Standardization of chromatographic signals - Part I: Towards obtaining instrument-agnostic fingerprints in gas chromatography.

One of the main causes for the sparse use of multivariate analytical methods in routine laboratory work is the dependency on the measuring instrument from which the analytical signal is acquired. This issue is especially critical in chromatographic equipment and results in limitations of their applicability. The solution to this problem is to obtain a standardized instrument-independent signal -or instrument-agnostic signal- regardless of the measuring instrument or of the state of the same instrument from which it has been acquired. The combined use of both internal and external standard series, allows us to have external and transferable references for the normalization of both the intensity and the position of each element of the data vector being arranged from the raw signal. From this information, a simple mathematical data treatment process is applied and instrument-agnostic signals can be secured. This paper describes and applies the proposed methodology to be followed for obtaining standardized instrumental fingerprints from two significant fractions of virgin olive oil (volatile organic compounds and triacylglycerols), obtained by gas chromatography coupled to mass spectrometry (GC-MS) and analysed with two temperature conditions (conventional and high-temperature, respectively). The results of both case studies show how the instrument-agnostic fingerprints obtained are coincidental, regardless of the state of the chromatographic system or the time of acquisition.

Self-Referenced Multifrequency Phase-Resolved Luminescence Spectroscopy.

Phase-resolved luminescence chemical sensors provide the analyte determination based on the estimation of the luminescence lifetime. The lifetime is estimated from an analysis of the amplitudes and/or phases of the excitation and emission signals at one or several modulation frequencies. This requires recording both the excitation signal (used to modulate the light source) and the emission signal (obtained from an optical transducer illuminated by the luminescent sensing phase). The excitation signal is conventionally used as reference, in order to obtain the modulation factor (the ratio between the emission and the excitation amplitudes) and/or the phase shift (the difference between the emission and the excitation phases) at each modulation frequency, which are used to estimate the luminescence lifetime. In this manuscript, we propose a new method providing the luminescence lifetimes (based either on amplitudes or phases) using only the emission signal (i.e., omitting the excitation signal in the procedure). We demonstrate that the luminescence lifetime can be derived from the emission signal when it contains at least two harmonics, because in this case the amplitude and phase of one of the harmonics can be used as reference. We present the theoretical formulation as well as an example of application to an oxygen measuring system. The proposed self-referenced lifetime estimation provides two practical advantages for luminescence chemical sensors. On one hand, it simplifies the instrument architecture, since only one analog-to-digital converter (for the emission signal) is necessary. On the other hand, the self-referenced estimation of the lifetime improves the robustness against degradation of the sensing phase or variations in the optical coupling, which reduces the recalibration requirements when the lifetimes are based on amplitudes.

A Polynomial-Exponent Model for Calibrating the Frequency Response of Photoluminescence-Based Sensors.

In this work, we propose a new model describing the relationship between the analyte concentration and the instrument response in photoluminescence sensors excited with modulated light sources. The concentration is modeled as a polynomial function of the analytical signal corrected with an exponent, and therefore the model is referred to as a polynomial-exponent (PE) model. The proposed approach is motivated by the limitations of the classical models for describing the frequency response of the luminescence sensors excited with a modulated light source, and can be considered as an extension of the Stern-Volmer model. We compare the calibration provided by the proposed PE-model with that provided by the classical Stern-Volmer, Lehrer, and Demas models. Compared with the classical models, for a similar complexity (i.e., with the same number of parameters to be fitted), the PE-model improves the trade-off between the accuracy and the complexity. The utility of the proposed model is supported with experiments involving two oxygen-sensitive photoluminescence sensors in instruments based on sinusoidally modulated light sources, using four different analytical signals (phase-shift, amplitude, and the corresponding lifetimes estimated from them).

Discrimination and classification of extra virgin olive oil using a chemometric approach based on TMS-4,4'-desmetylsterols GC(FID) fingerprints of edible vegetable oils.

A single out-line HPLC-GC (FID) analytical method is applied to acquire the chromatographic fingerprint characteristic of the TMS-4,4'-desmetylsterol derivative fraction of several marketed edible vegetable oils in order to identify and discriminate the most valuable extra-virgin olive oils from the other vegetal oils (canola, corn, grape seed, linseed, olive pomace, peanut, rapeseed, soybean, sesame, seeds (non-specified composition but usually a blend of corn and sunflower) and sunflower). The natural structure of the preprocessed data undergoes a preliminary exploration using principal component analysis and heat map-based cluster analysis. A partial least squares-discriminant model is first trained from 53 oil samples (only 3 latent variables) and externally validated from 18 test oil samples. No classification errors are found and all the test samples are correctly classified. Additional classification models are also built in order to discriminate among vegetables-oil families and excellent results have been also achieved.

A metabolic fingerprinting approach based on selected ion flow tube mass spectrometry (SIFT-MS) and chemometrics: A reliable tool for Mediterranean origin-labeled olive oils authentication.

Selected Ion flow tube mass spectrometry (SIFT-MS) in combination with chemometrics was used to authenticate the geographical origin of Mediterranean virgin olive oils (VOOs) produced under geographical origin labels. In particular, 130 oil samples from six different Mediterranean regions (Kalamata (Greece); Toscana (Italy); Meknès and Tyout (Morocco); and Priego de Córdoba and Baena (Spain)) were considered. The headspace volatile fingerprints were measured by SIFT-MS in full scan with H3O+, NO+ and O2+ as precursor ions and the results were subjected to chemometric treatments. Principal Component Analysis (PCA) was used for preliminary multivariate data analysis and Partial Least Squares-Discriminant Analysis (PLS-DA) was applied to build different models (considering the three reagent ions) to classify samples according to the country of origin and regions (within the same country). The multi-class PLS-DA models showed very good performance in terms of fitting accuracy (98.90-100%) and prediction accuracy (96.70-100% accuracy for cross validation and 97.30-100% accuracy for external validation (test set)). Considering the two-class PLS-DA models, the one for the Spanish samples showed 100% sensitivity, specificity and accuracy in calibration, cross validation and external validation; the model for Moroccan oils also showed very satisfactory results (with perfect scores for almost every parameter in all the cases).

Assessing the varietal origin of extra-virgin olive oil using liquid chromatography fingerprints of phenolic compound, data fusion and chemometrics.

High Performance Liquid Chromatography (HPLC) with diode array (DAD) and fluorescence (FLD) detection was used to acquire the fingerprints of the phenolic fraction of monovarietal extra-virgin olive oils (extra-VOOs) collected over three consecutive crop seasons (2011/2012-2013/2014). The chromatographic fingerprints of 140 extra-VOO samples processed from olive fruits of seven olive varieties, were recorded and statistically treated for varietal authentication purposes. First, DAD and FLD chromatographic-fingerprint datasets were separately processed and, subsequently, were joined using "Low-level" and "Mid-Level" data fusion methods. After the preliminary examination by principal component analysis (PCA), three supervised pattern recognition techniques, Partial Least Squares Discriminant Analysis (PLS-DA), Soft Independent Modeling of Class Analogies (SIMCA) and K-Nearest Neighbors (k-NN) were applied to the four chromatographic-fingerprinting matrices. The classification models built were very sensitive and selective, showing considerably good recognition and prediction abilities. The combination "chromatographic dataset+chemometric technique" allowing the most accurate classification for each monovarietal extra-VOO was highlighted.

In-Depth Two-Year Study of Phenolic Profile Variability among Olive Oils from Autochthonous and Mediterranean Varieties in Morocco, as Revealed by a LC-MS Chemometric Profiling Approach.

Olive oil phenolic fraction considerably contributes to the sensory quality and nutritional value of this foodstuff. Herein, the phenolic fraction of 203 olive oil samples extracted from fruits of four autochthonous Moroccan cultivars ("Picholine Marocaine", "Dahbia", "Haouzia" and "Menara"), and nine Mediterranean varieties recently introduced in Morocco ("Arbequina", "Arbosana", "Cornicabra", "Frantoio", "Hojiblanca", "Koroneiki", "Manzanilla", "Picholine de Languedoc" and "Picual"), were explored over two consecutive crop seasons (2012/2013 and 2013/2014) by using liquid chromatography-mass spectrometry. A total of 32 phenolic compounds (and quinic acid), belonging to five chemical classes (secoiridoids, simple phenols, flavonoids, lignans and phenolic acids) were identified and quantified. Phenolic profiling revealed that the determined phenolic compounds showed variety-dependent levels, being, at the same time, significantly affected by the crop season. Moreover, based on the obtained phenolic composition and chemometric linear discriminant analysis, statistical models were obtained allowing a very satisfactory classification and prediction of the varietal origin of the studied oils.

High performance optical oxygen sensors based on iridium complexes exhibiting interchromophore energy shuttling.

A doubly pyrene-grafted bis-cyclometallated iridium complex with engineered electronically excited states demonstrates reversible electronic energy transfer between adjacent chromophores giving rise to extremely long-lived red luminescence in solution (τ = 480 µs). Time-resolved spectroscopic studies afforded determination of pertinent photophysical parameters including rates of energy transfer and energy distribution between constituent chromophores in the equilibrated excited molecule (ca. 98% on the organic chromophores). Incorporation into a nanostructured metal-oxide matrix (AP200/19) gave highly sensitive O2 sensing films, as the detection sensitivity was 200-300% higher than with the commonly used PtTFPP and approaches the sensitivity of the best O2-sensing dyes reported to date.

Copper(I) complexes as alternatives to iridium(III) complexes for highly efficient oxygen sensing.

The complex [Cu(xantphos)(dmp)][PF6] (dmp = 2,9-dimethyl-1,10-phenanthroline) in a nanostructured metal oxyde matrix shows better sensitivity to oxygen (KSV = 9.74 ± 0.87 kPa(-1) between 0 and 1 kPa pO2 and 5.59 ± 0.15 kPa(-1) between 0 and 10 kPa pO2) than cyclometallated iridium complexes in the same conditions.

Improved multifrequency phase-modulation method that uses rectangular-wave signals to increase accuracy in luminescence spectroscopy.

We propose a novel multifrequency phase-modulation method for luminescence spectroscopy that uses a rectangular-wave modulated excitation source with a short duty cycle. It is used for obtaining more detailed information about the luminescence system: the information provided by different harmonics allows estimating a model for describing the global frequency response of the luminescent system for a wide range of analyte concentration and frequencies. Additionally, the proposed method improves the accuracy in determination of the analyte concentration. This improvement is based on a simple algorithm that combines multifrequency information provided by the different harmonics of the rectangular-wave signal, which can be easily implemented in existing photoluminescence instruments by replacing the excitation light source (short duty cycle rectangular signal instead of sinusoidal signal) and performing appropriate digital signal processing after the transducer (implemented in software). These claims have been demonstrated by using a well-known oxygen-sensing film coated at the end of an optical fiber [a Pt(II) porphyrin immobilized in polystyrene]. These experimental results show that use of the proposed multifrequency phase-modulation method (1) provides adequate modeling of the global response of the luminescent system (R(2) > 0.9996) and (2) decreases the root-mean-square error in analytical determination (from 0.1627 to 0.0128 kPa at 0.5 kPa O2 and from 0.9393 to 0.1532 kPa at 20 kPa O2) in comparison with a conventional phase-modulation method based on a sinusoidally modulated excitation source (under equal luminous power conditions).

Electrophoretic deposition as a new approach to produce optical sensing films adaptable to microdevices.

We report the fabrication of optical oxygen sensor films using electrophoretic deposition (EPD) of poly(styrene-co-maleic anhydride) nanoparticles containing the oxygen-sensitive dye platinum(ii) meso-tetra(pentafluorophenyl)porphine. Compared to other deposition methods, the EPD is simple and allows easy control over deposition, which is crucial for the implementation of optical sensing films in microdevices. By optimizing the synthesis of the functional nanoparticles, anodic EPD can be performed. The amount of deposited particles can be tuned by varying either the electrical potential or the deposition time. The sensing phases were characterized using a phase-modulation technique showing a Stern-Volmer constant (kSV1) between 45 and 52 bar(-1) for gas and of 20.72 bar(-1) in the aqueous phase without leaching of the particles from the surface. The small thickness of the layers lead to short response times (<0.4 s). This is the first time that polymeric optical sensing films have been obtained by EPD from dispersions of oxygen sensing nanoparticles.

High performance optical sensing nanocomposites for low and ultra-low oxygen concentrations using phase-shift measurements.

The accurate and real-time measurement of low and ultra-low concentrations of oxygen using non-invasive methods is a necessity for a multitude of applications, from brewing beer to developing encapsulating barriers for optoelectronic devices. Current optical methods and sensing materials often lack the necessary sensitivity, signal intensity, or stability for practical applications. In this report we present a new optical sensing nanocomposite resulting in an outstanding overall performance when combined with the phase-shift measurement method (determination of luminescence lifetime in the frequency domain). For the first time we have incorporated the standard PtTFPP dye (PtTFPP = platinum(II) 5,10,15,20-meso-tetrakis-(2,3,4,5,6-pentafluorophenyl)-porphyrin) into AP200/19, a nanostructured aluminium oxide-hydroxide solid support. This sensing film shows an excellent sensitivity between 0 and 1% O2 (KSV = 3102 ± 132 bar⁻¹) and between 0 and 10% O2 (KSV = 2568 ± 614 bar⁻¹) as well as Δτ0.05% (62.53 ± 3.66%), which makes it 62 times more sensitive than PtTFPP immobilized in polystyrene and also 8 times more sensitive than PtTFPP immobilized on silica beads. Furthermore the phase-shift measurement method results in a significant improvement (about 23 times) in stability compared to the use of intensity recording methods. The film also displays full reversibility, long shelf stability (no change observed after 12 months), and it is not affected by humidity. To establish this sensing methodology and develop sensors over the full range of the visible light, we also studied three other dye-AP200/19 nanocomposites based on phosphorescent cyclometalated iridium(III) complexes.

In vitro oxygen sensing using intraocular microrobots.

We present a luminescence oxygen sensor integrated with a wireless intraocular microrobot for minimally-invasive diagnosis. This microrobot can be accurately controlled in the intraocular cavity by applying magnetic fields. The microrobot consists of a magnetic body susceptible to magnetic fields and a sensor coating. This coating embodies Pt(II) octaethylporphine (PtOEP) dyes as the luminescence material and polystyrene as a supporting matrix, and it can be wirelessly excited and read out by optical means. The sensor works based on quenching of luminescence in the presence of oxygen. The excitation and emission spectrum, response time, and oxygen sensitivity of the sensor were characterized using a spectrometer. A custom device was designed and built to use this sensor for intraocular measurements with the microrobot. Due to the intrinsic nature of luminescence lifetimes, a frequency-domain lifetime measurement approach was used. An alternative sensor design with increased performance was demonstrated by using poly(styrene-co-maleic anhydride) (PS-MA) and PtOEP nanospheres.