Institution
Hanyang University
Education•Seoul, South Korea•
About: Hanyang University is a education organization based out in Seoul, South Korea. It is known for research contribution in the topics: Thin film & Population. The organization has 29387 authors who have published 58815 publications receiving 1190144 citations. The organization is also known as: Hanyang Taehakkyo.
Topics: Thin film, Population, Oxide, Membrane, Catalysis
Papers published on a yearly basis
Papers
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TL;DR: Flexible three-dimensional artificial chemical synapse networks enable a direct emulation of correlated learning and trainable memory capability with strong tolerances to input faults and variations, which shows the feasibility of using them in futuristic electronic devices.
Abstract: If a three-dimensional physical electronic system emulating synapse networks could be built, that would be a significant step toward neuromorphic computing. However, the fabrication complexity of complementary metal-oxide-semiconductor architectures impedes the achievement of three-dimensional interconnectivity, high-device density, or flexibility. Here we report flexible three-dimensional artificial chemical synapse networks, in which two-terminal memristive devices, namely, electronic synapses (e-synapses), are connected by vertically stacking crossbar electrodes. The e-synapses resemble the key features of biological synapses: unilateral connection, long-term potentiation/depression, a spike-timing-dependent plasticity learning rule, paired-pulse facilitation, and ultralow-power consumption. The three-dimensional artificial synapse networks enable a direct emulation of correlated learning and trainable memory capability with strong tolerances to input faults and variations, which shows the feasibility of using them in futuristic electronic devices and can provide a physical platform for the realization of smart memories and machine learning and for operation of the complex algorithms involving hierarchical neural networks. High-density information storage calls for the development of modern electronics with multiple stacking architectures that increase the complexity of three-dimensional interconnectivity. Here, Wu et al. build a stacked yet flexible artificial synapse network using layer-by-layer solution processing.
218 citations
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TL;DR: In this paper, the effect of dopants on the electrochemical properties of LiNiO 2-based cathode materials was investigated, and the cathode material containing 5 mol% Co had the lowest impedance, 47 ǫ cm 2, while undoped, Ti-doped, and Al-Doped materials had impedance of 64, 62, and 99 ǔ cm 2, respectively.
218 citations
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TL;DR: In this paper, the mass of the dynamical ejecta can be estimated without a direct electromagnetic observation of the kilonova, using GW measurements and a phenomenological model calibrated to numerical simulations of mergers with dynamical ejecteda.
Abstract: The source of the gravitational-wave (GW) signal GW170817, very likely a binary neutron star merger, was also
observed electromagnetically, providing the first multi-messenger observations of this type. The two-week-long
electromagnetic (EM) counterpart had a signature indicative of an r-process-induced optical transient known as a
kilonova. This Letter examines how the mass of the dynamical ejecta can be estimated without a direct
electromagnetic observation of the kilonova, using GW measurements and a phenomenological model calibrated to
numerical simulations of mergers with dynamical ejecta. Specifically, we apply the model to the binary masses
inferred from the GW measurements, and use the resulting mass of the dynamical ejecta to estimate its contribution
(without the effects of wind ejecta) to the corresponding kilonova light curves from various models. The
distributions of dynamical ejecta mass range between = - - - M M ej 10 10
3 2 for various equations of state,
assuming that the neutron stars are rotating slowly. In addition, we use our estimates of the dynamical ejecta mass
and the neutron star merger rates inferred from GW170817 to constrain the contribution of events like this to the
r-process element abundance in the Galaxy when ejecta mass from post-merger winds is neglected. We find that if
10% of the matter dynamically ejected from binary neutron star (BNS) mergers is converted to r-process
elements, GW170817-like BNS mergers could fully account for the amount of r-process material observed in the
Milky Way.
217 citations
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University of Tokyo1, Budker Institute of Nuclear Physics2, École Polytechnique Fédérale de Lausanne3, University of Sydney4, University of Melbourne5, Panjab University, Chandigarh6, Polish Academy of Sciences7, University of Maribor8, Fu Jen Catholic University9, National Taiwan University10, National Central University11, Hanyang University12, Yonsei University13, Gyeongsang National University14, Sungkyunkwan University15, University of Cincinnati16, University of Ljubljana17, Korea University18, Nagoya University19, Nara Women's University20, Tohoku Gakuin University21, Kyungpook National University22, Saga University23, Tokyo Institute of Technology24, Niigata University25, Graduate University for Advanced Studies26, University of Giessen27, Seoul National University28, University of Science and Technology of China29, Austrian Academy of Sciences30, Osaka City University31, Tokyo University of Agriculture and Technology32, Toho University33, Kanagawa University34, Virginia Tech35, University of Nova Gorica36, Tokyo Metropolitan University37, National United University38
TL;DR: In this paper, the authors presented a method to solve the PDE problem using the Web of Science Record created on 2010-11-05, modified on 2017-12-10.
Abstract: Reference EPFL-ARTICLE-154418doi:10.1103/PhysRevD.78.072004View record in Web of Science Record created on 2010-11-05, modified on 2017-12-10
217 citations
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Wellcome Trust1, Los Alamos National Laboratory2, Wellcome Trust Sanger Institute3, Lund University4, Erasmus University Medical Center5, Radboud University Nijmegen6, Hanyang University7, Université libre de Bruxelles8, University of Texas MD Anderson Cancer Center9, University of Antwerp10, Royal Brisbane and Women's Hospital11, University of Queensland12, University of Iceland13, University of Dundee14, University of Amsterdam15, University of Oslo16, Harvard University17, Medical Research Council18, Cambridge University Hospitals NHS Foundation Trust19
TL;DR: Using somatic mutation catalogues from 560 breast cancer whole-genome sequences, it is shown that each of 12 base substitution, 2 insertion/deletion (indel) and 6 rearrangement mutational signatures present in breast tissue, exhibit distinct relationships with genomic features relating to transcription, DNA replication and chromatin organization.
Abstract: Somatic mutations in human cancers show unevenness in genomic distribution that correlate with aspects of genome structure and function. These mutations are, however, generated by multiple mutational processes operating through the cellular lineage between the fertilized egg and the cancer cell, each composed of specific DNA damage and repair components and leaving its own characteristic mutational signature on the genome. Using somatic mutation catalogues from 560 breast cancer whole-genome sequences, here we show that each of 12 base substitution, 2 insertion/deletion (indel) and 6 rearrangement mutational signatures present in breast tissue, exhibit distinct relationships with genomic features relating to transcription, DNA replication and chromatin organization. This signature-based approach permits visualization of the genomic distribution of mutational processes associated with APOBEC enzymes, mismatch repair deficiency and homologous recombinational repair deficiency, as well as mutational processes of unknown aetiology. Furthermore, it highlights mechanistic insights including a putative replication-dependent mechanism of APOBEC-related mutagenesis.
217 citations
Authors
Showing all 29583 results
Name | H-index | Papers | Citations |
---|---|---|---|
John A. Rogers | 177 | 1341 | 127390 |
Charles M. Lieber | 165 | 521 | 132811 |
Jongmin Lee | 150 | 2257 | 134772 |
Rajesh Kumar | 149 | 4439 | 140830 |
Prashant V. Kamat | 140 | 725 | 79259 |
Tae Jeong Kim | 132 | 1420 | 93959 |
Jie Liu | 131 | 1531 | 68891 |
Junghwan Goh | 128 | 1068 | 77137 |
Young Hee Lee | 122 | 1168 | 61107 |
Allan H. MacDonald | 119 | 926 | 56221 |
Terence G. Langdon | 117 | 1158 | 61603 |
Yang-Kook Sun | 117 | 781 | 58912 |
Sang Yup Lee | 117 | 1005 | 53257 |
Yoshinobu Unno | 115 | 875 | 66107 |
Xi Chen | 105 | 1547 | 52533 |