Self Driving Labs

From Data to Discovery

Self driving labs, which combine artificial intelligence and machine learning with automated laboratories, are transforming materials discovery, process optimization, and chemical manufacturing – enabling faster, smarter decision-making.

At AM Academy, we provide the tools and insights to help you leverage AI-driven approaches in your work.

Explore more today and unlock the power of machine learning in materials science!

Resources

videos

Overview of AMLearn

Master advanced materials synthesis and automation. In this overview video, explore how AMLearn simplifies complex processes, accelerates research, and empowers...

articles

Pushing nanomaterials up to the kilogram scale – An accelerated approach for synthesizing antimicrobial ZnO with high shear reactors, machine learning and high-throughput analysis

This article details the first use of AM's platform - combining machine learning and nanomaterials synthesis - to rapidly optimise...

articles

A Machine Learning-Enabled Autonomous Flow Chemistry Platform for Process Optimization of Multiple Reaction Metrics

This article introduces a self-optimizing flow chemistry system that uses machine learning to efficiently balance multiple reaction metrics, such as...

articles

A machine learning-enabled process optimization of ultra-fast flow chemistry with multiple reaction metrics

This study integrates a machine learning workflow with a flow chemistry platform to optimize reaction conditions for lithium–halogen exchange reactions,...

articles

Automated pH Adjustment Driven by Robotic Workflows and Active Machine Learning

This article presents a strategy that uses an automated liquid handling, with predictive modeling and active machine learning in a...

webinars

The Basics of Self-Driving Labs: How Machine Learning Accelerates R&D Workflows

Learn from the developer of AMLearn, Dr. Mohammed Jeraal (Lead Engineer), as he distills how different tools, from Bayesian optimisation...