Institution
Nanjing University
Education•Nanjing, China•
About: Nanjing University is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Catalysis & Population. The organization has 85961 authors who have published 105504 publications receiving 2289036 citations. The organization is also known as: NJU & Nanking University.
Topics: Catalysis, Population, Adsorption, Magnetization, Graphene
Papers published on a yearly basis
Papers
More filters
••
TL;DR: This study provides direct evidence that sulphur vacancies exist in molybdenum disulphide, and introduces localized donor states inside the bandgap, suggesting that the low-carrier-density transport is dominated by hopping via these localized gap states.
Abstract: Molybdenum disulphide is a novel two-dimensional semiconductor with potential applications in electronic and optoelectronic devices. However, the nature of charge transport in back-gated devices still remains elusive as they show much lower mobility than theoretical calculations and native n-type doping. Here we report a study of transport in few-layer molybdenum disulphide, together with transmission electron microscopy and density functional theory. We provide direct evidence that sulphur vacancies exist in molybdenum disulphide, introducing localized donor states inside the bandgap. Under low carrier densities, the transport exhibits nearest-neighbour hopping at high temperatures and variable-range hopping at low temperatures, which can be well explained under Mott formalism. We suggest that the low-carrier-density transport is dominated by hopping via these localized gap states. Our study reveals the important role of short-range surface defects in tailoring the properties and device applications of molybdenum disulphide.
948 citations
••
TL;DR: A self-assembling plasmonic absorber which can enable an average measured absorbance of ~99% across the wavelengths from 400 nm to 10 μm is reported, the most efficient and broadband plas Monte Carlo absorber reported to date.
Abstract: The study of ideal absorbers, which can efficiently absorb light over a broad range of wavelengths, is of fundamental importance, as well as critical for many applications from solar steam generation and thermophotovoltaics to light/thermal detectors. As a result of recent advances in plasmonics, plasmonic absorbers have attracted a lot of attention. However, the performance and scalability of these absorbers, predominantly fabricated by the top-down approach, need to be further improved to enable widespread applications. We report a plasmonic absorber which can enable an average measured absorbance of ~99% across the wavelengths from 400 nm to 10 μm, the most efficient and broadband plasmonic absorber reported to date. The absorber is fabricated through self-assembly of metallic nanoparticles onto a nanoporous template by a one-step deposition process. Because of its efficient light absorption, strong field enhancement, and porous structures, which together enable not only efficient solar absorption but also significant local heating and continuous stream flow, plasmonic absorber–based solar steam generation has over 90% efficiency under solar irradiation of only 4-sun intensity (4 kW m−2). The pronounced light absorption effect coupled with the high-throughput self-assembly process could lead toward large-scale manufacturing of other nanophotonic structures and devices.
946 citations
••
TL;DR: In this article, the authors demonstrate parity-time-symmetric optics on a chip at the 1,550-nm wavelength in two directly coupled high-Q silica-microtoroid resonators with balanced effective gain and loss.
Abstract: On-chip parity–time-symmetric optics is experimentally demonstrated at a wavelength of 1,550 nm in two directly coupled, high-Q silica microtoroid resonators with balanced effective gain and loss. Switchable optical isolation with a nonreciprocal isolation ratio between −8 dB and +8 dB is also shown. The findings will be useful for potential applications in optical isolators, on-chip light control and optical communications. Compound-photonic structures with gain and loss1 provide a powerful platform for testing various theoretical proposals on non-Hermitian parity–time-symmetric quantum mechanics2,3,4,5 and initiate new possibilities for shaping optical beams and pulses beyond conservative structures. Such structures can be designed as optical analogues of complex parity–time-symmetric potentials with real spectra. However, the beam dynamics can exhibit unique features distinct from conservative systems due to non-trivial wave interference and phase-transition effects. Here, we experimentally realize parity–time-symmetric optics on a chip at the 1,550 nm wavelength in two directly coupled high-Q silica-microtoroid resonators with balanced effective gain and loss. With this composite system, we further implement switchable optical isolation with a non-reciprocal isolation ratio from −8 dB to +8 dB, by breaking time-reversal symmetry with gain-saturated nonlinearity in a large parameter-tunable space. Of importance, our scheme opens a door towards synthesizing novel microscale photonic structures for potential applications in optical isolators, on-chip light control and optical communications.
943 citations
••
TL;DR: The present work highlights the potential for using amino-functionalized Fe(3)O(4)@SiO(2) magnetic nanoparticles as an effective and recyclable adsorbent for the removal of heavy metal ions in water and wastewater treatment.
932 citations
••
08 Sep 2016TL;DR: A method to perform sequencediscriminative training of neural network acoustic models without the need for frame-level cross-entropy pre-training is described, using the lattice-free version of the maximum mutual information (MMI) criterion: LF-MMI.
Abstract: In this paper we describe a method to perform sequencediscriminative training of neural network acoustic models without the need for frame-level cross-entropy pre-training. We use the lattice-free version of the maximum mutual information (MMI) criterion: LF-MMI. To make its computation feasible we use a phone n-gram language model, in place of the word language model. To further reduce its space and time complexity we compute the objective function using neural network outputs at one third the standard frame rate. These changes enable us to perform the computation for the forward-backward algorithm on GPUs. Further the reduced output frame-rate also provides a significant speed-up during decoding. We present results on 5 different LVCSR tasks with training data ranging from 100 to 2100 hours. Models trained with LFMMI provide a relative word error rate reduction of ∼11.5%, over those trained with cross-entropy objective function, and ∼8%, over those trained with cross-entropy and sMBR objective functions. A further reduction of ∼2.5%, relative, can be obtained by fine tuning these models with the word-lattice based sMBR objective function.
930 citations
Authors
Showing all 86514 results
Name | H-index | Papers | Citations |
---|---|---|---|
Yi Chen | 217 | 4342 | 293080 |
H. S. Chen | 179 | 2401 | 178529 |
Zhenan Bao | 169 | 865 | 106571 |
Gang Chen | 167 | 3372 | 149819 |
Peter G. Schultz | 156 | 893 | 89716 |
Xiang Zhang | 154 | 1733 | 117576 |
Rui Zhang | 151 | 2625 | 107917 |
Yi Yang | 143 | 2456 | 92268 |
Markku Kulmala | 142 | 1487 | 85179 |
Jian Yang | 142 | 1818 | 111166 |
Wei Huang | 139 | 2417 | 93522 |
Bin Liu | 138 | 2181 | 87085 |
Jun Lu | 135 | 1526 | 99767 |
Hui Li | 135 | 2982 | 105903 |
Lei Zhang | 135 | 2240 | 99365 |