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.

Defect structure-searching employing chemically-guided bond distortions

Imaging system for analyzing defects of semiconductor wafers and chips

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.

Python code to simulate phonon transport in nanodevices using the Monte Carlo method from ab-initio phonon data.

How to use Artificial Intelligence to Discover New Semiconductors

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.

Sweep through ranges of command line hyperparameters to create testcases for multiple corners

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.