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FEbeam: Cavity and electron emission data conversion, processing, and analysis. A freeware toolkit for rf injectors.

Mitchell Schneider¹, Emily Jevarjian¹, Jiahang Shao²

¹Department of Electrical and Computer Engineering, Michigan State University, East Lansing, Michigan 48824, USA.

The Review of Scientific Instruments

|July 10, 2021

Summary

FEbeam software analyzes field emission cathode performance in RF injectors by extracting key parameters from Fowler-Nordheim equations. This open-source tool processes beam imaging data and is adaptable for various RF field emission injectors.

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Area of Science:

Physics
Engineering
Materials Science

Background:

Field emission cathodes are crucial components in radio-frequency (RF) injectors.
Accurate analysis of cathode performance is essential for optimizing injector efficiency and stability.
Existing methods for field emission analysis can be complex and time-consuming.

Purpose of the Study:

To introduce FEbeam, an integrated software interface for processing field emission data.
To enable the extraction of critical field emission parameters, including field enhancement factor, local field, and effective emission area.
To facilitate the analysis of beam imaging micrographs through its integration with FEpic software.

Main Methods:

Utilizes the Fowler-Nordheim equations for data extraction.
Processes data from field emission measurements in RF injectors.
Integrates with FEpic for the analysis of beam imaging micrographs.

Main Results:

FEbeam successfully extracts field enhancement factor, local field, and effective emission area.
The software is designed for the Argonne Cathode Test-stand but is adaptable to other RF field emission injectors.
FEbeam provides a streamlined approach to field emission cathode performance analysis.

Conclusions:

FEbeam offers a comprehensive solution for analyzing field emission cathode performance in RF injectors.
The software's open-source nature and adaptability promote wider adoption and development.
FEbeam enhances the capability to understand and optimize critical parameters in particle accelerators.