Institution
National Cheng Kung University
Education•Tainan City, Taiwan•
About: National Cheng Kung University is a education organization based out in Tainan City, Taiwan. It is known for research contribution in the topics: Population & Thin film. The organization has 49723 authors who have published 69799 publications receiving 1437420 citations. The organization is also known as: NCKU.
Topics: Population, Thin film, Dielectric, Heat transfer, Microstructure
Papers published on a yearly basis
Papers
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TL;DR: In this paper, the improvement on physical and chemical properties of pulverized biomass from torrefaction was investigated to evaluate the potential of biomass as solid fuel used in boilers and blast furnaces.
260 citations
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TL;DR: The proposed method can accurately estimate the SOH of the battery in a short period, and the average error of the prediction is 0.28% and the standard deviation is 1.15%.
Abstract: In this study, a probabilistic neural network (PNN) is used to estimate the state of health (SOH) of Li-ion batteries. The accurate prediction of SOH can help avoid inconveniences or fatal accidents from the sudden malfunction of the battery. A total of 110 pieces of Li-Co batteries are used. Constant current/voltage recharging and constant current discharging are performed for the life-cycle test of the battery. The data obtained from the recharging and discharging electric characteristics as well as the life-cycle test of the battery are used to estimate the SOH of the battery. The test data show that the constant current charging time, the instantaneous voltage drop at the start of discharging, and the open circuit voltage are the most important characteristics for estimating the SOH of the battery. The PNN is trained using 100 pieces of batteries. The remaining 10 pieces are used to verify the feasibility of the proposed method. The effectiveness of the PNN training using a number of samples is discussed and analyzed. The results show that the average error of the prediction is 0.28% and the standard deviation is 1.15%. The computation time of the PNN is 62.5 ms. Thus, the proposed method can accurately estimate the SOH of the battery in a short period.
260 citations
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TL;DR: A comprehensive review of the research and development on the effects of catalysts on the thermochemical conversion of biomass to determine the progress of catalytic thermochemical transformation processes is presented in this article.
Abstract: The increasing demand for energy and diminishing sources of fossil fuels have called for the discovery of new energy sources. The effective energy conversion process of biomass is able to fulfill energy needs. Among the advanced biomass conversion technologies, thermochemical processes hold considerable potential approaches and needed for optimization. Thus, this study presents a comprehensive review of the research and development on the effects of catalysts on the thermochemical conversion of biomass to determine the progress of catalytic thermochemical conversion processes. The effects of catalysts on torrefaction, pyrolysis, hydrothermal liquefaction, and gasification are highlighted. Aspects related to reaction conditions, reactor types, and products are discussed comprehensively with the reaction mechanisms involved in the catalytic effects. Hydrogenation and hydrodeoxygenation can occur in the presence of zeolite catalysts during fast pyrolysis while producing highly aromatic bio-oil. A heterogeneous catalyst in liquefaction increases the hydrocarbon content and decreases viscosity, acid value, and oxygenated compounds in the bio-oil. Thus, expanding and enhancing knowledge about catalyst utilization in the thermochemical conversion technologies of biomass will play an important role in the generation of renewable and carbon-neutral fuels.
260 citations
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TL;DR: In this paper, the Riccati equation approach is used to obtain the memoryless linear state feedback control of uncertain dynamic delay systems, where uncertainties are time varying and within a given compact set.
Abstract: The authors present a procedure for obtaining the memoryless linear state feedback control of uncertain dynamic delay systems. The uncertainties are time varying and within a given compact set. This method is an extension of the Riccati equation approach proposed by I.R. Petersen and C.V. Hollot (1986). The extension is straightforward. Also the uncertainties do not need to satisfy the matching conditions. >
260 citations
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TL;DR: In this article, a microstructural model and its equivalent circuit based on a series connection with semiconducting domain interior, insulating domain boundary, and insulating grain boundary have been established, which not only solve the contradictory explanation of the dielectric response b...
Abstract: The delicate self-intertwined domain structures inside the grains of the polycrystalline CaCu3Ti4O12 (CCTO) were discovered by scanning electron microscopy (SEM) and high-resolution transmission electron microscopy (HRTEM), which provided a direct clue in understanding the mystery of the huge dielectric response of this intriguing material. Domain morphologies with and without terrace and ledge were observed by SEM. The detailed domain structures were further examined by HRTEM, and it was found that they contained strained and unstrained domains. The strained domains essentially are constructed by various dimensional superlattices. The coherent domain boundaries were considered to be strained, composition-disordered, and insulating. A microstructural model and its equivalent circuit based on a series connection with semiconducting domain interior, insulating domain boundary, and insulating grain boundary have been established, which not only solve the contradictory explanation of the dielectric response b...
259 citations
Authors
Showing all 49872 results
Name | H-index | Papers | Citations |
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Yi Chen | 217 | 4342 | 293080 |
Yang Yang | 164 | 2704 | 144071 |
R. E. Hughes | 154 | 1312 | 110970 |
Mercouri G. Kanatzidis | 152 | 1854 | 113022 |
Thomas J. Smith | 140 | 1775 | 113919 |
Hui Li | 135 | 2982 | 105903 |
Gerald M. Reaven | 133 | 799 | 80351 |
Chi-Huey Wong | 129 | 1220 | 66349 |
Joseph P. Vacanti | 119 | 441 | 50739 |
Kai Nan An | 109 | 953 | 51638 |
Ding-Shinn Chen | 104 | 774 | 46068 |
James D. Neaton | 101 | 331 | 64719 |
David C. Christiani | 100 | 1052 | 55399 |
Jo Shu Chang | 99 | 639 | 37487 |
Yu Shyr | 98 | 542 | 39527 |