Carlos E. Boschetti

Multiple response optimization of styrene-butadiene rubber emulsion polymerization

Abstract A multiple response optimization of styrene–butadiene rubber (SBR) emulsion batch polymerization is proposed. Several properties of latex and rubber were optimized to obtain a particular grade of SBR, namely 1712. Artificial neural networks (ANNs) were employed for the modelling of the following properties: solid content of latex, Mooney viscosity and polydispersity. The training was done by feeding the ANNs with experimental data obtained from a central composite design in which the concentration of some of the polymerization reagents (initiator, activator and chain transfer agent) was varied. The one-dimensional desirability function was used for optimization, in order to obtain a single set of reaction conditions for the multiple responses. With optimum conditions, polymerization experiments were carried out and good agreement was found between predicted and experimental values of the required properties.

Screening of oil samples on the basis of excitation-emission room-temperature phosphorescence data and multiway chemometric techniques. Introducing the second-order advantage in a classification study.

Room-temperature phosphorescence excitation-emission matrices and multiway methods have been analyzed as potential tools for screening oil samples, based on full matrix information for polyaromatic hydrocarbons. Crude oils obtained from different sources of similar geographic origin, as well as light and heavy lubricating oils, were analyzed. The room-temperature phosphorescence matrix signals were processed by applying multilayer perceptron artificial neural networks, parallel factor analysis coupled to linear discriminant analysis, discriminant unfolded partial least-squares, and discriminant multidimensional partial least-squares (DN-PLS). The ability of the latter algorithm to classify the investigated oils into four categories is demonstrated. In addition, the combination of DN-PLS with residual bilinearization allows for a proper classification of oils containing unsuspected compounds not present in the training sample set. This second-order advantage concept is applied to a classification study for the first time. The employed approach is fast, avoids the use of laborious chromatographic analysis, and is relevant for oil characterization, identification, and determination of accidental spill sources.

A new genetic algorithm applied to the near infrared analysis of gasolines

A new genetic algorithm is presented for sensor selection, in order to predict the octane number and the content of benzene, toluene and total aromatics in gasolines, based on partial least squares multivariate calibration of near infrared spectral data. The algorithm separately labels each of the selected wavenumber ranges with a relative inclusion ranking. Relative prediction errors (% of root mean square error with respect to the mean calibration value) achieved after sensor selection are: octane number, 0.5%, benzene, 0.6%, toluene, 0.6%, and total aromatics, 1.1%. The results are compared with those provided by the spark-ignition engine fuel research method for octane number and by gas chromatography for the remaining parameters.

Net Analyte Preprocessing: A New and Versatile Multivariate Calibration Technique. Analysis of Mixtures of Rubber Antioxidants by NIR Spectroscopy

A new multivariate calibration technique called net analyte preprocessing is introduced for the study of mixtures by near infrared spectroscopy. It involves the construction of a space spanned by all sources of variability except one component (or reference property). Both the data matrix and the unknown sample spectrum are preprocessed through a projection orthogonal to the latter space, yielding a set of net analyte signals appropriate for quantifying a particular mixture component. The construction of the net analyte space is carried out using a certain number of spectral factors, which can be estimated by cross-validation. Advantages of the presently discussed method include the estimation of figures of merit (sensitivity, selectivity and limit of determination) and the presentation of data in a useful pseudounivariate mode. An example involving the successful analysis of mixtures of the two rubber antioxidants tris-(nonylphenyl)-phosphite and 4,6-bis-(octylthiomethyl)-o-cresol is described, and compared with classical techniques such as principal component regression and partial least-squares.

Near-infrared spectroscopic determination of antioxidants and organic acids in rubbers assisted by a new multivariate calibration method based on direct orthogonalization

A newly introduced multivariate calibration method combining direct orthogonalization and classical least-squares is optimized and applied to the determination of the content of antioxidants and organic acids in rubber by near-infrared spectroscopy. A large calibration set was built for rubbers having varying values of the target parameters, which were previously determined by reference techniques. The results obtained for a validation set were compared with those rendered by partial least-squares, including several spectral pretreatment procedures.

Influence of empty space and internal stresses on dielectric strength in two-phase polymer

In the present work, a study on the dependence of the Dielectric Strength (DS) as a function of the empty space and the internal stresses into polymer samples has been performed. The empty space was measured by means of positron annihilation lifetime spectroscopy. The internal stresses into the polymer matrix, due to the appearance of the crystalline zones, were determined by applying the inclusion theory results to the dynamic mechanical analysis measurements. Attention to the effect of the chain movement on the electrical breakdown process has been paid. The study has been performed at a mesoscopic scale with the aim of demonstrating the influence of the thermal, mechanical or electrical stresses on the chains movement and their effect on the dielectric breakdown phenomenon. It has been verified that, DS is a function of the empty space into the sample and also of the internal stresses acting at the polymer chains, which result from the crystalline state promoted by chemicrystallization. The empty space decrease and the internal stresses act overlapped against the electrical force operating on the polymer chains. It is deduced from the work, that the precursor phenomenon for the electrical breakdown is the bend of polymer chains, prior to the onset of their collective movement promoted by the electrical forces.

Synthesis and elastase inhibitory activity of 6α-chloro-2,2-dimethyl-3α-(pivaloyloxy)methylpenam sulfone, 6α-chloro-2,2-dimethyl-3-exo-methylenepenam sulfone, benzyl and methyl 6α-substituted penicillanate sulfones

The triflates and pivalates of 3 alpha-hydroxymethyl-6-substituted-2,2-dimethylpenam sulfones 3, 5; methyl and benzyl 6-substituted penicillanates 6-9 and 3-exo-methylene-6-substituted-2,2-dimethylpenam sulfone 4 were synthesized. These novel compounds were evaluated as elastase inhibitors using porcine pancreatic elastase. The effects that structural modifications of substituents on C-3 and C-6 in the penam nucleus have on elastase activity were examined and several similarities and distinctions were identified when compared to the reported penicillin esters and amides elastase inhibitors.

Synthesis and porcine pancreatic elastase inhibitory evaluation of 6α-(sulfonyl)oxy-and 6α-chloropenicillanate sulfone esters and 3α-(acyloxy)methyl-6α-chloropenam sulfones

Abstract The synthesis of 6α-chloropenicillanate sulfone esters 4a-c, 9, the acetate and benzoate of 3α-hydroxymethyl-6α-chloropenam sulfones 6a-b and pivaloyloxymethyl and benzyl esters of several 6α-(sulfonyl)oxypenicillanate sulfones 12, 15a1-a3, 15b1-b3 are reported. When tested as inhibitors of porcine pancreatic elastase, the acetate of 3α-hydroxymethylpenam 6a proved to be more active in comparison with the esters of 3α-carboxylic acid counterparts 4a-c and 9. Compounds with diverse 6α-(sulfonyl)oxy substituents showed elastase inhibitory activity improved over the corresponding 6α-chloro derivatives 4a-c and 9; among those, compounds 15a2 and 15b2 were rather unstable, but compounds 15a1, 15a3, 15b1, 15b3 combined fair activity with better stability.

Optimization of Environmentally Benign Polymers Based on Thymine and Polyvinyl Sulfonate Using Plackett-Burman Design and Surface Response

Traditional approaches to the development of integrated circuits involve the use and/or manufacture of toxic materials that have a potential environmental impact. An extensive research has been done to design environmentally benign synthetic polymers containing nucleic acid bases, which can be used to enhance the photoresistor technologies. Water soluble, environmentally benign photopolymers of 1-(4-vinylbenzyl) thymine (VBT) and vinylphenyl sufonate (VPS) undergo a photodimerization reaction when exposed to low levels of ultraviolet irradiation leading to an immobilization of the copolymer on a variety of substrates. Plackett-Burman design (PBD) and central composite design (CCD) were applied to identify the significant factors influencing the polymer crosslinking and dye adsorption processes, which are relevant in the fabrication of copolymer films for potential photoresist use. The PBD results assigned a maximum absorption signal of 0.67, while optimal conditions obtained in this experiment following the CCD method predictions provided a response of 0.83 ± 0.03, being a solid foundation for further use of this methodology in the production of potential photoresistors. The pH effect was relevant for low concentrations but not significant for higher concentrations. To the best of our knowledge, this was the first report applying statistical experimental designs to optimize the crosslinking of thymine-based polymers.

Thymine based copolymers: feasible sensors for the detection of persistent organic pollutants in water

Polycyclic Aromatic Hydrocarbons (PAHs) are among the main persistent organic pollutants in water, because they can cause serious diseases in living organisms. The PAHs trace levels in environmental samples makes their detection particularly difficult. The development of new fluorescence spectroscopic sensors is a realistic alternative for the quantification of PAHs at very low concentrations. Bio-inspired copolymers based on thymine and charged groups showed high affinity for benzo[a]pyrene, the nastiest contaminant of the PAHs group, and can be used to enhance their native luminescence. In the present work we rationalized the observed experimental evidence using a theoretical model that studies the plausible non-covalent interactions (polar hydrogen–π, π–π “stacking”, etc.) between these compounds, in order to make a realistic design of new thymine-based copolymers sensors.