Institution
Memorial University of Newfoundland
Education•St. John's, Newfoundland and Labrador, Canada•
About: Memorial University of Newfoundland is a education organization based out in St. John's, Newfoundland and Labrador, Canada. It is known for research contribution in the topics: Population & Context (language use). The organization has 13818 authors who have published 27785 publications receiving 743594 citations. The organization is also known as: Memorial University & Memorial University of Newfoundland and Labrador.
Topics: Population, Context (language use), Health care, Gadus, Computer science
Papers published on a yearly basis
Papers
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TL;DR: In this paper, the physicochemical properties of pulse starches isolated from different cultivars of faba beans (FB), black beans (BB), and pinto beans (PB) were examined.
189 citations
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TL;DR: It was concluded that cytochrome P-450 was responsible for most of the peroxidase activity of liver microsomes and a mechanism for the microsomal peroxIDase activity is proposed in which LAHPO oxidizes the P- 450 thiol ligand to form high spin P-420.
189 citations
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12 Oct 2003TL;DR: It has been found that the proposed design has yielded successful simulation and experimental results, and the maximum load inertia corresponding to the rotor-bar depth has been determined from the simulation results.
Abstract: This paper presents a successful design of a high-efficiency small but novel interior permanent-magnet motor using NdBFe magnets. It is designed to operate both at line and variable frequencies. Line start with high inertia load was a special consideration. Time-stepping finite-element analysis has been used to successfully predict the dynamic and transient performances of the prototype motors. It has been found that the proposed design has yielded successful simulation and experimental results. The maximum load inertia corresponding to the rotor-bar depth has been determined from the simulation results.
189 citations
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TL;DR: In this paper, a review of large scale pyrolysis process units, reactor mathematical models, mechanisms for conversion of woody biomass and overview of heat of pyrolyses is presented.
Abstract: The thermal decomposition of woody biomass in the absence of oxygen, or pyrolysis, is a series of complex reactions involving hundreds of compounds. The species of residue, form of residue (bark, sawdust, and other residues), age, storage conditions, among other factors, will impact the composition of the residue which in turn impacts the pyrolytic reactions. The reaction rates must be understood to optimize the pyrolysis reactor. However, the determination of intrinsic kinetics in this system is complex (both due to feedstock composition and the nature of reactions at pyrolysis temperatures) and as such the approach has been to use an overall reaction rate or series of simplified reactions. In this study, a review of large scale pyrolysis process units, reactor mathematical models, mechanisms for conversion of woody biomass and overview of heat of pyrolysis is presented. In addition, the presented kinetic models have been compared to experimental data obtained from pyrolysis of different liginocellulosic biomass (i.e. sawdust, bark, and wood chips) in a lab-scale tube furnace reactor, to determine the “best” kinetic model for the fast pyrolysis of sawmill residues. The results show that the chemical percolation devolatilization model (Lewis et al. Energy Fuels 2013; 27:942–953. doi:10.1021/ef3018783) predicts the pyrolysis products most accurately. Furthermore, the competitive model (Chan et al. Fuel 1985; 64:1505–1513. doi:10.1016/0016-2361(85)90364-3) shows very good agreement for bio-oil experimental data. Although the pyrolysis of biomass has been widely investigated in recent decades, the models have some limitations which could limit their application to a broad spectrum of feedstock and pyrolysis operating conditions.
189 citations
Authors
Showing all 13990 results
Name | H-index | Papers | Citations |
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Daniel Levy | 212 | 933 | 194778 |
Rakesh K. Jain | 200 | 1467 | 177727 |
Peter W.F. Wilson | 181 | 680 | 139852 |
Martin G. Larson | 171 | 620 | 117708 |
Peter B. Jones | 145 | 1857 | 94641 |
Dafna D. Gladman | 129 | 1036 | 75273 |
Guoyao Wu | 122 | 764 | 56270 |
Fereidoon Shahidi | 119 | 951 | 57796 |
David Harvey | 115 | 738 | 94678 |
Robert C. Haddon | 112 | 577 | 52712 |
Se-Kwon Kim | 102 | 763 | 39344 |
John E. Dowling | 94 | 305 | 28116 |
Mark J. Sarnak | 94 | 393 | 42485 |
William T. Greenough | 93 | 200 | 29230 |
Soottawat Benjakul | 92 | 891 | 34336 |