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Bio-based materials with excellent acoustic absorption properties are in great demand in architecture, interior, and human settlement applications for efficient noise control. In this study, crayfish shells, a form of kitchen waste, are utilized as the primary material to produce ultralight and multifunctional chitin aerogels, which effectively eliminate noise. Different replacement solvents and freezing rates were employed to regulate the porous structures of chitin aerogels, and their resulting acoustic absorption performance was investigated. Results demonstrate that employing deionized water as the replacement solvent and utilizing a common-freeze mode (frozen via refrigerator at -26 °C) can produce chitin aerogels with larger porosity (96.26%) and apertures, as well as thicker pore walls. This results in superior broadband acoustic absorption performance (with a maximum absorption coefficient reaching 0.99) and higher Young's modulus (28 kPa). Conversely, chitin aerogels solvent-exchanged with tert -butyl alcohol or subjected to quick-freeze mode (frozen via liquid nitrogen) exhibit smaller porosity (92.32% and 94.84%) and apertures, thereby possessing stronger diffuse reflection of visible light (average reflectance of 94.30% and 88.18%), and enhanced low-frequency (500 to 1600 Hz) acoustic absorption properties. Additionally, the acoustic absorption mechanism of fabricated chitin aerogels was predicted using a simple three-parameter analysis Johnson-Champoux-Allard-Lafarge (JCAL) model. This study presents a novel approach to developing multifunctional biomass materials with excellent acoustic absorption properties, which could have a wide range of potential applications., Competing Interests: The authors declare that they have no conflict of interest., (This journal is © The Royal Society of Chemistry.)

SAR imagery plays a crucial role in geological and environmental monitoring, particularly in highland mountainous regions. However, inherent geometric distortions in SAR images often undermine the precision of remote sensing analyses. Accurately identifying and classifying these distortions is key to analyzing their origins and enhancing the quality and accuracy of monitoring efforts. While the layover and shadow map (LSM) approach is commonly utilized to identify distortions, it falls short in classifying subtle ones. This study introduces a novel LSM ground-range slope (LG) method, tailored for the refined identification of minor distortions to augment the LSM approach. We implemented the LG method on Sentinel-1 SAR imagery from the tri-junction area where the Xiaojiang, Pudu, and Jinsha rivers converge at the Yunnan-Sichuan border. By comparing effective monitoring-point densities, we evaluated and validated traditional methods-LSM, R-Index, and P-NG-against the LG method. The LG method demonstrates superior performance in discriminating subtle distortions within complex terrains through its secondary classification process, which allows for precise and comprehensive recognition of geometric distortions. Furthermore, our research examines the impact of varying slope parameters during the classification process on the accuracy of distortion identification. This study addresses significant gaps in recognizing geometric distortions and lays a foundation for more precise SAR imagery analysis in complex geographic settings.

Cellulose aerogels have great prospects for noise reduction applications due to their sustainable value and superior 3D interconnected porous structures. The drying principle is a crucial factor in the preparation process for developing high-performance aerogels, particularly with respect to achieving high acoustic absorption properties. In this study, multifunctional cellulose nanocrystal (CNC) aerogels were conveniently prepared using two distinct freeze-drying principles: refrigerator conventional freezing (RCF) and liquid nitrogen unidirectional freezing (LnUF). The results indicate that the rapid RCF process resulted in a denser CNC aerogel structure with disordered larger pores, causing a stronger compressive performance (Young's modulus of 40 kPa). On the contrary, the LnUF process constructed ordered structures of CNC aerogels with a lower bulk density (0.03 g/cm 3 ) and smaller apertures, resulting in better thermal stability, higher diffuse reflection across visible light, and especially increased acoustic absorption performance at low-mid frequencies (600-3000 Hz). Moreover, the dissipation mechanism of sound energy in the fabricated CNC aerogels is predicted by a designed porous media model. This work not only paves the way for optimizing the performance of aerogels through structure control, but also provides a new perspective for developing sustainable and efficient acoustic absorptive materials for a wide range of applications.

The tropospheric delay caused by the temporal and spatial variation of meteorological parameters is the main error source in interferometric synthetic aperture radar (InSAR) applications for geodesy. To minimize the impact of tropospheric delay errors, it is necessary to select the appropriate tropospheric delay correction method for different regions. In this study, the interferogram results of the InSAR, corrected for tropospheric delay using the Linear, Generic Atmospheric Correction Online Service for InSAR (GACOS) and ERA-5 atmospheric reanalysis dataset (ERA5) methods, are presented for the study area of the junction of the Hengduan Mountains and the Yunnan-Kweichow Plateau, which is significantly influenced by the plateau monsoon climate. Four representative regions, Eryuan, Binchuan, Dali, and Yangbi, are selected for the study and analysis. The phase standard deviation (STD), phase-height correlation, and global navigation satellite system (GNSS) data were used to evaluate the effect of tropospheric delay correction by integrating topographic, seasonal, and meteorological factors. The results show that all three methods can attenuate the tropospheric delay, but the correction effect varies with spatial and temporal characteristics.

Al-Ti-C-(Ce) grain refiners were prepared by combining in-situ reaction, hot extrusion, and adding CeO 2 . The effects of second phase TiC particle size and distribution, extrusion ratio, and Ce addition on the grain-refining performance of grain refiners were investigated. The results show that about 10 nm TiC particles are dispersed on the surface and inside of 100-200 nm Ti particles by in-situ reaction. The Al-Ti-C grain refiners, which are made, by hot extrusion, of a mixture of in-situ reaction Ti/TiC composite powder and Al powder, increase the effective nucleation phase of α-Al and hinder grain growth due to the fine and dispersed TiC; this results in the average size of pure aluminum grains to decrease from 1912.4 μm to 504.8 μm (adding 1 wt.% Al-Ti-C grain refiner). Additionally, with the increase of the extrusion ratio from 13 to 30, the average size of pure aluminum grains decreases further to 470.8 μm. This is because the micropores in the matrix of grain refiners are reduced, and the nano-TiC aggregates are dispersed with the fragmentation of Ti particles, resulting in a sufficient Al-Ti reaction and an enhanced nucleation effect of nano-TiC. Furthermore, Al-Ti-C-Ce grain refiners were prepared by adding CeO 2 . Under the conditions of holding for 3-5 min and adding a 5.5 wt.% Al-Ti-C-Ce grain refiner, the average size of pure aluminum grains is reduced to 48.4-48.8 μm. The reason for the excellent grain-refining and good anti-fading performance of the Al-Ti-C-Ce grain refiner is presumedly related to the Ti 2 Al 20 Ce rare earth phases and [Ce] atoms, which hinder agglomeration, precipitation, and dissolution of the TiC and TiAl 3 particles.

To extract blue roofs (BRs) from remote sensing images quickly, first, this study used WorldView-2 and WorldView-3 as the data sources and created a new BR spectral area model (BRSAM) using the polygon area difference between the spectral curves of BRs and other image categories in bands 2-8. Then the extraction effect of BRSAM with those of the blue ground object spectral index (BGOSI), blue object spectrum index (BOSI) and maximum likelihood classification was compared; the results showed that BRSAM overcomes the shortcomings of BGOSI and BOSI, i.e. erroneously extracted shadow and white and yellow ground objects as BRs. However, BRSAM has the disadvantage of erroneously extracting some vegetation and green plastic playground as BRs. Considering that the disadvantage of one of BRSAM, BGOSI, and BOSI in extracting BRs can be compensated by the two other spectral models/indices, we combined the three spectral models/indices and used the synthetic spectral model to extract BRs. Notably, the synthetic spectral model overcomes the shortcomings of the three spectral models in BR extraction, and its effect is better than any one of them separately used. Meanwhile, the spectral model/index method used in BR extraction is better than the classification method. The spectral model/index method is a convenient and effective method for BR extraction, which could be used as a reference in the classification of other data., Competing Interests: The authors declare no conflict of interest., (© 2022 The Author(s).)