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Enhanced properties of aluminum alloys using high strain rate deformation

Keikinzoku/Journal of Japan Institute of Light Metals 2016年第4期66卷 192-199页

作者： Horikawa, Keitaro Ogura, Tomo Kobayashi, Hidetoshi Department of Mechanical Science and Bioengineering Graduate School of Engineering Science Osaka University 1-3 Machikaneyama Toyonaka-shi Osaka560-8531 Japan Division of Material and Manufacturing Science Graduate School of Engineering Osaka University Toyonaka-shi Osaka Japan

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Band gap and band alignment prediction of nitride based semiconductors using machine learning

arXiv

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arXiv 2018年

作者： Huang, Yang Yu, Changyou Chen, Weiguang Liu, Yuhuai Li, Chong Niu, Chunyao Wang, Fei Jia, Yu International Laboratory for Quantum Functional Materials of Henan School of Physics and Engineering Zhengzhou University Zhengzhou450001 China Materials Science and Engineering Program University of California San Diego La JollaCA92093 United States National Center for International Joint Research of Electronic Materials and Systems School of Information Engineering Zhengzhou University Zhengzhou450001 China Quantum Materials Research Center College of Physics and Electronic Engineering Zhengzhou Normal University Zhengzhou450044 China Institute of Materials and Systems for Sustainability Nagoya University Nagoya464-8603 Japan Key Laboratory for Special Functional Material of Ministry of Education School of Materials Science Henan University Kaifeng475004 China

Nitride has been drawing much attention due to its wide range of applications in optoelectronics and remains plenty of room for materials design and discovery. Here, a large set of nitrides have been designed, with their band gap and alignment being studied by first-principles calculations combined with machine learning. Band gap and band offset against wurtzite GaN accurately calculated by the combination of screened hybrid functional of HSE and DFT-PBE were used to train and test machine learning models. After comparison among different techniques of machine learning, when elemental properties are taken as features, support vector regression (SVR) with radial kernel performs best for predicting both band gap and band offset with prediction root mean square error (RMSE) of 0.298 eV and 0.183 eV, respectively. The former is within HSE calculation uncertainty and the latter is small enough to provide reliable predictions. Additionally, when band gap calculated by DFT-PBE was added into the feature space, band gap prediction RMSE decreases to 0.099 eV. Through a feature engineering algorithm, elemental feature space based band gap prediction RMSE further drops by around 0.005 eV and the relative importance of elemental properties for band gap prediction was revealed. Finally, band gap and band offset of all designed nitrides were predicted and two trends were noticed that as the number of cation types increases, band gap tends to narrow down while band offset tends to go up. The predicted results will be a useful guidance for precise investigation on nitride engineering. Copyright © 2018, The Authors. All rights reserved.

关键词： Energy gap

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Author Correction: Genomic footprints of activated telomere maintenance mechanisms in cancer (Dec, 10.1038/s41467-019-13824-9, 2022)

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NATURE COMMUNICATIONS 2022年第1期13卷 1-1页

作者： Sieverling, Lina Hong, Chen Koser, Sandra D. Ginsbach, Philip Kleinheinz, Kortine Hutter, Barbara Braun, Delia M. Cortes-Ciriano, Isidro Xi, Ruibin Kabbe, Rolf Park, Peter J. Eils, Roland Schlesner, Matthias Brors, Benedikt Rippe, Karsten Jones, David T. W. Feuerbach, Lars Division of Applied Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Faculty of Biosciences Heidelberg University 69120 Heidelberg Germany Division of Applied Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Biosciences Heidelberg University Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Department for Bioinformatics and Functional Genomics Institute for Pharmacy and Molecular Biotechnology (IPMB) and BioQuant 69120 Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Institute of Pharmacy and Molecular Biotechnology and BioQuant Heidelberg University Heidelberg Germany German Cancer Consortium (DKTK) Heidelberg Germany National Center for Tumor Diseases (NCT) Heidelberg Heidelberg Germany Heidelberg Center for Personalized Oncology (DKFZ-HIPO) German Cancer Research Center (DKFZ) Heidelberg Germany German Cancer Consortium (DKTK) German Cancer Research Center (DKFZ) Heidelberg Germany Division of Chromatin Networks German Cancer Research Center (DKFZ) and BioQuant 69120 Heidelberg Germany Department of Biomedical Informatics Harvard Medical School Boston Massachusetts 02115 USA Department of Chemistry Centre for Molecular Science Informatics University of Cambridge Cambridge CB2 1EW UK Ludwig Center at Harvard Medical School Boston Massachusetts 02115 USA Department of Biomedical Informatics Harvard Medical School Boston MA USA Department of Chemistry Centre for Molecular Science Informatics University of Cambridge Cambridge UK Ludwig Center at Harvard Medical School Boston MA USA School of Mathematical Sciences and Center for Statistical Science Peking University Beijing 100871 China Heidelberg University Heidelberg Germany New BIH Digital Health Center Berlin Institute of Health (BIH) and Charité - Universitätsmedizin Berlin Berlin Germany Bioi

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The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

arXiv

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arXiv 2023年

作者： Poldrack, Russell A. Markiewicz, Christopher J. Appelhoff, Stefan Ashar, Yoni K. Auer, Tibor Baillet, Sylvain Bansal, Shashank Beltrachini, Leandro Bénar, Christian G. Bertazzoli, Giacomo Bhogawar, Suyash Blair, Ross W. Bortoletto, Marta Boudreau, Mathieu Brooks, Teon L. Calhoun, Vince D. Castelli, Filippo Maria Clement, Patricia Cohen, Alexander L. Cohen-Adad, Julien D'Ambrosio, Sasha de Hollander, Gilles de la Iglesia-Vayá, María de la Vega, Alejandro Delorme, Arnaud Devinsky, Orrin Draschkow, Dejan Duff, Eugene Paul DuPre, Elizabeth Earl, Eric Esteban, Oscar Feingold, Franklin W. Flandin, Guillaume Galassi, Anthony Gallitto, Giuseppe Ganz, Melanie Gau, Rémi Gholam, James Ghosh, Satrajit S. Giacomel, Alessio Gillman, Ashley G. Gleeson, Padraig Gramfort, Alexandre Guay, Samuel Guidali, Giacomo Halchenko, Yaroslav O. Handwerker, Daniel A. Hardcastle, Nell Herholz, Peer Hermes, Dora Honey, Christopher J. Innis, Robert B. Ioanas, Horea-Ioan Jahn, Andrew Karakuzu, Agah Keator, David B. Kiar, Gregory Kincses, Balint Laird, Angela R. Lau, Jonathan C. Lazari, Alberto Legarreta, Jon Haitz Li, Adam Li, Xiangrui Love, Bradley C. Lu, Hanzhang Maumet, Camille Mazzamuto, Giacomo Meisler, Steven L. Mikkelsen, Mark Mutsaerts, Henk Nichols, Thomas E. Nikolaidis, Aki Nilsonne, Gustav Niso, Guiomar Norgaard, Martin Okell, Thomas W. Oostenveld, Robert Ort, Eduard Park, Patrick J. Pawlik, Mateusz Pernet, Cyril R. Pestilli, Franco Petr, Jan Phillips, Christophe Poline, Jean-Baptiste Pollonini, Luca Raamana, Pradeep Reddy Ritter, Petra Rizzo, Gaia Robbins, Kay A. Rockhill, Alexander P. Rogers, Christine Rokem, Ariel Rorden, Chris Routier, Alexandre Saborit-Torres, Jose Manuel Salo, Taylor Schirner, Michael Smith, Robert E. Spisak, Tamas Sprenger, Julia Swann, Nicole C. Szinte, Martin Takerkart, Sylvain Thirion, Bertrand Thomas, Adam G. Torabian, Sajjad Varoquaux, Gael Voytek, Bradley Welzel, Julius Wilson, Martin Yarkoni, Tal Gorgolewski, Krzysztof J. Department of Psychology Stanford University StanfordCA United States Max Planck Institute for Human Development Berlin Germany University of Colorado Anschutz Medical Campus AuroraCO United States School of Psychology University of Surrey Guildford United Kingdom McConnell Brain Imaging Centre Montréal Neurological Institute McGill University Montréal Canada Department of Bioengineering University of California San Diego La Jolla CA United States School of Physics Astronomy Cardiff University Wales United Kingdom Institut de Neurosciences des Systèmes Marseille France Neurophysiology Lab IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli Brescia Italy Center for Mind/Brain Sciences - CIMeC University of Trento TN Rovereto Italy Brigham and Women’s Hospital BostonMA United States Massachusetts General Hospital BostonMA United States Harvard Medical School BostonMA United States Rackspace Technology San AntonioTX United States NeuroPoly Lab Polytechnique Montréal MontréalQC Canada Georgia State Georgia Tech Emory AtlantaGA United States University of Florence Sesto Fiorentino Italy Bioretics srl Cesena Italy Department of Medical Imaging Ghent University Hospital Ghent Belgium Department of Diagnostic Sciences Ghent University Ghent Belgium Department of Neurology Boston Children's Hospital BostonMA United States Dipartimento di Scienze della Salute dell'Università degli Studi di Milano Milan Italy Department of Clinical and Experimental Epilepsy University College London United Kingdom Zurich Center for Neuroeconomics Department of Economics University of Zurich Zurich Switzerland UMIB-FISABIO Valencia Spain The University of Texas at Austin AustinTX United States SCCN University of California San Diego La Jolla CA United States Department of Neurology NYU Langone Medical Center New YorkNY United States Department of Experimental Psychology University of Oxford Oxford United Kingdom UK Dementia Research Ins

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS. © 2023, CC BY.

关键词： Data structures

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Animal Models for Microbiome Research and Drug Discovery

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Drug Discovery Today: Disease Models 2018年 28卷 1-2页

作者： Philip J. Richter Pieter C. Dorrestein Rob Knight Department of Pathology and Animal Care Program and Center for Veterinary Sciences and Comparative Medicine UC San Diego La Jolla CA 92093 USA Skaggs School of Pharmacy and Pharmaceutical Sciences Center for Microbiome Innovation and Departments of Pharmacology and Pediatrics UC San Diego La Jolla CA 92093 USA Center for Microbiome Innovation and Departments of Pediatrics Bioengineering and Computer Science & Engineering UC San Diego La Jolla CA 92093 USA

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High-Throughput Screening: One-Step Generation of a Drug-Releasing Hydrogel Microarray-On-A-Chip for Large-Scale Sequential Drug Combination Screening (Adv. Sci. 3/2019)

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Advanced science 2019年第3期6卷 1970014-1970014页

作者： Seo Woo Song Su Deok Kim Dong Yoon Oh Yongju Lee Amos Chungwon Lee Yunjin Jeong Hyung Jong Bae Daewon Lee Sumin Lee Jiyun Kim Sunghoon Kwon Department of Electrical and Computer Engineering Seoul National University Seoul 08826 South Korea Institutes of Entrepreneurial BioConvergence Seoul National University Seoul 08826 South Korea Department of Mechanical Science and Engineering University of Illinois at Urbana-Champaign Urbana IL 61801 USA Nano Systems Institute Seoul National University Seoul 08826 South Korea Interdisciplinary Program in Bioengineering Seoul National University Seoul 08826 South Korea School of Materials Science and Engineering Ulsan National Institute of Science and Technology Ulsan 44919 South Korea

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Elucidating the atomistic mechanisms underpinning plasticity in Li-Si nanostructures

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Physical Review materials 2017年第5期1卷 055401-055401页

作者： Xin Yan Afif Gouissem Pradeep R. Guduru Pradeep Sharma Department of Mechanical Engineering University of Houston Texas 77004 USA School of Engineering Brown University Providence Rhode Island 02912 USA Department of Physics University of Houston Texas 77004 USA Material Science and Engineering Program University of Houston Texas 77004 USA

Amorphous lithium-silicon (a-Li-Si), especially in nanostructure form, is an attractive high-capacity anode material for next-generation Li-ion batteries. During cycles of charging and discharging, a-Li-Si undergoes substantive inelastic deformation and exhibits microcracking. The mechanical response to repeated lithiation-delithiation eventually results in the loss of electrical contact and consequent decrease of capacity, thus underscoring the importance of studying the plasticity of a-Li-Si nanostructures. In recent years, a variety of phenomenological continuum theories have been introduced that purport to model plasticity and the electro-chemo-mechanical behavior of a-Li-Si. Unfortunately, the micromechanisms and atomistic considerations underlying plasticity in Li-Si material are not yet fully understood and this impedes the development of physics-based constitutive models. Conventional molecular dynamics, although extensively used to study this material, is grossly inadequate to resolve this matter. As is well known, conventional molecular dynamics simulations can only address phenomena with characteristic time scales of (at most) a microsecond. Accordingly, in such simulations, the mechanical behavior is deduced under conditions of very high strain rates (usually, 108s−1 or even higher). This limitation severely impacts a realistic assessment of rate-dependent effects. In this work, we attempt to circumvent the time-scale bottleneck of conventional molecular dynamics and provide novel insights into the mechanisms underpinning plastic deformation of Li-Si nanostructures. We utilize an approach that allows imposition of slow strain rates and involves the employment of a new and recently developed potential energy surface sampling method—the so-called autonomous basin climbing—to identify the local minima in the potential energy surface. Combined with other techniques, such as nudged elastic band, kinetic Monte Carlo and transition state theory, we assess the b

关键词： Mechanical deformation Plasticity Energy materials Nanostructures Multiscale modeling

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Author Correction: Stretchable, dynamic covalent polymers for soft, long-lived bioresorbable electronic stimulators designed to facilitate neuromuscular regeneration

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Nature communications 2021年第1期12卷 415页

作者： Yeon Sik Choi Yuan-Yu Hsueh Jahyun Koo Quansan Yang Raudel Avila Buwei Hu Zhaoqian Xie Geumbee Lee Zheng Ning Claire Liu Yameng Xu Young Joong Lee Weikang Zhao Jun Fang Yujun Deng Seung Min Lee Abraham Vázquez-Guardado Iwona Stepien Ying Yan Joseph W Song Chad Haney Yong Suk Oh Wentai Liu Hong-Joon Yoon Anthony Banks Matthew R MacEwan Guillermo A Ameer Wilson Z Ray Yonggang Huang Tao Xie Colin K Franz Song Li John A Rogers Center for Bio-Integrated Electronics Northwestern University Evanston IL 60208 USA. Querrey Simpson Institute for Biotechnology Northwestern University Evanston IL 60208 USA. Department of Materials Science and Engineering Northwestern University Evanston IL 60208 USA. Department of Bioengineering University of California Los Angeles Los Angeles CA 90095 USA. Division of Plastic and Reconstructive Surgery Department of Surgery National Cheng Kung University Hospital College of Medicine National Cheng Kung University Tainan 70456 Taiwan. International Research Center for Wound Repair and Regeneration National Cheng Kung University Tainan 70456 Taiwan. School of Biomedical Engineering Korea University Seoul 02841 Republic of Korea. Interdisciplinary Program in Precision Public Health Korea University Seoul 02841 Republic of Korea. Department of Mechanical Engineering Northwestern University Evanston IL 60208 USA. Department of Medicine University of California Los Angeles Los Angeles CA 90095 USA. State Key Laboratory of Structural Analysis for Industrial Equipment Dalian University of Technology 116024 Dalian China. Department of Engineering Mechanics Dalian University of Technology 116024 Dalian China. International Research Center for Computational Mechanics Dalian University of Technology 116024 Dalian China. State Key Laboratory of Chemical Engineering College of Chemical and Biological Engineering Zhejiang University 310027 Hangzhou China. Department of Biomedical Engineering Northwestern University Evanston IL 60208 USA. State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University 200240 Shanghai China. Center for Developmental Therapeutics Chemistry Life Processes Institute Northwestern University Evanston IL 60208 USA. Department of Neurological Surgery Washington University School of Medicine St. Louis MO 63110 USA. Center for Advanced Molecular Imaging Northwestern University Evanston IL

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Myocardial Cell Signaling During the Transition to Heart Failure

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Comprehensive Physiology 2019年第1期9卷 75-125页

作者： Matthew R. Zeglinski Adel Rezaei Moghadam Sudharsana R. Ande Kimia Sheikholeslami Pooneh Mokarram Zahra Sepehri Haleh Rokni Nima Khadem Mohtaram Mansour Poorebrahim Anahita Masoom Mehnosh Toback Niketa Sareen Sekaran Saravanan Davinder S. Jassal Mohammad Hashemi Hassan Marzban Dedmer Schaafsma Pawan Singal Jeffrey T. Wigle Michael P. Czubryt Mohsen Akbari Ian M.C. Dixon Saeid Ghavami Joseph W. Gordon Sanjiv Dhingra St. Boniface Hospital Research Centre Department of Physiology and Pathophysiology University of Manitoba Winnipeg Canada Department of Human Anatomy & Cell Science Max Rady College of Medicine Rady Faculty of Health Sciences University of Manitoba Winnipeg Canada Department of Internal Medicine University of Manitoba Winnipeg Canada Faculty of Medicine University of Toronto Toronto Ontario Canada Colorectal Research Center and Department of Biochemistry School of Medicine Shiraz University of Medical Sciences Shiraz Iran Department of Internal Medicine Zabol University of Medical Sciences Zabol Iran Laboratory for Innovation in Microengineering (LiME) Department of Mechanical Engineering University of Victoria Victoria British Columbia Canada Department of System Design Engineering Program of Biomedical Engineering University of Waterloo Department of Medical Biotechnology School of Advanced Technologies in Medicine Tehran University of Medical Sciences Tehran Iran Faculty of Medicine Mashhad Islamic Azad University Mashhad Iran Foothills Hospital Libin Cardiovascular Institute of Alberta Calgary Alberta Canada CeNTAB Department of Bioengineering SCBT SASTRA University Thanjavur India Department of Clinical Biochemistry School of Medicine Zahedan University of Medical Sciences Zahedan Iran Biology of Breathing Theme Children's Hospital Research Institute of Manitoba University of Manitoba Winnipeg Canada Health Policy Research Center Institute of Health Shiraz University of Medical Sciences Shiraz Iran College of Nursing and Children's Hospital Research Institute of Manitoba Rady Faculty of Health Sciences University of Manitoba Winnipeg Canada

Cardiovascular disease leading to heart failure (HF) remains a leading cause of morbidity and mortality worldwide. Improved pharmacological and interventional coronary procedures have led to improved outcomes following acute myocardial infarction. This success has translated into an unforeseen increased incidence in HF. This review summarizes the signaling pathways implicated in the transition to HF following cardiac injury. In addition, we provide an update on cell death signaling and discuss recent advances in cardiac fibrosis as an independent event leading to HF. Finally, we discuss cell-based therapies and their possible use to avert the deteriorating nature of HF. © 2019 American Physiological Society. Compr Physiol 9:75-125, 2019.

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Frontispiece: π–π Stacking Interaction in an Oxidized CuII–Salen Complex with a Side-Chain Indole Ring: An Approach to the Function of the Tryptophan in the Active Site of Galactose Oxidase

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Chemistry – A European Journal 2019年第32期25卷

作者： Dr. Hiromi Oshita Takashi Suzuki Kyohei Kawashima Prof. Dr. Hitoshi Abe Prof. Dr. Fumito Tani Prof. Dr. Seiji Mori Prof. Dr. Tatsuo Yajima Prof. Dr. Yuichi Shimazaki Graduate School of Science and Engineering Ibaraki University Mito Ibaraki 310-8512 Japan Present address: Department of Chemistry of Functional Molecules Konan University Higashinada-ku Kobe 658-8501 Japan Photon Factory Institute of Materials Structure Science High Energy Accelerator Research Organization Tsukuba Ibaraki 305-0801 Japan Institute for Material Chemistry and Engineering Kyushu University Nishi-ku Fukuoka 819-0395 Japan Faculty of Chemistry Materials and Bioengineering Kansai University Suita Osaka 564-8680 Japan

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