1. Effect of dead layer on the efficiency of planar semiconductor neutron detectors
G. Prasanna, P. Manoj Kumar, K. Prabhakar, M. Raghuram, S. Tripura Sundari, J. Jayapandian and C. S. Sundar
Materials Science Group
Indira Gandhi Centre for Atomic Research
Kalpakkam
Introduction
Neutron detection
Existing detectors
Basic construction
The Intrinsic detection efficiency
Gas filled & thin film coated ion tubes. 3He or 10BF3 6Li , 235U and 10B.etc…
Thermo-luminescent
crystal detectors(6LiF).
Scintillation detectors.
Usually bulky, susceptible to mechanical vibrations and power hungry.
The product of :
The probability that a neutron interacts in the converter region
and
The probability that the product Ion energy deposited in the depletion region exceeds a minimum threshold.
Neutron detection is important in
Reactor instrumentation.
Nuclear fuel reprocessing plant instrumentation.
Personal dosimetry for radiation safety.
Portal monitoring of special nuclear materials.
Materials science research.
Recent advances in construction
Generally fabricated in a planar configuration with a converter material (10B or 6LiF) coating on top of a planar PIN diode.
The probability that a neutron entering the detector volume gets detected
Micro-Structured Semiconductor neutron detectors (MSNDs).
Factors affecting the intrinsic detection efficiency
Semiconductor detectors
Thin film coated PN junction Planar diode detectors.
The drawback
detector construction
Relative orientation of the converter and semiconductor depletion regions.
Planar & trench types
Poor intrinsic neutron detection efficiency
Typical values ~20% as compared to gas filled detectors with efficiencies ~ 80%
detector dimensions
Advantages
Detector modeling and simulation of neutron interaction
Relative and absolute dimensions of
converter
Dead layer &
semiconductor depletion
region.
Insensitivity to
micro phonics
smaller size
Low power
requirements.
Energy threshold
Objective& Motivation
Monte- Carlo simulations have been performed to estimate the effect of various design parameters on the intrinsic detection efficiency
To enable optimization of detector design for maximum intrinsic detection efficiency before fabrication.
The low level discrimination threshold energy.
Effect of dead layer on efficiency
The dead layer
Electron-hole pairs generated here cannot be separated.
Simulation Methodology Overview
Simulation results
Determines the maximum value of probability of ion energy being above threshold.
Planar diode efficiency with boron converter
Neutron capture product ion types & energies
Ion interaction media properties
Dead layer
Regions with very weak or zero electric field- usually near the bias terminals
SRIM & TRIM Monte-Carlo codes
Variation of neutron detector efficiency of a planar diode with 10B thickness. Unit cell dimension was 100 μm2 and LLD was set at 300 keV
Detector model basis-
The unit cell
Manual input of incremental path lengths upto maximum ion range
Product- ion tracks
Ion range data
Table Curve
Curve fitting software
The unit cell concept helps exploit the periodicity in the MSND structure for simulation of ion energy deposition in multiple semiconductor and converter regions.
Assigning unity value to the ratio W/Wcell converts the model to the planar case.
Path Length Vs Residual Energy data for each ion in converter, Dead layer and semiconductor medium
Variation of neutron detector efficiency of a planar diode with LLD setting. 10B thickness was fixed at 2.5 μm.
Empirical fits
path length as a function of residual energy and vice versa
For each product ion in converter material, Dead layer and semiconductor media.
Dimensions of detector constituent regions viz.
Converter material
Dead layer
Depleted semiconductor region
Detection principle
Effect of dead layer thickness on efficiency
Neutron interaction produces two product ions in the converter material, ejected in opposite directions in space.
One of the ions impinge on the reverse biased PIN diode depletion region, creating electron-hole pairs along the track.
A high electric field sweeps these charges to the biasing terminals, producing a current pulse in external circuit.
Current pulse processed to extract deposited ion energy information
neutron interaction event identified and registered .
Variation of neutron detector efficiency of a planar diode with the thickness of a sandwiched dead layer of Gold(Au).
MSND Efficiency code (Monte Carlo MATLAB code based on Shultis McGregor methodology for straight trench detectors).
Estimate of detector intrinsic efficiency
Model -Assumptions
LLD setting
The silicon semiconductor is transparent to neutrons and neutron scattering effects are ignored.
The detector is irradiated with a parallel beam of thermal-neutrons uniformly and normally illuminating the top surface of the detector.
The neutron absorption cross-section for 6LiF and 10B converter material in respective cases is the ion producing cross-section (i.e., neutron reactions with F in 6LiF case and Si in both cases are ignored).
All energy deposited in the semiconductor material is assumed to contribute to the pulse-height signal of the detector, thereby, ignoring charge transport properties and imperfections in the semiconductor diode.
Conclusions
The maximum achievable efficiency of a planar semiconductor neutron detector is ~ 4% for both converter materials i.e., 10B or 6LiF.
A 1 μm Au dead layer sandwiched between the silicon diode and converter material reduces the efficiency of the planar diode to ~ 3%..
Intermediate data from SRIM & TRIM codes for Gold dead layer
Materials used
Boron -10 (10B);density =2.14 g/cm3
6LiF; density =2.54g/cm3
Converter
Fabrication attempts
semiconductor
Silicon; density= 2.32g/cm3
Attempts underway to coat boron thick films on BEL make commercial PIN diodes to form planar neutron detector
Dead layer
Gold; density=19.31g/cm3
Path length as function of Residual Energy-Empirical fit
Residual Energy as function of Path length-Empirical fit
Preliminary results:
Am-241 alpha spectrum obtained with 28 KeV resolution
for bare PIN diode
Acknowledgements
Dr. Steve L. Bellinger of Kansas State University, USA for providing the Monte Carlo simulation MATLAB codes.
The Director, IGCAR for encouragement and support.