...
首页> 外文期刊>Microscopy and microanalysis: The official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada >Determination of Electron Optical Properties for Aperture Zoom Lenses Using an Artificial Neural Network Method
【24h】

Determination of Electron Optical Properties for Aperture Zoom Lenses Using an Artificial Neural Network Method

机译:用人工神经网络方法确定孔径变焦镜头的电子光学性能

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

Multi-element electrostatic aperture lens systems are widely used to control electron or charged particle beams in many scientific instruments. By means of applied voltages, these lens systems can be operated for different purposes. In this context, numerous methods have been performed to calculate focal properties of these lenses. In this study, an artificial neural network (ANN) classification method is utilized to determine the focused/unfocused charged particle beam in the image point as a function of lens voltages for multi-element electrostatic aperture lenses. A data set for training and testing of ANN is taken from the SIMION 8.1 simulation program, which is a well known and proven accuracy program in charged particle optics. Mean squared error results of this study indicate that the ANN classification method provides notable performance characteristics for electrostatic aperture zoom lenses.
机译:在许多科学仪器中,多元素静电光圈透镜系统广泛用于控制电子或带电粒子束。通过施加电压,可以将这些透镜系统用于不同的目的。在这种情况下,已经执行了许多方法来计算这些透镜的聚焦特性。在这项研究中,人工神经网络(ANN)分类方法用于确定像点上聚焦/未聚焦的带电粒子束,作为多元件静电光圈透镜的透镜电压的函数。用于神经网络训练和测试的数据集来自SIMION 8.1仿真程序,该程序是带电粒子光学中众所周知的经过验证的精度程序。这项研究的均方误差结果表明,ANN分类方法为静电光圈变焦镜头提供了显着的性能特征。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号