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RISS 인기검색어
- 검색키워드
- 저자 : Runxin Wang (검색결과 3 건)
- 무료
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- 유료
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Small-Signal Analysis of the Lower-Frequency Power Transfer Model
Runxin Wang,Jinjun Liu,Hao Wang 전력전자학회 2007 ICPE(ISPE)논문집 Vol.- No.-
This paper presents the most recent progress in deep research to the large-signal modeling technique for current-mode-controlled SMPS modules. The small-signal analysis to the lower-frequency power transfer model is carried out and the conclusion is obtained that the power stage model does not lose any small-signal information so the proposed large-signal simulation scheme is able to be used in small-signal analysis when the system under study reaches its steady state point. This conclusion is quite valuable in both theory and engineering practices.
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Modeling Diode Reverse Recovery and Corresponding Implementation in Fast Time-Domain Simulation
Hao Wang,Jinjun Liu,Runxin Wang,Qinsan Hou 전력전자학회 2007 ICPE(ISPE)논문집 Vol.- No.-
Existing power diode models in most time-domain circuit simulators cannot accurately present the reverse recovery characteristics of actual diode devices with fast simulation speed. Ma-Lauritzen model is a relatively simple solution for modeling the reverse recovery of diode with reasonable accuracy but so far little result has been reported on the methodology and process for applications in circuit simulators. Based on Ma-Lauritzen model, this paper proposes a configuration and implementation methodology for building diode models with reverse recovery characteristics in an ordinary time-domain circuit simulator like SIMPLIS. A silicon power diode 8ETX06 is selected for simulation speed and accuracy evaluation regarding the proposed modeling methodology and implementation approach. Furthermore, simulation and hardware test results on a switching power converter are shown to verify that the diode model following the proposed building method is reasonably accurate and fast in dynamic waveform emulation and component stress estimation for the reverse recovery process.
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Linhui Wang,Yi Zhao,Runxin Lu,Yao Peng,LI GUO,Li Hai,Mei Guan,Yong Wu 성균관대학교(자연과학캠퍼스) 성균나노과학기술원 2018 NANO Vol.13 No.1
Magnetic targeting, which utilizes a magnetic field to specifically deliver therapeutic agents to the targeted regions, can greatly improve the treatment efficiency. Herein, ibuprofen-loaded brain targeting magnetic nanoparticles (AA-Ibu-PEG-DA@MNPs) modified with ascorbic acid (AA) for central nervous system (CNS) drug delivery was designed and synthesized in order to effectively deliver ibuprofen to the brain through Na+ dependent vitamin C transporter 2 (SVCT2) and glucose transporter 1 (GLUT1). The brain targeting magnetic nanoparticles, AA-Ibu-PEG-DA@MNPs, have a particle size of 82.5 nm, 2% drug loading capacity and limited cytotoxicity against bEnd.3 cells. What's more, the nanoparticles maintained the magnetic property with a saturation magnetization level at 52.17 emu/g and could release ibuprofen when incubated in different mediums, including various buffers, mice plasma and brain homogenate. The results indicate that the magnetic nanoparticles may have the potential to be a promising approach to selectively deliver drugs into the brain. This study may be conducive to the field of CNS drugs delivery.
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