Algorithms for self-driving labs

Autonomous laboratories, also known as self-driving labs, have emerged as a powerful strategy to accelerate chemical discovery. By highly integrating different key parts including artificial intelligence (AI), robotic experimentation systems and automation technologies into a continuous closed-loop cycle, autonomous laboratories can efficiently conduct scientific experiments with minimal human intervention.

Ruthenium oxides (RuOx) are promising alternatives to iridium catalysts for the oxygen-evolution reaction in proton-exchange membrane water electrolysis but lack stability in acid. Alloying with other elements can improve stability and performance but enlarges the search space.

Microwave technology offers rapid, selective, and efficient heating, making it a valuable tool for process intensification. In this context, this study employed microwave energy for rapid reaction optimization and reliable kinetic analysis for the catalytic conversion of glucose. Dehydration (DeH) and retro-aldol condensation (RAC) are two main routes for the catalytic conversion of glucose into valuable platform chemicals such as levulinic acid, methyl lactate, and other byproducts.