Artificial Intelligence in Nanotechnology

Artificial Intelligence is reshaping nanotechnology by accelerating discovery, improving measurement and interpretation, enabling closed-loop experimentation, and strengthening the path from lab results to scalable manufacturing. But the nanoscale is unforgiving: surface effects dominate, data is noisy and instrument-dependent, and “convincing but wrong” conclusions can emerge without rigorous validation.

Artificial Intelligence in Nanotechnology is a practical, engineering-focused book that connects modern AI methods to real nanotech workflows—from synthesis and characterization to autonomous labs, quality control, safety governance, and commercialization. It emphasizes multi-modal data (images + spectra + process logs), uncertainty-aware decisions, and deployment-grade validation strategies designed to survive batch variation, instrument drift, and scale-up realities.

You will learn:

• How AI supports nanomaterials discovery, screening, and inverse design
• How to build robust AI pipelines for microscopy and spectroscopy
• How closed-loop experimentation and self-driving labs accelerate iteration
• Where AI-driven nanotech is delivering results (energy, electronics, coatings, environment, and more)
• How to handle safety, ethics, traceability, and regulation-ready governance
• How to translate promising nano results into reproducible, scalable products

Written for engineers, researchers, advanced students, and technology professionals, this book avoids hype and focuses on reliable methods, realistic constraints, and disciplined workflows for real-world impact.