Raman investigation of corrosion products on Roman copper-based artefacts

<p class="Abstract">This paper illustrates a case study related to the characterisation of corrosion products present on recently excavated artefacts. The archaeological findings, from the Rakafot 54 site (Beer-Sheva, Israel), consist of 23 coins and a pendant, all dating back to the Roman period. Raman spectroscopy was used to identify the corrosion products that compose the patina covering the objects. To facilitate and support their identification, spectra were then processed using principal components analysis. This chemometric technique allowed the identification of two main compounds, classified as atacamite and clinoatacamite, which formed the main components of the patinas. The results of this investigation can help in assessing the conservation state of artefacts and defining the correct restoration strategy.</p>

Evaluation of Trans Fat in Vermicelli by Fourier Transform Infrared Spectroscopy in Combination with Chemometric Technique

Since there is limited knowledge about trans fat levels in snack foods available in Pakistan. This study aimed to determine trans fat content in fried vermicelli (a common snack food). It is prepared in partially hydrogenated oil (ghee), which is the main cause of trans fat formation. Twenty-one fried vermicelli samples were collected from different local shops of Hyderabad, Pakistan and subjected to oil extraction by using Soxhlet method. Partial least square regression model was developed to quantify trans fats in fried vermicelli using FTIR spectroscopy. Total oil content in fried vermicelli ranged between 17.28- 32.99%. FTIR results revealed that fried vermicelli showed trans fats in between 7.3-20.9% in extracted oil, whereas total trans fat in food was ranged at 1.3-5.9%. The FTIR data of trans fat was compared with GC-MS data and found comparable results (pandgt;0.05). Presence of high trans fat in fried vermicelli is an alarming issue for the health of consumers.

PHARMACEUTICAL FORMULATION MANUFACTURER DISCRIMINATION BY INFRARED SPECTROSCOPY AND PRINCIPAL COMPONENT ANALYSIS

In the present work Fournier transform infrared (IR) spectroscopy in association with chemometric technique was employed to identify kind of tablet formulations containing paracetamol and/or caffeine as active pharmaceutical ingredients. 13 samples of 5 commercially available brand tablets of different manufacturers and batches were bayed in local pharmacies. IR spectra of samples were recorded in the range 600—4000 cm-1 and subjected to and principal component analysis (PCA) which allowed to clearly identify 5 clusters in the scores plot using the third and the second principal components, corresponding to the brands of tablets. For Paracetamol and Caffeine-sodium benzoate tablets the combination of IR spectroscopy and PCA was able to recognize the manufacturer on the basis of distance between samples in clusters in the PCA scores plot.

Chemometric Calculation for Determination of Betamethasone and Neomycin Mixture in Cream Supply by Ultraviolet Spectrophotometry

BACKGROUND: Chemometric can be defined as a branch of analytical chemistry using statistical principles to design and select optimal analytical procedures and experiments. The chemometric technique that applies in the design of quantitative calibration curves in the spectral analysis is very important in quality control of the component contained in the drug mixture of 2 or 3 drug components or more, especially the component that has the adjacent wavelength when the spectrum overlap. AIM: The purpose of this study was to conduct research that examines betamethasone and neomycin mixture in cream with the UV spectrophotometric methods using a chemometric calculation. METHODS: Chemometric calculation for determination of betamethasone and neomycin mixture in cream supply by ultraviolet spectrophotometric. RESULTS: The result of betamethasone and neomycin levels were 91.35% and 97.56%, relative standard deviation (RSD) for betamethasone and neomycin 0.93%; 1.73% and recovery percentage 99.09%; 99.94%. On the multivariate calibration of PLS ​​betamethasone and neomycin with each RMSEC value of 0.0230 and 0.3553 with the value of RMSECV 0.7187 and 0.3586 with RMSEP value 0.1558 and 0.0820. Thus, the predictive ability of the research is still acceptable and is well used for grade determination of betamethasone and neomycin content ​​fulfil the requirement for cream preparation according to USP edition XXX. CONCLUSION: Methods of UV spectrophotometric with chemometric can be used in the determination of BET and NEO levels in cream preparations and BET level is 91.35% with a range of 90-110%, and NEO level is 97.56% with a range of 94.45-98.71%. These levels have met the requirements of the levels listed in Indonesian Pharmacopoeia, 2014.

PREDICTIVE SIMULATION AND OPTIMIZATION ORIENTED MODELING FOR THE EXTRACTION OF METAL IONS FROM SOLUTIONS INTO A NOVEL BIS-SCHIFF BASE

Metal ions present in waste samples, industrial effluents, acid mines and other aqueous media constitute a serious challenge in different human activities. Solvent extraction a technique for preconcentration, separation and identification of trace amount of metal ions coupled with multivariate chemometric technique was used for the determination of Fe(II) and Cr(III) from solutions in the presence of bis(salicylidene)ethylenediamine (SALEN). The influence of main extraction variables affecting the extraction efficiency was simultaneously studied and regression model equations illustrating the relationship between variables predicted. The extraction parameters (time of extraction, acid concentration, ligand concentration, temperature and metal concentration) were optimized using experimental designs with the contributions of the various parameters to extraction of the metal ions bound to the complexone evaluated using SPSS19.0 software. The statistically determined simulated models for the parameters were R2 = 0.946, 0.727, 0.793, 0.53, 0.53, 1.000 and F- values of 70.400, 13. 285, 15.348, 4.646 and 2.569×105 respectively for time of extraction, acid concentration, ligand concentration, temperature and metal concentration for Cr (III). For Fe (II), R2 = 0.243, 0.371, 0.519, 0.446, 1.000 and F-values of 0.964, 2.953, 4.310, 3.216 and 2.516×105 for time of extraction, acid concentration, ligand concentration, temperature and metal concentration respectively. The level of significance of the models as predicted was both lower than 5% making it feasible, efficient, reproducible and accurate. This means that metal ions at the conditions stated could be removed from waste samples, industrial effluents, acid mines and other aqueous media with extension in industrial scale application.

Chromatographic analysis of peptidoglycan samples with the aid of a chemometric technique: introducing a novel analytical procedure to classify bacterial cell wall collection

The present work introduces a simple analytical procedure using self-organising map (SOM) analysis to analyse the large number of complex chromatographic data sets from bacterial peptidoglycan samples.

Spatial Variation and Possible Sources Assessment at Federal Territory of Kuala Lumpur Water Treatment Plan Using Chemometric Technique

This study aims to identify the possible sources in drinking water parameters heavy metal and organic parameters (HMOPs) and spatial variation between untreated water and treated water at Federal Territory of Kuala Lumpur water treatment plant. The indicator HMOPs in drinking water in Kuala Lumpur were selected as parameters to discriminate the possible source of water treatment plants (WTPs) pollutant. Chemometric technique such as principal component analysis (PCA) and discriminant analysis (DA) was identified based on the five years’ availability data starting from 2012 to 2016. PCA were used to identify the most significant parameters which are highlighted eleven strong factors loading of parameter respectively out of sixteen for PCs and classified as possible sources in WTPs. Continue with DA analysis that is successful distinguish two categories region in WTP using the forward stepwise and backward stepwise with significant amount is 98.46%. From this study, we can conclude that this chemometric is the best technique of analysis to get a lot of information such as identify possible sources of pollutant and discriminant of two station sampling categories that will give novelty to Malaysian Ministry of Health (MOH) and collaboration agency in National Drinking Water Quality Surveillances Program (NDWQSP).

Pattern Recognition of Melaleuca cajuputi Powell Essential Oils Fingerprint in Terengganu, Malaysia Using Chemometric Approach

Cajuputi essential oil is extracted from the leaves of Melaleuca cajuputi Powell. This study is performed to spatially classify the variation of Melaleuca cajuputi essential oil fingerprint based on different sampling location using chemometric technique along Terengganu coastal area. Discriminant Analysis (DA) successfully discriminate 10 fingerprint of essential oil into three different groups with three significant peaks in FTIR analysis. Hierarchical agglomerative cluster analysis (HACA) successfully grouped the 10 sampling stations into three groups (cluster A, B and C).Classification criteria is based on the intensity movement of functional group either bending or stretching of the essential oil compound Multiple linear regression (MLR) was used to develop an equation model that explains the prediction of species fingerprint in each cluster by different locations.

Spatial Assessment of Selangor, Malaysia Water Treatment Plant Performance Using Chemometric Technique

This study aims to identify the most significant parameters in drinking water quality, spatial disparities of treated water (TW) and performance of water treatment plant (WTP) in Selangor. Physico- chemical (PCPs), Inorganic (IPs), Heavy metal and organic (HMOPs) and pesticide (PPs) were selected as parameters to discriminate the source of WTP pollutant. Chemometric technique such as principle component analysis (PCA), one-way analysis of variance (ANOVA) and discriminant analysis (DA) was applied to validate the performance of water treatment plant. PCA identified the most significant parameters which are highlighted six out of eight parameters for PCPs, six out of twelve parameters for IPs, nine out of sixteen parameters for HMOPs and all seventh parameters for PP. ANOVA for distinguish two categories region in WTP and showed both of PCPs and IPs had significant differences due to their concentration (p < 0.5) and HMOPs suggested fifth of significant differences within regions (p < 0.05). PP doesn’t give any significant differences (p > 0.05). DA was suggested PCPs, IPs and HMOPs in good performance (76.96%, 91.90% and 93.27%) except PP (50.43%). We can conclude that this chemometric technique can expose which area of WTP need to be properly maintains their performance to produce high quality of drinking water.