Wednesday 4 July 2018

Scientists have successfully developed a technology that can harness muons – essentially heavy electrons derived from space particles – to detect and safely manage radioactive waste.

The £7m project, led by scientists from National Nuclear Laboratory (NNL), the University of Glasgow and spin-off company Lynkeos Technology Ltd, could have major implications for nuclear decommissioning, the storing of historic waste and the testing of new waste management techniques.

The technology has created a method for detecting when muons – particles produced when cosmic rays collide with the earth’s atmosphere – pass through uranium.Dr Craig Shearer, project leader at NNL, said:

“About 10,000 muons are hitting every square metre of the earth’s surface every minute. Dozens hit you every second and when they do, they pass straight through you – with almost no distinguishable deviation. This is not true when they hit uranium however. Instead, they scatter.

“When we first looked at this in 2009, we thought we had a 50/50 chance of turning this idea into a product that could be commercialised for the nuclear industry. But the results surpassed expectations at every stage.”

NNL are currently deploying the technology at Sellafield and the detector has now been commercialised by Lynkeos Technology, ready to be sold on the global market.Professor Ralf Kaiser, CEO of Lynkeos, said:

“The Muon Imaging System (MIS) can be used for a variety of purposes, whether that’s inspecting old/spent material used in nuclear production to see if it’s safe to store, for imaging the products of thermal treatment processes or inspecting historic waste without needing to chip away its concrete encasing.

“This form of detection is providing the nuclear industry with an inexpensive method for testing waste materials, to which there is currently no other technological option. This should help to significantly lower costs within the nuclear industry.”

The project, which received initial seed funding from NNL, has also been supported with a £1.6m research contract from Innovate UK, £4.8m funding from Sellafield Ltd and further grants and fellowships from EPSRC, STFC and the Royal Society of Edinburgh.