Author: Boutachkov, P.
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TUP29 ZnO(In) Scintillation Light Spectra Investigation for Heavy Ion Detector Application 294
 
  • M. Saifulin, C. Trautmann
    TU Darmstadt, Darmstadt, Germany
  • P. Boutachkov, M. Saifulin, C. Trautmann, B. Walasek-Höhne
    GSI, Darmstadt, Germany
  • E.I. Gorokhova
    GOI, St Petersburg, Russia
  • P. Rodnyi, I.D. Venevtsev
    SPbPU, St. Petersburg, Russia
 
  Funding: DLR financed this research within the framework of the ERA. Net RUS Plus Project RUSST2017-051
ZnO-based ceramics are known as promising scintillators exhibiting light emission in the ultraviolet (UV) spectral region (~390 nm) and ultrafast decay times (<1 ns). They are of great interest for applications in scintillation counters and screens at high-energy heavy ion accelerators. In this contribution, the deterioration of scintillating properties of ZnO-based ceramics subjected to heavy ion exposure at high doses is investigated. The scintillation light spectra of ZnO(In) as a function of fluence for 4.8 MeV/u 48Ca and 197Au ions were studied. We observed that the deterioration of the scintillation intensity with increasing fluence follows the Birks-Black model.
* The results presented in this contribution are based on the work performed before the 24th of February, 2022.
** m.saifulin@gsi.de (corresponding author)
 
DOI • reference for this paper ※ doi:10.18429/JACoW-IBIC2022-TUP29  
About • Received ※ 08 September 2022 — Revised ※ 10 September 2022 — Accepted ※ 11 September 2022 — Issue date ※ 01 November 2022
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TUP36 Beam Characterization of Slow Extraction Measurement at GSI-SIS18 for Transverse Emittance Exchange Experiments 318
 
  • J. Yang, P. Boutachkov, P. Forck, T. Milosic, R. Singh, S. Sorge
    GSI, Darmstadt, Germany
 
  Funding: This project has received funding from the European Union’s Horizon 2020 Research and Innovation programme under GA No 101004730.
The quality of slowly, typically several seconds, extracted beams from the GSI synchrotron SIS18 is characterized with respect to the temporal beam stability, the so-called spillμstructure on the 100 µs scale. A pilot experiment was performed utilizing transverse emittance exchange to reduce the beam size in the extraction plane, and the improvement of spillμstructure was found. Important beam instrumentation comprises an Ionization Profile Monitor for beam profile measurement inside the synchrotron and a plastic scintillator at the external transfer line for ion counting with up to several 106 particles per second and 20 µs time slices. The performant data acquisition systems, including a scaler and a fast Time-to-Digital Converter (TDC), allow for determining the spill quality. The application of the TDC in the measurement and related MAD-X simulations are discussed.
 
DOI • reference for this paper ※ doi:10.18429/JACoW-IBIC2022-TUP36  
About • Received ※ 08 September 2022 — Revised ※ 10 September 2022 — Accepted ※ 11 September 2022 — Issue date ※ 11 October 2022
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WEP42 Application of Machine Learning towards Particle Counting and Identification 508
 
  • S.E. Engel
    University of Essex, Physics Centre, Colchester, United Kingdom
  • P. Boutachkov, R. Singh
    GSI, Darmstadt, Germany
 
  An exploration into the application of three machine learning (ML) approaches to identify and separate events in the detectors used for particle counting at the GSI Helmholtz Centre for Heavy Ion Research. A convolutional neural network (CNN), a shape-based template matching algorithm (STMF) and Peak Property-based Counting Algorithm (PPCA) were developed to accurately count the number of particles without domain-specific knowledge required to run the currently used algorithm. The three domain-agnostic ML algorithms are based on data from scintillation counters commonly used in beam instrumentation and represent proof-of-work for an automated particle counting system. The algorithms were trained on a labelled set of over 150 000 experimental particle data. The results of the three classification approaches were compared to find a solution that best mitigates the effects of particle pile-ups. The two best-achieving algorithms were the CNN and PPCA, achieving an accuracy of 99.8\%.
This project has received funding from the European Union’s Horizon 2020 Research and Innovation programme under GA No 101004730.
 
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DOI • reference for this paper ※ doi:10.18429/JACoW-IBIC2022-WEP42  
About • Received ※ 11 September 2022 — Revised ※ 25 October 2022 — Accepted ※ 01 December 2022 — Issue date ※ 08 December 2022
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WE3I1 Novel Fast Radiation-Hard Scintillation Detectors for Ion Beam Diagnostics 515
 
  • P. Boutachkov, M. Saifulin, C. Trautmann, B. Walasek-Höhne
    GSI, Darmstadt, Germany
  • E.I. Gorokhova
    GOI, St Petersburg, Russia
  • P. Rodnyi, I.D. Venevtsev
    SPbPU, St. Petersburg, Russia
 
  Novel radiation-hard scintillators were developed in the last years based on indium-doped ZnO ceramic with an extremely short decay time below a ns. Fast counting detectors and fast screens were considered as potential beam diagnostic applications of this material. At the GSI/FAIR facility, scintillation detectors are commonly used for measuring the intensity and detailed time structure of relativistic heavy ion beams. The scintillating material is inserted directly into the beam path. Signals from individual ions are counted, providing systematic-error-free beam intensity information. Standard scintillators require frequent maintenance due to radiation damage. To address this limitation, a large area ZnO radiation-hard detector was developed. The prototype detector operates at orders of magnitude higher irradiation levels, at higher counting rates and has better time resolution compared to a plastic scintillator. In addition, the novel detector material opens the possibilities for applications in other beam diagnostic systems, for example, scintillation screens for transverse profile measurements. Therefore, ZnO scintillation ceramics are of general interest for beam diagnostics.  
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DOI • reference for this paper ※ doi:10.18429/JACoW-IBIC2022-WE3I1  
About • Received ※ 24 September 2022 — Revised ※ 24 October 2022 — Accepted ※ 25 October 2022 — Issue date ※ 27 November 2022
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