Effect of Cu doping on the secondary electron yield of carbon films on Ag-plated aluminum alloy

2021 ◽  
Author(s):  
Tiancun Hu ◽  
Shukai Zhu ◽  
Yanan Zhao ◽  
Xuan Sun ◽  
Jing Yang ◽  
...  
Keyword(s):  
Aluminum Alloy ◽  
Secondary Electron ◽  
Carbon Films ◽  
Cu Doping ◽  
Secondary Electron Yield ◽  
Electron Yield

scholarly journals The Effect of Ultrasonic Cleaning on the Secondary Electron Yield, Surface Topography, and Surface Chemistry of Laser Treated Aluminum Alloy

Materials ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 296
Author(s):  
Jie Wang ◽  
Yong Gao ◽  
Zhiming You ◽  
Jiakun Fan ◽  
Jing Zhang ◽  
...  
Keyword(s):  
Aluminum Alloy ◽  
Surface Chemistry ◽  
Secondary Electron ◽  
High Energy ◽  
Surface Cleaning ◽  
Secondary Electron Yield ◽  
Ultrasonic Cleaning ◽  
Electron Yield ◽  
Vacuum Systems ◽  
The Impact

Laser ablation technique is a novel method for obtaining a surface with a low secondary electron yield (SEY) that can mitigate electron cloud in high-energy accelerators. Before the installation of laser processed aluminum alloy, surface cleaning is of the essence to reduce the contaminations of ultra-high vacuum systems for providing appropriate pressure for beam operation consequently. Laser processed aluminum alloy is one of the crucial candidates for the vacuum system construction of future accelerators. Moreover, ultrasonic cleaning is an essential procedure for most materials applied in vacuum systems. Therefore, in order to verify the stability of the laser created structures by ultrasonic cleaning and evaluate the impact of the cleaning on the SEYs, the surface topographies, and the surface chemistries of laser treated aluminum alloy, SEY measurements and related tests were performed. After ultrasonic cleaning, the SEYs of laser treated aluminum alloy increased from 0.99, 1.05, and 1.16 to 1.43, 1.74, and 1.38, respectively. Compared to the surface roughness of uncleaned laser treated aluminum samples, the cleaned laser treated ones decreased from 10.7, 7.5, and 14.5 to 9.4, 6.9, and 12.9, respectively. The results indicate that ultrasonic cleaning can induce the SEY increase of laser processed aluminum alloy. The correlative mechanism between the surface morphology, the surface chemistry, and SEY increase were analyzed for the first time.

Monte Carlo Modelling of Secondary Electron Yield from Rough Surfaces

1990 ◽  
Vol 48 (1) ◽  
pp. 422-423
Author(s):  
John C. Russ
Keyword(s):  
Monte Carlo ◽  
Energy Loss ◽  
Secondary Electron ◽  
Secondary Electron Emission ◽  
Analytical Calculation ◽  
Mean Free Path ◽  
Single Scattering ◽  
High Energy ◽  
Secondary Electron Yield ◽  
Electron Yield

Monte-Carlo programs are well recognized for their ability to model electron beam interactions with samples, and to incorporate boundary conditions such as compositional or surface variations which are difficult to handle analytically. This success has been especially powerful for modelling X-ray emission and the backscattering of high energy electrons. Secondary electron emission has proven to be somewhat more difficult, since the diffusion of the generated secondaries to the surface is strongly geometry dependent, and requires analytical calculations as well as material parameters. Modelling of secondary electron yield within a Monte-Carlo framework has been done using multiple scattering programs, but is not readily adapted to the moderately complex geometries associated with samples such as microelectronic devices, etc.This paper reports results using a different approach in which simplifying assumptions are made to permit direct and easy estimation of the secondary electron signal from samples of arbitrary complexity. The single-scattering program which performs the basic Monte-Carlo simulation (and is also used for backscattered electron and EBIC simulation) allows multiple regions to be defined within the sample, each with boundaries formed by a polygon of any number of sides. Each region may be given any elemental composition in atomic percent. In addition to the regions comprising the primary structure of the sample, a series of thin regions are defined along the surface(s) in which the total energy loss of the primary electrons is summed. This energy loss is assumed to be proportional to the generated secondary electron signal which would be emitted from the sample. The only adjustable variable is the thickness of the region, which plays the same role as the mean free path of the secondary electrons in an analytical calculation. This is treated as an empirical factor, similar in many respects to the λ and ε parameters in the Joy model.

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