AI Can Be Used to Find Good CO2 Absorbing Micro Capsules

Micro-Encapsulated CO2 Sorbents (MECS) are a possible technology to capture carbon from the atmosphere. They are tiny, reusable capsules full of a sodium carbonate solution that can absorb carbon dioxide from the air. Scientists run three fluids through a series of microfluidic components to create drops that turn into capsules when exposed to ultraviolet light downstream. However, fluid properties and flow rates can change during experiments. These changes can lead to capsules that are defective, improperly-sized or otherwise unusable, resulting in device clogging, contaminated samples and wasted time.

Lawrence Livermore National Laboratory (LLNL) scientists can now use machine learning to automate microencapsulation quality control in real-time. They have an algorithm to determine “good” capsules from “bad” and developing a valve-based mechanism that can sort them without human intervention.

Lab on a Chip- Automated detection and sorting of microencapsulation via machine learning

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