Welcome to AEcroscopy#
\(_{Yongtao}\) \(_{Liu}\)
\(_{liuy3@ornl.gov,}\) \(_{youngtaoliu@gmail.com}\)
\(_{July}\) \(_{2026}\)
Transforming Microscopy from Manual Observation to Autonomous Discovery.#
Welcome to AEcroscopy! AEcroscopy is a Python-based ecosystem designed to bridge the gap between complex experimental design and microscope execution, providing researchers with the tools and tutorials needed to translate high-level experiment plans into executable Python programs, enabling a new era of automated and autonomous microscopy.
For a broader overview of what self-driving microscopy is capable of and how it stands to transform science, see:
From Automation to True Autonomy#
While automated experiments leverage robotics and software to perform repetitive tasks with precision, autonomous experiments go a step further. By integrating Artificial Intelligence (AI) and Machine Learning (ML), autonomous systems don’t just follow a script—they analyze data in real-time, make informed decisions, and optimize parameters on the fly.
The Power of Agentic AI#
We are pushing the boundaries of what’s possible by introducing LLM-powered agentic AI into the AEcroscopy framework. This allows researchers to interact with their experiments using natural language and high-level reasoning.
Note
This book covers AEcroscopy V2, distributed as the Python package aecroscopywave. The package name and imports are also referred to as AEcroscopyWave.