Recent advances in chemical multi-way calibration with second-order or higher-order advantages: Multilinear models, algorithms, related issues and applications
Introduction
With the increasing number of available second- and higher-order analytical instruments, the multidimensional experimental data array for each sample can be obtained more and more easily and quickly. It is a challenge for analysts to process and make full use of this kind of data, and is also a major opportunity for the revolution in analytical chemistry. Multi-way calibration is a powerful analytical method based on high-order instrument data for the quantification of analytes of interest in complex systems. The work of multi-way calibration first began in 1978 [1], and in the past two decades, it has made tremendous progress and has become a hotspot of theoretical interest and intensive experimental research [[2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23]], which benefits from the emergence of more high-order analytical instruments and efficient algorithms, as well as their revolutionary “second-order advantage” [24], that is, one can directly quantify several components of interest even in the presence of uncalibrated components in predicted samples. It realizes the dreams of many analysts in a simple and special way, and a large number of applications in various scientific fields have confirmed its derived benefits: (1) clean-up and pre-separation steps may no longer be needed; (2) in combination with spectroscopic technology, real-time reaction process monitoring of target analytes in complex systems can be achieved; (3) in combination with chromatographic technology, full chromatographic separation of the analytes is not required and the experiment process is much simpler; (4) baseline effects in chromatographic analysis can be easily modeled and removed from the scene; (5) the same calibration set can be applied to multiple scenes with different unknown background interferences; (6) the sensitivity, selectivity and anti-collinearity increase as the number of instrumental modes increases, which can be regard as the “higher-order advantages” [12].
Non-pollution or little pollution during chemical experiment will be the trend of analytical chemistry, while the advantages of the multi-way calibration are highly consistent with the concept of green analytical chemistry. The use of multi-way calibration always makes the analysis process simpler and greener, and “mathematical separation” will completely or partially replace the “physical/chemical separation”, which saves time, cost, solvent, manpower and energy. Although some recent reviews have covered multi-way calibration in different fields based on different focuses [[15], [16], [17], [18],[21], [22], [23]], a more comprehensive review is needed. In this context, this paper systematically reviews models (focus on multilinear models), algorithms with second-order or higher-order advantages, general considerations and recent representative applications for multi-way calibration along the basic logic from theory to practical application, aiming to provide a guide for analysts. In addition, the contribution of multi-way calibration to green analytical chemistry is highlighted.
Section snippets
Terminology and nomenclature
Some confusion and misunderstandings may arise in multi-way analysis area. In this review, we provide the usual terminology and nomenclature. It may help the general reader to understand the remaining of the review.
Multi-way data
Multilinear algebra has developed rapidly in the field of analytical chemistry, thanks in part to the fact that modern analytical instruments can easily acquire chemical data that conforms to multilinear structures, which means that instrumental phenomena along various data modes are independent from each other, and also independent on the sample. When performing the second- or higher-order calibration, it requires each sample to be capable to generate second- or higher-order data. Second-order
Dealing with the scattering in excitation-emission matrix fluorescence
The EEM spectra often includes light scattering effects, such as first- and second-order Rayleigh and Raman scatterings (Fig. 7(a)), which destroys the multilinear structure of data array, so that multi-way calibration algorithms cannot be used directly. Therefore, data preprocessing is usually necessary before performing EEM fluorescence data analysis. Low-intensity Raman scattering can be removed by subtracting the background signal using a blank sample, however, this method cannot eliminate
Applications
Based on the different dimensions of multi-way data array, this paper mainly focuses on the recent applications of the three-, four-, and five-way calibration methods for quantitative analysis of target analytes in complex systems from 2015 to 2020.
Conclusions and outlook
In order to achieve accurate quantitative analysis, traditional analytical strategies usually require tedious sample pretreatments, such as separation, enrichment, purification, extraction, and long-time gradient elution. These processes often need to consume a lot of toxic organic solvents and manpower, which obviously violates the purpose of protecting the environment and controlling pollution. Chemical multi-way calibration has outstanding “second-order or higher-order advantages.” It can be
Acknowledgments
The authors gratefully acknowledge the National Natural Science Foundation of China (Grant No. 21575039, 21775039 and 21521063) for financial support.
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