In this study, the sound absorption characteristics of hexagonal close-packed and face-centered cubic lattices were estimated by theoretical analysis. Propagation constants and characteristic impedances were obtained by dividing each structure into elements perpendicular to the incident direction of sound waves and by approximating each element to a clearance between two parallel planes. Consequently, the propagation constant and the characteristic impedance were treated as a one-dimensional transfer matrix in the propagation of sound waves, and the normal incident sound absorption coefficient was calculated by the transfer matrix method. The theoretical value of the sound absorption coefficient was derived by using the effective density applied to the measured tortuosity. As a result, the theoretical value was becoming closer to the measured value. Therefore, the measured tortuosity is reasonable.
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http://dx.doi.org/10.3390/ma15207393 | DOI Listing |
Adv Sci (Weinh)
January 2025
Department of Pediatrics and Adolescent Medicine, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, 91054, Germany.
Multispectral optoacoustic tomography is a promising medical imaging modality that combines light and sound to provide molecular imaging information at depths of several centimeters, based on the optical absorption of endogenous chromophores, such as hemoglobin. Assessment of inflammatory bowel disease has emerged as a promising clinical application of optoacoustic tomography. In this context, preclinical studies in animal models are essential to identify novel disease-specific imaging biomarkers and understand findings from emerging clinical pilot studies, however to-date, these studies have been limited by the precise identification of the bowel wall.
View Article and Find Full Text PDFInt J Biol Macromol
January 2025
College of Textiles Science and Engineering, Wuhan Textile University, Wuhan 430200, China; State Key Laboratory of New Textile Materials and Advanced Processing Technologies, Wuhan Textile University, Wuhan 430200, China. Electronic address:
Faced with all kinds of serious ecological and environmental protection problems in today's society, development must take the sustainable and green road. Nanocellulose aerogels with the advantages of wide resource of raw materials, low cost, good biocompatibility and biodegradation, are good thermal and sound insulation materials. Herein, a versatile composite aerogel with good thermal stability and heat-insulating property was prepared by freeze-drying method using cellulose nanocrystals (CNCs), waterborne polyurethane (WPU) and sepiolite (SEP) as substrates.
View Article and Find Full Text PDFSmall
January 2025
Faculty of Physics and Astronomy, Adam Mickiewicz University, Poznan, 61-614, Poland.
The behavior of triple-cation mixed halide perovskite solar cells (PSCs) under ultrashort laser pulse irradiation at varying fluences is investigated, with a focus on local heating effects observed in femtosecond transient absorption (TA) studies. The carrier cooling time constant is found to increase from 230 fs at 2 µJ cm⁻ to 1.3 ps at 2 mJ cm⁻ while the charge population decay accelerates from tens of nanoseconds to the picosecond range within the same fluence range.
View Article and Find Full Text PDFAdv Sci (Weinh)
January 2025
Department of Biotechnology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China.
Current sound-absorbing materials, reliant on nonrenewable resources, pose sustainability and disposal challenges. This study introduces a novel collagen-lignin sponge (CLS), a renewable biomass-based material that combines collagen's acoustic properties with lignin's structural benefits. CLSs demonstrate high porosity (>0.
View Article and Find Full Text PDFSci Rep
January 2025
School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai, 201620, China.
This research presents a method based on deep learning for the reverse design of sound-absorbing structures. Traditional methods require time-consuming individual numerical simulations followed by cumbersome calculations, whereas the deep learning design method significantly simplifies the design process, achieving efficient and rapid design objectives. By utilizing deep neural networks, a mapping relationship between structural parameters and the sound absorption coefficient curve is established.
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