00:00 - Introduction 02:03 - Beginning of the talk 03:31 - Materials Acceleration Platforms 06:05 - Organic LASER with self-driving labs 15:02 - Discovery of redox flow battery molecules 22:10 - Workflow and ML in electrochemistry 28:51 - Hardware Automation and Miniaturization 42:25 - Challenges and Outlook Q&A: 45:26 - Comment: Really cheap potentiostats and galvanostats 46:45 - Q1: Automated screening versus Machine-Learning-driven automation 52:03 - Q2: Getting new knowledge from the ML-driven automated experiments 58:40 - Q3: Solid vs liquid phase exploration 1:00:56 - Q4: Discovery of solids and materials 1:04:27 - Q5: Machine learning for polymers 1:06:57 - Q6: Role of students and postdocs 1:10:45 - Q7: Accidental discoveries in automated experiments 1:15:18 - Q8: Digging through others’ data (forensic analysis)
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