Researchers at the Pacific Northwest National Laboratory have developed a contactless technique to better measure, in real-time, the acidity of highly radioactive solutions, as well as the concentration of specific chemicals in those solutions.
The goal of this work is to provide industry partners with a more efficient and safer mechanism to reprocess and recycle spent nuclear fuel without opening, sampling, or otherwise handling the substance. Spent nuclear fuel cannot stay long-term in sites’ ageing tanks, meaning experts must dispose of it or reprocess it.
In two papers published in the journal Analytical Chemistry, the PNNL scientists explain that there is a growing interest to find a means to better determine the pH level and chemical structure of dissolved nuclear fuel—after it has been fired in a reactor—to improve the safety and efficiency of reprocessing and enhance the overall sustainability of the nuclear fuel cycle.
The reason for this interest is that as the fuel is reprocessed to separate reusable fuel material from radioactive waste, variables like alkalinity and other chemical involvement can interfere with how well materials can be recovered and recycled.
In addition to this, researchers are also looking for ways to increase the safety of workers and the environment by reducing contact with radioactive waste. Normally, people measuring the pH of dissolved nuclear fuel have to go into the process stream and manually collect a sample to determine which chemicals need to be added and confirm if the radioactive materials have left the solution.
The sample then only represents the solution at the point in time it was retrieved, offering limited accuracy in dynamic solution environments like those associated with nuclear fuel recycling.
Taking all these detrimental factors into consideration, PNNL interns Hope Lackey and Andrew Clifford, under the mentorship of chemist Sam Bryan, created a remote pH sensing technique for measuring light’s interaction with chemical bonds, or optical monitoring of visible light spectra, using Raman spectroscopy. In contrast to traditional probes, Raman probes are physically robust and can function for extended periods in harsh environments.
The approach also employs machine learning. This type of learning in particular, called chemometrics, creates an algorithm for a computer to follow in its calculations to turn the spectral response into a measure of acidity. Sample analysis occurs in real-time, with more rapid and cost-effective results. This online monitoring also precludes the worker from coming into contact with the solution.
“Basically, instead of manually dealing with these caustic solutions, we’re adapting robust probes to shine an intense light on solutions, but the ‘camera’ we use doesn’t make coloured images, it gives us ‘pictures’ in real-time to record the solution’s response to light,” Lackey said in a media statement.
The researcher and co-author also found an additional application for online, optical monitoring – to characterize and quantify, in real-time, not just the pH but also chemicals present in radioactive waste.
This approach uses chemometrics to measure the concentrations of phosphates. Under different levels of acidity, phosphate can take four chemical forms based on proton removal. Clifford and Lackey’s technique quantifies each type of phosphate and the total phosphate, at any pH.
According to the pair, online monitoring for phosphates allows nuclear experts to perform initial separations of the chemical, which is crucial to assure phosphates do not interfere with overall processing. Similarly, this detection may be of use in the analysis of other types of phosphates present during waste purification and storage.
In their view and that of their mentors, besides the nuclear power industry, other sectors like the fertilizer and pharmaceutical drug industry could benefit from quick and easy pH measurement and phosphoric acid detection.