Researchers at the Pacific Northwest National Laboratory (PNNL) have developed an artificial intelligence system capable of dramatically speeding up the recovery of critical minerals from industrial waste.
The new platform, known as CICERO, combines AI agents, robotics, and laboratory instruments to design and test mineral extraction methods in a matter of days rather than months or years. The breakthrough could help strengthen domestic supplies of minerals needed for advanced technologies and clean energy systems.
Topic Snapshot
- US researchers developed the CICERO AI platform
- The system accelerates critical mineral recovery research
- AI, robotics, and laboratory equipment work together
- Testing focused on industrial waste and spent magnets
- Recovery methods can be designed within days
- The technology could support US critical mineral security
What Is CICERO?
The system is called Computer Intelligence for Critical Elements Recovery and Optimization (CICERO).
Developed by a research team at PNNL led by materials scientist Elias Nakouzi, the platform combines several advanced technologies into a semi-autonomous workflow.
These include:
- Artificial intelligence agents
- Robotic laboratory systems
- Analytical instruments
- Automated sample handling
Together, these tools can evaluate mineral recovery opportunities and determine whether extraction methods are technically and economically viable.
Reducing Years of Research to Days
Traditionally, developing an effective process to separate valuable minerals from waste materials can take months or even years.
Researchers say CICERO can dramatically reduce that timeline.
Using AI-driven analysis and automated testing, the system can identify promising recovery methods and begin laboratory validation within days.
This rapid approach allows scientists to evaluate many possible extraction techniques far more efficiently than conventional research methods.
How the AI System Works?
The process begins with AI agents analyzing waste materials and identifying minerals that may be worth recovering.
The system then reviews scientific literature and available research data to design experimental programs.
In one demonstration, CICERO developed:
- Chemical processing recipes
- Testing sequences
- Timing instructions
- Laboratory workflows
The AI generated 96 separate experiments within a single day, which were then carried out by robotic laboratory equipment.
Testing on Industrial Waste Streams
Researchers evaluated the system using two different waste sources:
Spent Magnets
Used magnets contain valuable rare earth elements that can potentially be recovered and reused.
The AI recommended recovering:
- Neodymium
- Praseodymium
- Samarium
These rare earth elements are widely used in high-performance magnets found in electric vehicles, wind turbines, and electronics.
Oil and Gas Wastewater
The system also analyzed wastewater generated by oil and gas operations.
CICERO identified magnesium as a promising mineral for recovery from these waste streams.
Supporting Critical Mineral Supply Chains
Critical minerals are essential components in many modern industries.
Applications include:
- Electric vehicles
- Renewable energy systems
- Aerospace technologies
- Defense equipment
- Semiconductors
- Nuclear energy systems
Growing demand for these materials has increased interest in finding new domestic sources beyond traditional mining operations.
Turning Waste into Valuable Resources
One of CICERO’s key advantages is its focus on extracting minerals from materials that would otherwise be discarded.
Potential sources include:
- Industrial waste
- Mine tailings
- Manufacturing by-products
- End-of-life products
- Wastewater streams
Recovering valuable materials from these sources can reduce waste while creating new supply opportunities.
Reducing Dependence on New Mining Projects
Researchers believe technologies like CICERO may complement traditional mining by helping recover minerals already present in waste streams.
Benefits could include:
- Faster resource development
- Lower environmental impact
- Improved resource efficiency
- Reduced waste management costs
- Stronger domestic supply chains
The approach uses chemical and separation techniques that are already common in industrial operations, potentially making future implementation more practical.
AI’s Growing Role in Materials Science
The development of CICERO reflects a broader trend toward integrating artificial intelligence into scientific research.
AI systems are increasingly being used to:
- Design experiments
- Analyze data
- Identify new materials
- Improve manufacturing processes
- Accelerate scientific discovery
In the critical minerals sector, these capabilities may help shorten development timelines and improve resource recovery rates.
Closing
The development of CICERO marks an important step forward in the use of AI for critical minerals recovery. By combining artificial intelligence, robotics, and laboratory automation, researchers at PNNL have created a system capable of identifying and testing mineral recovery methods at unprecedented speed. As demand for critical minerals continues to grow, technologies like CICERO could help transform industrial waste into valuable domestic resources while strengthening supply chain resilience.
