<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-06-03T15:52:43Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/CAB01B65-3F6F-4D9D-9003-68C56FFF3D1C" ns1:id="CAB01B65-3F6F-4D9D-9003-68C56FFF3D1C"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/B33319D4-C129-4DC7-A829-C9C5607F52CC" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/A6D03427-091A-4E39-A48F-35C8CB7FCEB5" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/A6D03427-091A-4E39-A48F-35C8CB7FCEB5" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2026-03-30T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/5A53B2B0-48E6-452E-BA16-0D5167A3D941" ns1:rel="FUND" ns1:start="2026-02-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10179861</ns2:identifier></ns2:identifiers><ns2:title>FUNGiMET: AI-empowered fungal biomineralisation to upcycle precious metals from e-waste into application-ready nanomaterials</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>The UK generates some of the highest levels of electronic waste in Europe, and valuable metals in discarded circuit boards are often lost or exported. Led by Novatica Technologies Ltd, FUNGiMET project addresses this by developing a bio-based way to turn e-waste into useful nanomaterials for diagnostics and advanced manufacturing. Our process uses fungal biomineralisation at low temperature and minimises hazardous chemicals, making it cleaner and easier to scale than conventional, energy-intensive routes that first produce bulk metal.

A key feature is data-driven optimisation: we apply machine learning to speed up process tuning, improve consistency, and cut costs and waste. This helps create a reliable UK supply of application-ready nanomaterials, reducing import dependence and shortening lead times for industry.

We will work with the University of Chester and Loughborough University on bioprocess and modelling aspects. The project supports the circular economy, lowers environmental impact, and develops skills through student involvement. Upon upscale, FUNGiMET will stimulate new green jobs, anchor value from UK e-waste onshore, and provide sustainable materials to health, electronics, and other sectors, thus benefiting the economy and the environment in the UK and beyond.</ns2:abstractText></ns2:project>