Developing Innovative Radiation Measurement Technologies for Decommissioning

dfa86368-cc31-496e-ab47-f1e96966c448

Closed

EPSRC
EPSRC
EPSRC
EPSRC
EPSRC

£1,265,190

Sept. 30, 2017

March 31, 2020

In the process of decommissioning of the Fukushima Dai-ichi Nuclear Power Plants, a large amount of radioactive wastes such as fuel debris, structural materials, rubble, soil, and adsorbents for treating contaminated water has been generated. Analysis of radioactive nuclides has been essential for realising efficient and safe treatment and disposal of these radioactive wastes.

This project aims to develop a *micro total analysis system* (mu-TAS) based on continuous microfluidic-based extraction and using a thermal lens microscope for detection. The mu-TAS will be integrated on a chip, addressing the issues of speed, volume and waste associated with larger scale approaches.

Potential Impact:
The aim of the project is to develop a novel continuous analysis system based on microfluidics and on-line measurement to detect actinides and lanthanides in nuclear waste. In achieving this aim, the project will deliver experimental data on the behaviour of microfluidic devices, models for predicting this behaviour and an optimisation framework for the design of the _TAS device. The successful outcome of this project will lead to an increase in the technological readiness level of the underlying microfluidic chip concept, demonstrating the capability of these devices to be used in critical activities such as nuclear waste monitoring, assessment and disposal. The devices will inform strategies for the safe handling of the wastes.

The expansion in the use of nuclear energy require novel approaches to analyse the waste that are cheap, fast and can operate at very small sample volumes. Our research, the _TAS approach and the methodology for designing the device, will also have major impact in chemical, mineral and energy sectors where analysis of metal solutions is required. We will increase the impact through engagement with the nuclear power generation industry, as well as other process industries. These will be facilitated by existing research consortia. All models developed by the project will be made freely available in the open literature, enabling subsequent development and use. The optimisation framework will be based on the Strawberry algorithm. The code for Strawberry is already available for use and is provided as open source.

The anticipated expansion of the nuclear and biofuels industries will create the need for researchers and engineers with relevant knowledge and skills. The researchers involved in the project will be trained in interdisciplinary research skills and in technical skills relevant to nuclear power production as well as to process industries in general. Our research will have wider societal benefits leading through rapid analysis to better process control. It will be particularly beneficial in cases of accidents and will help informing decisions on course of action. We will disseminate the findings through publications of wider readership and outreach activities especially to young people.