Abstract
This study presents an effective method for the quantification of nitric acid (0.1-9 M) and the temperature (20-60 °C) through optimal experimental design, chemometrics, and Raman spectroscopy. Raman spectroscopy can be deployed using fiber-optic cables in hot cell environments to support processing operations in the nuclear field and industry. Chemical operations frequently use nitric acid and operate at nonambient temperatures either by design or by circumstance. Examples of Raman spectroscopy for the quantification of nitric acid with applications in the industrial field are profuse. However, the effect of temperature on quantification is often ignored and should be considered in real-world scenarios. Statistical design of experiments was used to build training sets for partial least-squares regression and support vector regression (SVR) models. The SVR model with a nonlinear kernel outperformed the top partial least-squares models with respect to temperature and resulted in percent root-mean-square error of prediction of 1.8% and 2.3% for nitric acid and temperature, respectively. The D-optimal design strategy decreased the sampling time by 75% compared to a more traditional seven-level full factorial option. The new method advances chemometric applications within and beyond the nuclear field and industry.
| Original language | English |
|---|---|
| Pages (from-to) | 45600-45609 |
| Number of pages | 10 |
| Journal | ACS Omega |
| Volume | 9 |
| Issue number | 45 |
| DOIs | |
| State | Published - Nov 12 2024 |
Funding
This work used resources at the Radiochemical Engineering Development Center operated by the US Department of Energy\u2019s Oak Ridge National Laboratory. This work was supported in part by the US Department of Energy Office of Science, Office of Workforce Development for Teachers and Scientists under the Science Undergraduate Laboratory Internships Program at Oak Ridge National Laboratory, administered by the Oak Ridge Institute for Science and Education. Funding for this work was provided by the U.S. Department of Energy, Office of Science, Office of Workforce Development for Teachers and Scientists (WDTS) under the Science Undergraduate Laboratory Internships Program (SULI) program at Oak Ridge National Laboratory, administered by the Oak Ridge Institute for Science and Education, which supported D.V.R., and the Advanced Research Projects Agency\u2013Energy under contract DE-AC05-00OR22725, which supported L.R.S., J.D.E, and L.H.D, and under Award Number DE-AR0001689, which supported J.D.B. The information, data, or work presented herein was funded in part by the Advanced Research Projects Agency-Energy (ARPA-E), U.S. Department of Energy, under contract DE-AC05-00OR22725 and Award Number DE-AR0001689. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.