Simulation and prediction of the attenuation behaviour of the KNN-LMN-based lead-free ceramics by FLUKA code and artificial neural network (ANN)-based algorithm

The significance and novelty of the present work are the preparation of the non-lead ceramic by the general formula of (1-x) K0.5Na0.5NbO3-xLa Mn0.5Ni0.5O3 (KNN-LMN) with different x (0<0.295) (mol) to examine the shielding qualities of KNN-LMN non-lead ceramic via FLUKA code. The obtained results via FLUKA code are used as input data for training the artificial neural network algorithm and prediction. For this purpose, the radio isotopic Cf-252 neutron source is simulated by the HI-PROBE, RADDECAY and DCYSCORE cards using the FLUKA code. As a result, the neutron-gamma photon shielding ability of the KNN-LMN lead-free ceramics exposed to the Cf-252 neutron source is estimated and predicted. Findings show that by increasing the concentration of the x in (1-x) K0.5Na0.5NbO3-xLa Mn0.5Ni0.5O3 lead-free ceramics results in an ascending trend in density. In addition, the increment of the x rate (x refers to the concentration of La Mn0.5Ni0.5O3 in KNN-LMN non-lead ceramics) causes an increase in the value of the neutron attenuation parameter (Sigma), and a strong relationship is monitored between Sigma and density. Moreover, descending order of (HVL)(x=0.01). (HVL)(x=0.04). (HVL)(x=0.07) > . . . > (HVL)(x=0.25) is reported for half-value layer values against gamma photon. From the attained results, it can be concluded that increaisng the rate of x results in the better shielding proficiency in terms of neutron and gamma photon for chosen KNN-LMN-based lead-free ceramics. [GRAPHICS] .

Automated summary

This study examines the shielding qualities of non-lead ceramic materials using FLUKA code and artificial neural network algorithm. The results show that increasing the concentration of a certain component in the material improves its density and neutron attenuation parameter, thereby enhancing its shielding ability.