Skip to main content

Envisioning is an emerging technology research institute and advisory.

LinkedInInstagramGitHub

2011 — 2026

research
  • Reports
  • Newsletter
  • Methodology
  • Origins
  • Vocab
services
  • Research Sessions
  • Signals Workspace
  • Bespoke Projects
  • Use Cases
  • Signal Scanfree
  • Readinessfree
impact
  • ANBIMAFuture of Brazilian Capital Markets
  • IEEECharting the Energy Transition
  • Horizon 2045Future of Human and Planetary Security
  • WKOTechnology Scanning for Austria
audiences
  • Innovation
  • Strategy
  • Consultants
  • Foresight
  • Associations
  • Governments
resources
  • Pricing
  • Partners
  • How We Work
  • Data Visualization
  • Multi-Model Method
  • FAQ
  • Security & Privacy
about
  • Manifesto
  • Community
  • Events
  • Support
  • Contact
  • Login
ResearchServicesPricingPartnersAbout
ResearchServicesPricingPartnersAbout
  1. Home
  2. Research
  3. Stratum
  4. AI-Powered Battery Mineral Recycling

AI-Powered Battery Mineral Recycling

NRC's AI-PAP project combines artificial intelligence with advanced recycling techniques to recover valuable materials from end-of-life lithium-ion batteries, launched September 2025 as a 3-year initiative.
Back to StratumView interactive version

The National Research Council of Canada launched the AI-PAP collaboration project in September 2025, a three-year initiative combining artificial intelligence with advanced processing and recycling techniques to recover valuable materials from spent lithium-ion batteries. The project uses machine learning to optimize hydrometallurgical and pyrometallurgical recycling processes, improving recovery rates for lithium, cobalt, nickel, and other critical minerals.

Battery recycling matters because the first massive wave of EV batteries will reach end-of-life in the late 2020s and 2030s, creating both an environmental challenge and a domestic mineral supply opportunity. Efficient recycling could provide a significant secondary source of critical minerals, reducing the need for new mining and creating a circular economy for battery materials. AI optimization of recycling processes can improve yield and reduce energy consumption.

This project reflects Canada's broader strategy of using its AI capabilities to enhance its natural resource industries — a cross-pollination between the country's two strongest innovation sectors. The three-year timeline suggests the technology could be ready for industrial-scale deployment by 2028-2029, coinciding with the expected surge in battery waste volumes.

TRL
5/9Validated
Impact
3/5
Investment
4/5
Category
Hardware

Book a research session

Bring this signal into a focused decision sprint with analyst-led framing and synthesis.
Research Sessions