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International Conference on Applied System Innovation (ICASI)

作者： Chia-Chih Wei Hsuan-Jung Chen Yi-Mu Lee Shao-Fu Chang Chien-Chon Chen College of Engineering and Science Ph.D. Program in Materials and Chemical Engineering National United University Miaoli Taiwan Department of Chemistry Michigan State University MI USA Department of Electronic National United University Miaoli Taiwan Department of Energy Engineering National United University Miaoli Taiwan

ISBN: (数字)9798350394924

ISBN: (纸本)9798350394931

In this paper, we have presented our experiment results including (a) use a slowly thermal spray process deposition an yttrium oxide (Y 2 O 3 ) film with thickness of $200\ \mu\mathrm{m}$ on the aluminum alloy (AA6061). The image analysis showed that the porosity of Y 2 O 3 film can be reduced to less than 2%. The further aerosol deposition can be used filling the pores and can reduce the porosity of the film to less than 0.5%. This low-porosity Y 2 O 3 film will be able to meet the increasingly stringent requirements for surface coating protection of semiconductor vacuum chamber. (b) Compared the corrosion characterization in 3.5 wt. % NaCl solution between naked AA6061 and AA6061 with Y 2 O 3 coating, a high corrosion reactivity ( $\mathrm{I}_{\text{corr}}=10^{-3.3}\mathrm{A}/\text{cm}^{2}$ ) of naked AA6061 then AA6061 with Y 2 O 3 coating ( $\mathrm{I}_{\text{corr}}=10^{-5.8}\mathrm{A}/\text{cm}^{2}$ ). The corrosion reactivity of AA6061 with Y 2 O 3 is reduced by 316 times to a naked AA6061.

关键词： Resistance Technological innovation Powders Image analysis Corrosion Semiconductor device manufacture Thermal spraying

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Conformity Experiment on Inelastic Scattering Exponent of Electrons in Two Dimensions

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Physical Review Letters 2024年第9期133卷 096302页

作者： Ching-Chen Yeh Pin-Chi Liao Yanfei Yang Wei-Chen Lin Alireza R. Panna Albert F. Rigosi Randolph E. Elmquist Chi-Te Liang Gaithersburg Maryland 20899 USA Department of Physics Graphene Waves Germantown Maryland 20876 USA Taiwan International Graduate Program Department of Engineering and System Science Center for Quantum Science and Engineering (CQSE) Taiwan Consortium of Emergent Crystalline Materials (TCECM) Taipei 106 Taiwan

The quantum Hall (QH) effect is one of the most widely studied physical phenomenon in two dimensions. The plateau-plateau transition within this effect can be comprehensively described by the scaling theory, which encompasses three pivotal exponents: the critical exponent κ, the inelastic scattering exponent p, and the universal exponent γ. Prior studies have focused on measuring κ and estimating γ, assuming a constant p value of 2 across magnetic fields. Here, our work marks a significant advancement by measuring all three exponents within a single graphene device and a conventional two-dimensional electron system. This study uniquely determines p at low magnetic fields (weak localization region and well outside the QH regime) and high magnetic fields (in the vicinity of the QH regime). Employing a comprehensive analytical approach that includes weak localization, plateau-plateau transitions, and variable range hopping, we have directly determined κ, p, and γ. Our findings reveal a distinct variation in p, shifting from 1 in the low magnetic field regime to 2 in the QH regime in graphene.

关键词： Electrical properties Fermions Landau levels Quantum interference effects Quantum phase transitions

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Unveiling Processing–Property Relationships in Laser Powder Bed Fusion: The Synergy of Machine Learning and High-throughput Experiments

arXiv

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arXiv 2024年

作者： Amiri, Mahsa Foumani, Zahra Zanjani Cao, Penghui Valdevit, Lorenzo Bostanabad, Ramin Materials and Manufacturing Technology Program University of California IrvineCA92697 United States Department of Mechanical and Aerospace Engineering University of California IrvineCA92697 United States Department of Materials Science and Engineering University of California IrvineCA92697 United States Department of Civil and Environmental Engineering University of California IrvineCA92697 United States

Achieving desired mechanical properties in additive manufacturing requires many experiments and a well-defined design framework becomes crucial in reducing trials and conserving resources. Here, we propose a methodology embracing the synergy between high-throughput (HT) experimentation and hierarchical machine learning (ML) to unveil the complex relationships between a large set of process parameters in Laser Powder Bed Fusion (LPBF) and selected mechanical properties (tensile strength and ductility). The HT method envisions the fabrication of small samples for rapid automated hardness and porosity characterization, and a smaller set of tensile specimens for more labor-intensive direct measurement of yield strength and ductility. The ML approach is based on a sequential application of Gaussian processes (GPs) where the correlations between process parameters and hardness/porosity are first learnt and subsequently adopted by the GPs that relate strength and ductility to process parameters. Finally, an optimization scheme is devised that leverages these GPs to identify the processing parameters that maximize combinations of strength and ductility. By founding the learning on larger "easy-to-collect" and smaller "labor-intensive" data, we reduce the reliance on expensive characterization and enable exploration of a large processing space. Our approach is material-agnostic and herein we demonstrate its application on 17-4PH stainless steel. © 2024, CC BY.

关键词： Global positioning system

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New insight into pyrrolic-N site effect towards the first NIR window absorption of pyrrolic-N-rich carbon dots

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Nano Research 2023年第4期16卷 6001-6009页

作者： Fitri Aulia Permatasari Reza Umami Citra Deliana Dewi Sundari Tirta Rona Mayangsari Atthar Luqman Ivansyah Fahdzi Muttaqien Takashi Ogi Ferry Iskandar Department of Physics Faculty Mathematics and Natural SciencesInstitut Teknologi BandungJalan Ganesha 10BandungWest Java 40132Indonesia Collaboration Research Center for Advanced Energy Materials National Research and Innovation Agency-Institut Teknologi BandungJalan Ganesha 10BandungWest Java 40132Indonesia Department of Chemistry Faculty of Mathematics and Natural SciencesInstitut Teknologi BandungJl.Ganesha 10BandungWest Java 40132Indonesia Department of Chemistry Education UIN Sunan Gunung Djati BandungJl.CimincrangBandungWest Java 40292Indonesia Department of Chemistry Universitas PertaminaJakarta 12220Indonesia Master Program in Computational Science Faculty of Mathematics and Natural SciencesInstitut Teknologi BandungJl.Ganesha 10BandungWest Java 40132Indonesia Instrumentation and Computational Physics Research Group Faculty of Mathematics and Natural SciencesInstitut Teknologi BandungJl.Ganesha 10Bandung 40132Indonesia Research Center for Nanoscience and Nanotechnology Institut Teknologi BandungJalan Ganesha 10BandungWest Java 40132Indonesia Chemical Engineering Program Department of Advanced Science and EngineeringGraduate School of Advanced Science and EngineeringHiroshima UniversityHigashi-Hiroshima 739-8527Japan

Controlled C-N configurations,i.e.,pyrrolic-N,pyridinic-N,and graphitic-N,are promising strategies to tailor the carbon dots’(CDs)optical properties into the first near infrared(NIR)window(650-900 nm),a responsive range for biomedical ***,a deep understanding of the role of the C-N configuration in the CDs’properties is still challenging and thoughtprovoking owing to their complex ***,an underlying pyrrolic-N concentration and position effect on the pyrrolic-N-rich CDs’absorption was comprehensively elucidated based on the integrated experimental and computational *** assynthesized pyrrolic-N-rich CDs exhibit a first NIR window absorption centered at 650 nm with high photothermal ***-N concentrations from 1.4%to 11.3%and positions(edge and mid-site)were systematically investigated.A mid-site pyrrolic-N was subsequently generated after the pyrrolic-N concentration more than 10%.Edge-site pyrrolic-N induces a frontier orbital hybridization,reducing bandgap energy,while mid-site pyrrolic-N plays a critical role in inducing a first NIR window absorption owing to their high charge ***,pyrrolic-N-rich CDs inherit a bowl-like topological feature,elevating the CDs’layer thickness as much as 0.71 *** study shed light on the design and optimization of pyrrolic-N on CDs for the first NIR window responsive materials in any biomedical application.

关键词： absorption carbon dots charge transfer first near infrared(NIR)window frontier orbital hybridization mid-site pyrrolic-N

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Mineralogy of the deep lower mantle in the presence of H2O

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National science Review 2021年第4期8卷 21-28页

作者： Qingyang Hu Jin Liu Jiuhua Chen Bingmin Yan Yue Meng Vitali B.Prakapenka Wendy L.Mao Ho-Kwang Mao Center for High Pressure Science and Technology Advanced Research(HPSTAR) Department of Geological Sciences Stanford University Center for Study of Matter under Extreme Conditions Department of Mechanical and Materials Engineering Florida International University High Pressure Collaborative Access Team(HPCAT) X-ray Science Division Argonne National Laboratory Center for Advanced Radiation Sources University of Chicago

Understanding the mineralogy of the Earth's interior is a prerequisite for unravelling the evolution and dynamics of our planet. Here, we conducted high pressure-temperature experiments mimicking the conditions of the deep lower mantle（DLM, 1800–2890 km in depth） and observed surprising mineralogical transformations in the presence of water. Ferropericlase,（Mg,Fe）O, which is the most abundant oxide mineral in Earth, reacts with H2O to form a previously unknown（Mg,Fe）O2Hx（x ≤ 1）phase. The（Mg,Fe）O2Hxhas a pyrite structure and it coexists with the dominant silicate phases,bridgmanite and post-perovskite. Depending on Mg content and geotherm temperatures, the transformation may occur at 1800 km for(Mg0.6Fe0.4)O or beyond 2300 km for(Mg0.7Fe0.3)O. The（Mg,Fe）O2Hxis an oxygen excess phase that stores an excessive amount of oxygen beyond the charge balance of maximum cation valences(Mg2+, Fe3+and H+). This important phase has a number of far-reaching implications including extreme redox inhomogeneity, deep-oxygen reservoirs in the DLM and an internal source for modulating oxygen in the atmosphere.

关键词： lower mantle water-mantle interaction ferropericlase high pressure mantle mineralogy

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Micromechanical origin of heat transfer to granular flow

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Physical Review E 2024年第4期109卷 L042902-L042902页

作者： Xintong Zhang Sarath Adapa Tianshi Feng Jian Zeng Ka Man Chung Clifford Ho Kevin Albrecht Renkun Chen Department of Mechanical and Aerospace Engineering University of California San Diego La Jolla California 92093 USA Program in Materials Science and Engineering University of California San Diego La Jolla California 92093 USA Concentrating Solar Technologies Department Sandia National Laboratories 1515 Eubank Boulevard SE Albuquerque New Mexico 87123 USA

Heat transfer across a granular flow is comprised of two resistances in series : near the wall and within the bulk particle bed, neither of which is well understood due to the lack of experimental probes to separate their respective contribution. Here, we use a frequency modulated photothermal technique to separately quantify the thermal resistances in the near-wall and the bulk bed regions of particles in flowing states. Compared to the stationary state, the flowing leads to a higher near-wall resistance and a lower thermal conductivity of bulk beds. Coupled with discrete element method simulation, we show that the near-wall resistance can be explained by particle diffusion in granular flows.

关键词： Fluidized beds Granular flows Granular materials Granular packing Interparticle interactions

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Structural evaluation of Poly(lactic acid) degradation at standardized composting temperature of 58 degrees

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Chemosphere 2024年 354卷 141729页

作者： Oh, Jiwon Park, Sung Bae Cha, Chaenyung Hwang, Dong Ki Park, Seul-A Park, Jeyoung Oh, Dongyeop X. Jeon, Hyeonyeol Koo, Jun Mo Ulsan44429 Korea Republic of Ulsan44919 Korea Republic of Pohang37673 Korea Republic of Department of Chemical and Biomolecular Engineering Sogang University Seoul04107 Korea Republic of Department of Polymer Science and Engineering and Program in Environmental and Polymer Engineering Inha University Incheon22212 Korea Republic of Daejeon34113 Korea Republic of Department of Organic Materials Engineering Chungnam National University Daejeon34134 Korea Republic of

The accumulation of petroleum-based plastics on our planet is causing serious environmental pollution. Biodegradable plastics, promoted as eco-friendly solutions, hold the potential to address this issue. However, their impact on the environment and the mechanisms of their natural degradation remain inadequately understood. Furthermore, the specific conditions set forth in international standards for evaluating the biodegradability of biodegradable plastics have led to misconceptions about their real-world behavior. To properly elucidate the relationship between their degradability and structure, this study mimics the thermal effect on poly(lactic acid) (PLA) under standardized composting temperature. The higher the crystallinity of PLA, the lower the degradation rate, which suggests that crystallinity is a key factor in determining degradation. The composting temperature of 58 °C induces crystallization by having a structural effect on the polymer, which in turn reduces the degradation rate of PLA. Therefore, control over temperature and crystallization during the processing and degradation of PLA is crucial, as it not only determines the biodegradability but also enhances the utility. © 2024

关键词： Biodegradability

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Periodic phase diagrams in micromagnetics with an eigenvalue solver

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IEEE Transactions on Magnetics 2025年

作者： Ai, Fangzhou Lin, Zhuonan Duan, Jiawei Lomakin, Vitaliy University of California Department of Electrical and Computer Engineering San DiegoCA92093 United States University of California Center for Memory and Recording Research San DiegoCA92093 United States University of California Program in Materials Science and Engineering San Diego92093 United States

This work introduces an approach to compute periodic phase diagram of micromagnetic systems by solving a periodic linearized Landau-Lifshitz-Gilbert (LLG) equation using an eigenvalue solver with the Finite Element Method formalism. The linear operator in the eigenvalue problem is defined as a function of the periodic phase-shift wave vector. The dispersion diagrams are obtained by solving the eigenvalue problem for complex eigenfrequencies and corresponding eigenstates for a range of prescribed wave vectors. The presented approach incorporates a calculation of the periodic effective field, including the exchange and magnetostatic field components. The approach is general in that it allows 3D problems to be handled with any 1D, 2D, and 3D periodicities. The ability to calculate periodic diagrams provides insights into the spin wave propagation and localized resonances in complex micromagnetic structures. © 1965-2012 IEEE.

关键词： Spin waves

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

arXiv

引用

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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Uncertainty Quantification and Propagation for Multiscale materials Systems with Agglomeration and Structural Anomalies

SSRN

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SSRN 2024年

作者： Comlek, Yigitcan Mojumder, Satyajit van Beek, Anton Prabhune, Prajakta Ciampaglia, Alberto Apley, Daniel W. Brinson, L. Catherine Liu, Wing Kam Chen, Wei Department of Mechanical Engineering Northwestern University Evanston United States Theoretical and Applied Mechanics Program Northwestern University Evanston United States School of Mechanical and Materials Engineering University College Dublin Dublin Ireland Thomas Lord Department of Mechanical Engineering and Materials Science Duke University Durham United States Department of Mechanical and Aerospace Engineering Politecnico di Torino Turin Italy Department of Industrial Engineering and Management Sciences Northwestern University Evanston United States

Advancements in manufacturing technologies have enabled material system design optimization at multiple length scales. However, the microstructural anomalies and uncertainties present at each scale have not been considered comprehensively enough for systems to be robust to manufacturing variations. Consequently, considering anomalies at various length scales of the material’s structure and understanding their effects on a part’s response are crucial for designing engineered parts that are robust to various sources of uncertainty. In this work, an efficient bottom-up hierarchical uncertainty quantification and propagation framework bridging multiple scales to establish a design allowable range for the material system at the part-scale is presented. We demonstrate our framework on an additively manufactured polymer nanocomposite material system that is subject to anomalies at different length scales that impact the material properties. Specifically, agglomeration defects formed due to attractive forces between nanoparticles at the microscale and structural variabilities caused by the voids resulting from different processing conditions at the mesoscale are considered. The introduced hierarchical sampling framework combines (i) an innovative microstructure image characterization and reconstruction, (ii) a mechanistic reduced-order model that enables fast property predictions for high-dimensional microstructural design spaces, and (iii) efficient uncertainty quantification and propagation through Copula-based sampling across multiple length scales to reduce the sampling budget by 95%. Through validation of our method, we demonstrate the importance of considering the effects of process-induced microstructure features on the performance of a part. © 2024, The Authors. All rights reserved.

关键词： Microstructure

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