A Reaction-Based Optical Fingerprinting Strategy for the Recognition of Fat-Soluble Samples: Discrimination of Motor Oils

Abstract

Optical “fingerprints” are widely used for chemometrics-assisted recognition of samples of different types. An emerging trend in this area is the transition from obtaining “static” spectral data to reactions analyzed over time. Indicator reactions are usually carried out in aqueous solutions; in this study, we developed reactions that proceed in an organic solvent, thereby making it possible to recognize fat-soluble samples. In this capacity, we used 5W40, 10W40, and 5W30 motor oils from four manufacturers, with six samples in total. The procedure involved mixing a dye, sample, and reagents (HNO3, HCl, or tert-butyl hydroperoxide) in an ethanolic solution in a 96-well plate and measuring absorbance or near-infrared fluorescence intensity every several minutes for 20–55 min. The obtained photographic images were processed by linear discriminant analysis (LDA) and the k-nearest neighbors algorithm (kNN). Discrimination accuracy was evaluated by a validation procedure. A reaction of oxidation of a dye by nitric acid allowed us to recognize all six samples with 100% accuracy for LDA. Merging of data from the four reactions that did not provide complete discrimination ensured an accuracy of 93% for kNN. The newly developed indicator systems have good prospects for the discrimination of other fat-soluble samples. Overall, the results confirm the viability of the kinetics-based discrimination strategy.

Monitoring Different Water Types for Engine Oil–Water-Soluble Fraction and Iron(2+) Using a Reaction-Based Optical Sensing Strategy: A Proof-of-Concept Study

“…The methodology as a whole is empirical, so the search for indicator reactions is empirical, too. However, the selection can be facilitated by using the pool of reactions previously developed for the discrimination of various samples. − …”

“…33−45 The kinetic approach adds dimensionality to the optical data on the one hand and allows to obtain signals from compounds and samples that do not exhibit intense fluorescence or absorption and do not form colored complexes, etc., on the other hand. This strategy showed its efficiency in the discrimination of bottled mineral waters, 34 rennet samples, 41 engine oils, 42 and estimation of doses received by irradiated food. 40,44 Chemical sensor arrays with optical signal measurement have been developed to detect model organic pollutants in water, such as pesticides 46 or surfactants, 47 but there are few publications on recognition of individual samples of natural water.…”

“…Most commonly, optical fingerprinting of samples was based on absorbance or intrinsic fluorescence measurements . The use of dyes to produce colorimetric sensor arrays started in late 1990s, and the addition of fluorophores to samples has been practiced since 2007; the latter approach makes it possible to measure intrinsic emission along with the fluorophore signal that is dependent on the composition of the sample. , Since late 2010s, a kinetic version of the technique has been employed, in which an indicator reaction (such as dye oxidation) is conducted in the presence of samples to be discriminated. − The kinetic approach adds dimensionality to the optical data on the one hand and allows to obtain signals from compounds and samples that do not exhibit intense fluorescence or absorption and do not form colored complexes, etc., on the other hand. This strategy showed its efficiency in the discrimination of bottled mineral waters, rennet samples, engine oils, and estimation of doses received by irradiated food. , …”

A dual channel fluorescence tongue for catechin recognition based on the MnO2 nanorods–Amplex Red–o-phenylenediamine reaction system

“…Fortunately, chemical arrays (“nose/tongue”) provide a feasible approach for large-scale identification of analytes. 17–23 Although some work has reported the use of several different sensor elements to cross interact with analytes to obtain signals for simultaneous detection of multiple catechins, 24,25 the preparation of sensor arrays is more complex as these methods involve multiple sensor elements. Therefore, many efforts are still needed to develop sensors for simultaneous detection of multiple catechins.…”