Study on grid inefficiency for mesh-type Frisch-grid ionization chambers

In this study, the grid inefficiency $$\sigma$$ for a mesh-type Frisch-grid ionization chamber (FGIC) was investigated using the finite element method and Monte Carlo method. A grid inefficiency $$\sigma$$ evaluation model was developed, which can determine the relationship between the physical parameters of the detector and the grid inefficiency with reasonable accuracy. An artificial neural network (ANN) was applied in the investigation of the grid inefficiency factor $$\sigma$$. The trained ANN was able to describe and predict the grid inefficiency factor $$\sigma$$ with different physical parameters for the mesh-type FGIC. Thus, it can serve as a reference for the development of mesh-type FGICs and correct grid inefficiency $$\sigma$$ measurements