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Publication Information
Title Nb3Sn Coating of Twin Axis Cavity for Accelerator Applications
Abstract A Superconducting twin axis cavity consisting of a modi-fied cell with two identical beam pipes that can accelerate and decelerate beams within the same structure has been proposed for the Energy Recovery Linac (ERL) applica-tions. Two niobium twin axis cavities fabricated at JLab are processed to deposit the Nb3Sn layer inside using the vapor diffusion method for the first time. Nb3Sn is a po-tential alternative material for replacing Nb in SRF cavi-ties for better performance and reducing operational costs of the accelerators. Because of advanced geometry, larger surface area, increased number of ports and hard to reach areas of the twin axis cavities, the usual coating approach developed for typical elliptical single-axis cavi-ties must be evaluated and requires to be adjusted. In this contribution, we report the first results from the coating of a twin axis cavity and discuss current challenges with an outlook for the future.
Author(s) Jayendrika Tiskumara, Jean Delayen, Subashini De Silva, Uttar Pudasaini, Charlie Reece, Grigory Eremeev
Publication Date August 2021
Category SRF Technology
Document Type Meeting, Proceedings
Primary Institution Old Dominion University
Affiliation Accelerator Ops, R&D / Inst for SRF Sci & Tech / SRF Research & Dev
Funding Source Nuclear Physics (NP)
Proprietary? No
This publication conveys Technical Science Results
Document Numbers
JLAB Number: JLAB-ACC-21-3395 OSTI Number: 1825884
LANL Number: Other Number: DOE/OR/23177-5214
Associated with an experiment No
Associated with EIC No
Supported by Jefferson Lab LDRD Funding No
Meeting / Conference
Meeting Name IPAC21
Meeting Date 5/24/2021
Document Subtype Paper (proceedings only)
Proceedings
Title Proceedings of IPAC 2021
Editor(s) Liu Lin, John M. Byrd, Regis Neuenschwander, Renan Picoreti, Volker R. W. Schaa
Publisher JACOW
Refereed No
Page Number 1175-1178
Year 2021
Attachments/Datasets/DOI Link
Document(s)
mopab384.pdf (Accepted Manuscript)
DOI Link
Dataset(s) (none)
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