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Resolving Contradictory Estimates of Band Gaps of Bulk PdSe2: A Wannier-Localized Optimally-Tuned Screened Range-Separated Hybrid Density Functional Theory Study

arXiv

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arXiv 2025年

作者： Florio, Fred Camarasa-Gómez, María Ohad, Guy Naveh, Doron Kronik, Leeor Ramasubramaniam, Ashwin Department of Mechanical and Industrial Engineering University of Massachusetts Amherst AmherstMA01003 United States Department of Molecular Chemistry and Materials Science Weizmann Institute of Science Rehovoth7610001 Israel Institute for Nanotechnology and Advanced Materials Bar-Ilan University Ramat Gan52900 Israel Materials Science and Engineering Graduate Program University of Massachusetts Amherst AmherstMA01003 United States

Palladium diselenide (PdSe2)—a layered van der Waals material—is attracting significant attention for optoelectronics due to the wide tunability of its band gap from the infrared through the visible range as a function of the number of layers. However, there continues to be disagreement over the precise nature and value of the optical band gap of bulk PdSe2, owing to the rather small value of this gap that complicates experimental measurements and their interpretation. Here, we design and employ a Wannier-localized optimally-tuned screened range-separated hybrid (WOT-SRSH) functional to investigate the electronic bandstructures and optical absorption spectra of bulk and monolayer PdSe2. In particular, we account carefully for the finite exciton center-of-mass momentum within a time-dependent WOT-SRSH framework to calculate the indirect optical gap and absorption onset accurately. Our results agree well with the best available photoconductivity measurements, as well as with state-of-the-art many-body perturbation theory calculations, confirming that bulk PdSe2 has an optical gap in the mid-infrared (upper-bound of 0.44 eV). More generally, this work further bolsters the utility of the WOT-SRSH approach for predictive modeling of layered semiconductors. Copyright © 2025, The Authors. All rights reserved.

关键词： Layered semiconductors

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Formability of Third Generation Advanced High Strength Steel: Experimental and Theoretical Approach

SSRN

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SSRN 2024年

作者： Butuc, Marilena C. Vincze, Gabriela Santos, Rafael Pereira, António Santos, Abel D. Amaral, Rui L. Barlat, Frederic Centre for Mechanical Technology and Automation Department of Mechanical Engineering University of Aveiro Portugal LASI - Intelligent Systems Associate Laboratory Guimarães Portugal Graduate Program in Metallurgical Engineering Universidade Federal Fluminense Rio de Janeiro Volta Redonda Brazil Faculty of Engineering University of Porto R. Dr. Roberto Frias s/n Porto4200-465 Portugal INEGI – Institute of Science and Innovation in Mechanical and Industrial Engineering Portugal Graduate Institute of Ferrous Technology Pohang University of Science and Technology Korea Republic of

The aim of this paper is to evaluate, predict and analyze the plastic properties and formability of third-generation advanced high-strength steel (3genAHSS), with a specific focus on USS CR980XG3™️ AHSS as the reference material. Forming limit diagrams were determined, utilizing a range of experimental methods, including Nakajima tests, Erichsen tests, uniaxial tensile tests, and the Bulge test. A pivotal aspect is the application of an advanced sheet metal forming limit model based on Marciniak-Kuczynski analysis to simulate localized necking onset. Various constitutive equations, such as von Mises, Hill 48, and Yld2000-2d yield conditions, were used in simulation, alongside strain hardening laws like Swift and Voce. Comparative analyses were conducted to assess the accuracy of different models in predicting forming limits, with a particular emphasis on the influence of strain rate sensitivity. The study underscores the significant impact of the experimental method on forming limit values, highlighting that Yld2000-2d and the Swift hardening law with strain rate sensitivity provide optimal reproducibility of experimental data. Furthermore, the research emphasizes the necessity of considering strain rate sensitivity for accurate numerical simulations, stressing the effectiveness of the Marciniak-Kuczynski model when combined with proper constitutive equations in predicting forming limits for USS CR980XG3™️ AHSS. © 2024, The Authors. All rights reserved.

关键词： Strain hardening

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Study of Machine Learning Techniques for Damage Identification in a Beam 10th

Study of Machine Learning Techniques for Damage Identifica...

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10th International Conference on Wave Mechanics and Vibrations, WMVC 2022

作者： da Silva Coelho, Jefferson de Sousa, Amanda Aryda Silva Rodrigues Machado, Marcela Rodrigues Dutkiewicz, Maciej Department of Mechanical Engineering University of Brasília Campus Universitário Darcy Ribeiro Faculdade de Tecnologia - Asa Norte DF Brasília Brazil Post-Graduate Program - Integrity of Engineering Materials University of Brasília Campus Universitário Darcy Ribeiro Faculdade de Tecnologia - Asa Norte DF Brasília70910-900 Brazil Faculty of Civil Environmental Engineering and Architecture University of Science and Technology Bydgoszcz85-796 Poland

ISBN: (纸本)9783031157578

Damage is defined as any change to the material, geometry or boundary condition that can modify the structure’s properties or response. In the past, damage identification was performed through periodical inspection, non-destructive testing/non-destructive evaluation, or visual observation. Structural health monitoring (SHM) has emerged to transition from offline damage identification to near real-time and online damage assessment. Hence, SHM is a damage detection strategy to monitor a structure for a period using a series of continuous measurement devices, which then collect the system’s characteristics and subsequently perform statistical analysis to assess the current circumstances and health of the structure. One of the first steps for the study of SHM is damage detection followed by monitoring. Machine Learning (ML) techniques can be used to develop viable algorithms to make potential predictions. ML algorithms are therefore providing the tools needed to enhance the capabilities of SHM systems and provide intelligent solutions to past challenges. Preliminary studies have reviewed that the extension of ML into SHM has dramatically increased the system’s capabilities, providing innovative solutions to different research challenges. This work conducts a study of the use of ML to identify damage in a beam and discuss the challenge of usage, performance and implementation of each technique. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Decision trees

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NOMAD: nonlinear manifold decoders for operator learning 22

NOMAD: nonlinear manifold decoders for operator learning

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Proceedings of the 36th International Conference on Neural Information Processing Systems

作者： Jacob H. Seidman Georgios Kissas Paris Perdikaris George J. Pappas Graduate Program in Applied Mathematics and Computational Science University of Pennsylvania Department of Mechanical Engineering and Applied Mechanics University of Pennsylvania Department of Electrical and Systems Engineering University of Pennsylvania

ISBN: (纸本)9781713871088

Supervised learning in function spaces is an emerging area of machine learning research with applications to the prediction of complex physical systems such as fluid flows, solid mechanics, and climate modeling. By directly learning maps (operators) between infinite dimensional function spaces, these models are able to learn discretization invariant representations of target functions. A common approach is to represent such target functions as linear combinations of basis elements learned from data. However, there are simple scenarios where, even though the target functions form a low dimensional submanifold, a very large number of basis elements is needed for an accurate linear representation. Here we present NOMAD, a novel operator learning framework with a nonlinear decoder map capable of learning finite dimensional representations of nonlinear submanifolds in function spaces. We show this method is able to accurately learn low dimensional representations of solution manifolds to partial differential equations while outperforming linear models of larger size. Additionally, we compare to state-of-the-art operator learning methods on a complex fluid dynamics benchmark and achieve competitive performance with a significantly smaller model size and training cost.

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Multiplex Magnetic Biosensor Microarrays Facilitate Personalized Vaccination Schedules for Sars-Cov-2 Variants

SSRN

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SSRN 2024年

作者： Um, Hyun-Kyung Kim, Songeun Wang, Shan X. Lee, Jung-Rok Department of Mechanical and Biomedical Engineering Ewha Womans University Seoul03760 Korea Republic of Graduate Program in Smart Factory Ewha Womans University Seoul03760 Korea Republic of Department of Materials Science and Engineering Stanford University Stanford CA94305 United States Department of Electrical Engineering Stanford University Stanford CA94305 United States

Rapid, sensitive, multiplexed antibody detection technologies are essential for assessing vaccine efficacy and recipient immunity against viruses. As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continue to emerge, and the fact that novel viruses may pose potential threats in the near future, personalized vaccines can be precisely tailored to an individual’s measured immunity to help mitigate the symptoms of infection and viral spread. Here, we present giant magnetoresistive (GMR) biosensor microarrays for the quantitative multiplexed detection of antibodies against SARS-CoV-2 variants. The multiplexed GMR biosensor microarrays demonstrated high sensitivity, comparable to that of the single-plex enzyme-linked immunosorbent assay, enabling multiplexed measurements using blood obtained from finger pricks. Additionally, the GMR biosensor microarrays demonstrated compatibility with clinical samples and could detect variant-specific antibodies in serum, allowing for the assessment of current immunity status. Notably, an increased concentration of antibodies against the Omicron variant was clearly observed two weeks after receiving an Omicron-based booster vaccination. These results indicate that GMR biosensor microarrays offer a practical point-of-care tool for monitoring humoral immunity and guiding personalized vaccination schedules, thereby supporting immunity management against SARS-CoV-2 and future viral threats. © 2024, The Authors. All rights reserved.

关键词： Giant magnetoresistance

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Porous Mesh Manifold for Enhanced Pool Boiling Performance

SSRN

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SSRN 2024年

作者： Giglio, Roman Shattique, Muhammad Rubaiet Dede, Ercan M. Narumanchi, Sreekant Asheghi, Mehdi Goodson, Kenneth E. Palko, James W. Department of Mechanical Engineering University of California MercedCA United States Materials and Biomaterials Science and Engineering Graduate Program University of California MercedCA United States Toyota Research Institute of North America Ann ArborMI United States National Renewable Energy Laboratory GoldenCO United States Department of Mechanical Engineering Stanford University StanfordCA United States

High performance electronics are continuously demanding cooling of higher heat fluxes. Phase change cooling, including pool boiling, is a useful approach to address this challenge, however competition between liquid and vapor flows generally limit the heat fluxes that can be dissipated. Here a manifold structure formed from metallic mesh is introduced to control the disposition of liquid and vapor phases above a boiling surface enhanced with a porous structure. Copper mesh forms defined liquid flow paths using capillary action to guide and distribute liquid evenly over the heated surface and open channels to facilitate vapor escape. The manifold performance is characterized in pool boiling with water above a laser textured aluminum nitride heat dissipation surface with pin fin structures having heights of 110 µm and spacing of 30 µm with a heated area of 5 mm x 5 mm. Maximum heat flux of 490W/cm is reached with the manifold in the pool boiling configuration, representing a 64% increase over the porous surface alone. Maximum superheat found for the manifold is 36 K, which is 14 K higher than the porous surface without manifold. Factors limiting performance of the manifold are analyzed. Based on variation of manifold geometry and numerical simulation, the primary limitation to heat flux is found to be viscous resistance to liquid flow in the manifold mesh. The increased superheat is attributed to partial flooding of the boiling surface as indicated by reduction in superheat using external suction. Similar systems and structures for enhanced two-phase cooling are compared. © 2024, The Authors. All rights reserved.

关键词： Heat flux

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Droplet digital quantification of nucleic acids with Cas13a 25

Droplet digital quantification of nucleic acids with Cas13a

引用

25th International Conference on Miniaturized Systems for Chemistry and Life sciences, MicroTAS 2021

作者： Liu, Frank X. Cui, Johnson Q. Yao, Shuhuai Department of Mechanical and Aerospace Engineering The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong Bioengineering Graduate Program Department of Chemical and Biological Engineering The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong

ISBN: (纸本)9781733419031

The isothermal amplification coupled with CRISPR detection has attracted tremendous interest for the sensitive, specific, and qualitative detection of nucleic acids. We report here a Microfluidics Enabled Digital Isothermal CRISPR-cas13a Assay (MEDICA) which leverages the droplet microfluidics technology to enable recombinase polymerase amplification (RPA) and Cas13a trans-cleavage reporting in individual droplet partitions for absolute quantification. The optimal one-pot MEDICA achieved single nucleic acid molecule detection within 30 min. We applied MEDICA to quantify HPV 16 and 18 viral loads in clinical samples, indicating complete accordance with quantitative polymerase chain reaction (qPCR) results. © 2021 MicroTAS 2021 - 25th International Conference on Miniaturized Systems for Chemistry and Life sciences. All rights reserved.

关键词： Drops

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Laser Processed Aluminum Nitride Structures for Enhanced Two-Phase Cooling

SSRN

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SSRN 2024年

作者： Giglio, Roman Shattique, Muhammad Rubaiet Md. Dede, Ercan M. Narumanchi, Sreekant Asheghi, Mehdi Goodson, Kenneth E. Palko, James W. Department of Mechanical Engineering University of California MercedCA United States Materials and Biomaterials Science and Engineering Graduate Program University of California MercedCA United States Toyota Research Institute of North America Ann ArborMI United States National Renewable Energy Laboratory GoldenCO United States Department of Mechanical Engineering Stanford University StanfordCA United States

The demand for higher heat flux cooling is increasing as the use of power electronics continues to expand. Two-phase cooling approaches that are tightly integrated into electronic packages offer potential for high performance. Here we describe a method to produce microscale pillars directly in aluminum nitride using UV laser ablation that is compatible with existing substrates for power electronics packaging and offers high precision and short production time. The resulting structures show significantly enhanced performance in pool boiling compared to unmodified surfaces. Effectiveness in two-phase cooling is investigated in terms of critical heat flux, heat transfer coefficient, and thermal resistance. The micropillar structures achieve a maximum critical heat flux of 299 W/cm2 and heat transfer coefficients up to 20 W/cm2 K for cooled areas of 0.25 cm2 in deionized water. Performance is attributed to the effective capillary rewetting of the surface during boiling and increased surface area. Corrosion of the aluminum nitride surface by the water working fluid is observed and contributes to a slow degradation of the measured heat transfer coefficient. The potential for simple processing routes to allow tight integration of two-phase cooling of electronics more generally is considered. © 2024, The Authors. All rights reserved.

关键词： Heat flux

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Bridging technology and community: Local perceptions of earthquake sensors in Aceh's seismic zones, Indonesia

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International Journal of disaster Risk Reduction 2025年 126卷

作者： Cut Isna Rina Suryani Oktari Agussabti Agussabti M. Dirhamsyah Muksin Umar Graduate Program in Disaster Science Universitas Syiah Kuala Banda Aceh 23111 Indonesia Tsunami and Disaster Mitigation Research Center (TDMRC) Graduate Program in Disaster Science and Department of Family Medicine Faculty of Medicine Universitas Syiah Kuala Banda Aceh 23111 Indonesia Graduate Program in Disaster Science Department of Agribusiness Faculty of Agriculture and Center for Rural Development & Sustainable Agriculture Studies Universitas Syiah Kuala Banda Aceh 23111 Indonesia Graduate Program in Disaster Science and Department of Mechanical Engineering Faculty of Engineering Universitas Syiah Kuala Banda Aceh 23111 Indonesia Tsunami and Disaster Mitigation Research Center (TDMRC) Graduate Program in Disaster Science and Department of Physics Faculty of Mathematics and Natural Sciences Universitas Syiah Kuala Banda Aceh 23111 Indonesia

The 2004 Aceh tsunami triggered by a major earthquake taught us the importance of disaster mitigation efforts, one of which is monitoring seismic activity using earthquake sensors. However, the success of these sensors is highly dependent on community involvement, awareness, and active maintenance of the technology. This study aims to examine the perceptions of the Acehnese community regarding earthquake sensors and to identify factors that influence their perceptions of this disaster mitigation technology. The study was conducted in six districts in Aceh Province: Aceh Besar, Aceh Selatan, Aceh Singkil, Aceh Utara, Lhokseumawe, and Aceh Tengah, which were selected due to their high seismic activity and the installation of existing earthquake sensors. The study involved 112 respondents who completed a questionnaire to assess their knowledge, perceptions, and attitudes toward sensors. A One Sample T-Test was used to assess each factor influenced perceptions. The study showed that experience was the most influential factor in shaping perceptions, indicating that individuals directly involved in installing the sensors were more likely to appreciate their benefits. This study emphasizes the importance of more targeted educational campaign efforts that emphasize the role and importance of earthquake sensors in reducing earthquake risk and bridging the gap in public understanding of earthquake sensors. By directly involving the community in installing or maintaining earthquake sensors, it can improve their perception and increase the effectiveness of disaster preparedness strategies.

关键词： Community preparedness disaster education Earthquake mitigation Participatory approach

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The Performance Investigation of Smart Diagnosis for Bearings Using Mixed Chaotic Features with Fractional Order

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Sensors 2023年第8期23卷 3801-3801页

作者： Li, Shih-Yu Tam, Lap-Mou Wu, Shih-Ping Tsai, Wei-Lin Hu, Chia-Wen Cheng, Li-Yang Xu, Yu-Xuan Cheng, Shyi-Chyi Graduate Institute of Manufacturing Technology National Taipei University of Technology Taipei10608 Taiwan Institute for the Development and Quality 999078 China Department of Electromechanical Engineering Faculty of Science and Technology University of Macau 999078 China Master Program Graduate Institute of Mechatronic Engineering National Taipei University of Technology Taipei10608 Taiwan Department of Mechanical Engineering National Taipei University of Technology Taipei10608 Taiwan Department of Computer Science and Engineering National Taiwan Ocean University Keelung City202301 Taiwan

This article presents a performance investigation of a fault detection approach for bearings using different chaotic features with fractional order, where the five different chaotic features and three combinations are clearly described, and the detection achievement is organized. In the architecture of the method, a fractional order chaotic system is first applied to produce a chaotic map of the original vibration signal in the chaotic domain, where small changes in the signal with different bearing statuses might be present;then, a 3D feature map can be obtained. Second, five different features, combination methods, and corresponding extraction functions are introduced. In the third action, the correlation functions of extension theory used to construct the classical domain and joint fields are applied to further define the ranges belonging to different bearing statuses. Finally, testing data are fed into the detection system to verify the performance. The experimental results show that the proposed different chaotic features perform well in the detection of bearings with 7 and 21 mil diameters, and an average accuracy rate of 94.4% was achieved in all cases. © 2023 by the authors.

关键词： Fault detection

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