Understanding Ion Implantation Defect Distributions in Silicon Induced by FIB and Other Ion Sources Using Advanced STEM
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Engineering topics
Publications and source records attributed to Scrymgeour, David.
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Prior to every ion implantation experiment a simulation of the ion range and other relevant parameters is performed using Monte-Carlo based codes. Although increasing computing power has improved the speed of these calculations, the demands on Monte-Carlo codes are also increasing, requiring evaluation of the optimal number of simulations while ensuring accuracy within threshold bounds. We evaluate the “Stopping and Range of Ions in Matter” (SRIM) code due to its widespread usage. We show how dividing simulations into multiple parallel simulations with different random seeds can lead to calculation speedup and find lower bounds for the required number of ion traces simulated based on an exemplar system of a Ga focused ion beam and a high energy C beam as used in high linear energy transfer testing. Here our results indicate simulations can yield results within the underlying data accuracy of SRIM at 10X and 100X shorter simulation time than the SRIM default values.
Presentation at MRS2023 Spring meeting on APAM robustness topic from FAIR DEAL GC.
Abstract not provided.
Abstract not provided.