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arXiv 2023年

作者： Qi, Ji Aitken, Z.H. Pei, Qingxiang Tan, Anne Marie Z. Zuo, Yunxing Jhon, M.H. Quek, S.S. Wen, T. Wu, Zhaoxuan Ong, Shyue Ping Materials Science and Engineering Program University of California San Diego 9500 Gilman Dr Mail Code 0448 La Jolla CA92093-0448 United States 1 Fusionopolis Way Connexis #16-16 Singapore138632 Singapore Department of NanoEngineering University of California San Diego 9500 Gilman Dr Mail Code 0448 La Jolla CA92093-0448 United States Department of Mechanical Engineering The University of Hong Kong Hong Kong Department of Materials Science and Engineering City University of Hong Kong Hong Kong Hong Kong Institute for Advanced Study City University of Hong Kong Hong Kong

Dual-phase γ-TiAl and α2-Ti3Al alloys exhibit high strength and creep resistance at high temperatures. However, they suffer from low tensile ductility and fracture toughness at room temperature. Experimental studies show unusual plastic behaviour associated with ordinary and superdislocations, making it necessary to gain a detailed understanding on their core properties in individual phases and at the two-phase interfaces. Unfortunately, extended superdislocation cores are widely dissociated beyond the length scales practical for routine first-principles density-functional theory (DFT) calculations, while extant interatomic potentials are not quantitatively accurate to reveal mechanistic origins of the unusual core-related behaviour in either phases. Here, we develop a highly-accurate moment tensor potential (MTP) for the binary Ti-Al alloy system using a DFT dataset covering a broad range of intermetallic and solid solution structures. The optimized MTP is rigorously benchmarked against both previous and new DFT calculations, and unlike existing potentials, is shown to possess outstanding accuracy in nearly all tested mechanical properties, including lattice parameters, elastic constants, surface energies, and generalized stacking fault energies (GSFE) in both phases. The utility of the MTP is further demonstrated by producing dislocation core structures largely consistent with expectations from DFT-GSFE and experimental observations. The new MTP opens the path to realistic modelling and simulations of bulk lattice and defect properties relevant to the plastic deformation and fracture processes in γ-TiAl and α2-Ti3Al dual-phase alloys. © 2023, CC BY.

关键词： Aluminum alloys

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Full Crystallographic Imaging of Hexagonal Boron Nitride Monolayers with Phonon-Enhanced Sum-Frequency Microscopy

arXiv

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arXiv 2025年

作者： Mueller, Niclas S. Fellows, Alexander P. John, Ben Naclerio, Andrew E. Carbogno, Christian Gharagozloo-Hubmann, Katayoun Baláž, Damián Kowalski, Ryan A. Heenen, Hendrik H. Scheurer, Christoph Reuter, Karsten Caldwell, Joshua D. Wolf, Martin Kidambi, Piran R. Thämer, Martin Paarmann, Alexander Department of Physical Chemistry Fritz-Haber-Institute of the Max-Planck-Society Berlin14195 Germany Department of Chemical and Biomolecular Engineering Vanderbilt University NashvilleTN37235 United States Theory Department Fritz-Haber-Institute of the Max-Planck-Society Berlin14195 Germany Department of Physics Freie Universität Berlin Berlin14195 Germany Department of Mechanical Engineering Vanderbilt University NashvilleTN37235 United States Interdisciplinary Materials Science Program Vanderbilt University NashvilleTN37235 United States

Hexagonal boron nitride (hBN) is an important 2D material for van der Waals heterostructures, single photon emitters, and infrared nanophotonics. The optical characterization of mono- and few-layer samples of hBN however remains a challenge as the material is almost invisible optically. Here we introduce phase-resolved sum-frequency microscopy as a technique for imaging monolayers of hBN grown by chemical vapor deposition (CVD) and visualize their crystal orientation. A combination of femtosecond mid-infrared (IR) and visible laser pulses is used for sum-frequency generation (SFG), which is imaged in a wide-field optical microscope. The IR laser resonantly excites a phonon of hBN that leads to an ~800-fold enhancement of the SFG intensity, making it possible to image large 100x100 µm2 sample areas in less than 1 s. Implementing heterodyne detection in combination with azimuthal rotation of the sample further provides full crystallographic information. Through combined knowledge of topography and crystal orientation, we find that triangular domains of CVD-grown monolayer hBN have nitrogen-terminated zigzag edges. Overall, SFG microscopy can be used as an ultra-sensitive tool to image crystal structure, strain, stacking sequences, and twist angles, and is applicable to the wide range of van der Waals structures, where location and identification of monolayer regions and interfaces with broken inversion symmetry is of paramount importance. © 2025, CC BY.

关键词： Van der Waals forces

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Recover energy and materials from agricultural waste via thermalchemical conversion (vol 5, pg 1200, 2022)

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ONE EARTH 2022年第12期5卷 1404-1404页

作者： Lee, Kuan-Tieng Chen, Wei-Hsin Sarles, Paul Park, Young-Kwon Ok, Yong Sik Department of Aeronautics and Astronautics National Cheng Kung University Tainan 701 Taiwan Research Center for Smart Sustainable Circular Economy Tunghai University Taichung 407 Taiwan Department of Mechanical Engineering National Chin-Yi University of Technology Taichung 411 Taiwan International Master Degree Program on Energy National Cheng Kung University Tainan 701 Taiwan School of Environmental Engineering University of Seoul Seoul 02504 Republic of Korea Korea Biochar Research Center APRU Sustainable Waste Management Program & Division of Environmental Science and Ecological Engineering Korea University Seoul Republic of Korea

Every year, at least 1,300 million tons of agricultural waste is produced, and the amount is likely to expand further in a world with a growing population to feed. Our current linear approach to handling this vast amount of waste via landfills and incineration has already contributed to about 3% of global greenhouse gas emissions and also created various toxic pollutants. There is an urgent need to sustainably manage agricultural waste that can benefit both the environment and humans. Thermochemical conversion emerges as a promising technology that can convert agricultural waste into a variety of valuable products, creating circularity opportunities. In this primer, we explain the thermochemical conversion of agricultural waste by illustrating four mainstreaming processes. We further discuss the potential tradeoffs of these processes in terms of their environmental externalities and reflect upon the potential toward a circular and net-zero future.

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Mimicking the motion of metallic interfaces with spacetime switching

Mimicking the motion of metallic interfaces with spacetime s...

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International Congress on Advanced Electromagnetic Materials in Microwaves and Optics (METAMATERIALS)

作者： D. M. Solís S. Yin E. Galiffi A. Alù N. Engheta Departamento de Tecnología de los Computadores y de las Comunicaciones University of Extremadura Cáceres Spain Photonics Initiative Advanced Science Research Center City University of New York New York USA Physics Program Graduate Center City University of New York New York USA Department of Electrical and Systems Engineering University of Pennsylvania Philadelphia PA USA

ISBN: (数字)9798350373493

ISBN: (纸本)9798350373509

Inspired by the need of recognizing novel mechanisms to engineer time and spacetime inhomogeneities, we theoretically explore the possibilities of inducing fast temporal changes in the structural dispersion of a one-dimensional parallel-plate cavity. In this work, we delve into the variation of interplate distance not by actual motion of the cavity’s metallic boundaries, but through the effective subluminal synthetic motion that emerges from a judicious switching operation in the metallic region, parameterized as a lossless spacetime-varying plasma. We theoretically show how, depending on the nature of this time-dispersive switching process, different boundary conditions apply, providing richer physics than true motion.

关键词： Frequency synthesizers Resonant frequency Switches Boundary conditions Nonhomogeneous media Frequency conversion Metamaterials Plasmas Fabry-Perot Physics

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Oxygen Transfer and Fragmentation of Aspergillus niger Pellets in Stirred Tank and Concentric-Duct Airlift Bioreactors

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Industrial Biotechnology 2020年第2期16卷 67-74页

作者： Buffo, Mariane M. Esperança, Mateus N. Béttega, Rodrigo Farinas, Cristiane S. Badino, Alberto C. Graduate Program of Chemical Engineering Federal University of São Carlos São Carlos13565-905 Brazil Federal Institute of Education Science and Technology of São Paulo Campus Capivari Capivari Brazil Embrapa Instrumentation São Carlos Brazil

The hydrodynamic environment in bioreactors is an important parameter because cultivation conditions that provide satisfactory oxygen transfer rates tend to be harmful to microorganisms, due to the effect of shear on the cellular structure. Consequently, it is a challenge to find the ideal set of bioreactor operating conditions that favor production of the metabolites of interest. The present work evaluated the fragmentation of Aspergillus niger pellets in two different types of bioreactor: a conventional stirred tank bioreactor (STB) and a concentric-duct airlift (CDA) bioreactor. Both were operated under similar oxygen transfer or shear conditions. Oxygen transfer was quantified by means of the volumetric oxygen transfer coefficient (kLa). The shear condition was determined using the average shear rate (γav), obtained using computational fluid dynamics (CFD), together with pellet fragmentation. The findings showed that the CDA bioreactor caused less fragmentation of the pellets, compared to the STB, when both systems were operated with the same kLa values. For similar fragmentation levels, the kLa value for the CDA bioreactor was 38% higher than observed for the STB. Considering the results for both bioreactor models, the fragmentation of A. niger pellets, represented by the variation of the average normalized A. niger pellet equivalent diameter (Deq/Deq,0) after fragmentation assays of 4 h duration (Δfrag), exhibited a linear relation with γav (R2 = 0.97). The CDA bioreactor also presented advantages in terms of specific power consumption and mass transfer efficiency. These results should assist in the selection of suitable bioreactor models and operating conditions, in order to improve the efficiency of industrial production of bio-based products. © 2020, Mary Ann Liebert, Inc., publishers 2020.

关键词： Bioreactors

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Deep-operator-network-based Mars entry parametric bank angle profile optimization

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Chinese Journal of Aeronautics 2025年

作者： Bo TANG Yanning GUO Youmin GONG Jie MEI Weiren WU School of Aerospace Science Harbin Institute of Technology Shenzhen 518055 China Department of Control Science and Engineering Harbin Institute of Technology Harbin 150001 China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen 518055 China Lunar Exploration Program and Space Engineering Center Beijing 100190 China

Rapid and reliable onboard optimization of bank angle profiles is crucial for mitigating uncertainties during Mars atmospheric entry. This paper presents a neural-network-accelerated methodology for optimizing parametric bank angle profiles in Mars atmospheric entry missions. The methodology includes a universal approach to handling path constraints and a reliable solution method based on the Particle Swarm Optimization (PSO) algorithm. For illustrative purposes, a mission with the objective of maximizing terminal altitude is considered. The original entry optimization problem is converted into optimizing three coefficients for the bank angle profiles with terminal constraints by formulating a parametric Mars entry bank angle profile and constraint handling methods. The parameter optimization problem is addressed using the PSO algorithm, with reliability enhanced by increasing the PSO swarm size. To improve computational efficiency, an enhanced Deep Operator Network (DeepONet) is used as a dynamics solver to predict terminal states under various bank angle profiles rapidly. Numerical simulations demonstrate that the proposed methodology ensures reliable convergence with a sufficiently large PSO swarm while maintaining high computational efficiency facilitated by the neural-network-based dynamics solver. Compared to the existing methodologies, this methodology offers a streamlined process, the reduced sensitivity to initial guesses, and the improved computational efficiency.

关键词： Mars entry Bank angle profile Particle swarm optimization Neural networks Operator learning

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Molecular interaction volume model of mixing enthalpy for molten salt system: An integrated calorimetry-model case study of LaCl3-(LiCl-KCl)

arXiv

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arXiv 2024年

作者： Goncharov, Vitaliy G. Smith, William Li, Jiahong Eakin, Jeffrey A. Reinhart, Erik D. Boncella, James Gibson, Luke D. Bryantsev, Vyacheslav S. Gong, Rushi Shang, Shun-Li Liu, Zi-Kui Xu, Hongwu Clark, Aurora Guo, Xiaofeng Department of Chemistry Washington State University PullmanWA99164 United States Materials Science and Engineering Program Washington State University PullmanWA99164 United States Computational Sciences and Engineering Division Oak Ridge National Laboratory P.O. Box 2008 Oak RidgeTN37831 United States Chemical Science Division Oak Ridge National Laboratory P.O. Box 2008 Oak RidgeTN37831 United States Department of Materials Science and Engineering Pennsylvania State University University ParkPA16802 United States Earth and Environmental Sciences Division Los Alamos National Laboratory Los Alamos New MexicoNM87545 United States Arizona State University TempeAZ United States Department of Chemistry The University of Utah Salt Lake CityUT84112 United States

Calorimetric determination of enthalpies of mixing (ΔHmix) of multicomponent molten salts often employs empirical models that lack parameters with clear physical interpretation (e.g., coordination numbers, molar volumes, and pair potentials). Although such physics informed models are not always needed, a thermodynamic understanding of the relationships between excess energies of mixing and local to intermediate solvation structures is particularly important for pyrochemical separation, as is the case for lanthanides (Ln), which are common neutron poisons and critical industrial elements found in spent nuclear fuels. Here we implement the molecular interaction volume model (MIVM) to synthesize information from experimentally measured ΔHmix (using high temperature melt drop calorimetry) and the distribution of solvation structures from ab initio molecular dynamics (AIMD) simulations. This was demonstrated by a case study of molten salt system consisted of LaCl3 mixing with a eutectic LiCl-KCl (58mol% - 42mol%) at 873 K and 1133 K. The parameters modelled from MIVM were used to extrapolate excess Gibbs energy (ΔGmix), and compositional dependence of La3+ activity in the LaCl3-(LiCl-KCl) system. In contrast, by AIMD or polarizable ion model (PIM) simulations, a significant deviation regarding the predicted ΔHmix was seen if computed directly from the molecular dynamic trajectories. The integrated experimental and simulation data within the MIVM formalism are generalizable to a wide variety of molten salts and demonstrate a significant improvement over currently employed methods to study molten salts for nuclear and separations sciences. Copyright © 2024, The Authors. All rights reserved.

关键词： Enthalpy

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Ultrasound-Guided Deep Learning for Regional Nerve Block Anesthesia in Scapular Fracture

Ultrasound-Guided Deep Learning for Regional Nerve Block Ane...

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Distributed Computing and Electrical Circuits and Electronics (ICDCECE), IEEE International Conference on

作者： Upasna Joshi Mohan Raparthi Ramswaroop Reddy Pramod Kumar Praveen Thuniki Mohammad Shabaz Delhi Technical Campus Greater Noida India Software Engineer Alphabet Life Science Dallas Texas USA Yellu Independent Research Richmond VA 23233 University of Texas Austin US Ganga Institute of Technology and Management Haryana India Independent Research Sr Program Analyst Georgia Cumming GA USA Model Institute of Engineering and Technology Jammu J&K India

ISBN: (数字)9798350318609

ISBN: (纸本)9798350318616

This study introduces a novel approach to regional nerve block anesthesia in scapular fractures by integrating ultrasound guidance with deep learning techniques. The proposed method leverages advanced imaging modalities and state-of-the-art deep learning models to achieve precise nerve localization amidst complex fracture patterns. Through extensive experimentation and evaluation, we demonstrate the effectiveness of the proposed method in enhancing surgical planning, intraoperative decision-making, and patient safety. This study represents a significant advancement in the field of orthopedic surgery, offering a promising solution for improving outcomes and quality of life for patients with scapular fractures. The method this study suggests for locating nerves in shoulder fractures advances orthopaedic surgery. We can improve, expedite, and streamline procedures with the use of AI and medical imaging. This will improve the quality of life and outcomes for scapular fractures.

关键词： Deep learning Location awareness Ultrasonic imaging Orthopedic surgery Decision making Shoulder Anesthesia

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Towards RehabCoach: Design and Preliminary Evaluation of a Conversational Agent Supporting Unsupervised Therapy After Stroke

Towards RehabCoach: Design and Preliminary Evaluation of a C...

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IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)

作者： Giada Devittori Mehdi Akeddar Alexandra Retevoi Fabian Schneider Viktoria Cvetkova Daria Dinacci Antonella Califfi Paolo Rossi Claudio Petrillo Tobias Kowatsch Olivier Lambercy Rehabilitation Engineering Laboratory ETH Zurich Switzerland Department of Technology Management and Economics ETH Zurich Switzerland Clinica Hildebrand Centro di riabilitazione Brissago Switzerland Institute for Implementation Science in Health Care University of Zurich Switzerland School of Medicine University of St. Gallen Switzerland Future Health Technologies program Singapore-ETH Centre Campus for Research Excellence and Technological Enterprise (CREATE) Singapore

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

Unsupervised therapy after stroke is a promising way to boost therapy dose without significantly increasing the workload on healthcare professionals. However, it raises important challenges, such as lower adherence to therapy in the absence of social interaction with therapists. We present the initial prototype of RehabCoach, a novel smartphone-based app with conversational agent to support unsupervised therapy. RehabCoach is designed to increase patients' engagement and adherence to therapy and to provide information (e.g., about stroke, health) in an interactive and user-friendly manner. We report on the design and usability evaluation of the first prototype of RehabCoach, assessed by four stroke patients and five healthcare professionals, who interacted with the app in a single testing session. Task completion time and success rates were measured for 15 representative tasks, and participants assessed usability via questionnaires and a semi-structured interview. Results show that it was feasible for stroke patients to successfully interact with RehabCoach (task success ≥93%) without requiring extensive training. Participants positively rated the usability of RehabCoach (mean mHealth App Usability Questionnaire score: 1.3 for primary users, 1.4 for healthcare professionals, on a scale from 1 (positive evaluation) to 7). The feedback collected in this work opens the door to further enhance RehabCoach as an interactive digital tool to support unsupervised rehabilitation.

关键词： Training Medical treatment Prototypes Stroke (medical condition) Particle measurements Time measurement Usability Interviews Robots Testing

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Revealing preference in popular music through familiarity and brain response

arXiv

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arXiv 2021年

作者： Sangnark, Soravitt Autthasan, Phairot Ponglertnapakorn, Puntawat Chalekarn, Phudit Sudhawiyangkul, Thapanun Trakulruangroj, Manatsanan Songsermsawad, Sarita Assabumrungrat, Rawin Amplod, Supalak Ounjai, Kajornvut Wilaiprasitporn, Theerawit Bio-inspired Robotics and Neural Engineering Lab. School of Information Science and Technology Vidyasirimedhi Institute of Science & Technology Rayong Thailand Vision and Learning Lab. School of Information Science and Technology Vidyasirimedhi Institute of Science & Technology Rayong Thailand School of Energy Science and Engineering Vidyasirimedhi Institute of Science & Technology Rayong Thailand Biological Engineering program Faculty of Engineering Neuroscience Center for Research and Innovation Learning Institute King Mongkut’s University of Technology Thonburi Thailand Faculty of Electrical Engineering Sirindhorn International Institute of Technology Thammasat University Thailand School of Engineering Tohoku University Japan

Music preference was reported as a factor, which could elicit innermost music emotion, entailing accurate ground-truth data and music therapy efficiency. This study executes statistical analysis to investigate the distinction of music preference through familiarity scores, response times (response rates), and brain response (EEG). Twenty participants did self-assessment after listening to two types of popular music’s chorus section: music without lyrics (Melody) and music with lyrics (Song). We then conduct a music preference classification using a support vector machine, random forest, and k-nearest neighbors with the familiarity scores, the response rates, and EEG as the feature vectors. The statistical analysis and F1-score of EEG are congruent, which is the brain’s right side outperformed its left side in classification performance. Finally, these behavioral and brain studies support that preference, familiarity, and response rates can contribute to the music emotion experiment’s design to understand music, emotion, and listener. Not only to the music industry, the biomedical and healthcare industry can also exploit this experiment to collect data from patients to improve the efficiency of healing by music. © 2021, CC BY-NC-ND.

关键词： Decision trees

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