Basic Process Equation for Analytical Chemistry – An Inclusive and Conciliatory Approach

The proposal outlined in this article aims to use information flow as a benchmark for analytical chemistry. It starts with raw information, mostly implicit and nonobvious (latent information), enclosed in the analytical signal, which is transformed into explicit and interpretable target chemical information (patent information). A basic process equation is proposed, derived from the currently accepted definition of analytical chemistry, which reflects the paradigm change from measurement to information. The main innovation lies in the inclusion of a term called the 'analytical operator,' which is responsible for transforming the information. The terms of this equation are interpreted and matched with different analytical methods, as well as with the R&D activities involved in current analytical chemistry. The proposal provides, for the first time, an inclusive approach that reconciles traditional analytical methods, relying on univariate data, with analytical methods derived from the application of chemometrics (or, in the same way, data mining, machine/deep learning, artificial intelligence, etc.) based on multivariate data. For better understanding, the determination of the iodine value in vegetable oils has been considered as a guiding example demonstrating how the proposed process equation is valid throughout the different periods of analytical chemistry, regardless of the analytical method applied.

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Publication Details

Journal
Analytical Chemistry
Published
2025-12-30
DOI
https://doi.org/10.1021/acs.analchem.5c05444
Primary Topic
Spectroscopy and Chemometric Analyses
Type
article
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article

Basic Process Equation for Analytical Chemistry – An Inclusive and Conciliatory Approach

Cuadros-Rodriguez Luis
Analytical Chemistry
Spectroscopy and Chemometric Analyses
article

Basic Process Equation for Analytical Chemistry – An Inclusive and Conciliatory Approach

Cuadros-Rodriguez Luis
article en

Abstract

The proposal outlined in this article aims to use information flow as a benchmark for analytical chemistry. It starts with raw information, mostly implicit and nonobvious (latent information), enclosed in the analytical signal, which is transformed into explicit and interpretable target chemical information (patent information). A basic process equation is proposed, derived from the currently accepted definition of analytical chemistry, which reflects the paradigm change from measurement to information. The main innovation lies in the inclusion of a term called the 'analytical operator,' which is responsible for transforming the information. The terms of this equation are interpreted and matched with different analytical methods, as well as with the R&D activities involved in current analytical chemistry. The proposal provides, for the first time, an inclusive approach that reconciles traditional analytical methods, relying on univariate data, with analytical methods derived from the application of chemometrics (or, in the same way, data mining, machine/deep learning, artificial intelligence, etc.) based on multivariate data. For better understanding, the determination of the iodine value in vegetable oils has been considered as a guiding example demonstrating how the proposed process equation is valid throughout the different periods of analytical chemistry, regardless of the analytical method applied.

Analytical ChemistryVol. 98(1)
Universidad de Granada (ES)
Industry, innovation and infrastructure
Openalex Percentile: Top 41%
Spectroscopy and Chemometric Analyses
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