A new method for defect prediction of polycrystalline silicon tfts with realistic grain boundary model

We investigate the deviation of threshold voltage (V_th) of p-channel polycrystalline silicon thin film transistors (poly-Si TFTs) using a new GB (grain boundary) model that better reflects reality. And we proposed new method for defect prediction using by this new GB model. The new GB model reflects a gaussian distribution of grain size and GB position. And by introducing a new parameter (β) which represents the defect ratio between GB and grain, the V_th deviation that increases as the channel gets shorter can be matched with the actual measurement results. And we found that the increase in the V_th deviation in the short channel becomes larger as the number of defects increases in GB (as the β increases). And we found that the β is an important physical parameter to explain why the V_th deviation of the short channel is rapidly increased. In this way, using this β value in our GB model, it is possible to predict the relative density of defect states of GB in the poly-Si by monitoring the V_th deviation in short channel TFTs in the process of developing polycrystalline TFTs.