Yasin mohammad salehi - Imam Hossein University, Physics Department, Tehran, Iran
Fahimeh Delavari - Bu-Ali Sina University, Technical Department, Hamadan, Touyserkan
Mansour Asgari - Imam Hossein University, Physics Department, Tehran, Iran

Gamma and X-ray detection methods is widely used in industry and medical imaging. High detection efficiency is a key requirement for gamma-ray spectrometry in order to get a good signal to noise ratio. This ratio increases with increasing in detection efficiency[1]. For finding a method to enhance measurement of the gamma ray and X ray, in first the analytical calculations for CdTe detector were performed in several source to detector distances and various sizes. Intrinsic efficiency calculation were performed for value of the ratio of source – detector distance (d) to detector radius (R) that appears by d/R value. This value varies from 0.01 to 20. Mapale 2015 software were employed for intrinsic efficiency calculation. Linear attenuation coefficient data on the Amptec website were used for linear attenuation coefficient calculation in this work. Afterwards, simulation were performed in the energy range of 10 keV to 1 MeV for various size and different distance by using MCNP 4C code. Then the results were analyzed by using the Dirac theory for the mean cord of photons in the detector. In investigated detectors, the Intrinsic efficiency with energies above 100 keV reached to the maximum in the regions less than d/R=0.01 or more than d/R=10 at the same energies. For the energies below the 100 keV, intrinsic efficiency started rising at 0.01 value and reached to the maximum in 9 value. These results were independent of the type of sensor that was used. In the medical imaging or industry imaging with the observance of calculated ratios in the design and calibration of sensors, image can be obtained with highest efficiency. Also the highest efficiency is obtained in imaging in semiconductor based on CdTe as a sensor.

semiconductor, medical imaging, detector, sensor, intrinsic efficiency, Monte Carlo