activity
20162023
most citedSuperconducting radio-frequency cavity fault classification using machine learning at Jefferson Laboratory

55 citations · 110 across the 8 of their papers we have counts for

collaborators

8 papers

physics.plasm-ph2023

Simulation of the dynamics of gas mixtures during plasma processing in the C75 Cavity

N. K. Raut, T. Ganey, P. Dhakal +1

Plasma processing using a mixture of noble gas and oxygen is a technique that is currently being used to reduce field emission and multipacting in accelerating cavities. Plasma is…

physics.acc-ph2023★ 23 cited

Development of a prototype superconducting radio-frequency cavity for conduction-cooled accelerators

G. Ciovati, J. Anderson, S. Balachandran +18

The higher efficiency of superconducting radio-frequency (SRF) cavities compared to normal-conducting ones enables the development of high-energy continuous-wave linear accelerator…

physics.acc-ph2022★ 1 cited

In Situ Plasma Processing of Superconducting Cavities at Jefferson Lab

Tom Powers, Natalie Brock, Tiffany Ganey

Jefferson Lab began a plasma processing program start-ing in the spring of 2019. Plasma processing is a common technique for removing hydrocarbons from surfaces, which increases th…

physics.acc-ph2022★ 2 cited

Plasma Processing for In-Situ Field Emission Mitigation of Superconducting Radiofrequency (SRF) Cryomodules

M. Martinello, P. Berrutti, B. Giaccone +14

Field emission (FE) is one of the main limiting factors of superconducting radio-frequency (SRF) cavities operating in accelerators and it occurs whenever contaminants, like dust,…

physics.acc-ph2020★ 10 cited

Demonstration of electron cooling using a pulsed beam from an electrostatic electron cooler

M. W. Bruker, S. Benson, A. Hutton +19

Cooling of hadron beams is critically important in the next generation of hadron storage rings for delivery of unprecedented performance. One such application is the electron-ion c…

physics.acc-ph2020★ 55 cited

Superconducting radio-frequency cavity fault classification using machine learning at Jefferson Laboratory

Chris Tennant, Adam Carpenter, Tom Powers +3

We report on the development of machine learning models for classifying C100 superconducting radio-frequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facilit…