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Unit 4 — Applied AI to Nanotechnology

Overview

Large Language Models and Computer Vision applied to real problems in nanotechnology research.

Topics

  • LLMs for materials science (Materials Project API + RAG)
  • Computer Vision for SEM/TEM microscopy
  • Spectroscopic analysis with AI (Raman, XRD)
  • Time series analysis for MD simulations
  • Bayesian optimization and evolutionary algorithms

Key Technologies

  • Google Gemini / Gemma — LLMs for scientific Q&A
  • Materials Project API — Experimental crystallographic database
  • OpenCV / torchvision — Computer Vision
  • scikit-optimize — Bayesian optimization

Learning Outcomes

  1. Build RAG pipelines with real crystallographic data
  2. Classify nanomaterials from SEM/TEM images
  3. Analyze Raman and XRD spectra with ML
  4. Optimize synthesis parameters with Bayesian methods

Notebooks

Open in GitHub