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Recharge Industries™ and Deakin University’s Applied Artificial Intelligence Institute (A2I2) have collaborated to create Molecule OS™, an artificial intelligence and machine learning program that understands the battery-making process from the collection of raw materials, through manufacturing, and out to the in-use end product applications. Molecule OS™ allows optimisation of the production line processes to effectively reduce waste as an output of the manufacturing process.

Machine Learning

Molecule OS™ is an example of using machine learning to accelerate the experimental design process, which is the basis of which almost all products and processes are invented. The machine learning allows for new and novel materials and alloys to be discovered and used in the battery making process.

Deakin University’s Applied Artificial Intelligence Institute (A2I2) is co-directed by Professor Kon Mouzakis and Professor Svetha Venkatesh. The Institute is committed to pushing the boundaries of artificial intelligence and tackling real-world problems using machine learning, deep learning, and software engineering practices.

Molecule OS™

Molecule OS™ will allow Recharge Industries™ and A2I2 to have a better understanding of how to make better, cleaner, waste-conscious battery cells that can be reused or recycled to better contribute to the circular economy.


The broader system outputs will be able to make sure the battery cells can be disposed of and stripped properly of valuable components. The aim is to ensure that most of the elements in the cells can be repurposed and sent back into the supply chain and eventually, into a new battery.

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