UV–Vis spectroscopy with chemometric data treatment: an option for on-line control in nuclear industry Dmitry Kirsanov 1,2 • Alisa Rudnitskaya 3 • Andrey Legin 1,2 • Vasily Babain 2,4 Received: 3 March 2017 / Published online: 22 April 2017 Ó Akade ´miai Kiado ´, Budapest, Hungary 2017 Abstract Chemometrics can be very useful for the clas- sical field of UV–Vis determination of metals in aqueous solutions. A conventional approach consisting of using selective bands in a univariate mode is often not applicable to the real-world samples from e.g. hydrometallurgical processes, because of overlapping signals, light scattering on foreign particles, gas bubble formation, etc. And this is where chemometrics can do a good job. This paper over- views certain contributions to the field of multivariate data processing of UV–Vis spectra for seemingly simple case of metal detection in aqueous solutions. Special attention is given to applications in nuclear technology field. Keywords UV–Vis spectroscopy Á Chemometrics Á Metals Á On-line control Á Process analytical technology Á Nuclear technology Introduction Origins of chemometrics are usually placed in the 1960s when computing became largely available for the scientific community. Accessibility of the computers stimulated the development of theoretical chemistry involving complex calculation, e.g. molecular modelling or quantitative structure–activity relationship, as well as applications of statistics to analytical chemistry in particular to the treat- ment of complex instrumental signals. Thus, the advent of analytical instruments generating for each sample a large number of measurements, which were often collinear and non-selective, was another catalyzer for the introduction of chemometrics. The term ‘‘chemometrics’’, which came to designate a combination of statistics, computationally intensive multivariate methods and experimental design applied to analytical chemistry, was coined by Wold in 1972 [1]. Since then various methods and applications of chemometrics have been developed. Multivariate calibra- tion, structure–activity modelling, pattern recognition, classification, discriminant analysis, and multivariate pro- cess modelling and monitoring were identified as areas, where chemometrics has been the most successful [2]. Further evidence of chemometrics success is its widespread use in the industry as it was introduced for process moni- toring in all kinds of manufacturing processes, from petrochemical to pharmaceutical and food. Though numerous chemometric methods and algorithms have been developed in the course of the years, Principal Component Analysis (PCA) and Partial Least Square regression (PLSR) remain the most popular. One of the most striking examples of usefulness of chemometrics is Near-Infrared (NIR) spectroscopy. NIR spectroscopy was first introduced in the 1950s but was scarcely used till 80s. It was deemed a ‘‘sleeper among & Dmitry Kirsanov d.kirsanov@gmail.com 1 Institute of Chemistry, St. Petersburg State University, Universitetskaya nab. 7/9, St. Petersburg, Russia 199034 2 Laboratory of Artificial Sensory Systems, ITMO University, Kronverkskiy pr. 49, St. Petersburg, Russia 197101 3 CESAM and Chemistry Department, Aveiro University, Campus Universita ´rio De Santiago, 3810-193 Aveiro, Portugal 4 Three Arc MiningInc., Stary Tolmachevsky per. 5, Moscow, Russia 115184 123 J Radioanal Nucl Chem (2017) 312:461–470 DOI 10.1007/s10967-017-5252-8