We are delighted to welcome you to our AIchemy Hub’s monthly webinar series.
This month’s talks:
Professor Jason Hein – Real-Time Data and Modular Robotics for Scalable Workflow Automation
The future of chemistry demands experimental systems that are flexible, data rich, and built for iteration. This talk will explore how modular automation platforms that integrate real time analytics with robotic execution are transforming how we develop, optimize, and scale chemical processes. I will share our experience building reconfigurable systems that connect high resolution analytical tools with programmable robotics to drive autonomous workflows across applications from crystallization to liquid-liquid extraction. Two key examples will be highlighted: DirectInjection, a real time HPLC-MS integration system that enables online monitoring and control in complex reaction environments; and IvoryOS, an open source orchestration framework designed to coordinate modular hardware across diverse lab tasks. Together, these tools support scalable, chemist-in-the-loop workflows that balance autonomy with insight and help accelerate discovery while preserving the nuance of expert-driven chemistry.
Sriram Vijayakrishnan – Autonomous Mobile Robots For Exploratory Synthetic Chemistry
Autonomous laboratories can accelerate discoveries in chemical synthesis, but this requires automated measurements coupled with reliable decision-making Most autonomous laboratories involve bespoke automated equipment and reaction outcomes are often assessed using a single, hard-wired characterization technique. Any decision-making algorithms must then operate using this narrow range of characterization data. By contrast, manual experiments tend to draw on a wider range of instruments to characterize reaction products, and decisions are rarely taken based on one measurement alone. Our modular workflow combines mobile robots, an automated synthesis platform, a liquid chromatography–mass spectrometer and a benchtop nuclear magnetic resonance spectrometer. A heuristic decision-maker processes the orthogonal measurement data, selecting successful reactions to take forward and automatically checking the reproducibility of any screening hits. This strategy is particularly suited to exploratory chemistry that can yield multiple potential products, as for supramolecular assemblies.
Following the presentations, there will be time for questions from the audience.
Jason Hein
Professor of Chemistry
Sriram Vijayakrishnan
Postdoctoral Researcher
