Determination of volatile organics in gaseous phase using porous adsorbents

A novel procedure is developed for the quantitative determination of volatile organics in the gas phase over samples. Substances were extracted and preconcentrated from the gas phase on porous polymer adsorbents under the conditions of thermodynamic equilibrium, followed by back extraction from the adsorbent using organic solvents. The final monitoring was performed by capillary gas chromatography with an internal standard. The influence of adsorption time and the concentration of substances in an aqueous solution on the degree of extraction were also studied; linear correlations between the quantities of substances in the gas and aqueous phases were found. The method was used for the determination of volatile substances in the gas phase over liquid and solid matrixes of different origin.     

Partial least squares modeling and genetic algorithm optimization in quantitative structure-activity relationships

Quantitative structure-activity relationship (QSAR) studies based on chemometric techniques are reviewed. Partial least squares (PLS) is introduced as a novel robust method to replace classical methods such as multiple linear regression (MLR). Advantages of PLS compared to MLR are illustrated with typical applications. Genetic algorithm (GA) is a novel optimization technique which can be used as a search engine in variable selection. A novel hybrid approach comprising GA and PLS for variable selection developed in our group (GAPLS) is described. The more advanced method for comparative molecular field analysis (CoMFA) modeling called GA-based region selection (GARGS) is described as well. Applications of GAPLS and GARGS to QSAR and 3D-QSAR problems are shown with some representative examples. GA can be hybridized with nonlinear modeling methods such as artificial neural networks (ANN) for providing useful tools in chemometric and QSAR.     

A computer program for use in quantitative electron probe microanalysis

Summary A computer program for use in the conversion of electron probe X-ray intensity ratios into chemical compositions has been written. The inclusion of several of the more successful correction procedures facilitates the comparison of these procedures and allows an investigator to select the correction procedure which will give the best results for the system being studied. Theoretical calibration calculations of the intensity ratio versus composition can be performed and these results can be plotted by machine. The program has been designed to be as versatile as possible and still retain simple experimental input requirements. Some results obtained using recently published correction procedure are discussed.

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Zusammenfassung Ein Computerprogramm wurde geschrieben, um Intensitätsverhältnisse der Elektronenstrahlmikroanalyse in chemische Zusammensetzungen umzurechnen. Die Einfügung einiger besonders erfolgversprechender Korrekturverfahren erleichtert den Vergleich dieser Verfahren und ermöglicht dem Bearbeiter, jenes Korrekturverfahren auszuwählen, das für das eben untersuchte System die besten Ergebnisse liefert. Die theoretischen Berechnungen des Intensitätsverhältnisses in Abhängigkeit von der Zusammensetzung können als Eichung durchgeführt werden und diese Ergebnisse kann die Maschine ausdrucken. Das Programm wurde so vielseitig wie möglich erstellt, beinhaltet aber dennoch einfache experimentelle Eingabemöglichkeiten. Einige Ergebnisse, die durch den Gebrauch kürzlich veröffentlichter Korrekturverfahren erhalten wurden, werden diskutiert.

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Résumé Un programme d'ordinateur servant à convertir les rapports d'intensité de rayons X de sonde électronique en compositions chimiques a été rédigé. L'inclusion de plusieurs procédures de correction parmi celles qui ont obtenu le plus de succès facilite la comparaison de ces procédures et permet à l'investigateur de choisir la procédure de correction qui, à son avis, donnera les meilleurs résultats pour lè système étudié. Des calculs théoriques de calibrage entre le rapport d'intensité et la composition peuvent être faits et ces résultats peuvent être rapportés sur graphique mécaniquement. De par sa conception, le programme jouit du maximum de souplesse tout en gardant le plus de simplicité possible aux données expérimentales nécessaires à l'entrée. Certains résultats obtenus à l'aide de procédures de correction récemment publiés, font l'objet de discussions.

     

A colorimetric sensor array for organics in water

Molecular recognition of organic compounds in aqueous solutions is inherently challenging due to the potential interference from the very high concentration of water. Here we present a simple colorimetric sensor array that probes a wide range of chemical properties. By printing hydrophobic dyes on a hydrophobic membrane, sensor arrays are easily prepared that provide substantial chemical selectivity for the identification and quantification of various organics (both single compounds and complex mixtures) dissolved in water. It is possible to differentiate easily even among closely related organic compounds. Upon immersion in aqueous solutions, digital imaging of the dye array before and after exposure to an analyte provide a color change profile that is a fingerprint for the organic components of the solution. Facile identification of a wide variety of aqueous organic solutions is possible over a concentration range of 0.1 M to 1 muM. Complex mixtures present no inherent difficulty; for example, a series of commercial soft drinks were easily distinguished using the colorimetric sensor array approach.     

Challenges in quantitative analyses for volatile organic compounds bound to lipocalins

In this communication, I describe the challenges in quantitative analyses for volatile organic compounds in mouse urine, which are primarily caused by the presence of the major urinary proteins, a lipocalin subfamily, that sequester volatile ligands. The analyses of volatile compounds in mouse urine have been performed since the late 1970s. However, none of them considered the binding interactions of the quantified compounds with the urinary proteins. Some volatile ligands are tightly bound to the proteins and may not be extracted completely by organic solvents. The amounts of volatile ligands measured by external standard calibration represent those of the unbound ligands in the headspace, not the total amounts in urine. Addition of internal standards displaces ligands bound to the proteins, resulting in a completely different volatile profile. Normalization of volatile compounds using relative peak area (or height) ratios may not be used in the conditions where displacement of ligands bound to the proteins occurs. Because of the unique chemical properties of mouse urine, I have not been able to find a good quantification method for the volatile compounds released from mouse urine. I hope that the identification of these issues will stimulate others to come up with novel approaches.     

Acuchem: A computer program for modeling complex chemical reaction systems

Acuchem is a program for solving the system of differential equations describing the temporal behavior of spatially homogeneous, isothermal, multicomponent chemical reaction systems. It is designed to provide modelers, data evaluators, and laboratory scientists with an easy to use program for modeling complex chemical reactions, and for presenting the results in tabular or graphical form. The program is described and some examples of its application given. Acuchem is designed to operate on the IBM Personal Computer family and other compatible microcomputers, and is available in a compiled version on a floppy disk.     

Determination of volatile organics in drinking water with USEPA method 524.2 and the ion trap detector

New drinking water regulations require the monitoring of eight volatile organic compounds that have established maximum contaminant levels (MCLs) and 51 other volatile organics for which MCLs are not established. A laboratory analytical method (Method 524.2) for the determination of 58 of these compounds is investigated, and precision and accuracy data are obtained. The method uses a standard inert gas purge extraction, isolation of the volatile organics on a three-stage solid-phase trap, thermal desorption into a gas chromatograph, separation with a fused-silica capillary column, and identification and measurement with a relatively low cost, benchtop ion trap detector that functions as a mass spectrometer. At a concentration of 2 micrograms/L (2 parts per billion), the grand mean measurement accuracy for 54 compounds was 95% of the true value with a mean relative standard deviation (RSD) of 4%. At 0.2 micrograms/L (200 parts per trillion), the grand mean measurement accuracy for 52 compounds was 95% of the true value with a mean RSD of 3%.     

A stoichiometric approach to quantitative structure-property relationships (QSPR)

An unusual analogy between the quantitative structure-property relationships (QSPR), stoichiometry, chemical thermodynamics, and kinetics is presented. Namely, the conventional ordinary least-squares (OLS) QSPR analysis is modified so as to explicitly minimize the residuals of the species subject to a set of linear relations among the residuals. The ways the linear relations among the residuals are visualized and defined totally resemble the formalism of chemical stoichiometry and, therefore, were called isostructural reactions. It is further proved that the residuals may be uniquely partitioned into a sum of contributions associated with a set of isostructural reactions that have the same properties as the response reactions (RERs) previously deduced by us from chemical thermodynamics and kinetics. This finding is shown to be a useful tool for a deeper understanding of the QSPR. In particular, the isostructural RERs approach may be effectively used to detect the outliers.     

A rapid spreadsheet method for the estimation of dead time

Summary A method has been developed for the rapid estimation of chromatographic column dead time. This utilises a commercial spreadsheet running on a Personal Computer, allowing automated dead time calculation in less than 30 seconds. Retention data from the literature have been used to illustrate the accuracy of this carbon number method. The method was also validated by using GC retention data experimentally recorded during this work.     

Development of a graphic program for quantitative drug design

A graphic program for quantitative drug design is described; it is used for the design stage of candidate compounds after a regression equation has been established for estimation of biological potencies in the Hansch—Fujita and Free—Wilson methods. Information flow is controlled by function-key and concomitant alphanumeric-key operations. In the program, substituents are easily introduced into a parent structure, and a perspective molecular model of the resulting derivative is displayed. Conformational changes of a molecule can be followed by rotating atomic groups. The data bank contains 337 possible substituents with 20 physicochemical parameter values and constituent atomic coordinates for each substituent. Examples are shown to illustrate the program.     

Concentration and analysis of trace volatile organics in gases and biological fluids with a new solid adsorbent

Summary A new procedure for sampling, transfer, and analysis of volatile organic compounds by gas chromatography has been developed. An adsorbent trap ultimately becomes an insert for a modified injector port, and a valve system allows the sample to be transferred to a cooled precolumn and finally to the separating column. Several traps may be used for sampling (for multiple injections), and it has been established that such traps may be stored without loss of sample. The ease and reproducibility of this procedure is amenable for the investigation of volatile organic compounds involving air and water pollution, flavor, and aroma analyses, and body fluid metabolites.     

Atomic charge calculations for quantitative structure—property relationships

A previously published empirical charge scheme has been adapted for use in studies of quantitative structure-property relationships. New parameters have been developed to allow the inclusion of nitrates, nitriles, sulfides, thiols, thiophenes, and sulfoxides. No changes have been made to the original scheme, thus preserving all previous results. A few simple additions to the program have made it possible to calculate atomic charges in a variety of ionic structures containing a formally positive nitrogen or a formally negative oxygen. The results obtained for ions are consistent with a number of concepts surrounding the familiar inductive and resonance effects.     

Solid phase microextraction for the determination of volatile organics in the foliage of Fraser fir (Abies fraseri)

Solid phase micro extraction (SPME) was investigated for the determination of volatile chemicals in the foliage of Fraser fir (Abies fraseri). Advantages of SPME include its speed, sensitivity, and ability to determine volatiles without chemical solvents. In this study, qualitative comparisons were performed of the volatiles emitted from living foliage (in situ), damaged living foliage (in situ damaged), and severed foliage (ex situ). These studies suggest that β-phellandrene and γ-terpinene may be emitted as a response to foliar injury. Comparisons were made of the volatiles collected by SPME with ex situ sampling to previous studies in our laboratory using methylene chloride extraction. Similar results were obtained by the two extraction methods.     

A Monte Carlo approach for estimating measurement uncertainty using standard spreadsheet software

Despite the importance of stating the measurement uncertainty in chemical analysis, concepts are still not widely applied by the broader scientific community. The Guide to the expression of uncertainty in measurement approves the use of both the partial derivative approach and the Monte Carlo approach. There are two limitations to the partial derivative approach. Firstly, it involves the computation of first-order derivatives of each component of the output quantity. This requires some mathematical skills and can be tedious if the mathematical model is complex. Secondly, it is not able to predict the probability distribution of the output quantity accurately if the input quantities are not normally distributed. Knowledge of the probability distribution is essential to determine the coverage interval. The Monte Carlo approach performs random sampling from probability distributions of the input quantities; hence, there is no need to compute first-order derivatives. In addition, it gives the probability density function of the output quantity as the end result, from which the coverage interval can be determined. Here we demonstrate how the Monte Carlo approach can be easily implemented to estimate measurement uncertainty using a standard spreadsheet software program such as Microsoft Excel. It is our aim to provide the analytical community with a tool to estimate measurement uncertainty using software that is already widely available and that is so simple to apply that it can even be used by students with basic computer skills and minimal mathematical knowledge.