capture experiments. Compared with pure TiO2, the photodegradation performance of MB was significantly improved under visible light irradiation. In addition, the material prepa-ration is green, simple, and low-cost. We can confirm that the TiO2/C composites prepared from waste sawdust had sustainable and efficient advantages, reducing the consumption of fossil resources.

Black spot caused by Alternaria brassicicola is one of the most common fungal diseases of postharvest broccoli. The present study investigated the biocontrol efficacy of Meyerozyma guilliermondii against black spot of postharvest broccoli and the mechanisms involved in the enhanced disease resistance of broccoli based on its effects on reactive oxygen species (ROS) metabolism. Our investigation proved that M. guilliermondii could decrease the disease index of postharvest broccoli caused by A. brassicicola. This antagonistic yeast could potentially increase peroxidase, catalase and superoxide dismutase activities, and the activities of enzymes involved in ascorbate-glutathione cycle and glutathione peroxidase cycle, such as ascorbate peroxidase, glutathione peroxidase and glutathione reductase. Furthermore, the contents of non-enzymatic antioxidants, including ascorbic acid and glutathione, were enhanced by this yeast. Accordingly, the accumulation of ROS, including hydrogen peroxide (H2O2) and superoxide anion (O2-), was reduced by M. guilliermondii, as well as malondialdehyde amount which was one of the membrane lipid peroxides. Our results suggested that M. guilliermondii could improve the activities of ROS scavenging enzymatic system and the levels of antioxidant substances to scavenge excessive ROS, and then protect cells from oxidative damage, which enhanced the disease resistance of broccoli to pathogens. Overall, our study provides a new disease control strategy for postharvest broccoli by improving the ability of ROS scavenging to resist pathogens.

Ultraviolet (UV) photodetectors have attracted increasing attention in military and civilian fields.In this work, the prepared TiO2-graphene composite was fabricated by hydrothermal synthesis method and it was used in photoelectrochemical type photodetector for UV detection. The results of the photoelectrochemical measurements demonstrate that the TiO2-graphene composite have a remarkable enhancement on photoresponse compared to pure TiO2, which is effectively demonstrate the introduction of graphene will reduce the probability of electron-hole recombination and increase the photocurrent of light detection. In addition, owing to the unique solid-liquid contact mechanism of PEC-type photodetector, it can work under 0 V bias and exhibited excellent photoresponse ability that can reach11uA/W at the UV wavelength of 365 nm. Moreover, the as-prepared TiO2-graphene composite based photodetector possessed preferable performance with the weak irradiation. Even if the light intensity reduced to 6 mW/cm(2), the photocurrent density can also reach to 5 uA/cm(2). With the excellent absorbtion of the UV and remarkable self-powered ability make the TiO2-graphene composite based PEC-type photodetector have great promising on UV detection field.

A quality control (QC) process which handles surface impacts is an important step toward successful assimilation of the Advanced Baseline Imager (ABI) water vapor (WV) band radiances. If the QC is too relaxed, many surface contaminated radiances get assimilated. If the QC is too stringent, useful radiances are rejected. Either way can result in reduced or even compromised observation impacts. A new machine learning‐based QC scheme for the three ABI WV bands is developed and optimized to help understand the importance and effectiveness of the scheme. Unlike previous schemes which are dependent on the background, this scheme extracts and blends the surface information from 7 ABI bands (bands 8–10, 13–16) to determine if a WV radiance is affected by the surface. Simulation studies show that the new QC scheme is effective in retaining radiances that are either unaffected by the surface or have very small surface contamination. It is highly effective in rejecting radiances with large surface contamination. Numerical experiments from a single case study of Hurricane Harvey (2017) were carried out to optimize the QC and to understand the potential impacts on forecasts. The use of the new QC scheme shows that radiances from each WV band have substantially added value. Combining them has a positive impact on hurricane track forecasts compared with existing QC schemes. Hence, it is critical that an optimized QC scheme is used for infrared WV radiance assimilation. It provides a balance between positive impacts from useful radiances and negative impacts from surface contaminated radiances.

The preparation of lime-based materials through calcining limestone or siliceous/clay limestone (including air lime and hydraulic lime) directly/indirectly emits large amounts of CO2 due to limestone decomposition and energy consumption. In this study, a sinter-free hydraulic lime (HL) was proposed by mixing carbide slag (CS) and white Portland cement (WPC), which can effectively utilize solid wastes and in future that may prove to be effective for CO2 mitigation. Results showed the flexural strength of HL mortars decreased from 6.3 MPa to 0.5 MPa, compressive strength decreased from 42.0 MPa to 2.2 MPa, air permeability increased from 0.440 to 2.468 Ln (pressure)/min and water permeability increased from 6.576 x 10(-7) to 47.362 x 10(-7) m(3)/min(0.5) with the increase of CS from 20% to 40%, 60% and 80% in HL. However, the mechanical properties still meet the standard requirements when the CS content is 80%. Carbonation treatment can refine pore size and improve mechanical properties of HL mortar. CS is expected to become the main raw material for HL preparation.

The characteristics of mesoscale convective systems (MCSs) over the Yunnan–Guizhou Plateau (YGP) during the warm seasons (April–August) are investigated using an automatic tracking algorithm based on long‐term (2000–2018) hourly geostationary satellites data of temperature of black body. A total of 1,845 MCSs generated over the YGP are identified and further classified into the eastward moving type (EMT; ~13.1%) and noneastward moving/dissipating type (NDT; ~86.9%). The two types of MCSs exhibit varying characteristics. The EMTs are mainly active in the eastern flank of the YGP with a longer mean lifespan (~16.5 hr), while the NDTs occur anywhere over the YGP with a preference for the central YGP with a shorter mean lifespan (~7.6 hr). The MCSs are observed most frequently during June–July, while the ratio of EMTs reaches the highest in April due to the strongest steering flows. The abundant moisture supply plays a vital role in the generation and development of MCSs in June, whereas the dynamic forcing and high CAPE are favourable to MCSs in July. In terms of the diurnal cycle, the NDTs are generally initiated in the afternoon, reach mature in the late afternoon, and dissipate at night. By contrast, the mature stage of EMTs shows double diurnal peaks in the late afternoon and early morning. The MCSs are usually generated in an instable environment accompanied by strong vertical wind shear and intense low‐level water vapour flux over the YGP, and the MCSs tend to vacate the YGP with strong mid‐level westerlies and instable environment in the downstream regions. Compared to MCSs in Tibetan Plateau, the ratio of the EMTs is higher with longer lifespans though fewer MCSs are generated over the YGP.

Two-dimensional (2D) molybdenum disulfide (MoS2) nanomaterials have become one of the promising options for constructing excellent supercapacitors. However, the application of MoS2 materials is limited by low energy density, and the difficulty of large-scale and low-cost preparation seriously hinders its practical application in the field of energy storage. Here, the exfoliation of the MoS2 nanosheets and the loading of MnO2 nanoparticles on the MoS2 nanosheets are realized in one step by electrochemical method. A series of characterization methods have fully confirmed that the electrochemical method has successfully prepared the MoS2 nanosheet/MnO2 (MoS2 NS/MnO2) heterojunction. The experimental results show that the MoS2 NS/MnO2 heterojunction has better electrochemical performance than a single MoS2 nanosheet. It has a good capacitance even in a neutral solution, and its specific capacitance is 275 F g-1 at a current density of 2 A g-1. In addition, a supercapacitor device based on MoS2 NS/MnO2 heterojunction was constructed, which not only exhibited excellent capacitive performance, but also exhibited 10,000 charge-discharge cycle stability under 10 A g-1 conditions. This work provides an experimental basis for the preparation of 2D nanosheets and the large-scale preparation of functionalized 2D material heterojunctions by electrochemical methods.

Cloud detection is a crucial step in the optical satellite image processing pipeline for Earth observation. Clouds in optical remote sensing images seriously affect the visibility of the background and greatly reduce the usability of images for land applications. Traditional methods based on thresholding, multi-temporal or multi-spectral information are often specific to a particular satellite sensor. Convolutional Neural Networks for cloud detection often require labeled cloud masks for training that are very time-consuming and expensive to obtain. To overcome these challenges, this paper presents a hybrid cloud detection method based on the synergistic combination of generative adversarial networks (GAN) and a physics-based cloud distortion model (CDM). The proposed weakly-supervised GAN-CDM method (available online https://github.com/Neooolee/GANCDM) only requires patch-level labels for training, and can produce cloud masks at pixel-level in both training and testing stages. GAN-CDM is trained on a new globally distributed Landsat 8 dataset (WHUL8-CDb, available online doi:https://doi.org/10.5281/zenodo.6420027) including image blocks and corresponding block-level labels. Experimental results show that the proposed GAN-CDM method trained on Landsat 8 image blocks achieves much higher cloud detection accuracy than baseline deep learning-based methods, not only in Landsat 8 images (L8 Biome dataset, 90.20% versus 72.09%) but also in Sentinel-2 images ("S2 Cloud Mask Catalogue" dataset, 92.54% versus 77.00%). This suggests that the proposed method provides accurate cloud detection in Landsat images, has good transferability to Sentinel-2 images, and can quickly be adapted for different optical satellite sensors.

Due to the influence of mechanical vibration, high temperature creep and other factors, Si 3 N 4 turbine blades are prone to surface defects. Besides, traditional algorithms are incapable to detect and classify surface defects simultaneously. Aiming at solving these problems, an algorithm for defect detection and classification of Si 3 N 4 turbine blades based on convolutional neural network is proposed. The detection and classification network of this algorithm is optimized based on YOLOv5 network, the PAN structure and FPN structure of YOLOv5 are replaced by BiFPN structure. We establish the dataset of Si 3 N 4 turbine blades, which is expanded by data enhancement. For the purpose of achieving a higher level of feature fusion, the PAN and FPN structures of the Neck part are replaced by BiFPN structure. As a result, the accuracy of detecting and classifying the surface defects by this algorithm is as high as 97.4%, and the detection speed is as low as 16ms. This optimized algorithm is able to solve the problems of traditional detection methods such as heavy workload, long time consuming and low accuracy. The algorithm provides a feasible approach for the quality detection of Si 3 N 4 turbine blades and has certain engineering application value. Keywords Defect detection , Si , N , turbine blades , YOLOv5 algorithm , BiFPN structure , convolutional neural network

An optimization method for the gradually varied porous absorber is proposed. The Monte Carlo Ray Tracing method based on the acceptance-rejection sampling is established to obtain the absorption distribution of irradiation in the gradually varied porous absorber. The fluid flow, convection, and thermal radiation in the porous absorber are evaluated. Combined with the genetic algorithms, the distribution of porosity and pore size of the porous absorber could automatically adjust to match the non-uniform radiation flux in both radial and axial directions. Moreover, the internal flow layout could be regulated by an optimized radial pore distribution that directs more fluid enters the high heat flux zone. The optimization results demonstrate that the gradually varied porous absorber with porosity ranging from 0.95 to 0.90 and pore size ranging from 2.5mm to 1.5 mm could achieve high thermal efficiency and low flow resistance. Compared with the standard model of the uniform porous absorber, the thermal efficiency of the optimal gradually varied porous absorbers could be further increased by 1.23% to 9.76%, while the pressure drop could be reduced by 7.88% to 55.73%.

Abstract Thermodynamic information from low levels in the atmosphere is crucial for operational weather forecasts and meteorological researchers. The NOAA Unique Combined Atmospheric Processing System (NUCAPS) sounding products have been proven beneficial to fill the data gap between synoptic radiosonde observations (RAOBs). However, compared with the upper troposphere, the accuracy of NUCAPS soundings in the low levels still needs improvement. In this study, a deep neural network (DNN) is applied to fuse multiple data sources to enhance the NUCAPS temperature and moisture profiles in the lower atmosphere. The network is developed by combining satellite observations, including NUCAPS sounding retrievals and high resolution geostationary satellite observations from the Advanced Baseline Imager, and surface analysis from the Real‐Time Mesoscale Analysis (RTMA) as inputs, while collocated soundings from ECMWF re‐analysis version 5 are used as the benchmark for the training. The performance of the model is evaluated by using the independent testing data set, data from a different year, as well as collocated RAOBs, showing improvement to the temperature and moisture profiles by reducing the root‐mean‐squared‐error (RMSE) by more than 30% in the lower atmosphere (from 700 hPa to surface) in both clear sky and partially cloudy conditions. A convective event from June 18, 2017 is presented to illustrate the application of the enhanced low level soundings on high impact weather events. The enhanced soundings from fused data capture the large surface‐based convective available potential energy structures in the preconvection environment, which is very useful for severe storm nowcasting and forecasting applications.