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Project focused on optimizing artificial neural network (ANN) algorithms to generalize from experimental data describing the epitaxial synthesis of thin film semiconductor crystals. Incentivized by a project assignment in a CS 5300 - Artificial Neural Systems course taken at Western Michigan University.
SCLC-Modelling is a Python project that simulates the transition from field emission to space-charge-limited current (SCLC) in semiconductors. Using models based on the Fowler-Nordheim and Child-Langmuir laws, this repository provides insights into electron emission behaviors, applicable in both research and practical semiconductor design.
Inspection equipment for the semiconductor industry saves companies millions of dollars. This project uses the MIR-WM811K Corpus» of wafer maps to build a CNN classifier to automate classification of wafer defect patterns.
doped is a Python software for the generation, pre-/post-processing and analysis of defect supercell calculations, implementing the defect simulation workflow in an efficient, reproducible, user-friendly yet powerful and fully-customisable manner.