-
Charging effect of dielectric material due to electron beam irradiation has a significant influence on the microdischarge phenomenon of dielectric microwave component by multipactor. The discharge process caused by internal electron leakage can relieve this undesirable charging effect. In this paper, we study the transient discharge characteristics of a dielectric sample after being irradiated by electron beam through numerical simulation. Both the charging and discharging processes of a dielectric sample are considered with a comprehensive model. The Monte-Carlo method is used to simulate the interaction between primary electrons and material atoms before the irradiation is interrupted, including elastic scattering and inelastic scattering. The elastic scattering is calculated with the Mott scattering model, and the inelastic scattering is simulated with the fast secondary electron model or Penn model according to electron energy. Meanwhile, the transport process of internal charges in the sample during the discharge period is simulated including the charge diffusion under the force of charge density gradient, the drift due to built-in E-field, and the trap caused by material defect. In this work, the discharge process is taken to begin at the very moment of charging reaching saturation, with the internal charges kept almost unchanged. A polymer material widely used in advanced component is considered in this work due to its remarkable charging effects. Distributions of internal charges of the sample during the discharge process are simulated, and influences of sample parameters, including sample thickness, electron mobility and trap density in the discharge process, are analyzed. The results show that internal charges move to the bottom of the sample during the discharging, leading to the surface potential reaching an ultimate state which is determined by trap density of the material. The position corresponding to the maximum internal charge density shifts towards the grounded bottom. Although a sample with a larger electron mobility means a faster discharge process, fewer free electrons in this sample result in less discharge quantity. The time constant of discharge process decreases with the increase of sample electron mobility in the form of similar linearity. Although a sample with a larger thickness can hold more internal charges, the increase of sample thickness may increase the distance of internal charges leak yet. Hence, the quantity of discharge first increases and then decreases with the increase of sample thickness. In addition, a larger trap density of a dielectric sample makes charge leak harder, resulting in a lower discharge quantity. Finally, the proportion of discharge quantity in saturated charge quantity decreases from 1 to 0 exponentially with the increase of sample trap density. As a conclusion, those sample parameters have their corresponding effects on discharge characteristics by means of different physical mechanisms. Sample electron mobility determines the discharge time constant obviously by affecting the electron transport speed. The sample thickness affects the discharge quantity by shifting the charging balance mode, and material defect impedes part of discharge quantity from trapping internal free electrons. This simulation method and results can help to recede the charging effect and estimate the evolution charging and discharging states of dielectric material during and after electron beam irradiation.
-
Keywords:
- discharge transient /
- electon-beam irradiation /
- dielectric material /
- numerical simualtion
[1] Zhang N, Cui W Z, Hu T C, Wang X B 2011 Space Elec. Tech. 38 38 (in Chinese) [张娜, 崔万照, 胡天存, 王新波 2011 空间电子技术 38 38]
[2] Chen J R, Wu X D 1999 Space Elec. Tech. 1 19 (in Chinese) [陈建荣, 吴须大 1999 空间电子技术 1 19]
[3] Sazontov A, Buyanova M, Semenov V, Rakova E, Vdovicheva N, Anderson D 2005 Astrophys. J. 12 053102
[4] Tan C C, Ong K S 2010 Rev. Sci. Instrum. 81 064703
[5] Kim W, Jun I, Kokorowski M 2010 IEEE Trans. Nuc. Sci. 57 3143
[6] Rubinstein R Y, Ridder A, Vaisman R 2013 Fast Sequential Monte Carlo Methods for Counting and Optimization (Hoboken: John Wiley Sons, Inc.)
[7] Landau D P, Binder K 2014 A Guide to Monte Carlo Simulations in Statistical Physics (New York: Cambridge University Press)
[8] Penn D R 1987 Phy. Rev. B 35 482
[9] Mott N F, Sir H S, Massey W 1949 The Theory of Atomic Collisions (Oxford: Clarendon Press)
[10] Czyzewski Z, MacCallum D O, Romig A, Joy D C 1990 J. Appl. Phys. 68 3066
[11] Joy D C, Joy C S 1995 Microscopy Microanal. 1 109
[12] Raczka R, Raczka A 1958 Phys. Rev. 110 1469
[13] Joy D C 1995 Monte Carlo Modeling for Electron Microscopy and Microanalysis (New York: Oxford University Press)
[14] Ding Z J, Shimizu R 1996 Scanning 18 92
[15] Frhlich H, Mitra T K 1968 J. Phys. C 1 548
[16] Ganachaud J P, Mokrani A 1995 Surf. Sci. 334 329
[17] Fakhfakh S, Jbara O, Fakhfakh Z 2009 IEEE Conf. Electr. Insul. Dielectr. Phenomena 2009 441
[18] Fang Z Q, Hemsky J W, Look D C, Mack M P, Molnar R J, Via G D 1997 MRS Proceed. 482 881
[19] Sessler G M, Figueiredo M T, Ferreira G F L 2004 IEEE Trans. Dielectr. Electr. Insul. 11 192
[20] Feng G B, Cao M, Yan L P, Zhang H B 2013 Micron 52-53 62
[21] Feng G B, Wang F, Cao M 2015 Acta Phys. Sin. 64 227901 (in Chinese) [封国宝, 王芳, 曹猛 2015 物理学报 64 227901]
-
[1] Zhang N, Cui W Z, Hu T C, Wang X B 2011 Space Elec. Tech. 38 38 (in Chinese) [张娜, 崔万照, 胡天存, 王新波 2011 空间电子技术 38 38]
[2] Chen J R, Wu X D 1999 Space Elec. Tech. 1 19 (in Chinese) [陈建荣, 吴须大 1999 空间电子技术 1 19]
[3] Sazontov A, Buyanova M, Semenov V, Rakova E, Vdovicheva N, Anderson D 2005 Astrophys. J. 12 053102
[4] Tan C C, Ong K S 2010 Rev. Sci. Instrum. 81 064703
[5] Kim W, Jun I, Kokorowski M 2010 IEEE Trans. Nuc. Sci. 57 3143
[6] Rubinstein R Y, Ridder A, Vaisman R 2013 Fast Sequential Monte Carlo Methods for Counting and Optimization (Hoboken: John Wiley Sons, Inc.)
[7] Landau D P, Binder K 2014 A Guide to Monte Carlo Simulations in Statistical Physics (New York: Cambridge University Press)
[8] Penn D R 1987 Phy. Rev. B 35 482
[9] Mott N F, Sir H S, Massey W 1949 The Theory of Atomic Collisions (Oxford: Clarendon Press)
[10] Czyzewski Z, MacCallum D O, Romig A, Joy D C 1990 J. Appl. Phys. 68 3066
[11] Joy D C, Joy C S 1995 Microscopy Microanal. 1 109
[12] Raczka R, Raczka A 1958 Phys. Rev. 110 1469
[13] Joy D C 1995 Monte Carlo Modeling for Electron Microscopy and Microanalysis (New York: Oxford University Press)
[14] Ding Z J, Shimizu R 1996 Scanning 18 92
[15] Frhlich H, Mitra T K 1968 J. Phys. C 1 548
[16] Ganachaud J P, Mokrani A 1995 Surf. Sci. 334 329
[17] Fakhfakh S, Jbara O, Fakhfakh Z 2009 IEEE Conf. Electr. Insul. Dielectr. Phenomena 2009 441
[18] Fang Z Q, Hemsky J W, Look D C, Mack M P, Molnar R J, Via G D 1997 MRS Proceed. 482 881
[19] Sessler G M, Figueiredo M T, Ferreira G F L 2004 IEEE Trans. Dielectr. Electr. Insul. 11 192
[20] Feng G B, Cao M, Yan L P, Zhang H B 2013 Micron 52-53 62
[21] Feng G B, Wang F, Cao M 2015 Acta Phys. Sin. 64 227901 (in Chinese) [封国宝, 王芳, 曹猛 2015 物理学报 64 227901]
Catalog
Metrics
- Abstract views: 4744
- PDF Downloads: 132
- Cited By: 0
下载:
