Multivariate Curve Resolution By Alternating Least Squares Research Articles

Printing parameters affect the electrochemical performance of 3D-printed carbon electrodes obtained by fused deposition modeling

• 3D printed thermoplastic electrodes produced by fused deposition modeling (FDM). • 3D printing parameters affect the electrochemistry of the printed electrodes. • Proof-of-concept using carbon black/polylactic acid filament. • Printing orientation, layer thickness, perimeter and speed are evaluated. • Electrochemical and Raman spectroscopy data revealed the best printing conditions. Thermoplastic filaments containing conductive carbon materials have contributed tremendously to innovations in the scientific scenario, however, the high charge transfer resistance of available materials sets a challenge for the development of 3D-printed electrochemical sensors. To solve this problem, several research groups have proposed chemical and physical post-treatments that are time-consuming and affect the structural integrity of materials. Herein, we systematically investigated the influence of printing parameters (orientation, layer thickness, number of perimeters and printing perimeter speed) on the electrochemical performance of sensors. For these studies, 3D-printed electrodes (rectangular shape) were printed using an affordable filament of carbon black integrated in polylactic acid (CB/PLA), and measurements by cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS) using 10 mmol/L [Ru(NH 3 ) 6 ] 2+/3+ as redox probe were performed. The results showed that electrodes printed under vertical orientation, with lower layer thickness (0.05 mm) and print perimeter speed (30 mm s −1 ) using two perimeter numbers provided the best electrochemical performance (faradaic peak current intensity and lower peak-to-peak separation). To understand the improvement of electrochemical responses, experiments by Raman spectroscopy and multivariate curve resolution by alternating least squares (MCR-ALS) were carried out which showed greater availability and distribution of conducting sites under the selected conditions. Thus, it can be inferred that 3D-printing parameters are important features to allow the manufacture of improved carbon electrochemical platforms.

Unveiling scale differences in the two-phase transformation of [formula omitted][formula omitted][formula omitted] via operando X-ray absorption and diffraction studies

Lithium titanium oxide Li4Ti5O12 (Li[Li1/3Ti5/3]O4) has been receiving significant attention as an ideal electrode material for lithium-ion batteries, because its cubic lattice parameter (ac) changes negligibly during the electrochemical reaction. However, this same characteristic hinders in-depth understanding of the reaction mechanism, restricting widespread applications, such as use in electric vehicles. We thus employed the recently developed operando X-ray absorption spectroscopy (XAS) and X-ray diffraction (XRD) technique, combined with multivariate curve resolution by alternating least squares (MCR-ALS) method. The MCR-ALS analyses of both the XAS and XRD data confirmed a two-phase reaction scheme consisting of Li[Li1/3Ti5/3]O4 and Li2[Li1/3Ti5/3]O4, but differences in the structural transformations clearly appeared at the two different scales. Linear, reversible changes in the bond distance between Ti and O atoms were observed at the atomic scale (∼1 nm), whereas hysteresis in ac between the discharge and charge reactions was observed at the microscale (∼100 nm). This difference was found to originate from the difference in spatial resolutions between the XAS and XRD techniques.

Detection of Penicillin G Produced by Penicillium chrysogenum with Raman Microspectroscopy and Multivariate Curve Resolution-Alternating Least-Squares Methods.

Raman microspectroscopy is a minimally invasive technique that can identify molecules without labeling. In this study, we demonstrate the detection of penicillin G inside Penicillium chrysogenum KF425 fungal cells. Raman spectra acquired from the fungal cells had highly overlapped spectroscopic signatures and hence were analyzed with multivariate curve resolution by alternating least-squares (MCR-ALS) to extract the spectra of individual molecular constituents. In addition to detecting spatial distribution of multiple constituents such as proteins and lipids inside the fungal body, we could also observe the subcellular localization of penicillin G. This methodology has the potential to be employed in screening the production of bioactive compounds by microorganisms.

Fluorescence-kinetic four-way data generation and modeling for abacavir determination in water samples

The aim of this study was to develop a fluorescence-detection based analytical methodology consisting in the photolysis of abacavir induced by UV irradiation to determine the concentration of the analyte in complex samples. Initially, with the goal of maximizing the fluorescence signal, the optimal experimental conditions were determined by means of design of experiments using the response surface methodology. Once these conditions were established, two types of data were generated: excitation-emission fluorescence matrices acquired after UV irradiation of the analyte (second-order data), and excitation-emission fluorescence matrices recorded at different irradiation times (third-order data), which were processed using both multivariate curve resolution by alternating least squares (MCR-ALS) and parallel factor analysis (PARAFAC) algorithms. These strategies were carried out with the objective of assessing the chemometric advantages in terms of predictive ability by increasing the order of the data, and improvement in figures of merit, such as sensitivity and limits of detection and quantitation. Finally, test samples, containing the analyte and potential interferences, and water samples were evaluated. This study allowed the development of a simple and sensitive methodology for the determination of abacavir in water samples, and showed similar predictive ability between both algorithms. The analytical figures of merit displayed limits of detection and quantitation of 3–5 µg L−1 and 11–14 µg L−1, respectively. The main advantages of third-order data with respect to second-order data were associated with improvements in selectivity and precision.

Application of an Augmentation Method to MCR-ALS Analysis for XAFS and Raman Data Matrices in the Structural Change of Isopolymolybdates.

We measured X-ray absorption fine structure (XAFS) and Raman spectra of isopolymolybdates(VI) in highly concentrated HNO3 solution (0.15 - 4.0 M), which change their geometries depending on the acid concentration, and performed the simultaneous resolution of the XAFS and Raman data using a multivariate curve resolution by alternating least-squares (MCR-ALS) analysis. In iterative ALS optimization, initial data matrices were prepared by two different methods. For low sensitivity of the XAFS spectra to the geometrical change of the isopolymolybdates, the MCR-ALS result of single XAFS data matrix shows a large dependence on the preparation method of the initial data matrices. This problem is improved by the simultaneous resolution of the XAFS and Raman data: the MCR-ALS result of an augmented matrix of these data has little dependence on the initial data matrices. This indicates that the augmentation method effectively improves the rotation ambiguities in the MCR-ALS analysis of the XAFS data.

New Approach to Multivariate Standard Addition Based on Multivariate Curve Resolution by Alternating Least-Squares: Application to Voltammetric Data.

A multivariate version of the classical univariate standard addition method is proposed for the analysis of samples generating overlapping signals in the presence of notorious matrix effects. Unlike previous versions based on multivariate calibration by partial least-squares (PLS), the proposed strategy takes advantage of a self-modeling methodology: multivariate curve resolution by alternating least-squares (MCR-ALS) enhanced with signal shape constraints based on parametric functions. In this way, there is no need for the full multivariate response of a blank solution, and in multianalyte determinations, the standard additions can be made with a solution containing all of the analytes, which constitutes a clear advance as compared to PLS approach. The proposed method has been successfully tested in the voltammetric determination of hydroquinone and catechol in solutions of increasing complexity and appears to be a promising tool in the field of electroanalysis.

Enhancing sensitivity and selectivity in a label-free colorimetric sensor for detection of iron(II) ions with luminescent molybdenum disulfide nanosheet-based peroxidase mimetics

In the present study, we demonstrated that the luminescent molybdenum disulfide (MoS2) nanosheets, which were prepared hydrothermally by using sodium molybdate and thiourea as precursors, possessed peroxidase-like activity, and could catalyze the oxidation of peroxidase substrate o-phenylenediamine (OPD) in the presence of hydrogen peroxide (H2O2) to produce a yellow color reaction. Further addition of Fe2+ into the nanosheets led to peroxidase mimetics with greatly enhanced catalytic activity. The observation was exploited to develop a label-free colorimetric nanozyme sensor for detection of Fe2+. The fabricated MoS2/OPD/H2O2 sensor showed a wide linear range of 0.01–0.8µM with a detection limit of 7nM. Moreover, it was found that the MoS2/OPD/H2O2 sensor displayed enhanced sensitivity and selectivity toward Fe2+ compared with the OPD/H2O2 sensor, suggesting that the MoS2 nanosheets could improve the performance of the Fe2+ sensor. An advanced chemometrics algorithm, multivariate curve resolution by alternating least squares (MCR-ALS), was further applied to interpret the origin of enhancing sensitivity and selectivity in the Fe2+ sensor with the MoS2 nanosheets. The time-dependent UV–vis spectral data of the studied systems were collected, and submitted to the MCR-ALS. The results showed that the increased sensitivity and selectivity of the MoS2/OPD/H2O2 sensor for Fe2+ detection likely arose from its large reaction rate constant. Finally, the proposed MoS2/OPD/H2O2 sensor was successfully applied for detection of Fe2+ in water samples.

Source Apportionment of Inorganic and Organic PM in the Ambient Air around a Cement Plant: Assessment of Complementary Tools

ABSTRACTIn this study, we analyzed the sources of ambient PM inorganic and organic components near a cement plant using fossil fuels as well as alternative fuels, such as sewage sludge and biomass. Source apportionment methodologies, i.e., principal component analysis (PCA) and multivariate curve resolution by alternating least squares (MCR-ALS), and carbon isotope analysis (δ13C) were used to determine the potential sources and their contributions. Four sources of PM10 main tracer compounds constituents were identified: marine and secondary inorganic aerosol, cement plant/industrial, traffic and crustal. The contributions of those sources varied significantly depending on the period of the year. However, the inorganic tracer PM species in the area were mainly released by combustion sources, namely traffic and the activity of the cement plant, especially in winter months. The analyses of tracer organic compounds also indicated combustion sources, i.e., biomass burning and fossil fuel combustion, as the predominant contributors to ambient air PM (62, 59 and 69%, in PM10, PM2.5 and PM1, respectively). Organic dust was a significant source of PM10 (33%) while its contribution was found to be minor in the finest fractions (9 and 2% in PM2.5 and PM1, respectively). Results of δ13C corroborated a significant contribution of combustion sources, traffic or biomass fuel as well as a higher influence of mineral (calcite) powder in larger particles.

Three-Dimensional Voltammetry: A Chemometrical Analysis of Electrochemical Data for Determination of Dopamine in the Presence of Unexpected Interference by a Biosensor Based on Gold Nanoparticles

Multivariate curve resolution by alternating least-squares (MCR-ALS) was used for voltammetric determination of dopamine (DA) in the presence of epinephrine (EP) at a gold nanoparticles chemically modified carbon paste electrode (AuNPs/CPE). Scanning electron microscopy (SEM), electrochemical impedance spectroscopy (EIS), and cyclic voltammetry (CV) techniques were applied for characterization of the nanostructure modified electrode. Central composite rotatable design (CCRD) was employed to generate an experimental program to offer data to model the effects of different parameters on voltammetric responses. Response surface methodology (RSM) was applied to show the individual and interactive effects of chemical and instrumental variables at five levels, combined according to CCRD. For determination of DA in the presence of unexpected interference, three-way data were achieved from various pulse heights in differential pulse voltammetry (DPV) technique. This type of data construction, analyzed by MCR-ALS, makes it possible to exploit the so-called "second-order advantage". The second-order advantage provided unbiased results even in the presence of electroactive interferences with highly overlapped peaks. Also, an algorithm was applied to correct the detected potential shift in the voltammetric data. The voltammograms of the samples were then deposited in an augmented data matrix (column-wise) and subsequently analyzed by MCR-ALS. The effect of rotational ambiguity associated with a particular MCR-ALS solution under a set of constraints was also studied. The proposed method could be applied for the determination of DA and EP in the presence of each other in a wide concentration range of 0.1-205.0 μM, and the detection limit of DA has been found to be 35.5 nM. Finally, the technique has been used for the reliable analysis of DA in real samples.

New insight into protein–nanomaterial interactions with UV-visible spectroscopy and chemometrics: human serum albumin and silver nanoparticles

In recent years, great efforts have focused on the exploration and fabrication of protein nanoconjugates due to potential applications in many fields including bioanalytical science, biosensors, biocatalysis, biofuel cells and bio-based nanodevices. An important aspect of our understanding of protein nanoconjugates is to quantitatively understand how proteins interact with nanomaterials. In this report, human serum albumin (HSA) and citrate-coated silver nanoparticles (AgNPs) are selected as a case study of protein-nanomaterial interactions. UV-visible spectroscopy together with multivariate curve resolution by alternating least squares (MCR-ALS) algorithm is first exploited for the detailed study of AgNPs-HSA interactions. Introduction of the chemometrics tool allows extracting the kinetic profiles, spectra and distribution diagrams of two major absorbing pure species (AgNPs and AgNPs-HSA conjugate). These resolved profiles are then analysed to give the thermodynamic, kinetic and structural information of HSA binding to AgNPs. Transmission electron microscopy, circular dichroism spectroscopy and Fourier transform infrared spectroscopy are used to further characterize the complex system. Moreover, a sensitive spectroscopic biosensor for HSA is fabricated with the MCR-ALS resolved concentration of absorbing pure species. It is found that the linear range for the HSA nanosensor was from 1.9 nM to 45.0 nM with a detection limit of 0.9 nM. It is believed that the proposed method will play an important role in the fabrication and optimization of a robust nanobiosensor or cross-reactive sensors array for the detection and identification of biocomponents.

Blending process modeling and control by multivariate curve resolution

The application of the Multivariate Curve Resolution by Alternating Least Squares (MCR-ALS) method to model and control blend processes of pharmaceutical formulations is assessed. Within the MCR-ALS framework, different data analysis approaches have been tested depending on the objective of the study, i.e., knowing the effect of different factors in the evolution of the blending process (modeling) or detecting the blend end-point and monitoring the concentration of the different species during and at the end of the process (control). Data analysis has been carried out studying multiple blending runs simultaneously taking advantage of the multiset mode of the MCR-ALS method. During the ALS optimization, natural constraints, such as non-negativity (spectral and concentration directions) have been applied for blend modeling. When blending control is the main purpose, a variant of the MCR-ALS algorithm with correlation constraint in the concentration direction has been additionally used. This constraint incorporates an internal calibration procedure, which relates resolved concentration values (in arbitrary units) with the real reference concentration values in the calibration samples (known references) providing values in real concentration scale in the final MCR-ALS results. Two systems consisting of pharmaceutical mixtures of an active principle (acetaminophen) with two or four excipients have been investigated. In the first case, MCR results allowed the description of the evolution of the individual compounds and the assessment of some physical effects in the blending process. In the second case, MCR analysis allowed the detection of the end-point of the process and the assessment of the effects linked to variations in the concentration level of the compounds.

Interval Multivariate Curve Resolution in the Dereplication of HPLC–DAD Data from Jatropha gossypifolia

Jatropha gossypifolia has been used quite extensively by traditional medicine for the treatment of several diseases in South America and Africa. This medicinal plant has therapeutic potential as a phytomedicine and therefore the establishment of innovative analytical methods to characterise their active components is crucial to the future development of a quality product. To enhance the chromatographic resolution of HPLC-UV-diode-array detector (DAD) experiments applying chemometric tools. Crude leave extracts from J. gossypifolia were analysed by HPLC-DAD. A chromatographic band deconvolution method was designed and applied using interval multivariate curve resolution by alternating least squares (MCR-ALS). The MCR-ALS method allowed the deconvolution from up to 117% more bands, compared with the original HPLC-DAD experiments, even in regions where the UV spectra showed high similarity. The method assisted in the dereplication of three C-glycosylflavones isomers: vitexin/isovitexin, orientin/homorientin and schaftoside/isoschaftoside. The MCR-ALS method is shown to be a powerful tool to solve problems of chromatographic band overlapping from complex mixtures such as natural crude samples.

Can bismuth film screen printed carbon electrodes be used to study complexation?

Ex­ situ bismuth film on commercial screen-printed carbon electrodes (BiSPCE) has been used for the first time for the analysis of the complexation of Cd2+ by thiol containing compounds as glutathione (GSH) and phytochelatin (γ-Glu–Cys)2–Gly (PC2).Reproducibility of data is quite satisfactory and allows their treatment by multivariate curve resolution by alternating least squares (MCR-ALS). Unitary voltammograms and concentration profiles provided by MCR-ALS confirm the formation of 1:1 and 1:2 Cd2+:GSH and 1:2 Cd2+:PC2 complexes. These results are in agreement with those previously obtained by mercury electrodes, and allow us to propose the use of BiSPCE for further studies on complexation.

Application of different chemometric strategies to voltammetric and UV-vis spectroscopic data to obtain a complexation model: study of the Cu(ii) binding with the phytohormone 6-benzylaminopurine

The complexation processes of Cu(II) by the phytohormone and the possible antitumoral agent 6-benzylaminopurine (BAP) were studied by Differential Pulse Polarography (DPP) and ultraviolet-visible spectroscopy (UV-vis) in combination with chemometric programs such as Multivariate Curve Resolution by Alternating Least-Squares (MCR-ALS) and Gaussian Peak Adjustment (GPA). All data confirm the formation of the predominant 1 : 1 and 1 : 2 Cu(2+) : BAP complexes. The corroboration of the presented stoichiometries was performed by ElectroSpray Ionization-Mass Spectrometric (ESI-MS) experiments of the Cu(II)-BAP system at different ratios.

Second-order data obtained from differential pulse voltammetry: Determination of tryptophan at a gold nanoparticles decorated multiwalled carbon nanotube modified glassy carbon electrode

Three-way data obtained from different pulse heights of differential pulse voltammetry (DPV) was analyzed using multivariate curve resolution by alternating least squares (MCR-ALS) algorithm. Differential pulse voltammograms of tryptophan were recorded at a gold nanoparticles decorated multiwalled carbon nanotube modified glassy carbon electrode (GCE/MWCNTs-nanoAu). The determination of tryptophan was performed even in the presence of unexpected electroactive interference(s). Both the simulated and experimental data were non-bilinear. Therefore a potential shift algorithm was used to correct the observed shift in the data. After correction, the data was augmented and MCR-ALS was applied to the augmented data. A relative error of prediction of less than 8% for the determination of the simulated analyte of interest and tryptophan in synthetic samples indicated that the methodology employing voltammetry and second-order calibration could be applied to complex analytical systems.

Cadmium binding in mixtures of phytochelatins and their fragments: A voltammetric study assisted by multivariate curve resolution and mass spectrometry

Phytochelatins (PC(n), (gamma-Glu-Cys)(n)Gly) are cysteine-rich peptides synthesized by plants which are involved in metal bioregulation and phytoremediation. Multivariate Curve Resolution by Alternating Least Squares (MCR-ALS) is applied to voltammetric data obtained from the analysis of the competitive binding of Cys or Cys-Gly with PC(2) or PC(3) by Cd(2+). The displacements between ligands, the chain length dependence on the competitive binding to PC(n) and the possible existence of mixed ligand metal-complexes are investigated. The shape analysis of the resulting pure voltammograms and concentration profiles of the components resolved by MCR-ALS suggests that ligands containing more thiol groups are able to displace the shorter chain ligands from their metal complexes, whereas the opposite does not happen. Electrochemical results are compared with ESI-MS measurements.

Complexation of Hg2+ with α‐Lipoic and Dihydrolipoic Acids: Study by Differential Pulse Voltammetry on Rotating Au‐Disk Electrode and ESI‐MS

AbstractThe complexation of the natural antioxidants α‐lipoic acid (ALA) and its reduced form dihydrolipoic acid (DHLA) with Hg2+ was investigated by a recently proposed differential pulse voltammetric (DPV) method using the rotating Au‐disk electrode. Complexation processes are proposed from the multivariate curve resolution by alternating least squares (MCR‐ALS) analysis of DPV titration data. Main complexes were both 1 : 1 Hg : ALA and Hg : DHLA, although the formation of 1 : 2 complexes can be also deduced. ALA and DHLA show different Hg2+‐binding patterns at different pH. Voltammetric findings are completed with the data obtained by electrospray ionization mass‐spectrometry (ESI‐MS), especially in negative mode.

Comparison of the results obtained by four receptor modelling methods in aerosol source apportionment studies

In this work the performance and theoretical background behind two of the most commonly used receptor modelling methods in aerosol science, principal components analysis (PCA) and positive matrix factorization (PMF), as well as multivariate curve resolution by alternating least squares (MCR-ALS) and weighted alternating least squares (MCR-WALS), are examined. The performance of the four methods was initially evaluated under standard operational conditions, and modifications regarding data pre-treatment were then included. The methods were applied using raw and scaled data, with and without uncertainty estimations. Strong similarities were found among the sources identified by PMF and MCR-WALS (weighted models), whereas discrepancies were obtained with MCR-ALS (unweighted model). Weighting of input data by means of uncertainty estimates was found to be essential to obtain robust and accurate factor identification. The use of scaled (as opposed to raw) data highlighted the contribution of trace elements to the compositional profiles, which was key to the correct interpretation of the nature of the sources. Our results validate the performance of MCR-WALS for aerosol pollution studies.

Possibilities of multivariate curve resolution and partial least squares in the resolution of coeluted peaks in liquid chromatography with electrochemical detection

Two different strategies are compared for the resolution of coeluted peaks in liquid chromatography with electrochemical detection. The first is voltammetric detection (VD) for the acquisition of currents as a function of potential and time with multivariate curve resolution by alternating least squares (MCR-ALS) for data analysis and quantification. The second is amperometric detection (AD), i.e. recording currents as a function of time for a fixed potential and calibration by partial least squares (PLS). Both approaches are used to analyse a model mixture of pyrocatechol, dopamine and epinephrine. The results show that for high analyte concentrations VD-MCR-ALS provides accurate quantification with minimal effort (a single injection of the sample and each standard). However, at lower concentrations the excessive proportion of noise and the predominance of the capacitive contribution decrease the performance of VD-MCR-ALS, thus making AD-PLS preferable as its greater accuracy counters the more time-consuming calibration, which involves the injection of a large number of mixtures of different composition.

Multivariate curve resolution as a tool to minimize the effects of electrodic adsorption in normal pulse voltammetry

Multivariate curve resolution by alternating least squares (MCR-ALS) was applied to normal pulse voltammograms (NPV) of heavy metal complexes that adsorb on the electrode. Adsorption usually causes: (i) a maximum superimposed on NPV waves, (ii) a decrease of the limiting current and (iii) a shift of half-wave potentials. Together, these effects result in excessively high stability constants when electrochemical methods of equilibrium calculation are applied. As an example of this behaviour, the Cd(II)-polymethacrylate (PMA) system was chosen. Despite the non-linearity of electrodic adsorption, MCR-ALS allows the decomposition of currents into three ca. linear contributions: (i) reduction of the free metal ion diffusing from the bulk solution, (ii) reduction of the metal complex also diffusing from the bulk and (iii) reduction of the metal ion accumulated by adsorption onto the electrode surface prior to pulse application. This almost ideal situation is achieved at high pulse times (which ensures that the adsorptive contribution is not much higher than the diffusive ones) and especially when NPV signals are analyzed in derivative form. Under these conditions, reasonable lacks of fit are obtained, as well as stability constants coincident with these determined by reverse pulse voltammetry (RPV), a technique especially unaffected by adsorption.