SciTransfer
OPTIMINER · Project

AI-Driven Sustainable Recovery of Critical Raw Materials from Mining Waste and Low-Grade Ores

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Imagine trying to find a few gold needles in a massive haystack of old rocks. This project builds a smart toolkit that uses AI and biology to pick out valuable metals more efficiently. It's like giving a mine a digital brain and a set of high-tech filters to stop wasting materials and energy.

By the numbers
21
partners
8
countries
6
use cases
57%
industry ratio
The business problem

What needed solving

European mining companies struggle to profitably extract critical raw materials from low-grade ores and complex waste. This leads to resource inefficiency and high environmental toxicity.

The solution

What was built

A suite of CRM recovery tools including smart sorters, bioleaching systems, AI-enabled recovery selectors, Digital Twins for plant simulation, and a market observatory system.

Audience

Who needs this

Mining company CEOsMineral processing engineersEnvironmental compliance officersCritical raw material tradersMining software developers
Business applications

Who can put this to work

Mining and Metals
enterprise
Target: Mining operator

If you are a mining operator dealing with low-grade ores that are too expensive to process — this project developed a CRM Recovery Selector and smart ore sorters that identify and extract valuable materials more efficiently.

Environmental Services
SME
Target: Waste valorisation firm

If you are a waste valorisation firm dealing with toxic mining tailings — this project developed a toolkit for toxicity management and waste valorisation that turns hazardous leftovers into usable resources.

Industrial Software
mid-size
Target: Mining tech provider

If you are a mining tech provider dealing with inefficient plant monitoring — this project developed Digital Twins and a Virtual Miner NLP assistant that optimize productivity through simulation.

Frequently asked

Quick answers

What is the cost or price of these technologies?

Based on available project data, specific pricing or cost structures for the technologies are not provided.

Can this be implemented at an industrial scale?

Yes, the project includes DEMOMINER, which showcases 6 use cases across Spain, Greece, Poland, Finland, and Chile to test recovery in real-world settings.

How is the IP and licensing handled?

Based on available project data, there are no specific details regarding the licensing models or patent strategies.

How does this integrate with existing mining operations?

Integration is achieved through the DIGIMINER platform, which provides smart monitoring, control, and a Decision Support System for operators.

What is the timeline for deployment?

The project runs from 2025-01-01 to 2028-12-31, suggesting that pilot results and tools will be available toward the end of 2028.

Consortium

Who built it

The consortium is heavily weighted toward commercial application, with a 57% industry ratio consisting of 12 industrial partners, including 6 SMEs. This strong industrial presence, combined with 7 research entities and 1 university across 8 countries, suggests a high focus on market uptake and practical deployment rather than purely theoretical research.

How to reach the team

Contact the Research Center for Communication and Computing Systems (EL)

Next steps

Talk to the team behind this work.

Contact us to connect with the OPTIMINER consortium for pilot opportunities.

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