Real-time Microscopy Quantification Using Machine Learning
Current electron microscopy workflows are complex and labor intensive with a significantly long time-to-discovery. This work will drastically reduce time-to-discovery with an open data analysis platform with live feedback and real-time feature detection powered with advanced Artificial Intelligence (AI).
- Evaluation of Human-Bias in Machine Learning Models for Electron Microscopy
- Defect Detection Using Deep Learning
- Precipitate Stability and Helium Trapping in Advanced Steels
- Accelerated irradiation creep testing coupled with self-adaptive accelerated molecular dynamics simulations for scalability analysis
- Advance Castable Nanostructured Alloys for First-wall/Blanket Applications