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《Nanotechnology and Precision Engineering》 2007-04
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Application of Fuzzy Neural Network in the Internal Stress of SU-8 Photoresist

ZHU Shen-miao1,2,DU Li-qun1,2,LIU Chong1,YU Li-chuan2,WANG Zhi-hong1(1.Key Laboratory for Precision and Non-Traditional Machining Technology of Ministry of Education,Dalian University of Technology,Dalian 116023,China;2.Key Laboratory for Micro/Nano Technology and System of Liaoning Province,Dalian University of Technology,Dalian 116023,China)  
With the application of neural network,process parameters of negative SU-8 photoresist were optimized in terms of internal stress. Based on the principle of curvature method,a 33 factorial orthogonal array technique was designed to measure the internal stress of SU-8 photoresist with nine groups of different process parameters.Employing fuzzy neural network, a simulative model was established to investigate the influence of process parameters on the internal stress.Results of orthogonal experiment were trained by fuzzy neural network,and the prediction model was built between the internal stress and three main process parameters: soft baking(SB) temperature,exposure energy and post exposure baking(PEB) temperature.The prediction results were in good agreement with the experimental results.The internal stress was greatly reduced by using the optimized results of neural network.
【Fund】: 国家科技支撑计划项目(2006BAF04B13);; 国家自然科学基金资助项目(50675025)
【CateGory Index】: TG492
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