First Open-Source Industry-Specific Model for Semiconductors

We use MixedWM38, the mixed-type wafer defect pattern dataset for wafer defect pattern regcognition with visual transformers.

Lithography defect prediction for microchip manufacturing optimization with machine learning model

Practical example from the SPIE short course "Data Analytics and Machine Learning in Semiconductor Manufacturing: Applications for Physical Design, Process and Yield Optimization"

Data-Driven Optimization of Semiconductor Processes and Forecasting

MEMS patent

Czochralski Apparatus for Modeling Efficient Lattice growth

HackerFab IITB's website and documentation

Mask-aware wafer defect classification using a DenseNet-based CNN with explicit geometry masking and Grad-CAM explainability.

Semiconductor Process Control (ECE6455-A) @ Georgia Institute of Technology, Atlanta, GA, USA

High-fidelity process simulation dashboard built in Python. Features include Deal-Grove thermal oxidation (calibrated to BYU standards), Gaussian ion implantation profiling, and selective etch rate modeling with real-time cross-sectional visualization.

# Casimir Ultra-Smooth Fabrication Platform (Research)

klayout square array of auto-labeled alignment marks

A Minecraft mod adding realistic semiconductor manufacturing.

Calculating semiconductor chip yield against defect density using a Monte Carlo simulation is a common approach to assess the impact of defects on chip manufacturing. In this simulation, we'll randomly generate defect locations and evaluate chip yield based on specified criteria.

Micron AI Challenge 2025