This study addresses a critical issue faced in harsh desert environments characterized by intense sunlight and dusty conditions, which pose significant challenges for applications ranging from solar panels and optical devices to architectural surfaces. In response, we have developed a silica coating that may offer a solution to these environmental challenges. The silica coating exhibits excellent anti-reflective properties, drastically reducing the amount of sunlight reflected from the coated surface and thereby enhancing photon absorption. This study examines the controlled tuning of optical and morphological properties in silica thin films, fabricated through reactive RF magnetron sputtering of an SiO2 target, using various oxygen-to-argon flow ratios [r(O2)=O2/Ar]. Empirical properties of the coatings were systematically examined and demonstrated to be finely tunable by adjusting r(O2). Additionally, surface morphology, as assessed by average roughness (Ra) measurements, was found to be strongly influenced by the oxygen concentration during deposition. Hydrophilicity of the silica coatings was assessed using contact angle measurements, demonstrating that the oxygen content in the films plays a significant role in influencing their hydrophilic properties. Furthermore, micromechanical properties of these silica coatings right after sputtering deposition and those exposed to outdoor conditions were systematically evaluated using Vickers indentation, showing, on one hand, that the hardness of the silica coatings can be regulated by adjusting the oxygen levels introduced during the deposition process, and on the other hand, a high mechanical stability of these silica even after 24 months of outdoor exposure in desert environments. Finally, this study also highlights that dust accumulation on the surface of these silica coatings is inversely proportional to the oxygen content into the films, demonstrating the coatings' self-cleaning properties. The hydrophobicity of the deposited silica thin films further contributes to their self-cleaning capabilities, making them particularly valuable in enhancing the performance of photovoltaic modules, especially in desert environments where dust accumulation can significantly impact efficiency. This multifaceted approach not only improves optical and mechanical properties but also offers a sustainable solution for maintaining the efficiency of solar panels and other devices in challenging environmental conditions.

Lunar exploration has attracted considerable attention, with the lunar poles emerging as the next exploration hot spot for the cold trapping of volatiles in the permanently shadowed regions (PSRs) at these poles. Remote sensing via the satellite's optical load is one of the most important ways to get the scientific data of PSRs. However, the illumination conditions at the lunar poles are quite different from the low latitude areas and how to get appropriate optical signal remains challenging. Thus, simulation of the optical remote sensing process, which provides reference for the choice of satellites' imaging parameters to ensure the implementation of lunar exploration project, is of great value. In this article, an optical imaging chain modeling for the PSRs at the lunar south pole, which includes lunar 3-D topography, observing satellite's orbit, instrument's parameters, and other environmental parameters, has been built. To demonstrate the physical accuracy, some PSRs' observations acquired by narrow angle cameras (NACs) equipped on the lunar reconnaissance orbiter (LRO) are compared with the corresponding images simulated by the proposed imaging chain model. The digital value's difference between the simulated images and real captured images is generally less than 50 for 12-bit images ranging from 0 to 4095, indicating a good fit considering the uncertainty of soil's absolute reflectance and the noise in the real captured images. In addition, the impact of the imaging chain's parameters is revealed with the proposed algorithm. The simulation method will provide reference and assist future optical imaging of PSRs.

Geosynthetic materials are a sustainable solution for pavement applications, but this depends on the materials and their application. Geosynthetics are artificial materials used in pavement construction to improve soil stability, drainage, filtration, separation, and other functions. Geosynthetics in pavement foundations can reduce the need for natural resources such as aggregates, sand, and gravel, allowing conventional construction materials to be used more sustainably. Furthermore, geosynthetics have a longer life span and a lower carbon footprint during production, transportation, and installation when compared to traditional materials. The effectiveness of the geosynthetic material used depends on various factors, including the materials used, the manufacturing process, the application, and the end-of-life disposal. The article seeks to present an overview of geosynthetic products like geogrid and geofoam, as well as their interactions with different pavement foundation soils. This paper delves deeper into the load transfer mechanism in geogrid, and arching effect in the geofoam, and the optimal placement of these materials to improve load-carrying capacity and reduce surface deformations by increasing soil shear strength. Furthermore, the benefit of using geofoam as a replacement material for soil to promote sustainability by conserving natural resources and effectively reusing renewable and recyclable materials was studied. An in-depth evaluation of geofoam response under cyclic loading was also studied.

Salt weathering is a common deterioration phenomenon that affects outdoor cultural properties, and it is important to precisely predict the heat, moisture, and salt transfer in porous materials to suppress salt weathering. Osmosis and osmotic pressure were considered in the field of soil research, especially in clay research, but not in the field of outdoor cultural properties and building materials, which are the main target of salt weathering. Osmosis in clay is supposed to be caused by its surface charge. However, it has been suggested that sandstones and bricks that constitute cultural properties and buildings also have surface charge as clay. Thus, osmosis and osmotic pressure can occur in building materials, which may lead to materials degradation. In this study, we derive basic equations, based on nonequilibrium thermodynamics, for the simultaneous heat, dry air, water vapor, liquid water, cation, and anion transfer in building materials by considering osmosis. This equation was compared with existing model for heat and moisture transfer equations as well as models that considered the salt transfer. Based on the previous research for osmosis in clay, we summarized conditions under which osmosis occurs in building materials and presented an outlook for modeling the physical properties of materials related to osmosis.

This article presents an active acoustic excitation method for leak detection of buried gas pipelines based on cavity resonance reflection. The principles of gas leakage in pipelines are analyzed, including the gas passage model and the gas cavity model. The principle of Helmholtz resonator is employed to establish the cavity model. For the cavity model, the relationships between cavity resonance frequency, acoustic impedance, sound pressure amplification, and leakage damage size are derived. The resonant effect of the gas cavity on the acoustic signal is considered in this study to solve the problem that the echo signal after long distance propagation and reflection becomes very weak. Numerical simulations are conducted to demonstrate the relationships between acoustic reflection coefficient of the leak hole size, cavity volume, and pipe wall thickness. In order to verify the effectiveness of the proposed method, a pipeline experimental rig with a length of 100 m is constructed. Sound waves are generated by a speaker and reflected echoes are received by a microphone. The cavity resonance reflection and echo characteristics of different leak hole size, different transmitting acoustic frequency, and different cavity volume are analyzed. The empirical mode decomposition (EMD) algorithm is used to decompose and reconstruct the echo signals to eliminate the noise interference in the pipeline system. An echo time-distance conversion method is used to visualize the locations of the leak hole and welds. Experimental results show that the proposed method can effectively detect the leak holes and welds in the pipeline.

To provide foundational data for parameter design and performance analysis of high-performance processing equipment, the collision model between jujube-parts and the parameter effects on coefficient of restitution (COR) were investigated. Jujube samples from the sandy lands of southern Xinjiang during the harvest season were utilized, with experimental factors including collision angle, falling height, collision material, moisture content, and collision parts. Single-factor tests and mixed orthogonal tests were conducted to explore the impact of parameter on COR. Utilizing the specular reflection principle, a 3D impact analysis of jujube was performed, and a kinematic model of the falling and impact process was established to determine the COR. Results indicate that the COR of Jun (Zizyphus jujuba cv. Junzao) is higher than that of Hui (Zizyphus jujuba cv. Huizao), and the ventral part exhibits a higher COR compared to the other four parts. Collisions with steel yield higher COR values compared to soil. Furthermore, for collisions with steel material, both Jun and Hui exhibit a decrease in COR with increasing falling height and moisture content, while the COR increases with an increase in collision angle. The influencing factors on COR follow the order of collision material > variety > moisture content > collision angle > falling height > collision part. These findings offer valuable insights for jujube processing research and for preventing mechanical damage to jujube fruits.

Seismic isolation is an effective strategy to mitigate the risk of seismic damage in tunnels. However, the impact of surface -reflected seismic waves on the effectiveness of tunnel isolation layers remains under explored. In this study, we employ the wave function expansion method to provide analytical solutions for the dynamic responses of linings in an elastic half -space and an infinite elastic space. By comparing the results of the two models, we investigate the seismic isolation effect of tunnel isolation layers induced by reflected seismic waves. Our findings reveal significant differences in the dynamic responses of the lining in the elastic half -space and the infinitely elastic space. Specifically, the dynamic stress concentration factor (DSCF) of the lining in the elastic half -space exhibits periodic fluctuations, influenced by the incident wave frequency and tunnel depth, while the DSCF in the infinitely elastic space remain stable. Overall, the seismic isolation application of the tunnel isolation layer is found to be less affected by surfacereflected seismic waves. Our results provide valuable insights for the design and assessment of the seismic isolation effect of tunnel isolation layers.

Obtaining high-visibility images of the lunar polar permanently shadowed region (PSR) is quite important for internal landforms and material existence exploration. However, PSR images usually have poor quality due to a lack of sufficient illumination. Existing researches, that attempt to address this problem, face challenges caused by relying on virtual assumptions, manual processing, and paired data. To solve these problems, we aim to avoid using paired datasets and directly optimize PSR images, and accordingly propose a zero-shot parameter learning model (ZSPL-PSR) for PSR image enhancement. Our ZSPL-PSR, which enhances PSR images by estimating parameters to adjust image properties, consists of a parameter learning network and a parameter weight learning structure. Particularly, first, a parameter learning network that integrates robust information is constructed to separately estimate the midtone brightness parameters, shadow brightness parameters, and contrast parameters. Where these parameters are beneficial for iteratively improve the overall brightness, shadow brightness, and contrast of the image. Second, a parameter weight learning structure is exploited to coordinate the priority of different parameter maps. In addition, to highlight the terrain details in the enhanced PSR image, we use USM sharpening for postprocessing. The experimental results display the fully interpretable enhanced PSR maps of the lunar north and south poles and their sharpened versions, showcasing rich landforms in PSR. To validate the model performance, a benchmark PSR testing set has been constructed, and extensive comparisons conducted on it demonstrated that ZSPL-PSR exceeds other zero-shot learning methods significantly in image quality. Our code is available at https://github.com/dl-zfq/ZSPL-PSR.

Despite their small scales, lunar crustal magnetic fields are routinely associated with observations of reflected and/or backstreaming populations of solar wind protons. Solar wind proton reflection locally reduces the rate of space weathering of the lunar regolith, depresses local sputtering rates of neutrals into the lunar exosphere, and can trigger electromagnetic waves and small-scale collisionless shocks in the near-lunar space plasma environment. Thus, knowledge of both the magnitude and scattering function of solar wind protons from magnetic anomalies is crucial in understanding a wide variety of planetary phenomena at the Moon. We have compiled 5.5years of ARTEMIS (Acceleration, Reconnection, Turbulence and Electrodynamics of the Moon's Interaction with the Sun) observations of reflected protons at the Moon and used a Liouville tracing method to ascertain each proton's reflection location and scattering angles. We find that solar wind proton reflection is largely correlated with crustal magnetic field strength, with anomalies such as South Pole/Aitken Basin (SPA), Mare Marginis, and Gerasimovich reflecting on average 5-12% of the solar wind flux while the unmagnetized surface reflects between 0.1 and 1% in charged form. We present the scattering function of solar wind protons off of the SPA anomaly, showing that the scattering transitions from isotropic at low solar zenith angles to strongly forward scattering at solar zenith angles near 90 degrees. Such scattering is consistent with simulations that have suggested electrostatic fields as the primary mechanism for solar wind proton reflection from crustal magnetic anomalies.