Institution
Tohoku University
Education•Sendai, Japan•
About: Tohoku University is a education organization based out in Sendai, Japan. It is known for research contribution in the topics: Magnetization & Population. The organization has 72116 authors who have published 170791 publications receiving 3941714 citations. The organization is also known as: Tōhoku daigaku.
Topics: Magnetization, Population, Alloy, Amorphous solid, Amorphous metal
Papers published on a yearly basis
Papers
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TL;DR: This Review discusses structure prediction methods, examining their potential for the study of different materials systems, and presents examples of computationally driven discoveries of new materials — including superhard materials, superconductors and organic materials — that will enable new technologies.
Abstract: Progress in the discovery of new materials has been accelerated by the development of reliable quantum-mechanical approaches to crystal structure prediction. The properties of a material depend very sensitively on its structure; therefore, structure prediction is the key to computational materials discovery. Structure prediction was considered to be a formidable problem, but the development of new computational tools has allowed the structures of many new and increasingly complex materials to be anticipated. These widely applicable methods, based on global optimization and relying on little or no empirical knowledge, have been used to study crystalline structures, point defects, surfaces and interfaces. In this Review, we discuss structure prediction methods, examining their potential for the study of different materials systems, and present examples of computationally driven discoveries of new materials — including superhard materials, superconductors and organic materials — that will enable new technologies. Advances in first-principle structure predictions also lead to a better understanding of physical and chemical phenomena in materials. Recent breakthroughs in crystal structure prediction have enabled the discovery of new materials and of new physical and chemical phenomena. This Review surveys structure prediction methods and presents examples of results in different classes of materials.
415 citations
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TL;DR: The association between stroke risk and the pattern of circadian BP variation was analyzed with a Cox proportional hazards model and there was no significant association between total strokerisk and the nocturnal decline in BP (percentage decline from diurnal level) or between total strokes and the morning pressor surge.
Abstract: There is continuing controversy over whether the pattern of circadian blood pressure (BP) variation that includes a nocturnal decline in BP and a morning pressor surge has prognostic significance for stroke risk. In this study, we followed the incidence of stroke in 1430 subjects aged > or =40 years in Ohasama, Japan, for an average of 10.4 years. The association between stroke risk and the pattern of circadian BP variation was analyzed with a Cox proportional hazards model after adjustment for possible confounding factors. There was no significant association between total stroke risk and the nocturnal decline in BP (percentage decline from diurnal level) or between total stroke risk and the morning pressor surge. The cerebral infarction risk was significantly higher in subjects with a or =10% nocturnal decline in BP (P=0.04). The morning pressor surge was not associated with a risk of cerebral infarction. On the other hand, an increased risk of cerebral hemorrhage was observed in subjects with a large morning pressor surge (> or =25 mm Hg; P=0.04). Intracerebral hemorrhage was also observed more frequently in extreme dippers (those with a > or =20% nocturnal decline in BP) than dippers (those with a 10% to 19% decline; P=0.02). A disturbed nocturnal decline in BP is associated with cerebral infarction, whereas a large morning pressor surge and a large nocturnal decline in BP, which are analogous to a large diurnal increase in BP, are both associated with cerebral hemorrhage.
414 citations
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TL;DR: X-ray photoelectron spectroscopy studies on CeO2-x nanoparticles and ab initio computer simulation on BaTiO3 clusters show that the origin of expansion is the decrease of electrostatic force caused by valence reduction of Ce ions and the increase in ionicity of Ti ions, respectively.
Abstract: Anomalous lattice expansions have been measured for the first time in monodisperse ${\mathrm{CeO}}_{2\ensuremath{-}x}$ nanoparticles and in ${\mathrm{BaTiO}}_{3}$ single nanoparticles by electron diffraction. X-ray photoelectron spectroscopy studies on ${\mathrm{CeO}}_{2\ensuremath{-}x}$ nanoparticles and ab initio computer simulation on ${\mathrm{BaTiO}}_{3}$ clusters show that the origin of expansion is the decrease of electrostatic force caused by valence reduction of Ce ions and the increase in ionicity of Ti ions, respectively. The lattice constant change of oxide (ionic) nanoparticles with the increase in ionicity would depend on the structure of the particles. Hence, first-principles calculations of large ionic clusters are indispensable.
414 citations
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01 Oct 2017TL;DR: A generative model which can learn a semantic representation of unlabeled videos, and is capable of generating videos, is proposed, and a novel method to train it stably in an end-to-end manner is proposed.
Abstract: In this paper, we propose a generative model, Temporal Generative Adversarial Nets (TGAN), which can learn a semantic representation of unlabeled videos, and is capable of generating videos. Unlike existing Generative Adversarial Nets (GAN)-based methods that generate videos with a single generator consisting of 3D deconvolutional layers, our model exploits two different types of generators: a temporal generator and an image generator. The temporal generator takes a single latent variable as input and outputs a set of latent variables, each of which corresponds to an image frame in a video. The image generator transforms a set of such latent variables into a video. To deal with instability in training of GAN with such advanced networks, we adopt a recently proposed model, Wasserstein GAN, and propose a novel method to train it stably in an end-to-end manner. The experimental results demonstrate the effectiveness of our methods.
414 citations
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TL;DR: A review of metal borohydrides with high hydrogen density can be found in this article, with a focus on the fundamental dehydrogenation and rehydrogenation properties.
Abstract: The prerequisite for widespread use of hydrogen as an energy carrier is the development of new materials that can safely store it at high gravimetric and volumetric densities. Metal borohydrides M(BH4)n (n is the valence of metal M), in particular, have high hydrogen density, and are therefore regarded as one such potential hydrogen storage material. For fuel cell vehicles, the goal for on-board storage systems is to achieve reversible store at high density but moderate temperature and hydrogen pressure. To this end, a large amount of effort has been devoted to improvements in their thermodynamic and kinetic aspects. This review provides an overview of recent research activity on various M(BH4)n, with a focus on the fundamental dehydrogenation and rehydrogenation properties and on providing guidance for material design in terms of tailoring thermodynamics and promoting kinetics for hydrogen storage.
414 citations
Authors
Showing all 72477 results
Name | H-index | Papers | Citations |
---|---|---|---|
John Q. Trojanowski | 226 | 1467 | 213948 |
Aaron R. Folsom | 181 | 1118 | 134044 |
Marc G. Caron | 173 | 674 | 99802 |
Masayuki Yamamoto | 171 | 1576 | 123028 |
Kenji Watanabe | 167 | 2359 | 129337 |
Rodney S. Ruoff | 164 | 666 | 194902 |
Frederik Barkhof | 154 | 1449 | 104982 |
Takashi Taniguchi | 152 | 2141 | 110658 |
Yoshio Bando | 147 | 1234 | 80883 |
Thomas P. Russell | 141 | 1012 | 80055 |
Ali Khademhosseini | 140 | 887 | 76430 |
Marco Colonna | 139 | 512 | 71166 |
David H. Barlow | 133 | 786 | 72730 |
Lin Gu | 130 | 868 | 56157 |
Yoichiro Iwakura | 129 | 705 | 64041 |