Print Email Facebook Twitter Multi-electrode lens optimization using genetic algorithms Title Multi-electrode lens optimization using genetic algorithms Author Hesam Mahmoudi Nezhad, N. (TU Delft ImPhys/Imaging Physics; TU Delft ImPhys/Charged Particle Optics) Ghaffarian Niasar, M. (TU Delft DC systems, Energy conversion & Storage) Mohammadi Gheidari, A. (TU Delft ImPhys/Imaging Physics; TU Delft ImPhys/Charged Particle Optics) Hagen, C.W. (TU Delft ImPhys/Imaging Physics; TU Delft ImPhys/Charged Particle Optics) Kruit, P. (TU Delft ImPhys/Imaging Physics; TU Delft ImPhys/Charged Particle Optics) Department ImPhys/Imaging Physics Date 2019 Abstract In electrostatic charged particle lens design, optimization of a multi-electrode lens with many free optimization parameters is still quite a challenge. A fully automated optimization routine is not yet available, mainly because the lens potential calculations are often done with very time-consuming methods that require meshing of the lens space. A new method is proposed that improves on the low speed of the potential calculation while keeping the high accuracy of the mesh-based calculation methods. This is done by first using a fast potential calculation based on the so-called Second-Order Electrode Method (SOEM), at the cost of losing some accuracy, and then using a Genetic Algorithm (GA) for the optimization. Then, by using the parameters of the approximate systems found from this optimization based on SOEM, an accurate GA optimization routine is performed based on potential calculation with the commercial finite element package COMSOL. A six-electrode electrostatic lens was optimized accurately within a few hours, using all lens dimensions and electrode voltages as free parameters and the focus position and maximum allowable electric fields between electrodes as constraints. Subject genetic algorithms (GAs)Multi-electrode lens designoptimizationsecond-order electrode method (SOEM) To reference this document use: http://resolver.tudelft.nl/uuid:a7f071b5-92de-4ebb-b5b3-8f399e6e2e23 DOI https://doi.org/10.1142/S0217751X1942020X ISSN 0217-751X Source International Journal of Modern Physics B: condensed matter physics: statistical physics: applied physics, 34 (36) Part of collection Institutional Repository Document type journal article Rights © 2019 N. Hesam Mahmoudi Nezhad, M. Ghaffarian Niasar, A. Mohammadi Gheidari, C.W. Hagen, P. Kruit Files PDF s0217751x1942020x.pdf 2.3 MB Close viewer /islandora/object/uuid:a7f071b5-92de-4ebb-b5b3-8f399e6e2e23/datastream/OBJ/view