Samples Of Unknown Composition Research Articles

Efficient chemiluminescence of luminol in the presence of hemin without added hydrogen peroxide†.

The results reported herein demonstrate for the first time that typical reducing agents in an alkaline medium initiate chemiluminescence of luminol in the presence of hemin, and the efficiency of their action is comparable to that of hydrogen peroxide and exceeds it in the case of the superoxide anion. The pertinent implications of these findings refer to new possibilities for developing chemiluminescence assays and biosensors and to precautions for determining hydrogen peroxide using luminol and hemin in samples of unknown composition, most prominently, of biological origin.

Impact of emissions into the atmospheric air of a sewage sludge incineration plant on public health

Introduction. Urban wastewater sludge (UWS) is an important by-product of traditional urban wastewater treatment. Incineration is considered the most effective and universal method of reducing the volume of a large amount of UWS and their disinfection. However, the situation in the areas where the USW incineration plants are located, as a result of the pyrolytic process products entering the atmospheric air, creates complete uncertainty and unpredictability of the development of events that can lead in certain situations to the formation of an additional risk to public health. The purpose of the study. Hygienic characteristics of wastewater sludge incineration technology based on indicators of atmospheric air pollution and the magnitude of the risk to the health of the population living in the zone of influence of the implemented technology. Materials and methods. At the first stage, the analysis of the information presented in the international databases PubMed, Scopus, and PRINCE was carried out. Based on the results of the analysis, a list of chemical compounds was formed to identify the qualitative composition and determine the amount of pollutants in industrial emissions into the atmospheric air during the implementation of wastewater sludge incineration technology. Sanitary and chemical studies of industrial emissions into the atmospheric air were carried out by the chemical analytical center “Arbitration” of the D.I. Mendeleev Institute for Metrology. Modern high-precision analytical methods have been used to identify and quantify priority atmospheric pollutants. Results. Industrial emissions samples laboratory studies were carried out. Measurement results analysis showed that the indicators of quantitative emissions of harmful (polluting) substances do not exceed the international regulations requirements, most are below the detection limit, and the calculated concentrations do not exceed hygienic standards. The assessment of carcinogenic health risk are determined as acceptable, the probability of developing diseases additional cases from exposure to all the studied carcinogens throughout life in the population permanently residing in the territory in the area of the enterprise location is assessed as insignificant (less than one case). Limitations. In this study, there was a limitation associated with the method for determining concentrations of substances detection limit, which, nevertheless, satisfies the purpose of the study. Since a sample of unknown composition was taken, the entire possible substances spectrum in the emissions was evaluated. Substances with a carcinogenic effect were present in the emissions, but only those substances that had a carcinogenic potential factor were included in the carcinogenic risk assessment.

Supervised topic modeling for predicting molecular substructure from mass spectrometry

Small-molecule metabolites are principal actors in myriad phenomena across biochemistry and serve as an important source of biomarkers and drug candidates. Given a sample of unknown composition, identifying the metabolites present is difficult given the large number of small molecules both known and yet to be discovered. Even for biofluids such as human blood, building reliable ways of identifying biomarkers is challenging. A workhorse method for characterizing individual molecules in such untargeted metabolomics studies is tandem mass spectrometry (MS/MS). MS/MS spectra provide rich information about chemical composition. However, structural characterization from spectra corresponding to unknown molecules remains a bottleneck in metabolomics. Current methods often rely on matching to pre-existing databases in one form or another. Here we develop a preprocessing scheme and supervised topic modeling approach to identify modular groups of spectrum fragments and neutral losses corresponding to chemical substructures using labeled latent Dirichlet allocation (LLDA) to map spectrum features to known chemical structures. These structures appear in new unknown spectra and can be predicted. We find that LLDA is an interpretable and reliable method for structure prediction from MS/MS spectra. Specifically, the LLDA approach has the following advantages: (a) molecular topics are interpretable; (b) A practitioner can select any set of chemical structure labels relevant to their problem; (c ) LLDA performs well and can exceed the performance of other methods in predicting substructures in novel contexts.

Calibration Standard Samples for Multielement Analysis of Silicate Rocks Using Inductively Coupled Plasma Mass Spectrometry with Laser Ablation

A comparison of different standard samples—artificial glass SRM-612 (Standard Reference Material) and standard samples of natural composition SG-1A, SG-3, ST-1A, and SGD-1A—used for external calibration in the elemental analysis of silicate rocks in the form of fused glasses by inductively coupled plasma mass spectrometry and laser ablation (LA-ICP-MS) is carried out with a goal of selecting the most suitable samples for plotting the calibration dependence upon determination of the major and trace elements when using LA-ICP-MS for routine analysis. The results showed that the error of determination for both major and trace elements is lower (compared to SRM-612) when external calibration is carried out using the reference materials of natural composition with Si and Fe contents close to those in the analyzed samples. The use of internal standards in both cases decreases the systematic error attributed to the drift of LA parameters and different ablation yields. The correctness of the determination of 28 elements is proved in comparison of the results of the analysis of four standard samples with the reference values. The obtained results are used to select calibration standards for LA-ICP-MS analysis of the samples of unknown composition. The results of analysis of six samples of unknown composition match within the error limit the results of X-ray fluorescence analysis (major elements) and ICP-MS (trace elements in solutions). Refining of the content of trace elements in the previously certified reference materials allows them to be used for calibration in routine analysis of geological rocks. The developed LA-ICP-MS technique is a rapid method for determination of a wide range of elements, in particular, rare earth elements, in silicate rocks and can be used for routine analysis without additional sample preparation after X-ray fluorescence analysis.

Calibration standard samples for multi-element analysis of silicate rocks using inductively coupled plasma — mass spectrometry with laser ablation

A comparison of different standard samples — artificial glass SRM-612 (Standard Reference Material) and standard samples of natural composition SG-1A, SG-3, ST-1A and SGD-1A — used for external calibration in the elemental analysis of silicate rocks in the form of fused glasses by inductively coupled plasma mass spectrometry and laser ablation (LA-ICP-MS) is carried out with a goal of selecting the most suitable samples for plotting calibration dependence upon determination of the major and trace elements when using LA-ICP-MS for routine analysis. The results showed that the error of determination for both major and trace elements is lower (compared to SRM-612) when external calibration is carried out using the reference materials of natural composition with Si and Fe contents close to those in the analyzed samples. The use of internal standards in both cases decreases the systematic error attributed to the drift of LA parameters and different ablation yields. The correctness of the determination of 28 elements is proved in comparison of the results of the analysis of four standard samples with the reference values. The obtained results are used to select calibration standards for LA-ICP-MS analysis of the samples of unknown composition. The results of analysis of six samples of unknown composition match to the error limit the results of X-ray fluorescence analysis (major elements) and ICP-MS (trace elements in solutions). Refining of the content of trace elements in the previously certified reference materials allows them to be used for calibration in routine analysis of geological rocks. The developed LA-ISP-MS technique is a rapid method for determination of a wide range of elements, in particular rare earth elements, in silicate rocks and can be used for routine analysis without additional sample preparation after X-ray fluorescence analysis.

Preparation and Characterization of Protocatechuic Acid Sulfates.

Protocatechuic acid (3,4-dihydroxybenzoic acid; PCA) is a phenolic acid present in plants as a secondary metabolite and is also produced in the human organism as a metabolite from the degradation of polyphenols by the intestinal microbiota, particularly of flavonoids. However, PCA, like most polyphenols, is biotransformed in the human body to different conjugates as sulfates, which are found circulating in blood and could be involved in the bioactivity of the original compound. This paper describes a simple process for the preparation of PCA monosulfates with satisfactory yields. Two compounds were obtained that were identified as PCA-3-sulfate and PCA-4-sulfate by mass spectrometry and 1H and 13C nuclear magnetic resonance using one- and two-dimensional techniques (heteronuclear single-quantum coherence and heteronuclear multiple-bond correlation). Differential MS fragmentation behavior and UV spectra were observed for each compound, which could be used for their identification in samples of unknown composition. The described procedure can be used for the preparation of these polyphenol metabolites in view of their use in in vivo and in vitro studies, as well as standards for their analysis in biological fluids, to contribute to the elucidation of biological effects of dietary polyphenols.

Transmission of 155Eu lines: a quick method to create efficiencies for gamma spectroscopy estimating sample self-absorption at low energy

A method is presented to obtain efficiency calibration for samples of unknown composition in gamma spectrometry. It is based on photon transmission measurements using 155Eu, a multi-energetic gamma emitter. An iterative algorithm produces a virtual chemical composition reproducing the measured sample self-absorption in the range 43–146 keV. The composition is then used to numerically create a sample-specific efficiency calibration. The procedure was tested with IAEA certified sediment materials containing 210Pb, 241Am, 155Eu, and 226Ra. The deviation from certified values ranged between 3 and 22%, within the range of experimental uncertainty (between 5 and 35%, due to low isotope concentrations).

Determination of the effective atomic number of thick samples of unknown composition using scattering studies

The effective atomic number ( $ Z_{\rm eff}$ is a quantity which gives the fraction of the total number of electrons in a composite material participating in the photon-atom interaction. The effective atomic number has been determined for the materials of known composition by using different methods. However, no method has been reported so far to determine $ Z_{\rm eff}$ for thick samples of unknown composition. In view of this, we have evolved a simple method to determine the effective atomic number, which uses the scattering intensity ratios measured at two scattering angles, in which a sample of known $ Z_{\rm eff}$ or Z is taken as a reference sample. The values of $ Z_{\rm eff}$ obtained by this method agree with those obtained from the Auto-Zeff software within the stated errors. This method could be helpful in determining the effective atomic number of samples of unknown composition.

Analytical pyrolysis of proteins in samples from artistic and archaeological objects

The paper presents a study of proteins found in artistic and archaeological objects based on analytical pyrolysis. Proteins (mainly egg yolk and/or egg white, casein, animal glue and collagen) have been extensively used as paint binders, adhesives and varnishes in mural and easel paintings, and they can be found in archaeological findings, such as bones and skin tissues. In order to overcome limitations of wet chemical methods arising from the reduced solubility of aged proteins in samples of cultural heritage, a combination of analytical pyrolysis techniques was used to characterise reference materials, paint reconstructions and samples from different historical periods (2nd century BC-20th century AD) and geographical origins, which were collected from paintings and archaeological findings. In particular evolved gas analysis mass spectrometry (EGA/MS), pyrolysis coupled with gas chromatography/mass spectrometry (Py/GC/MS) and double shot pyrolysis/gas chromatography/mass spectrometry (DSP/GC/MS) were used. This analytical approach allowed us to characterise and differentiate the proteinaceous media, investigate their thermal behaviour and evidence changes occurring with ageing. Data clearly indicate that egg, casein and animal glue can be identified and distinguished in a sample of unknown composition using each of the analytical pyrolysis techniques used. With time though differences tend to disappear to the extent that extremely degraded samples present pyrolytic profiles extremely similar to each other, irrespective of the nature of the proteins present. The data also indicate that proteins tend to become more thermally stable with ageing, suggesting that extensive intramolecular and intermolecular aggregation, and/or covalent cross-linking occur with time.

Gamma-Spectrometric Determination of the Content and the Mass of Uranium Isotopes in Samples of Unknown Composition and Products of the Nuclear Fuel Cycle

The results of the uranium isotopes masses and content determination in depleted and low enriched uranium bearing samples using gamma-spectrometric data and iterative method were presented in the paper. Powders of UO2 and U3O8, compact products on their basis, metal uranium and scrap with an enrichment by the isotope 235U from 0,3 to 19,9 % were used as test samples. The sample mass ranged from tens of grams to several kilograms. Gamma-spectrometric data were processed using commercial software packages by Canberra Company: Genie 2000, MGAU, ISOCS and GeometryComposer. The proposed method provides a satisfactory correlation between the experimental and calculated data and allows estimating the quantitative characteristics (enrichment, mass of isotopes, uranium content in the matrix) of uranium bearing samples with different physical shape and chemical composition.

Neural network-random generation approach to analyze X-ray fluorescence spectra

Application of a feed-forward multilayer perceptron neural network to analyze X-ray fluorescence spectra of a compound material is investigated. For this purpose, a general approach is proposed to improve the learning process of the neural network. In this approach, randomly generated composite spectra are constructed from the set of reference spectra corresponding to the pure elements which compose the material. Instead of taking the spectrum as a whole, the input parameters of the neural network arereduced to the neighboring bins of each pure element peak. Bytesting themethodon the spectra of materials made of Ca, Fe, Ni and Cu elements, we obtained an efficiency of about 95% for predicting the relative concentrations of the four elements in the material. Multivariate Data Analysis refers to any statistical technique used to analyze data that arise from more than one variable.Multivariate classification methods based on machine learning techniques have become a fundamental ingredient to most analyses. The multivariate classifiers themselves have signifi- cantly evolved in recent years. Among the multivariate classification methods, Artificial Neural Networks (ANN) are widely used in various fields. Applications range from image analysis to financial movements predictions and analysis. In (1,8) a review of applications of ANN and its potentialities in atomic and nuclear physics is shown. In high energy physic, ANNis mainly used for classification tasks such assignal over background discrimi- nation. With the search for ever smaller signals in ever larger data sets, it has become essential to extract a maximum of the available information from the data (2). ANN are also applied in other cases where strong non-lineal effects are present like in the spectral analyses generated in analytical techniques like PIXE (3) and XRF (X-ray fluorescence) (4). Several types of artificial neural network are commonly used in the practice. Among these types, we can mention the multi layer perceptrons (MLP), the radial basis function networks (RBF) and theself- organizing maps (SOM). They differ by their processing elements and bythe specific manner in which these elements are connected. The potentialities of ANN seem to be more convenient in the repetitive analysis of many spectra presenting similar patterns with specificdifferences. A typical case is presented in the elementalanalysis of samples of unknown composition using energy dispersiveXRF spectroscopy.Their respective spectra

Characterisation of oriental lacquers from Rhus succedanea and Melanorrhoea usitata using in situ pyrolysis/silylation-gas chromatography mass spectrometry

Two oriental lacquers from Rhus succedanea and Melanorrhoea usitata were characterised by Py-GC–MS with in situ silylation using HMDS. Pyrolytic markers, which were helpful in differentiating between the lacquers, were identified in their silylated forms, and the mass spectra are presented and discussed. Aliphatic and aromatic hydrocarbons were formed as well as TMS derivatives of alkylcatechols and alkylphenols, and relative characteristic pyrolytic profiles were compared for the two lacquers. The method, here applied for the first time to the characterisation of the Vietnamese and Burmese lacquers, proved successful not only in distinguishing between the two lacquers, but also in highlighting the polymerisation processes undergone by the saps in the formation of the lacquer layers.The results obtained demonstrated that in situ Py/silylation-GC–MS with using HMDS is a suitable tool for the analysis of all oriental lacquers with possible application to diagnose their presence in samples of unknown composition.

Standardless Quantification Of Actinides By EPMA

Electron probe microanalysis (EPMA) is an analysis technique used to quantify with a high accuracy the amount of elements present on a sample of unknown composition. However, for some elements, such as the actinides, quantitative EPMA is not possible to achieve due to the lack of suitable reference standard samples. To overcome this difficulty, standardless methods can be employed with the use of virtual standards. Standardless method requires the accurate knowledge of absolute characteristic x-ray intensities. These x-ray intensities can be obtained by analytical calculations or by Monte Carlo (MC) simulations with mean of physical parameters. However, these parameters are not always well known and can lead to inaccurate results when used in standardless quantification methods. Validation by experimental measurements of the calculated x-ray intensities is needed.

Universal algorithm of preparation of soil samples for determination of hazardous chemicals

Hazardous chemicals (HC) with enterprises into the soil and accumulate it. As a consequence, fertility of contaminated soil is reduced and the risk of chronic and serious diseases increases of population when using for agricultural purposes. When the chemical analysis on content of HC in soil the most time consuming is the operation of sample preparation, the implementation of which depends on availability of appropriate methodologies, and on staff qualification. To select the method of argumentation and workflow preparation of soil samples, there is developed algorithm allowing preparation of soil samples of unknown composition for analysis for presence of HC in conditions of absence of a priori information about the sample.

Gold nanorods for surface Plasmon resonance detection of mercury (II) in flow injection analysis

This article investigates the flow injection analysis of mercury (II) ions in tap water samples via surface Plasmon resonance detection. Quantitative analysis of mercury (II) is based on the chemical interaction of metallic mercury with gold nanorods immobilized on a glass substrate. A new flow cell design is presented with the ability to accommodate the detecting substrate in the sample compartment of commercial spectrometers. Two alternatives are here considered for mercury (II) detection, namely stop-flow and continuous flow injection analysis modes. The best limit of detection (2.4ngmL−1) was obtained with the continuous flow injection analysis approach. The accurate determination of mercury (II) ions in samples of unknown composition is demonstrated with a fortified tap water sample.

Comparison method to differentiate between painted objects using polychromatic X-rays

X-radiography using the bremsstrahlung of a commercial broad spectrum X-ray source was used to quantify the differences and relationships between complex samples of unknown composition. The samples examined were painted and glazed ceramic mugs. The resulting pseudo-signatures were grey-level transmission spectra which can be usefully compared over a range of acceleration potential settings from 40 to 95 kV, taken at 1 kV intervals. These data are extracted from stacks of registered field-flattened X-ray images. It is shown that it is possible to differentiate between transmission spectra of the samples by concentrating mainly on the paint layers.

Detection and identification of multiple genetically modified events using DNA insert fingerprinting

Current screening and event-specific polymerase chain reaction (PCR) assays for the detection and identification of genetically modified organisms (GMOs) in samples of unknown composition or for the detection of non-regulated GMOs have limitations, and alternative approaches are required. A transgenic DNA fingerprinting methodology using restriction enzyme digestion, adaptor ligation, and nested PCR was developed where individual GMOs are distinguished by the characteristic fingerprint pattern of the fragments generated. The inter-laboratory reproducibility of the amplified fragment sizes using different capillary electrophoresis platforms was compared, and reproducible patterns were obtained with an average difference in fragment size of 2.4 bp. DNA insert fingerprints for 12 different maize events, including two maize hybrids and one soy event, were generated that reflected the composition of the transgenic DNA constructs. Once produced, the fingerprint profiles were added to a database which can be readily exchanged and shared between laboratories. This approach should facilitate the process of GMO identification and characterization.

Gas chromatographic–mass spectrometric characterisation of plant gums in samples from painted works of art

This paper presents an analytical GC–MS procedure to study the chemical composition of plant gums, determining aldoses and uronic acids in one step. The procedure is based on the silylation of aldoses and uronic acids, released from plant gums by microwave assisted hydrolysis, and previously converted into the corresponding diethyl-dithioacetals and diethyl-dithioacetal lactones. Using this method only one peak for each compound is obtained, thus providing simple and highly reproducible chromatograms. The analytical procedure was optimised using reference samples of raw plant gums (arabic, karaya, ghatti, guar, locust bean and tragacanth, cherry, plum and peach gums), commercial watercolours and paint layers prepared according to ancient recipes at the Opificio delle Pietre Dure of Florence (Italy). To identify gum media in samples of unknown composition, a decisional schema for the gum identification and the principal component analysis of the relative sugar percentage contents were employed. The procedure was used to study samples collected from wall paintings from Macedonian tombs (4th–3rd centuries bc) and from the Mycenaean “Palace of Nestor” (13th century bc) in Pylos, Greece. The presence of carbohydrates was ascertained and plant gum binders (fruit and a mixture of tragacanth and fruit tree gums) were identified in some of the samples.

Particle induced X-ray emission – relative yield ion energy dependence, an IBA chemical speciation method

The dependence of ion induced K and L shell relative yields upon the chemical composition of the target is a well-known effect. Nevertheless, its use in applications is quite recent and needs more development. In this work, the variation of the W L X-ray spectra on incident ion beam energy is presented for three different W chemical compounds. It is shown that for thick targets, the X-ray line relative intensity dependence on the ion beam energy produces variation patterns that contain information on the chemical species composition of the target. It is further shown that each of these patterns can be made to correspond to a vector in a hyperspace, in such a way that the angle between any two of these vectors is large, an important point when aiming at the use in samples of unknown composition.

Neutron Activation Analysis of Samples of Unknown Composition

The advantages of relative analytical methods over absolute methods for calculating element concentrations have been demonstrated. A procedure for the neutron activation analysis of samples of unknown composition was proposed based on the numerical simulation of the gamma spectra of test samples.