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20th European Conference on Composite materials: Composites Meet Sustainability, ECCM 2022

作者： Hartwig, Marie Gamstedt, E. Kristofer Wohlert, Malin Briot, Corentin Division of Applied Mechanics Department of Materials Science and Engineering Upspala University Uppsala Sweden École Nationale Supérieure de Mécanique et des Microtechniques Rue de l'Épitaphe Besançon France

ISBN: (纸本)9782970161400

In trees, reaction wood, different from the main wood tissue, is formed in branches in order to carry high bending moments and actuate the branch towards upward growth. In conifer species, such as pine and spruce, compressive wood is formed on the lower side of the branch, whereas the upper side is similar to normal wood, prevalent in most parts of the tree. This study explores the function of the compression wood, and shows how it contributes significantly to the flexural strength of the branch, and also serves as a moisture-driven actuator for branch bending. From a composite material perspective, the wood branches show an elegant way to design a beam with high flexural strength and an active bending function in a natural material with a limited number of building blocks (cellulose fibrils in a lignin/hemicellulose matrix). The cellular material is light, strong and stiff in bending, even in the presence of moisture. © 2022 Gamstedt et al.

关键词： Wood

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Hybrid Machine Learning-Enabled Potential Energy Model for Atomistic Simulation of Lithium Intercalation into Graphite from Plating to Overlithiation

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Journal of Chemical Theory and Computation 2023年第14期19卷 4533-4545页

作者： Yang, Po-Yu Chiang, Yu-Hsuan Pao, Chun-Wei Chang, Chien-Cheng Research Center for Applied Sciences Academia Sinica 128 Academia Road Section 2 Nankang Taipei 11529 Taiwan Institute of Applied Mechanics National Taiwan University No. 1 Roosevelt Road Section 4 Taipei 106216 Taiwan Department of Materials Science and Engineering National Dong-Hwa University No. 1 Section 2 Da Hsueh Road Shoufeng Hualien 974301 Taiwan

Graphite is one of the most widely used negative electrode materials for lithium ion batteries (LIBs). However, because of the rapid growth of demands pursuing higher energy density and charging rates, comprehensive insights into the lithium intercalation and plating processes are critical for further boosting the potential of graphite electrodes. Herein, by utilizing the dihedral-angle-corrected registry-dependent potential (DRIP) (Wen et al., Phys. Rev. B 2018, 98, 235404), the Ziegler-Biersack-Littmark (ZBL) potential (Ziegler and Biersack, Astrophysics, Chemistry, and Condensed Matter;1985, pp 93-129), and the machine learning-based spectral neighbor analysis (SNAP) potential (Thompson et al., J. Comput, Phys. 2015, 285, 316-330), we have successfully trained a hybrid machine learning-enabled potential energy model capable of simulating a wide spectrum of lithium intercalation scenario from plating to overlithiation. Our extensive atomistic simulations reveal the trapping of intercalated lithium atoms close to the graphite edges due to high hopping barriers, resulting in lithium plating. Furthermore, we report a stable dense graphite intercalation compound (GIC) LiC₄ with a theoretical capacity of 558 mAh/g, wherein lithium atoms occupy alternating upper/lower graphene hollow sites with a nearest Li-Li distance of 2.8 Å. Surprisingly, following the same lithium insertion manner would allow the nearest Li-Li distance to be retained until the capacity reaches 845.2 mAh/g, corresponding to a GIC of LiC_2.6. Hence, the present study demonstrates that the hybrid machine learning approach could further extend the scope of machine learning energy models, allowing us to investigate the lithium intercalation into graphite over a wide range of intercalation capacity to unveil the underlying mechanisms of lithium plating, diffusion, and discovery of new dense GICs for advanced LIBs with high charging rates and high energy densities. © 2023 American Che

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Autonomous Electron Tomography Reconstruction Using Bayesian Optimization

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Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada 2023年第1期29卷 1915-1916页

作者： Millsaps, William Schwartz, Jonathan Di, Zichao Wendy Jiang, Yi Hovden, Robert Department of Nuclear Engineering Radiological Sciences University of Michigan Ann Arbor MI United States Department of Materials Science and Engineering University of Michigan Ann Arbor MI United States Mathematics and Computer Science Division Argonne National Laboratory Lemont IL United States Advanced Photon Source Facility Argonne National Laboratory Lemont IL United States Applied Physics Program University of Michigan Ann Arbor MI United States

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Strain–Stress Estimation of Vibrational Beam and Plate Using Radiative Energy Transfer Method

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Journal of applied mechanics 2025年第6期92卷 061004页

作者： Zhong, Qiang Cui, Ding Xian, Yuqiang Dai, Chenghao Chen, Haibo National Key Laboratory of Science and Technology on Advanced Laser and High Power Microwave Institute of Applied Electronics Chinese Academy of Engineering Physics Mianyang Sichuan 621025 China CAS Key Laboratory of Mechanical Behavior and Design of Materials Department of Modern Mechanics University of Science and Technology of China Hefei Anhui 230027 China

This study aims to present simple conversion expressions of strains–stresses and the energy density for beams and plates subjected to high-frequency random forces using the radiative energy transfer method (RETM). Euler–Bernoulli beam theory and Kirchhoff plate theory are introduced to describe the deflections of beam and plate. The conversion expressions of strains–stresses and energy density for a single propagation wave are quickly established by dispersion relations. For multi-cylindrical wave fields, the strains–stresses are superimposed by the wave fields generated by the actual source in the domain and the wave fields reflected by the fictitious sources at boundaries according to Huygens’ superposition principle. The conversion expressions of strains–stresses and energy density in the energy finite element method (EFEM), which supposes that the superposition of plane waves forms the wave field, are also derived. Numerical examples indicate that in damping-frequency space, the conversion expressions obtained by RETM have a wider application region than those obtained by EFEM and can be applied to a low-frequency band than the corresponding energy algorithm itself.

关键词： vibration Density structures Waves stress analysis Stress wave propagation

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Transparent Porphyrin-Based Hybrid Films for Spectral Selective Solar Harvesting and Energy Generation

SSRN

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SSRN 2022年

作者： Shi, Donglu Lin, Jou Wang, Yuxin Lyu, Mengyao Deng, Zicheng The Materials Science and Engineering Program Department of Mechanical Materials Engineering College of Engineering and Applied Science University of Cincinnati CincinnatiOH45221 United States

Spectral-selectively solar harvest is achieved in designated frequency regions for photothermal energy generation. In this study, we have designed and synthesized porphyrin-based hybrids that typically exhibit two absorption peaks respectively near 400 nm (blue-violet) and 700 nm (NIR). To be able to tune the optical absorptions for more efficient solar harvest especially in the IR region, unique porphyrin hybrids are developed by incorporating another porphyrin compound such as phthalocyanine, and inorganic Fe 3 O 4 @Cu 2-x S nanoparticles with different absorption characteristics. By controlling the ratio of the components, the hybrids exhibit gradual and consistent changes in the optical spectra, showing high spectral tunability. Transparent thin films of the hybrids are deposited on glass substrates and constructed in parallel for 3D solar harvesting in a cuboid photothermal generator. Solar light is able to pass through the multilayers of thin films, generating significant thermal heat on each one for enhanced energy density. The structural features of the hybrids are well correlated to the optical behaviors based on Raman studies. Also discussed is the operating mechanisms underlying the photothermal behaviors associated with the hybrid structures. © 2022, The Authors. All rights reserved.

关键词： Multilayers

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Quantification of Litter in Cities Using a Smartphone Application and Citizen science in Conjunction with Deep Learning-Based Image Processing

SSRN

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SSRN 2023年

作者： Kako, Shin’ichiro Muroya, Ryunosuke Matsuoka, Daisuke Isobe, Atsuhiko Graduate School of Science and Engineering Department of Engineering Ocean Civil Engineering Program Kagoshima University Japan Japan Agency for Marine-Earth Science and Technology Japan Research Institute for Applied Mechanics Kyushu University Japan

We aimed to classify and quantify the abundance of litter in cities, which is a major source of marine plastic pollution, using citizen science combined with deep learning-based image processing. The project to collect image data including street litter through the smartphone application Pirika was launched in May 2018 and is ongoing and the total number of submitted images has reached one million. Of these, it was visually confirmed that images with clearly distinguished street litter accounted for approximately 30% of all images. Visual classification revealed that the most common types of litter were cans, followed by plastic bags, plastic bottles, cigarette butts, cigarette boxes, and masks. The top six categories account for approximately 80% of the total and the top three categories account for more than 60% of the total imaged litter. Based on these results, a classifier capable of classifying and quantifying these six litter types was constructed using image processing based on deep learning trained using the submitted images. This model was validated using images unused for training. The results revealed that both precision and recall derived from our model were higher than 75%. The quantity of litter derived from automated image processing was also plotted on a map using location data acquired concurrently with the images by the smartphone application. Therefore, we demonstrated that citizen science supported by smartphone applications and deep learning-based image processing is capable of visualizing/quantifying street litter in cities. © 2023, The Authors. All rights reserved.

关键词： Object detection

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Color-fast semi-transparent organic photovoltaics 25

Color-fast semi-transparent organic photovoltaics

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Organic Photonic materials and Devices XXV 2023

作者： Sheriff, Hafiz K.M. Li, Yongxi Forrest, Stephen R. Applied Physics Program University of Michigan Ann ArborMI48109 United States Department of Electrical Engineering University of Michigan Ann ArborMI48109 United States Department of Materials Science and Engineering University of Michigan Ann ArborMI48109 United States Department of Physics University of Michigan Ann ArborMI48109 United States

ISBN: (纸本)9781510659414

Equipping buildings with energy harvesting windows is a practical way to reduce greenhouse gas (GhG) emission. Utilizing semi-transparent organic photovoltaics (ST-OPVs) for this application requires the device to be colorfast, allowing for no change in the aesthetics or light harvesting property of the window. Here, we demonstrate an ST-OPV that is colorfast under 1 Sun AM 1.5G illumination at 50 °C and relative humidity of 34 %. © 2023 SPIE.

关键词： Energy harvesting

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Machine learning of microstructure–property relationships in materials with robust features from foundational vision transformers

arXiv

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arXiv 2025年

作者： Whitman, Sheila E. Latypov, Marat I. Graduate Interdisciplinary Program in Applied Mathematics University of Arizona TucsonAZ85721 United States Department of Materials Science and Engineering University of Arizona TucsonAZ85721 United States

Machine learning of microstructure–property relationships from data is an emerging approach in computational materials science. Most existing machine learning efforts focus on the development of task-specific models for each microstructure–property relationship. We propose utilizing pre-trained foundational vision transformers for the extraction of task-agnostic microstructure features and subsequent light-weight machine learning of a microstructure-dependent property. We demonstrate our approach with pre-trained state-of-the-art vision transformers (CLIP, DINOV2, SAM) in two case studies on machine-learning: (i) elastic modulus of two-phase microstructures based on simulations data;and (ii) Vicker’s hardness of Ni-base and Co-base superalloys based on experimental data published in literature. Our results show the potential of foundational vision transformers for robust microstructure representation and efficient machine learning of microstructure–property relationships without the need for expensive task-specific training or fine-tuning of bespoke deep learning models. © 2025, CC BY.

关键词： Elastic moduli

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Thin-lens equation in elasticity: Imaging with gradient-index phononic crystals

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Physical Review applied 2024年第6期22卷 064054-064054页

作者： P.H. Beoletto F. Nistri A.S. Gliozzi N.M. Pugno F. Bosia Department of Applied Science and Technology Politecnico di Torino C.so Duca degli Abruzzi 24 Torino 10129 Italy Laboratory for Bio-inspired Bionic Nano Meta Materials and Mechanics Department of Civil Environmental and Mechanical Engineering University of Trento Trento 38123 Italy School of Engineering and Materials Science Queen Mary University of London Mile End Road London E1 4NS United Kingdom

Many works in elasticity have exploited the concept of gradient-index (GRIN) lenses, borrowed from optics, for wave focusing and control. These effects are particularly attractive for cloaking, absorption, or energy-harvesting applications. Despite their potential, current lens designs suffer from limitations, mainly related to the difficulty of imaging pointlike sources. Here, we exploit an alternative GRIN lens design that enables a one-to-one correspondence between input and output phase and allows the focal length to be determined using the well-known thin-lens equation, effectively establishing an elastic equivalent of the convex lens in optics. This is demonstrated analytically, obtaining a bijective relation between the location of a pointlike source and its image. The results are also confirmed numerically and experimentally in an aluminum plate, in which the lens is realized by introducing rows of circular cavities of variable diameter. Moreover, a proof-of-concept experiment demonstrates the possibility of imaging sources of flexural waves at the centimeter scale with subwavelength resolution. This research can extend applications of elastic GRIN lenses to new fields such as imaging and nondestructive testing, in which the locations of defects can be identified by focusing the scattered field. Multiple sources can be imaged simultaneously, and the combined effects of multiple lenses can also be used to design more complex systems, opening new possibilities for the technological exploitation of elastic wave manipulation.

关键词： Gradient index optics

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Direct Current Pulse Atmospheric Pressure Plasma Jet Treatment on Electrochemically Deposited NiFe/Carbon Paper and Its Potential Application in an Anion-Exchange Membrane Water Electrolyzer

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Langmuir 2024年第29期40卷 14978-14989页

作者： Yu, Shuo-En Su, Yu-Lun Ni, I-Chih Chuang, Yi-Cheng Hsu, Cheng-Che Wu, Chih-I Chen, Yong-Song Cheng, I-Chun Chen, Jian-Zhang Graduate School of Advanced Technology National Taiwan University Taipei City106319 Taiwan Institute of Applied Mechanics National Taiwan University Taipei City106319 Taiwan Graduate Institute of Photonics and Optoelectronics and Department of Electrical Engineering National Taiwan University Taipei City106319 Taiwan Department of Mechanical Engineering and Advanced Institute of Manufacturing with High-Tech Innovations National Chung Cheng University Chiayi Minhsiung621301 Taiwan Department of Chemical Engineering National Taiwan University Taipei City106319 Taiwan Advanced Research Center for Green Materials Science and Technology National Taiwan University Taipei City106319 Taiwan

An atmospheric pressure plasma jet (APPJ) is used to process electrochemically deposited NiFe on carbon paper (NiFe/CP). The reactive oxygen and nitrogen species (RONs) of the APPJ modify the surface properties, chemical bonding types, and oxidation states of the material at the self-sustained temperature of the APPJ. The APPJ treatment further enhances the hydrophilicity and creates a higher disorder level in the carbon material. Moreover, the metal carbide bonds of NiFe/CP formed in the electrochemical deposition (ED) process are converted to metal oxide bonds after APPJ processing. The potential application of APPJ treatment on NiFe/CP in alkaline water electrolysis is demonstrated. With more oxygen-containing species and better hydrophilicity after APPJ treatment, APPJ-treated NiFe/CP is applied as the electrocatalyst for the oxygen evolution reaction (OER) in alkaline water electrolysis. APPJ-treated NiFe/CP is also used in a custom-made anion-exchange membrane water electrolyzer (AEMWE);this should contribute toward realizing the practical large-scale application of AEM for hydrogen production. © 2024 The Authors. Published by American Chemical Society.

关键词： Hydrophilicity

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