Purpose This work aims to study the increase in dead layer thickness of an HPGe N-type detector during its operational period from 2012 to 2018.Methods The dead layer was examined along three Ge-crystal surfaces,such ...Purpose This work aims to study the increase in dead layer thickness of an HPGe N-type detector during its operational period from 2012 to 2018.Methods The dead layer was examined along three Ge-crystal surfaces,such as outer frontal,outer lateral,and inner lateral.These parameters were optimized using response surface methodology(RSM)with a Box–Behnken design(BBD).The Monte Carlo calculations using the GAMOS(Geant4-based Architecture for Medicine-Oriented Simulations)code were performed to evaluate the detector’s efficiency at different values of the inactive germanium layer.Results and conclusion The optimal combination of dead layer thickness has been identified using the desirability function approach,which is a useful tool to optimize multi-response problems.To find the variation in dead layer thickness over the operational period,the optimization procedure was reiterated for both experimental efficiencies measured in 2012 and 2018.The obtained results show that dead layers thickness has increased from 0.6141 mm to 0.7447 mm,0.0803 mm to 2.2721 mm,and 1.5012 mm to 1.6091 mm for the outer frontal,outer lateral,and inner lateral surfaces,respectively.展开更多
文摘Purpose This work aims to study the increase in dead layer thickness of an HPGe N-type detector during its operational period from 2012 to 2018.Methods The dead layer was examined along three Ge-crystal surfaces,such as outer frontal,outer lateral,and inner lateral.These parameters were optimized using response surface methodology(RSM)with a Box–Behnken design(BBD).The Monte Carlo calculations using the GAMOS(Geant4-based Architecture for Medicine-Oriented Simulations)code were performed to evaluate the detector’s efficiency at different values of the inactive germanium layer.Results and conclusion The optimal combination of dead layer thickness has been identified using the desirability function approach,which is a useful tool to optimize multi-response problems.To find the variation in dead layer thickness over the operational period,the optimization procedure was reiterated for both experimental efficiencies measured in 2012 and 2018.The obtained results show that dead layers thickness has increased from 0.6141 mm to 0.7447 mm,0.0803 mm to 2.2721 mm,and 1.5012 mm to 1.6091 mm for the outer frontal,outer lateral,and inner lateral surfaces,respectively.
