A Study on the Optimal Make of X-ray Ionizer using the Monte Carlo N-Particle Extended Code(Ⅱ) 


Vol. 32,  No. 6, pp. 29-33, Dec.  2017
10.14346/JKOSOS.2017.32.6.29


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  Abstract

In order to solve this sort of electrostatic failure in Display and Semiconductor process, Soft X-ray ionizer is mainly used. Soft X-ray Ionizer does not only generate electrical noise and minute particle but also is efficient to remove electrostatic as it has a wide range of ionization. There exist variable factors such as type of tungsten thickness deposited on target, Anode voltage etc., and it takes a lot of time and financial resource to find optimal performance by manufacturing with actual X-ray tube source. Here, MCNPX (Monte Carlo N-Particle Extended) is used for simulation to solve this kind of problem, and optimum efficiency of X-ray generation is anticipated. In this study, X-ray generation efficiency was compared according to target material thickness using MCNPX and actual X-ray tube source under the conditions that tube voltage is 5 keV, 10 keV, 15 keV and the target Material is Tungsten(W). At the result, In Tube voltage 5 keV and distance 100 mm, optimal target thickness is 0.05 ㎛ and fastest decay time appears + decay time 0.28 sec. − deacy time 0.30 sec. In Tube voltage 10keV and distance 100 mm, optimal target Thickness is 0.16 ㎛ and fastest decay time appears + decay time 0.13 sec. − deacy time 0.12 sec. In the tube voltage 15 keV and distance 100 mm, optimal target Thickness is 0.28 ㎛ and fastest decay time appears + decay time 0.04 sec. − deacy time 0.05 sec.

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  Cite this article

[IEEE Style]

정필훈 and 이동훈, "A Study on the Optimal Make of X-ray Ionizer using the Monte Carlo N-Particle Extended Code(Ⅱ)," Journal of the Korean Society of Safety, vol. 32, no. 6, pp. 29-33, 2017. DOI: 10.14346/JKOSOS.2017.32.6.29.

[ACM Style]

정필훈 and 이동훈. 2017. A Study on the Optimal Make of X-ray Ionizer using the Monte Carlo N-Particle Extended Code(Ⅱ). Journal of the Korean Society of Safety, 32, 6, (2017), 29-33. DOI: 10.14346/JKOSOS.2017.32.6.29.

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