基于人工神经网络-粒子群算法激光烧蚀制备PDPhSM基纳米复合薄膜的工艺优化

材料科学与工艺, 2009, 17(1): 122-128.

基于人工神经网络-粒子群算法激光烧蚀制备PDPhSM基纳米复合薄膜的工艺优化

唐普洪 ^1, , 宋仁国 ^2, , 柴国钟 ^3, , 毛杰 ^4,

1.浙江工业大学机械制造及自动化教育部重点实验室,浙江,杭州,310014;嘉兴职业技术学院机电与汽车分院,浙江,嘉兴,314036

2.浙江工业大学机械制造及自动化教育部重点实验室,浙江,杭州,310014

3.浙江工业大学机械制造及自动化教育部重点实验室,浙江,杭州,310014

4.嘉兴职业技术学院机电与汽车分院,浙江,嘉兴,314036

基金项目: 浙江省教育厅专项项目(20051441) 浙江省自然科学基金青年科技人才培养基金(R405031)

关键词： PDPhSM基纳米复合薄膜 , 激光烧蚀 , 径向基函数神经网络 , 聚合效率 , 粒子群优化

Optimization of laser ablation technology for PDPhSM matrix nanocomposite thin film based upon artificial neural networks-particle swarm algorithm

为有效缩短脉冲激光烧蚀制备有机硅聚合物聚二苯基硅亚甲基硅烷(Polydiphenylsilylenemethyle,PDPhSM)基纳米复合薄膜工艺中繁琐的试验过程,本文将用径向基函数(Radial BasisFunction,RBF)人工神经网络对聚合物PDPhSM基纳米复合薄膜的制备工艺与聚合效率之间的关系进行建模;讨论了激光能量密度、环境压强、靶衬距离、沉积时间和聚合效率之间的关系.在此基础上.采用粒子群(Particle Swarm Optimization,PSO)算法对其进行工艺优化,200代以后,粒子素质明显提高,k值趋近于0,群体达到了最优,工艺参数的优化结果较为满意.从而为薄膜材料工艺优化研究探索了一条崭新的途径.

参考文献

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