Enhanced monitoring of fuel reprocessing relies on machine learning

November 8, 2021, 9:30AMNuclear News



Two student interns at Pacific Northwest National Laboratory looking for an easier way to monitor the acidity and phosphate concentrations of a process fluid like dissolved nuclear fuel have published research on a monitoring method that provides real-time data without the need for physical sampling of the substance. Their story was published on October 27 on PNNL’s website.

Student leaders: Hope Lackey conducted pH measurement and chemical analysis research during her Science Undergraduate Laboratory Internships (SULI) experience at PNNL in 2018 while she was working toward her undergraduate degree in environmental studies at the College of Idaho. Andrew Clifford, also a SULI intern and a student at the College of Idaho, partnered with Lackey between his junior and senior year, while studying for a dual bachelor’s in chemistry and math/physics.