1. Neutron detector based on Medipix
readout to measure ambient radiation
Srinidhi Bheesette*, Anthony Butler, Philip Butler, Anne Dabrowski,
Arkady Lokhovitskiy, Sophie Mallows
Universities of Otago and Canterbury, Christchurch, New Zealand, CERN and KIT, Germany
srinidhi.bheesette@cern.ch
Objectives
• Measurement of particle fluxes in a mixed radiation field
• Estimation of residual dose
• Provide input to single event upset analysis
• Verification of low flux rates at cavern wall near IP
• Comparison of results obtained with those recorded by
RADMON detectors installed on HF platform
Medipix location in the CMS cavern
• 14 Medipix3RX detectors to be installed at these 7 loca-
tions and their corresponding fluxes in cm-2 s-1 from the
RSP tool [5]:
– BHTOP - Top of Blockhouse (1e4)
– HFTOP - HF platform (1e5)
– X4FOR - X4 forward region handrail (3e3)
– HFX3 - HF electronics racks (1e4)
– YEtop - Top of YE4 tower (1e3)
– X3FOR - X3 balcony (5e3)
– X3IP - Cavern wall near IP (5e3)
Figure 1: Locations of Medipix detectors in CMS
Medipix3RX detector
• Hybrid pixel detector
• 256x256 pixels of 55µm x 55µm in size
• Single pixel and charge summing modes of operation
• Four different gain modes as per the required energy
range
Figure 2: Architecture of Medipix
MARSTM readout electronics
• The Medipix detector comprises of a sensor (Silicon or
Cadmium Zinc Telluride) bump bonded to a radiation
hardened front-end ASIC.
Figure 3: (a) Si sensor bonded to front-end ASIC, (b) De-
tector mounts installed in the cavern
• Medipix fingerboard and readout previously developed
for the MARSTM 3D CT scanner were modified for de-
ployment in the CMS cavern.
• Medipix2 detectors used in run I will be upgraded.
Figure 4: MARSTM back-end readout
Predicting mixed field radiation using FOCUS
• Mixed field radiation at the 7 Medipix detector locations
studied by scoring particle tracks using ”FOCUS” [4], a
CMS FLUKA package.
• Good agreement observed between average fluxes avail-
able on the RSP (web plotting) tool [5], predicted by stan-
dard FLUKA ’scoring’ methods and those obtained by in-
tegrating over FOCUS output data.
Figure 5: Average neutron and background fluxes assum-
ing 80mb inelastic scattering cross section, instantaneous
luminosity of 1e34 cm-2 s-1
• Energy and angular distributions of tracks were analysed
to determine the environment of the detector locations
and to optimise detector design and response.
Figure 6: Energy and angular distributions(at a plane per-
pendicular to z axis) of Neutrons (statistical uncertainties
<10%)
Medipix3RX detector modeling in FLUKA
• Medipix was modeled in FLUKA using custom scoring for
single event tracking. To detect neutrons, following extra
conversion layers were modeled to produce charge par-
ticles:
– Lithium Fluoride (LiF): efficient in case of neutron ener-
gies <100keV (6Li + n → α + 3H).
– Polyethylene (PE): preferred for higher energy neutrons
where protons are produced by elastic scattering (H +
n → p + n).
Figure 7: Medipix3RX detector visualised in FLAIR
• Lower threshold for neutron transport was adjusted
to 1.E-17GeV (default: 1.E-14 GeV); default step-size
changed in the sensor and the conversion layer to 1µm.
Full ion transport of particles like alpha, tritium, etc. was
activated using IONTRANS card in FLUKA.
Post processing and pattern recognition algorithm
• Single event track analysis of the FLUKA data is used
to separate neutron induced pixels from background by
applying suitable Medipix DAQ thresholds.
Figure 8: Lines, blobs, polylines and dotted lines pattern
reconstructed through simulation data
• The pixel triggering threshold for low energy neutron
detection is determined by plotting the energy yield
deposited on Silicon sensor layer by different primary
sources.
Figure 9: Setting threshold at 700keV for each voxel will
filter the background (secondary particles from electrons,
positron and pions)
• The detection efficiency (total pixels excited above
threshold to total no.of primary registered on Si sensor
layer) using Lithium Fluoride (100µm thick) and Polyethy-
lene of various thicknesses versus no conversion layer is
shown in Fig. 10(a) and 10(b) respectively.
• The higher yield produced by conversion layers to no con-
version layer indicate their efficiency at converting neu-
trons to charge particles.
Figure 10: (a) Energy distribution in Silicon layer per pixel
for all energy neutrons at X3IP location, (b) Detection ef-
ficiency for Polyethylene(PE) in the high energy neutron
range
Future plans
• Increase detection efficiency and improve pattern recog-
nition to separate tracks produced by neutrons from the
background.
• Install the Medipix3RX detectors in CMS cavern by next
year and integrate readout software into BRIL-DAQ.
References
[1] Ballabriga R. et al, The Medipix3RX: A high resolution,
zero dead-time pixel detector readout chip allowing spec-
troscopic imaging
[2] Pfeiffer D. et al, Design, Implementation and First Mea-
surements with the Medipix Neutron Camera in CMS.
[3] A. Ferrari, P.R.Sala, A. Fasso and J. Ranft, FLUKA: a
multi-particle transport code, CERN-2005-10 (2005).
[4] Fluka for CMS Users, https://espace.cern.ch/cms-
project-bril/SitePages/FocusBril.aspx
[5] RSP tool, https://cms-project-fluka-flux-map.web.cern.ch/cms-
project-fluka-flux-map/
Acknowledgements
I would like to thank the BRIL radiation simulation team and
in particular M. Guthoff, I. Kurochkin, S. Chitra for their con-
tinued support.
CMS week,14th - 18th November 2016, Tata Institute of Fundamental Research, Mumbai, INDIA