Complex numbers-partial least-squares applied to the treatment of electrochemical impedance spectroscopy data

Rodrigues, Dayvison Ribeiro; Olivieri, Alejandro C.; Fragoso, Wallace D.; Lemos, Sherlan G.

doi:10.1016/j.aca.2019.07.047

Cited by 8 publications

(5 citation statements)

References 24 publications

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“…As previously presented, a few works reported the use of first‐order multivariate calibration, mainly PLS, in the development of impedimetric methods of analysis 19,20,22 . In this sense, Table 5 presents a comparison between the analytical performances (RMSEP and REP) obtained with the method presented in this work and with PLS on the determination of hydroquinone and catechol in tap water.…”

Section: Resultsmentioning

confidence: 81%

“…As previously presented, a few works reported the use of first-order multivariate calibration, mainly PLS, in the development of impedimetric methods of analysis. 19,20,22 In this sense, Table 5 presents a comparison between the analytical performances (RMSEP and REP) obtained with the method presented in this work and with PLS on the determination of hydroquinone and catechol in tap water. Although a straightforward comparison between these two methodologies is not strictly adequate, because they are performed with data from different nature, one can consider some scenarios in which this comparison can be done.…”

Section: T a B L Ementioning

confidence: 99%

“…Using more than one electrical component for predicting analyte concentration could bring advantages inherent to the multivariate calibration approach such as (i) possibility of providing extra (and often complementary) information to the calibration model for each element added, once different elements may be influenced differently by experimental noise or interferents; (ii) possibility of simultaneous analysis of multiple analytes; and (iii) possibility of detecting the presence of interferents (first‐order advantage) 18 . The use of multivariate calibration applied to EIS data for the development of analytical methods is scarce and is mainly based on latent structures methods such as partial least squares (PLS) and principal component regression (PCR) on EIS full spectrum represented as real or complex numbers 19–22 . PCR and PLS show that they can produce impedimetric methods with good predictive abilities and the advantages associated to multivariate calibration, including calibration sets with a relatively small number of standards (or much smaller than the number of spectral variables).…”

Section: Introductionmentioning

confidence: 99%

“…18 The use of multivariate calibration applied to EIS data for the development of analytical methods is scarce and is mainly based on latent structures methods such as partial least squares (PLS) and principal component regression (PCR) on EIS full spectrum represented as real or complex numbers. [19][20][21][22] PCR and PLS show that they can produce impedimetric methods with good predictive abilities and the advantages associated to multivariate calibration, including calibration sets with a relatively small number of standards (or much smaller than the number of spectral variables). However, the proposition of a physical/chemical interpretation of the mathematical models built with latent structures-based methods is usually unfeasible, and a better understanding of the system is impaired.…”

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confidence: 99%

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Evaluation of multiple linear regression applied to impedimetric sensing

Rodrigues

Fragoso

Lemos

2020

Journal of Chemometrics

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In this work, the application of multiple linear regression (MLR) on the development of electroanalytical methods based on electrochemical impedance spectroscopy (EIS) data was investigated. This approach was proposed considering that more than one element of the equivalent electrical circuit fitted to impedance spectra could keep linear relationship with the analyte concentration and be used in a multivariate calibration model, rather than using only one element of the circuit in a univariate regression, the benchmark procedure in the context of impedimetric (bio)sensing. First, MLR was evaluated in the individual determination of the redox probe ferrocyanide in aqueous solutions, followed by the determination of catechol and hydroquinone in tap water samples. MLR produced better predictions than univariate regression when more complex electrochemical systems (catechol and hydroquinone) and more complex samples (tap water) were analyzed. The determinations of hydroquinone and catechol in the direct analysis of spiked tap water samples were successful, with apparent recoveries ranging from 94% to 136%.

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Section: Resultsmentioning

confidence: 81%

Section: T a B L Ementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Evaluation of multiple linear regression applied to impedimetric sensing

Rodrigues

Fragoso

Lemos

2020

Journal of Chemometrics

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“…The work presented here aimed at the evaluation of E-t-i data in association with secondorder calibration techniques in the development of electroanalytical methods. The methodology was initially evaluated with a model problem, namely the determination of ferrocyanide -a wellknown redox probe with well-reported electrochemical behavior [23,24] -in the presence of hydroquinone, as a strong interferent not included in the calibration step. Ferrocyanide and hydroquinone show highly overlapped voltammetric peaks, but distinct oxidation processes regarding electron transfer.…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional voltammetry: Use of chronoamperometric E-t-i data to achieve second-order advantage

Lemos

Gonzalez-Rodriguez

2020

Analytica Chimica Acta

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This work studied the use of three-dimensional voltammetry, particularly potential-time-current (Et-i) data, on the development of electroanalytical methods. E-t-i data was obtained by taking chronoamperograms at potentials applied as pulses on a staircase waveform. By using this threeway kind of data and appropriate calibration algorithms, the possibility of achieving the secondorder advantage was evaluated in the determination of ferrocyanide in the presence of the uncalibrated interference hydroquinone as a model system. The determination of acetaminophen in urine samples, where ascorbic acid and uric acid play the major roles as interferents was also studied. Parallel factor analysis (PARAFAC) and multivariate curve resolution alternating leastsquares (MCR-ALS) were the algorithms employed in this work. Both algorithms successfully achieved the second-order advantage by correctly predicting the concentrations of the validation synthetic samples. Excellent predictions were obtained in the direct analysis of acetaminophenspiked urine samples by E-t-i data and MCR-ALS.

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