Institution
Academia Sinica
Facility•Taipei, Taiwan•
About: Academia Sinica is a facility organization based out in Taipei, Taiwan. It is known for research contribution in the topics: Population & Galaxy. The organization has 52086 authors who have published 65998 publications receiving 1728114 citations. The organization is also known as: Central Research Academy.
Topics: Population, Galaxy, Large Hadron Collider, Gene, Higgs boson
Papers published on a yearly basis
Papers
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TL;DR: A significant band gap as high as 600 meV is observed for low BN concentrations and is attributed to the opening of the π-π* band gap of graphene due to isoelectronic BN doping.
Abstract: Band gap opening and engineering is one of the high priority goals in the development of graphene electronics. Here, we report on the opening and scaling of band gap in BN doped graphene (BNG) films grown by low-pressure chemical vapor deposition method. High resolution transmission electron microscopy is employed to resolve the graphene and h-BN domain formation in great detail. X-ray photoelectron, micro-Raman, and UV–vis spectroscopy studies revealed a distinct structural and phase evolution in BNG films at low BN concentration. Synchrotron radiation based XAS-XES measurements concluded a gap opening in BNG films, which is also confirmed by field effect transistor measurements. For the first time, a significant band gap as high as 600 meV is observed for low BN concentrations and is attributed to the opening of the π–π* band gap of graphene due to isoelectronic BN doping. As-grown films exhibit structural evolution from homogeneously dispersed small BN clusters to large sized BN domains with embedded d...
236 citations
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TL;DR: This research provides a simple method to obtain a graphene bilayer transistor with a moderate on/off current ratio, which can be stably operated in air without the need to use an additional top gate.
Abstract: The opening of an electrical band gap in graphene is crucial for its application for logic circuits. Recent studies have shown that anenergy gap in Bernal-stacked bilayer graphene can begeneratedbyapplyinganelectricdisplacement field.Moleculardopinghasalsobeenproposedto open the electrical gap of bilayer graphene by breaking either in-plane symmetry or inversion symmetry; however, no direct observation of an electrical gap has been reported. Here we discover that the organic molecule triazine is able to form a uniform thin coating on the top surface of a bilayergraphene,whichefficientlyblockstheaccessibledopingsitesandpreventsambientp-doping onthetoplayer.Thechargedistributionasymmetrybetweenthetopandbottomlayerscanthenbe enhanced simply by increasing the p-doping from oxygen/moisture to the bottom layer. The on/off current ratio for a bottom-gated bilayer transistor operated in ambient condition is improved by at least 1 order of magnitude. The estimated electrical band gap is up to ∼111 meV at room temperature. The observed electrical band gap dependence on the hole-carrier density increase agrees well with the recent density-functional theory calculations. This research provides a simple method to obtain a graphene bilayer transistor with a moderate on/off current ratio, which can be stably operated in air without the need to use an additional top gate.
236 citations
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TL;DR: In this article, a new method is proposed to calculate wave functions in k T -factorization in [H.-n. Li, S. Feng, J.P. Ma, Q. Wang, Phys. Lett. B 674 (2009) 182, arXiv:0808.0296].
236 citations
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13 Oct 2016TL;DR: In this article, a variational auto-encoder-decoder framework for spectral conversion with unaligned corpora is proposed. But it does not use parallel corpora or phonetic alignments to train a spectral conversion system.
Abstract: We propose a flexible framework for spectral conversion (SC) that facilitates training with unaligned corpora. Many SC frameworks require parallel corpora, phonetic alignments, or explicit frame-wise correspondence for learning conversion functions or for synthesizing a target spectrum with the aid of alignments. However, these requirements gravely limit the scope of practical applications of SC due to scarcity or even unavailability of parallel corpora. We propose an SC framework based on variational auto-encoder which enables us to exploit non-parallel corpora. The framework comprises an encoder that learns speaker-independent phonetic representations and a decoder that learns to reconstruct the designated speaker. It removes the requirement of parallel corpora or phonetic alignments to train a spectral conversion system. We report objective and subjective evaluations to validate our proposed method and compare it to SC methods that have access to aligned corpora.
235 citations
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University of Tokyo1, University of Wisconsin-Madison2, University of Toronto3, University of Kentucky4, University of Texas at Austin5, University of Washington6, University of St Andrews7, University of Portsmouth8, European Southern Observatory9, University of Nottingham10, National Autonomous University of Mexico11, University of Pittsburgh12, University of Cambridge13, New Mexico State University14, Carnegie Institution for Science15, University of Sydney16, New York University17, University of Utah18, University of Oxford19, University of California, Santa Cruz20, Max Planck Society21, Claude Bernard University Lyon 122, École normale supérieure de Lyon23, Texas Christian University24, University of Iowa25, Princeton University26, Case Western Reserve University27, University of La Laguna28, Chinese Academy of Sciences29, Academia Sinica30, University of Manchester31, Australian Astronomical Observatory32, Macquarie University33, Yale University34, Lawrence Berkeley National Laboratory35, University of Potsdam36, University of Victoria37, University of Groningen38
TL;DR: MaNGA (Mapping Nearby Galaxies at Apache Point Observatory) as discussed by the authors employs dithered observations with 17 fiber-bundle integral field units that vary in diameter from 12" (19 fibers) to 32" (127 fibers).
Abstract: We present an overview of a new integral field spectroscopic survey called MaNGA (Mapping Nearby Galaxies at Apache Point Observatory), one of three core programs in the fourth-generation Sloan Digital Sky Survey (SDSS-IV) that began on 2014 July 1. MaNGA will investigate the internal kinematic structure and composition of gas and stars in an unprecedented sample of 10,000 nearby galaxies. We summarize essential characteristics of the instrument and survey design in the context of MaNGA's key science goals and present prototype observations to demonstrate MaNGA's scientific potential. MaNGA employs dithered observations with 17 fiber-bundle integral field units that vary in diameter from 12" (19 fibers) to 32" (127 fibers). Two dual-channel spectrographs provide simultaneous wavelength coverage over 3600-10300 A at R~2000. With a typical integration time of 3 hr, MaNGA reaches a target r-band signal-to-noise ratio of 4-8 (per A, per 2" fiber) at 23 AB mag per sq. arcsec, which is typical for the outskirts of MaNGA galaxies. Targets are selected with stellar mass greater than 1e9 Msun using SDSS-I redshifts and i-band luminosity to achieve uniform radial coverage in terms of the effective radius, an approximately flat distribution in stellar mass, and a sample spanning a wide range of environments. Analysis of our prototype observations demonstrates MaNGA's ability to probe gas ionization, shed light on recent star formation and quenching, enable dynamical modeling, decompose constituent components, and map the composition of stellar populations. MaNGA's spatially resolved spectra will enable an unprecedented study of the astrophysics of nearby galaxies in the coming 6 yr.
235 citations
Authors
Showing all 52129 results
Name | H-index | Papers | Citations |
---|---|---|---|
Yi Chen | 217 | 4342 | 293080 |
Jing Wang | 184 | 4046 | 202769 |
Jie Zhang | 178 | 4857 | 221720 |
Hyun-Chul Kim | 176 | 4076 | 183227 |
Yang Yang | 164 | 2704 | 144071 |
Yuh Nung Jan | 162 | 460 | 74818 |
Jongmin Lee | 150 | 2257 | 134772 |
Hui-Ming Cheng | 147 | 880 | 111921 |
Teruki Kamon | 142 | 2034 | 115633 |
Jian Yang | 142 | 1818 | 111166 |
I. V. Gorelov | 139 | 1916 | 103133 |
S. R. Hou | 139 | 1845 | 106563 |
Kaori Maeshima | 139 | 1850 | 105218 |
Jiangyong Jia | 138 | 1173 | 91163 |
Kenneth Bloom | 138 | 1958 | 110129 |