Novel ionometallurgy routes for enabling the recovery of key raw materials.

Chemistry+AI

Project ION4RAW: Ionometallurgy of primary sources for an enhanced raw materials recovery.

The ION4RAW project proposes an energy-, material- and cost-efficient new mineral processing technology to recover by-products from primary sources by means of innovative Deep Eutectic Solvent (DES) ionic liquids and advanced electrorecovery as an only step. 

A joint recovery of by-products from primary sources which belong to the Cu-Ag-Au group is proposed. Most of the targeted by-products elements are Critical Raw Materials as bismuth (Bi), germanium (Ge), indium (In), cobalt (Co), platinum (Pt) and antimony (Sb). Accompanying major product metals, e.g. copper (Cu), silver (Ag) and gold (Au), may also be recovered by this process. 

The flexibility of the process (demonstrated to TRL 5 through a prototype) increases its market penetration potential as a sound systemic solution. The technical feasibility of this concept was supported by the TRL 2-3. From this starting point, the ION4RAW Project reaches TRL 5 by implementing a process prototype at TECNALIA (TEC) facilities. Furthermore, to produce a sound systemic solution, comprehensive by-product potential mapping will be carried out to link the Ion4Raw process with suitable sources. 

Finally, Ion4Raw project has a very promising business potential since it allows mining and mineral processing companies to fully exploit by-product potential by recovering them at their own facilities. This contributes to unlocking the full potential of Europe’s inner wealth by converting new and currently unexploited resources into reserves.


Our main tasks

  • Project coordination
  • Construction of a DES leaching mathematical model.
  • Development of a holistic mathematical model of Ion4Raw process.
  • Development of the multidisciplinary optimization (MDO) problem.
  • Evaluation of the optimization problem results, and re-evaluation until final process concept is reached.
  • Particularization of the model and distribution of the optimal results.
  • Conceptual and Basic engineering.
  • Roadmap and technical recommendations.


Partners

BRGM | CUMBRES EXPLORACIONES SAC | HELMHOLTZ-ZENTRUM DRESDEN-ROSSENDORF EV | IDENER.AI | L'UREDERRA | LGI CONSULTING | PNO | RINA CONSULTING-CSM | SCOTGOLD RESOUCES LIMITED | SINTEF AS | TECHNISCHE UNIVERSITAET BERGAKADEMIE FREIBERG | TECNALIA | WARDELL ARMSTRONG LLP


Start date – finish date

06 / 2019 - 11 / 2023


This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement Nº 815748