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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Cheng, J. Komissarov, I. Chen, G. Chakraborty, D. Kutcher, S. Chen, H. Trivedi, S. Sobolewski, Roman Materials Science Graduate Program University of Rochester RochesterNY14627 United States Laboratory for Laser Energetics University of Rochester RochesterNY14623 United States Department of Electrical and Computer Engineering University of Rochester RochesterNY14627 United States Brimrose Technology Corp SparksMD21152 United States

We developed a dual optical/x-ray ultrafast photodetector based on in-house grown Cdo * Mg0.03Te single crystals. The detector is characterized by ~200 ps full-width-at-half-maximum, readout-electronics limited photor... 详细信息

ISBN: (纸本)9781957171258

关键词： X ray detectors

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PET-derived bis(2-hydroxyethyl) terephthalate as a new linker source for solvent-free and hydrothermal synthesis of BDC-based MOFs

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materials Today Nano 2024年 25卷

作者： Krisbiantoro, Philip Anggo Kuo, Tzu-Jung Chang, Yu-Chia Liao, Weisheng Sun, Jih-Peng Yang, Chun-Yen Kamiya, Yuichi Shieh, Fa-Kuen Chen, Chia-Chin Wu, Kevin C.-W Molecular Science and Technology Program Taiwan International Graduate Program Academia Sinica Taipei11529 Taiwan International Graduate Program of Molecular Science and Technology National Taiwan University Taipei10617 Taiwan Department of Chemical Engineering National Taiwan University Taipei10617 Taiwan Faculty of Environmental Earth Science Hokkaido University Nishi 5 Kita 10 Kita-ku Sapporo060-0810 Japan Department of Chemistry National Central University Taoyuan32001 Taiwan Center of Atomic Initiative for New Materials National Taiwan University Taipei10617 Taiwan Department of Chemical Engineering and Materials Science Yuan Ze University Chung-Li Taoyuan Taiwan

To date, the high cost of organic linkers and the energy-consuming synthesis processes remain two of the main challenges for the commercialization of metal-organic frameworks (MOFs). Herein, we demonstrate that polyethylene terephthalate (PET)-derived bis(2-hydroxyethyl) terephthalate (BHET) is a new linker source that enables the facile solvent-free and hydrothermal synthesis of BDC-based MOFs. Using BHET as a linker source, UiO-66(Zr) was rapidly synthesized via a solvent-free "grind and bake" technique, while Ca-BDC and Ba-BDC were easily obtained by using hydrothermal synthesis. We found that the hydrolysis of BHET to terephthalate anion (BDC2−) over proton produced from the hydrolysis/clustering of Zr precursor and hydroxyl anion produced from the dissolution of M(OH)2 (M = Ca or Ba) was the key to the crystal growth of solvent-free synthesized UiO-66(Zr) and hydrothermally synthesized M-BDC (M = Ca or Ba), respectively. While the as-synthesized UiO-66(Zr) was highly active for the esterification of lactic acid (LA) with ethanol (EtOH), Ca-BDC and Ba-BDC exhibited remarkable electrochemical performance for lithium storage. Our strategy provides a major step towards realizing the idea of a more facile, green, and low-cost synthesis of PET-derived MOFs compared to prior arts applicable for catalysis and energy applications. © 2024

关键词： Lithium-ion batteries

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FIP-GNN: Graph neural networks for scalable prediction of grain-level fatigue indicator parameters

arXiv

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arXiv 2024年

作者： Sim, Gyu-Jang Lee, Myoung-Gyu Latypov, Marat I. Department of Materials Science and Engineering & RIAM Seoul National University 1 Gwanak-ro Gwanak-gu Seoul08826 Korea Republic of Department of Materials Science and Engineering University of Arizona TucsonAZ85721 United States Graduate Interdisciplinary Program in Applied Mathematics University of Arizona TucsonAZ85721 United States

High-cycle fatigue is a critical performance metric of structural alloys for many applications. The high cost, time, and labor involved in experimental fatigue testing call for efficient and accurate computer models of fatigue life. We present FIP-GNN – a graph neural network for polycrystals that (i) predicts fatigue indicator parameters as grain-level inelastic responses to cyclic loading quantifying the local driving force for crack initiation and (ii) generalizes these predictions to large microstructure volume elements with grain populations well beyond those used in training. These advances can make significant contributions to statistically rigorous and computationally efficient modeling of high-cycle fatigue – a long-standing challenge in the field. © 2024, CC BY.

关键词： High-cycle fatigue

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Study of chlorine removal from shredder residue: Thermal dechlorination and water leaching

Sustainable Chemistry for the Environment

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Sustainable Chemistry for the Environment 2024年 6卷

作者： Manera, Christian Perondi, Daniele Restelatto, Danielle Godinho, Marcelo Vilela, Antônio Cezar Faria Graduate Program in Mining Metallurgical and Materials Engineering Federal University of Rio Grande do Sul (UFRGS) Rio Grande do Sul Porto Alegre Brazil Graduate Program in Process Engineering and Technologies University of Caxias do Sul (UCS) Rio Grande do Sul Caxias do Sul Brazil Graduate Program in Materials Science and Engineering University of Caxias do Sul (UCS) Rio Grande do Sul Caxias do Sul Brazil

Shredder residue (SR) is an inevitable waste in the production of steel by scrap melting, and the presence of chlorine is the main responsible for its non-use of energy. This study aimed to remove chlorine from SR by thermal dechlorination and water leaching. Thermal dechlorination was first studied from a PVC sample to evaluate the optimum parameters of temperature, heating rate, residence time and atmosphere (N₂ or steam). Under optimal conditions for PVC dechlorination, chlorine removals of 73.7 (N₂) and 68.0% (steam) were achieved. Optimal parameters were applied to thermal dechlorination of a Brazilian SR with a chlorine content of 2.12 wt%. Reductions in chlorine content to 0.95 and 0.51 wt% were observed with N₂ and steam atmospheres, respectively. In an additional evaluation (conducted also with the Brazilian SR and in order to investigate the reactor rotation effect), it was observed that the reactor rotation does not influence the release of chlorine during the thermal treatment but modifies the granulometry of the produced solid. Samples obtained from this test were subjected to a water leaching study to further reduce the chlorine content. The parameters studied were the type of water (tap and distilled), granulometry and carbonation (contact with CO₂) in a total of five washing cycles. Carbonation and use of distilled water achieved the highest chlorine removal resulting in a reduction of chlorine content from 1.13 to 0.45 wt%. The obtained results show directions for chlorine removal aiming at the energetic use of shredder residue. © 2024 The Authors

关键词： Carbonation Chlorine leaching Design of experiment Polyvinyl chloride Shredder residue

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Technology Roadmap for Flexible Sensors

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ACS NANO 2023年第6期17卷 5211-5295页

作者： Luo, Yifei Abidian, Mohammad Reza Ahn, Jong-Hyun Akinwande, Deji Andrews, Anne M. Antonietti, Markus Bao, Zhenan Berggren, Magnus Berkey, Christopher A. Bettinger, Christopher John Chen, Jun Chen, Peng Cheng, Wenlong Cheng, Xu Choi, Seon-Jin Chortos, Alex Dagdeviren, Canan Dauskardt, Reinhold H. Di, Chong-an Dickey, Michael D. Duan, Xiangfeng Facchetti, Antonio Fan, Zhiyong Fang, Yin Feng, Jianyou Feng, Xue Gao, Huajian Gao, Wei Gong, Xiwen Guo, Chuan Fei Guo, Xiaojun Hartel, Martin C. He, Zihan Ho, John S. Hu, Youfan Huang, Qiyao Huang, Yu Huo, Fengwei Hussain, Muhammad M. Javey, Ali Jeong, Unyong Jiang, Chen Jiang, Xingyu Kang, Jiheong Karnaushenko, Daniil Khademhosseini, Ali Kim, Dae-Hyeong Kim, Il-Doo Kireev, Dmitry Kong, Lingxuan Lee, Chengkuo Lee, Nae-Eung Lee, Pooi See Lee, Tae-Woo Li, Fengyu Li, Jinxing Liang, Cuiyuan Lim, Chwee Teck Lin, Yuanjing Lipomi, Darren J. Liu, Jia Liu, Kai Liu, Nan Liu, Ren Liu, Yuxin Liu, Yuxuan Liu, Zhiyuan Liu, Zhuangjian Loh, Xian Jun Lu, Nanshu Lv, Zhisheng Magdassi, Shlomo Malliaras, George G. Matsuhisa, Naoji Nathan, Arokia Niu, Simiao Pan, Jieming Pang, Changhyun Pei, Qibing Peng, Huisheng Qi, Dianpeng Ren, Huaying Rogers, John A. Rowe, Aaron Schmidt, Oliver G. Sekitani, Tsuyoshi Seo, Dae-Gyo Shen, Guozhen Sheng, Xing Shi, Qiongfeng Someya, Takao Song, Yanlin Stavrinidou, Eleni Su, Meng Sun, Xuemei Takei, Kuniharu Tao, Xiao-Ming Tee, Benjamin C. K. Thean, Aaron Voon-Yew Trung, Tran Quang Wan, Changjin Wang, Huiliang Wang, Joseph Wang, Ming Wang, Sihong Wang, Ting Wang, Zhong Lin Weiss, Paul S. Wen, Hanqi Xu, Sheng Xu, Tailin Yan, Hongping Yan, Xuzhou Yang, Hui Yang, Le Yang, Shuaijian Yin, Lan Yu, Cunjiang Yu, Guihua Yu, Jing Yu, Shu-Hong Yu, Xinge Zamburg, Evgeny Zhang, Haixia Zhang, Xiangyu Zhang, Xiaosheng Zhang, Xueji Zhang, Yihui Zhang, Yu Zhao, Siyuan Zhao, Xuanhe Zheng, Yuanjin Zheng, Yu-Qing Zheng, Zijian Zhou, Tao Zhu, Bowen Zhu, Ming Zhu, Rong Zhu, Yangzhi Zhu, Yong Zou, Guijin Chen, Xiaodong 08-03 Innovis Singapore 138634 Republic of Singapore Innovative Centre for Flexible Devices (iFLEX) School of Materials Science and Engineering Nanyang Technological University Singapore 639798 Singapore Department of Biomedical Engineering University of Houston Houston Texas 77024 United States School of Electrical and Electronic Engineering Yonsei University Seoul 03722 Republic of Korea Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 United States Microelectronics Research Center The University of Texas at Austin Austin Texas 78758 United States Department of Chemistry and Biochemistry California NanoSystems Institute and Department of Psychiatry and Biobehavioral Sciences Semel Institute for Neuroscience and Human Behavior and Hatos Center for Neuropharmacology University of California Los Angeles Los Angeles California 90095 United States Colloid Chemistry Department Max Planck Institute of Colloids and Interfaces 14476 Potsdam Germany Department of Chemical Engineering Stanford University Stanford California 94305 United States Laboratory of Organic Electronics Department of Science and Technology Campus Norrköping Linköping University 83 Linköping Sweden Wallenberg Initiative Materials Science for Sustainability (WISE) and Wallenberg Wood Science Center (WWSC) SE-100 44 Stockholm Sweden Department of Materials Science and Engineering Stanford University Stanford California 94301 United States Department of Biomedical Engineering and Department of Materials Science and Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 United States Department of Bioengineering University of California Los Angeles Los Angeles California 90095 United States School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Singapore 637457 Singapore Nanobionics Group Department of Chemical and Biological Engineering Monash University Clayton Australia 3800 Monash

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze continued...challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative

关键词： soft materials mechanics engineering flexible electronics conformable sensors bioelectronics human-machine interfaces body area sensor networks technology translation sustainable electronics

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Diving into COVID-19: Visualizing SARS-CoV-2 Patient Proteins using Liquid-Electron Microscopy

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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 662-664页

作者： Berry, Samantha DiCecco, Liza-Anastasia Gray, Jennifer Boylan, Jack Solares, Maria Kelly, Deborah F. Department of Biomedical Engineering Pennsylvania State University University Park PA United States Department of Materials Science and Engineering McMaster University Hamilton ON Canada Materials Research Institute Pennsylvania State University University Park PA United States Molecular Cellular Integrative Biosciences Graduate Program Huck Institutes of the Life Sciences Pennsylvania State University University Park PA United States Huck Institutes of the Life Sciences Pennsylvania State University University Park PA United States

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materials Discovery with Extreme Properties via Reinforcement Learning-Guided Combinatorial Chemistry

arXiv

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arXiv 2023年

作者： Kim, Hyunseung Choi, Haeyeon Kang, Dongju Lee, Won Bo Na, Jonggeol School of Chemical and Biological Engineering Seoul National University Korea Republic of Department of Chemical Engineering and Materials Science Ewha Womans University Korea Republic of Graduate Program in System Health Science and Engineering Ewha Womans University Korea Republic of

The goal of most materials discovery is to discover materials that are superior to those currently known. Fundamentally, this is close to extrapolation, which is a weak point for most machine learning models that learn the probability distribution of data. Herein, we develop reinforcement learning-guided combinatorial chemistry, which is a rule-based molecular designer driven by trained policy for selecting subsequent molecular fragments to get a target molecule. Since our model has the potential to generate all possible molecular structures that can be obtained from combinations of molecular fragments, unknown molecules with superior properties can be discovered. We theoretically and empirically demonstrate that our model is more suitable for discovering better compounds than probability distribution-learning models. In an experiment aimed at discovering molecules that hit seven extreme target properties, our model discovered 1,315 of all target-hitting molecules and 7,629 of five target-hitting molecules out of 100,000 trials, whereas the probability distribution-learning models failed. Moreover, it has been confirmed that every molecule generated under the binding rules of molecular fragments is 100% chemically valid. To illustrate the performance in actual problems, we also demonstrate that our models work well on two practical applications: discovering protein docking molecules and HIV inhibitors. © 2023, CC BY-NC-SA.

关键词： Probability distributions

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DEVELOPMENT OF GREENER AND MORE EFFECTIVE HIGH-TEMPERATURE THERMAL INSULATORS 17

DEVELOPMENT OF GREENER AND MORE EFFECTIVE HIGH-TEMPERATURE T...

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17th Unified International Technical Conference on Refractories, UNITECR 2022

作者： Borges, O.H. dos Santos, T. Salvini, V.R. Pandolfelli, V.C. Federal University of Sao Carlos Graduate Program in Materials Science and Engineering SP Sao Carlos Brazil FIRE Associate Laboratory SP Sao Carlos Brazil Jordão Borghetti Street 480 SP Sertãozinho14160-050 Brazil

Aiming at reducing the remarkable shrinkage observed when porous ceramics are fired, the in-situ formation of hibonite (also known as CaO·6Al2O3 or CA6) was evaluated in a direct-foamed alumina-based macroporous thermal insulator with the addition of distinct calcium sources and contents. Among the tested compositions, that containing 12.9 wt% of CaCO3 showed promising results as high porosity (~ 80 %), no shrinkage after firing at 1600 ºC for 5 h, suitable mechanical strength, and a 200 ºC-lower strengthening temperature. However, the in-situ formation of CA6 took place just at high temperatures (~ 1600 ºC), implying a high energy consumption. To address this issue, SiO2, ZnO, and TiO2 were evaluated as mineralizing agents. The addition of 2.8 mol% of TiO2 induced CA6 formation at 1300ºC and low thermal conductivity (0.54 Wm-1K-1 at 1200 ºC), without significant changes in the refractoriness. © 2022 Unified International Technical Conference on Refractories, UNITECR 2022 - Proceedings. All rights reserved.

关键词： Titanium dioxide

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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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Intelligent micro/nanorobots for improved tumor therapy

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BMEMat(BioMedical engineering materials) 2023年第2期1卷 62-77页

作者： Zhaoli Sun Yanglong Hou Beijing Key Laboratory for Magnetoelectric Materials and Devices(BKL-MMD) School of Materials Science and EngineeringPeking UniversityBeijingChina Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program School of Life SciencesPeking UniversityBeijingChina

A major bottleneck underlying nanomaterial-based tumor therapy lies in complex biological environment and physiological ***/nanorobots with the features of self-propulsion and controllable navigation have gradually become a research hotspot in the tumor therapeutic community,exhibiting their advantages in efficient cargo loading,controllable cargo delivery,stimulitriggered cargo release,deeper tumor tissue penetration,and enhanced cargo accumulation in tumor *** this review,the self-propulsion and controllable navigation are introduced as two major properties of micro/nanorobots,in which micro/nanorobots are propelled by chemical reactions,physical fields,and biological systems and could be navigated by chemotaxis,remote magnetic guidance,and ***,the recent advances of micro/nanorobots for chemotherapy,immunotherapy,photothermal therapy,photodynamic therapy,chemodynamic therapy,and multimodal tumor therapy would be ***,the perspective and challenges are also *** is expected that this review gives an insight into intelligent micro/nanorobots for improved tumor therapy,aiming for more extensive and in-depth investigations,and final applications in the clinic.

关键词： intelligent motion micro/nanorobots tumor therapy

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