Benefits of applying combined diffuse reflectance FTIR spectroscopy and principal component analysis for the study of blue tempera historical painting

This paper explores the application of diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) to the examination of historic blue pigments and blue tempera paintings commonly found on works of art. The discussion is mainly focused on the practical benefits of using this technique joined to principal component analysis (PCA), a powerful multivariate analysis tool. Thanks to the study of several replica samples that contain either pure blue pigments (azurite, lapis lazuli and smalt), or pure binder (rabbit glue) and mixtures of each of the pigments with the binder (tempera samples), different aspects of these benefits are highlighted. Comparative results of direct spectra and multivariate analysis using transmittance-Fourier transform infrared spectroscopy (T-FTIR) are discussed throughout this study. Results showed an excellent ability of PCA on DRIFT spectra for discriminating replica samples according to differing composition. Several IR regions were tested with this aim; the fingerprint IR region exhibited the best ability for successfully clustering the samples. The presence of the binder was also discriminated. Only using this approach it was possible to completely separate all the studied replica samples. This demonstrates the potential benefits of this approach in identifying historical pigments and binders for conservation and restoration purposes in the field of Cultural Heritage.     

Non-invasive identification of organic materials in wall paintings by fiber optic reflectance infrared spectroscopy: a statistical multivariate approach

The aim of this study is to develop a method for the non-invasive and in situ identification of organic binders in wall paintings by fiber optic mid-FTIR reflectance spectroscopy. The non-invasive point analysis methodology was set-up working on a wide set of wall painting replicas of known composition and using statistical multivariate methods, in particular principal component analysis (PCA), for the interpretation, understanding, and management of data acquired with reflectance mid-FTIR spectroscopy. Results show that PCA can be helpful in managing and preliminary sorting of the large amount of spectra typically collected during non-invasive measurement campaigns and highlight further avenues for research. The developed PCA model was finally applied to the case of a Renaissance wall painting by Perugino assessing it predictability as compared to the interpretation of the single spectrum.     

Use of multivariate statistical analysis to evaluate experimental results for certification of two pharmaceutical reference materials

This paper demonstrates the use of the multivariate analysis for the quick and easy evaluation of the experimental results from the homogeneity test of two new certified reference materials (CRM) of active pharmaceutical ingredients (API): metronidazole and captopril. The principal component analysis (PCA) and the hierarchical cluster analysis (HCA) indicated that some results from the homogeneity test were statistically different when the concentrations of all API impurities were considered simultaneously. Through the use of these statistical tools, it was possible to reduce the standard uncertainty due to between-bottle (in)homogeneity (u _bb) and consequently the combined standard uncertainty of the certified reference materials (u _CRM) with 95% confidence level.     

Optimized sample preparation procedures for the analysis of solid materials by total-reflection XRF

The total reflection X-ray fluorescence (TXRF) method has been used for the analysis of various types of solid materials of biological, geological and environmental origin. The sample preparation step prior to TXRF measurements has been optimized for the various solid samples, including their decomposition by applying both a microwave oven and a PTFE bomb. Complete procedures for the optimized decomposition from the point of view of speed and completeness of digestion, as well as of the overall precision and accuracy are presented.     

Stratigraphic analysis of organic materials in wall painting samples using micro-FTIR attenuated total reflectance and a novel sample preparation technique

Wall paintings typically contain low concentrations of organic materials within a largely inorganic matrix and are characterised by their high porosity and long-term exposure to severe environmental conditions. The identification of organic materials within specific paint or plaster layers is challenging and the inherent characteristics of wall painting samples present further complications. Embedding materials (such as epoxy, polyester and acrylic-based resins) used to produce cross-sections often infiltrate porous and leanly bound samples, and compromise the interpretation of Fourier transform infrared attenuated total reflectance (FTIR-ATR) spectra and the qualitative identification of natural organic materials. An alternative method for the preparation of cross-sections of wall painting samples was developed using cyclododecane (C(12)H(24)) as a temporary consolidant and barrier coating to encapsulate the sample, and to provide necessary support to produce a cross-section through microtoming. Impacts of traditional and novel sample preparation techniques on the identification of organic materials with micro-FTIR-ATR were examined for both replica and real wall painting samples.     

Classification of the biological material with use of FTIR spectroscopy and statistical analysis

Rapid detection and discrimination of dangerous biological materials such as bacteria and their spores has become a security aim of considerable importance. Various analytical methods, including FTIR spectroscopy combined with statistical analysis have been used to identify vegetative bacteria, bacterial spores and background interferants. The present work discusses the application of FTIR technique performed in reflectance mode using Horizontal Attenuated Total Reflectance accessory (HATR) to the discrimination of biological materials. In comparison with transmission technique the HATR is more rapid and do not require the sample destruction, simultaneously giving similar absorbance bands. HATR-FTIR results combined with statistical analysis PCA and HCA demonstrate that this combination provides novel and accurate microbial identification technique.     

Diffuse reflectance FTIR study of the interaction of alumina surfaces with ozone and water vapor

The interaction of ozone with alumina has been examined at ambient temperature as a function of ozone concentration and relative humidity. The experiments used diffuse reflectance FTIR spectroscopy in a small flow reactor, which provided control of the temperature, pressure, and composition of the gas mixture to which the sample was continuously exposed. Treatment of alumina with ozone produced a new spectroscopic feature at 1380 cm(-1), which we attribute to an aluminum oxide species formed by interaction of O3 with Lewis acid sites on the alumina surface. After exposure of the alumina sample to O3 was stopped, subsequent exposure of the sample to humidified nitrogen resulted in the slow removal of the peak at 1380 cm(-1). Simultaneously, the uptake of water by the alumina increased as indicated by the growth of the adsorbed water features which extend from approximately 3700 to 2500 cm(-1). Treatment of dry alumina with humidified ozone strongly inhibited both the rate of formation of the spectral feature at 1380 cm(-1) and its limiting extent of formation. These observations are analyzed in terms of the adsorption and surface reaction properties of ozone on alumina. The observation that the new oxide feature on alumina, produced by reaction with ozone, can be removed by water is important for assessing the ability of mineral dust aerosols to process atmospheric trace gases over a significant time scale. We believe the work reported here to be the first direct and quantitative kinetic study of the competition between O3 and water for adsorption sites on alumina.     

A study for quality evaluation of Taxilli Herba from different hosts based on fingerprint-activity relationship modeling and multivariate statistical analysis

In this study, a fingerprint-activity relationship modeling between chemical fingerprints and antirheumatic activity was established, and multivariate statistical analysis was used to evaluate the quality of Taxilli Herba (TH) from different hosts. Characteristic fingerprints of 20 batches of TH samples were generated by high-performance liquid chromatography coupled with triple quadrupole-time of flight tandem mass spectrometry (HPLC-Triple TOF-MS/MS), and the similarity analysis was calculated based on thirteen common characteristic peaks by hierarchical clustering analysis (HCA). Subsequently, nine efficacy markers were discovered by combining fingerprints and antirheumatic activity through grey correlation analysis (GCA) and bivariate correlation analysis (BCA). Meanwhile, the content of 5 constituents in 9 markers was determined by high-performance liquid chromatography coupled with triple quadrupole-linear ion trap tandem mass spectrometry (HPLC-QTRAP-MS/MS). The comprehensive quality of TH was assessed using multivariate statistical analysis, including principal components analysis (PCA) and technique for order preference by similarity to ideal solution (TOPSIS). The results showed that a high dose of TH extract could markedly ameliorate arthritis damage compared to other doses, with flavonoids playing an important role in the antirheumatic activity. The comprehensive quality of samples from Morus alba L. (SS) was superior to those from Liquidambar formosana Hance (FXS). The present study will demonstrate the markers associated with efficacy, and provide an applicable strategy for more comprehensive quality control and evaluation of TH.     

Use of multivariate statistical techniques to optimize the separation of isoflavones by liquid chromatography

The aim of this paper is to optimize and validate a high performance liquid chromatography (HPLC) method for separation and quantification of five isoflavones. A statistical central composite design was used to separate all peaks. These multivariate procedures were efficient in determining the optimal separation condition using resolution, capacity factor, asymmetry and number of theoretical plates.      

Identification of the regulatory proteins in human pancreatic cancers treated with Trichostatin A by 2D-PAGE maps and multivariate statistical analysis

In this paper, principal component analysis (PCA) is applied to a spot quantity dataset comprising 435 spots detected in 18 samples belonging to two different cell lines (Paca44 and T3M4) of control (untreated) and drug-treated pancreatic ductal carcinoma cells. The aim of the study was the identification of the differences occurring between the proteomic patterns of the two investigated cell lines and the evaluation of the effect of the drug Trichostatin A on the protein content of the cells. PCA turned out to be a successful tool for the identification of the classes of samples present in the dataset. Moreover, the loadings analysis allowed the identification of the differentially expressed spots, which characterise each group of samples. The treatment of both the cell lines with Trichostatin A therefore showed an appreciable effect on the proteomic pattern of the treated samples. Identification of some of the most relevant spots was also performed by mass spectrometry.     

Prospective study to assess the clinical efficacy of bone scintigraphy--ROC analysis

The value of preoperative bone scans in patients with primaly breast and prostate cancer was evaluated prospectively. The methodology and some clinical results were described previously. The clinical efficacy of the bone scan was assessed by using ROC analysis and we obtained the following results. 1) Preoperative bone scan of carcinomas of the breast is effective for patients with clinical stage IIIA, IIIB and IV. It is not so effective for patients with clinical stage I and II, but there is no denying the importance of it, because it provides a base-line scan for comparison to subsequent scans obtained in the postoperative period. 2) Preoperative bone scan of prostate carcinomas is effective, especially for clavicle, the ribs and the cervical spine, when compared with bone X-ray. 3) Bone scan is effective means for patients who were diagnosed uncertainly to have bone metastasis.     

X-ray fluorescence analysis for the study of fragments pottery excavated at Tell Jendares site, Syria, employing multivariate statistical analysis

X-ray fluorescence analysis study of 44 archaeological pottery samples collected from Tell Jendares site north-west of Syria has been carried out. Four samples of the total previous investigated samples were obtained from the kiln found on Tell Jendares site. Seventeen different chemical elements were determined. The XRF results have been processed using two multivariate statistical cluster and factor analysis methods in order to determine the similarities and correlation between the selected samples based on their elemental composition. The methodology successfully separates the samples where three distinct chemical groups were discerned.     

A study of trace element contamination in river sediments in Serbia using microwave-assisted aqua regia digestion and multivariate statistical analysis

The aim of this study was the evaluation of the trace element contamination level in sediments of the most important rivers in Serbia and their tributaries. The determination of the aqua regia soluble contents of 12 micro- and macro-elements (Ca, Cd, Co, Cr, Cu, Fe, Mn, Pb, Ni, Zn, Be and V) in sediments was developed by the microwave digestion technique combined with inductively coupled plasma atomic emission spectrometry. Correlation analysis and principal component analysis distinguishes factors of lithogenic and anthropogenic origins. The Fe, Mn, Be and V contents are controlled by a regional lithogenic high background factor, while Cd, Cr, Pb, Ni, Zn and Cu are recognized as tracer of pollution. For Co, mixed sources from both lithogenic and anthropogenic inputs were evidenced.The investigated sediment of the major rivers and their tributaries in Serbia showed high concentrations of metals, especially of Cd, Pb, Cu and Zn, which may cause serious environmental impacts. Rivers which flow into the Danube from its entrance into Serbia significantly influence the chemical load of the water and sediments.The experimental study was conducted using two BCR standard reference materials. The calculated accuracy and precision confirmed the good performance of the adopted procedures.     

New masking liquids for the analysis of supported catalysts and functional materials by small-angle X-ray scattering

A new contrasting procedure is proposed for studying supported catalysts and functional materials by small-angle scattering. The main advantage over earlier analogues is the use of new masking liquids, which possess very low X-ray absorption at a relatively high density. A number of supported catalysts were studied using the new procedure, and almost complete agreement of the particle-size distributions of supported metals with transmission electron-microscopic data was demonstrated. The use of the new contrasting procedure on a typical small-angle diffractometer makes it possible to obtain the particle-size distributions of metals in supported catalysts containing noble metals at a level to 0.1 wt %.     

Instrumental neutron activation analysis applied to the determination of the chemical composition of metallic materials with study of interferences

Summary Instrumental neutron activation analysis was applied to evaluate the chemical composition of metallic materials, namely iron, steel, silicon and ferrosilicon certified reference materials. As, Co, Cr, Mn, Mo, Ni, V and W concentrations were analyzed in the iron and steel samples whereas 21 elements were determined in silicon and ferrosilicon samples. Accuracy and precision results of about 10% were achieved for most elements, indicating that the technique is suitable for the analysis of metallic materials. Interferences of Cr and Mn in V; Fe and Co in Mn; Co in Fe and Cr in Ti were quantified and only the last one was critical to the analysis of the materials employed in this work.     

A new theoretical approach for the determination of molecular orientation persistence length of adsorbed nanofilms by FTIR reflectance spectroscopy

FTIR-Reflectance experiments have proved to be a powerful tool for the determination of molecular orientation in thin films adsorbed onto highly reflecting metals. We propose an original method for determination of the persistence length of molecular orientation in the film. This approach is based on the fact that molecular orientation persists only over a given distance from the geometrical interface. This distance is called the “persistence length of molecular orientation”. We then suppose that the nanofilm adsorbed is stratified and consists of an oriented layer (in the near-interface region) plus an isotropic one. Correlation between infrared reflection absorption band intensities and simulated band intensities allows experimentators to determine accurate molecular orientation and persistence length of orientation of a considered functional group. This is accomplished by using various IR reflection angles and p-polarization state of the incident IR wave. Film thickness and complex refractive index spectra, n(v) − i · k(v), are only needed to deduce calculated specular reflectance intensities.     

Identification of Pulsatilla chinensis (Bge.) Regel and look-alike species by UHPLC-TOF-MS using multivariate statistical analysis

Pulsatillae Radix, the root of Pulsatilla chinensis (Bge.) Regel, is recorded in the Pharmacopoeia of the People's Republic of China and has been widely used for its pharmacological activities, such as anti-inflammatory, antioxidant, antibacterial, antitumor, and cardiovascular benefits. However, there are several look-alike species that can be marketed as Pulsatillae Radix. To distinguish P. chinensis (Bge.) Regel from its look-alikes, viz. Pulsatilla cernua (Thunb.) Bercht et Opiz., Pulsatilla dahurica (Fisch.) Spreng., Anemone tomeutosa (Maxim.) Pei., and Rhaponticum uniflorum (L.) DC, we used ultra high performance liquid chromatography with time-of-flight mass spectrometry combined with principal component analysis to compare their chemical compositions. Four ions, a (RT 8.98 min, m/z 1381.6671), b (RT 10.64 min, m/z 1219.6143), c (RT 11.52 min, m/z 1217.5978), and d (RT 13.6 min, m/z 749.4463), from P. chinensis (Bge.) Regel were identified as potential chemical markers to distinguish it from look-alike species using an unsupervised statistical model combined with orthogonal partial least-squares discriminant analysis. The results of this study provide an effective method for identifying and distinguishing P. chinensis (Bge.) Regel from similar plants.     

Qualitative interpretation of physico-chemical and isotopic parameters in the Krka River (Croatia) assessed by multivariate statistical analysis

Multivariate statistical analyses were applied on the measured physico-chemical (Cd, Pb, Cu, Zn, Mg, Ca, O₂, alkalinity, temperature, pH, SAS, DOC and DIC) and isotopic parameters (δ¹³C and δ¹⁸O) to estimate and distinguish anthropogenic from natural influences to the water system of the Krka River. Analyses were conducted on the data collected during six years from twelve sampling sites. On the basis of orientation, positioning and grouping of parameters arranged by biplots, four main hypotheses were defined and finally statistically confirmed. Thereof, two main and distinct processes occurring in the Krka River could be highlighted: (i) upstream pollution, caused by the inflow of untreated waste-waters of city of Knin and (ii) downstream self-purification, caused by the sedimentation and/or co-precipitation of pollutants coupled by the inflow of clean subterranean water (groundwater recharge). Grouping of (i) hydrological and carbon cycle connected parameters, and (ii) anthropogenically influenced correlated parameters were proposed as a result of statistical analysis. Regarding the pH, it is shown that a stream section influenced by the subterranean inflow of Zrmanja River is statistically significantly different for all sampling campaigns during six years, being lower for about 0.5 pH unit.     

A comparative study of diesel analysis by FTIR, FTNIR and FT-Raman spectroscopy using PLS and artificial neural network analysis

Diesel properties determined by ASTM reference methods as cetane index, density, viscosity, distillation temperatures at 50% (T50) and 85% (T85) recovery, and the total sulfur content (%, w/w) were modeled by FTIR-ATR, FTNIR, and FT-Raman spectroscopy using partial last square regression (PLS) and artificial neural network (ANN) spectral analysis. In the PLS models, 45 diesel samples were used in the training group and the other 45 samples were used in the validation. In the ANN analysis a modular feedforward network was used. Sixty diesel samples were used in the neural network training and other 30 samples were used in the validation. Two different ATR configurations were compared in the FTIR, a conventional (ATR1) and an immersion (ATR2) cell. The ATR1 cell presented the best results, with smaller prediction errors (root mean square error of prediction, RMSEP). The comparison of the three PLS models (FTIR-ATR1, FTNIR, and FT-Raman) shows that reasonable values of R² and RMSEP were obtained by the FTIR-ATR1 and FTNIR models in the evaluation of density, viscosity, and T50. The PLS/FT-Raman models presented reasonable results only for the T50 property. None of the techniques was able to generate suitable PLS calibration models for the determination of sulfur content. The ANN/FT-Raman models presented the best performances, with all models presenting R²-values above 85% some of them with RMSEP values significantly smaller than those obtained with FTIR-ATR and FTNIR. The ANN/FT-Raman and ANN/FTIR-ATR1 models were able to estimate the total sulfur content of diesel with 0.01% (w/w) accuracy.     

Two-dimensional correlation spectroscopy and multivariate curve resolution for the study of lipid oxidation in edible oils monitored by FTIR and FT-Raman spectroscopy

Accelerate oxidative degradation of six vegetable oils was monitored using FTIR and FT-Raman spectroscopy. Two-dimensional correlation spectroscopy and multivariate curve resolution alternating least squares (MCR-ALS) were applied to the analysis of the data. The use of hetero-spectral two-dimensional correlation of FTIR and FT-Raman data allowed the use of well established band assignments to interpret less clearly assigned spectral features. With a moving window approach it was possible to obtain simplified two-dimensional correlation maps and to detect compounds evolving with different kinetic. Simultaneous analysis of the oxidation experiments of the six different oils monitored by both spectroscopic techniques was performed using MCR-ALS. Although a complete resolution of the data was not possible, the spectral changes occurring during the oxidative degradation of the oils were described with a five-component model. The two fundamentally different chemometric approaches lead to coincident results.