Neural network based modeling of PL intensity in PLD-grown ZnO Thin Films

펄스 레이저 증착법으로 성장된 ZnO 박막의 PL 특성에 대한 신경망 모델링

The pulsed laser deposition process modeling is investigated using neural networks based on radial basis function networks and multi-layer perceptron. Two input factors are examined with respect to the PL intensity. In order to minimize the joint confidence region of fabrication process with varying the conditions, D-optimal experimental design technique is performed and photoluminescence intensity is characterized by neural networks. The statistical results were then used to verify the fitness of the nonlinear process model. Based on the results, this modeling methodology can be optimized process conditions for pulsed laser deposition process.