Battery R&D using AI Quantum Computing
ReNewAble leverages AI, quantum computing, and focuses on these key programs in battery R&D:
1. Battery Health Assessment: Quantum-enhanced AI predicts failures, monitors performance, and optimizes battery lifespan.
2. Innovative Disassembly: AI-driven robots, supported by quantum computing, enable precise disassembly, fault detection, and maximize material recovery.
3. Modular Storage Systems: Quantum-enhanced AI designs adaptive storage systems, optimizes energy load management, and extends battery lifecycle.
4. Program AMY (Analysis of Manufacturing Yield): Analyzes manufacturing data to optimize yield. This process includes scanning incoming batteries to find the root cause of the defects, running the data through our AI program to find all possible causes. This data is then given to the battery manufacturers, live, to adjust manufacturing and reduce future waste.
Data from AMY is shared with manufacturers to improve processes, aligning with the government’s SMART MANUFACTURING initiative. These innovations reinforce ReNewAble's commitment to sustainability and efficiency in battery technology.
Li-Ion Battery Recycling
Innovative Lithium-Ion Battery Recycling Process
Re-New-Able utilizes a patented process that combines mechanical processing and hydrometallurgy, eliminating high-temperature methods for a complete closed-loop recycling of lithium-ion batteries, producing battery-grade materials.
Mechanical Processing
Our process addresses the hazards of conventional methods by safely shredding batteries into safe organic materials. The dried material is then separated based on physical properties for further metallurgical processing. Iron, copper, and aluminum are recycled, while the black mass, containing electrode materials, is transferred to the next stage.