11 resultados para Non-isothermal method
em Universidade Federal do Rio Grande do Norte(UFRN)
Resumo:
The trioxsalen (Tri) is a low-dose drug used in the treatment of psoriasis and other skin diseases. The aim of the study was applying the thermal analysis and complementary techniques for characterization, evaluation of the trioxsalen stability and components of manipulated pharmaceutical formulations. The thermal behavior of the Tri by TG/DTG-DTA in dynamic atmosphere of synthetic air and nitrogen showed the same profile with a melting peak followed by a volatilization-related event. From the curves TG / DTG is observed a single stage of mass loss. By heating the drug in the stove at temperatures of 80, 240 and 260 °C, it had no change in chemical structure through the techniques of XRD, HPLC, MIR, OM and SEM. From the non-isothermal and isothermal TG kinetic studies was possible to calculate the activation energy and reaction order for the Tri. The drug showed good thermal stability. Studies on drug-excipient compatibility showed interaction of trissoralen with sodium lauryl sulfate 1:1. There was no interaction with aerosol, pregelatinized starch, sodium starch glycolate, cellulose, croscarmellose sodium, magnesium stearate, lactose and mannitol.The characterization of three trioxsalen formulations at concentrations of 2.5, 5, 7.5, 10, 12.5 and 15 mg was performed by DSC, TG / DTG, XRD, NIR and MIR. The PCA classification method based on spectral data from the NIR and MIR of trissoralen formulations allows successful differentiation into three groups. The formulation 3 was the one that best showed analytical profile with the following composition of aerosil excipients, pre-gelatinized starch and cellulose. The activation energy of the volatilization process of the drug was determined in binary mixtures and formulation 3 through fitting and isoconversional methods. The binary mixture with sodium starch glycolate and lactose showed differences in kinetic parameters compared to the drug isolated. The thermoanalytical techniques (DSC and TG / DTG) were shown to be promising methodologies for quantifying trioxsalen obtained by the linearity, selectivity, no use solvents, without sample preparation, speed and practicality.
Resumo:
In this work have been studied the preparation, characterization and kinetic study of decomposition of the polymerizing agent used in the synthesis under non-isothermal condition ceramics PrMO3 of general formula (M = Co and Ni). These materials were obtained starting from the respective metal nitrates, as a cations source, and making use of gelatin as polymerizing agent. The powders were calcined at temperatures of 500°C, 700°C and 900°C and characterized by X-ray Diffraction (XRD), Thermogravimetric Analysis (TG / DTG/ DTA), Infrared Spectroscopy (FTIR), Temperature Programmed Reduction (TPR) and Scanning Electron Microscopy (SEM). The perovskite phase was detected in all the X-rays patterns. In the infrared spectroscopy observed the oxide formation as the calcination temperature increases with the appearance of the band metal - oxygen. The images of SEM revealed uniform distribution for the PrCoO3 and particles agglomerated as consequence of particle size for PrNiO3. From the data of thermal analysis, the kinetics of decomposition of organic matter was employed using the kinetics methods called Model Free Kinetics and Flynn and Wall, in the heating ratios 10, 20 and 30° C.min-1 between room temperature and 700°C. Finally, been obtained the values of activation energy for the region of greatest decomposition of organic matter in samples that were determined by the degree of conversion (α)
Resumo:
The main objective of this study is to apply recently developed methods of physical-statistic to time series analysis, particularly in electrical induction s profiles of oil wells data, to study the petrophysical similarity of those wells in a spatial distribution. For this, we used the DFA method in order to know if we can or not use this technique to characterize spatially the fields. After obtain the DFA values for all wells, we applied clustering analysis. To do these tests we used the non-hierarchical method called K-means. Usually based on the Euclidean distance, the K-means consists in dividing the elements of a data matrix N in k groups, so that the similarities among elements belonging to different groups are the smallest possible. In order to test if a dataset generated by the K-means method or randomly generated datasets form spatial patterns, we created the parameter Ω (index of neighborhood). High values of Ω reveals more aggregated data and low values of Ω show scattered data or data without spatial correlation. Thus we concluded that data from the DFA of 54 wells are grouped and can be used to characterize spatial fields. Applying contour level technique we confirm the results obtained by the K-means, confirming that DFA is effective to perform spatial analysis
Resumo:
In recent years, the DFA introduced by Peng, was established as an important tool capable of detecting long-range autocorrelation in time series with non-stationary. This technique has been successfully applied to various areas such as: Econophysics, Biophysics, Medicine, Physics and Climatology. In this study, we used the DFA technique to obtain the Hurst exponent (H) of the profile of electric density profile (RHOB) of 53 wells resulting from the Field School of Namorados. In this work we want to know if we can or not use H to spatially characterize the spatial data field. Two cases arise: In the first a set of H reflects the local geology, with wells that are geographically closer showing similar H, and then one can use H in geostatistical procedures. In the second case each well has its proper H and the information of the well are uncorrelated, the profiles show only random fluctuations in H that do not show any spatial structure. Cluster analysis is a method widely used in carrying out statistical analysis. In this work we use the non-hierarchy method of k-means. In order to verify whether a set of data generated by the k-means method shows spatial patterns, we create the parameter Ω (index of neighborhood). High Ω shows more aggregated data, low Ω indicates dispersed or data without spatial correlation. With help of this index and the method of Monte Carlo. Using Ω index we verify that random cluster data shows a distribution of Ω that is lower than actual cluster Ω. Thus we conclude that the data of H obtained in 53 wells are grouped and can be used to characterize space patterns. The analysis of curves level confirmed the results of the k-means
Resumo:
This master thesis aims at developing a new methodology for thermochemical degradation of dry coconut fiber (dp = 0.25mm) using laboratory rotating cylinder reactor with the goal of producing bio-oil. The biomass was characterized by infrared spectroscopy with Fourier transform FTIR, thermogravimetric analysis TG, with evaluation of activation energy the in non-isothermal regime with heating rates of 5 and 10 °C/min, differential themogravimetric analysis DTG, sweeping electron microscopy SEM, higher heating value - HHV, immediate analysis such as evaluated all the amounts of its main constituents, i.e., lignin, cellulose and hemicelluloses. In the process, it was evaluated: reaction temperature (450, 500 and 550oC), carrier gas flow rate (50 and 100 cm³/min) and spin speed (20 and 25 Hz) to condensate the bio-oil. The feed rate of biomass (540 g/h), the rotation of the rotating cylinder (33.7 rpm) and reaction time (30 33 min) were constant. The phases obtained from the process of pyrolysis of dry coconut fiber were bio-oil, char and the gas phase non-condensed. A macroscopic mass balance was applied based on the weight of each phase to evaluate their yield. The highest yield of 20% was obtained from the following conditions: temperature of 500oC, inert gas flow of 100 cm³/min and spin speed of 20 Hz. In that condition, the yield in char was 24.3%, non-condensable gas phase was 37.6% and losses of approximately 22.6%. The following physicochemical properties: density, viscosity, pH, higher heating value, char content, FTIR and CHN analysis were evaluated. The sample obtained in the best operational condition was subjected to a qualitative chromatographic analysis aiming to know the constituents of the produced bio-oil, which were: phenol followed by sirigol, acetovanilona and vinyl guaiacol. The solid phase (char) was characterized through an immediate analysis (evaluation of moisture, volatiles, ashes and fixed carbon), higher heating value and FTIR. The non-condensing gas phase presented as main constituents CO2, CO and H2. The results were compared to the ones mentioned by the literature.
Resumo:
In last years it has talked a lot about the environment and the plastic waste produced and discarded. In last decades, the increasing development of research to obtain fuel from plastic material, by catalytic degradation, it has become a very attractive looking, as these tailings are discarded to millions worldwide. These materials take a long time to degrade themselves by ways said natural and burning it has not demonstrated a viable alternative due to the toxic products produced during combustion. Such products could bring serious consequences to public health and environment. Therefore, the technique of chemical recycling is presented as a suitable alternative, especially since could be obtain fractions of liquid fuels that can be intended to the petrochemical industry. This work aims to propose alternatives to the use of plastic waste in the production of light petrochemical. Zeolites has been widely used in the study of this process due to its peculiar structural properties and its high acidity. In this work was studied the reaction of catalytic degradation of high-density polyethylene (HDPE) in the presence HZSM-12 zeolites with different acid sites concentrations by thermogravimetry and pyrolysis coupled with GC-MS. The samples of the catalysts were mixed with HDPE in the proportion of 50% in mass and submitted to thermogravimetric analyses in several heating rates. The addition of solids with different acid sites concentrations to HDPE, produced a decrease in the temperature of degradation of the polymer proportional the acidity of the catalyst. These qualitative results were complemented by the data of activation energy obtained through the non-isothermal kinetics model proposed by Vyazovkin. The values of Ea when correlated to the data of surface acidity of the catalysts indicated that there is a exponential decrease of the energy of activation in the reaction of catalytic degradation of HDPE, in function of the concentration of acid sites of the materials. These results indicate that the acidity of the catalyst added to the system is one of the most important properties in the reaction of catalytic degradation of polyethylene
Resumo:
The aim of this study was to evaluate the potential of near-infrared reflectance spectroscopy (NIRS) as a rapid and non-destructive method to determine the soluble solid content (SSC), pH and titratable acidity of intact plums. Samples of plum with a total solids content ranging from 5.7 to 15%, pH from 2.72 to 3.84 and titratable acidity from 0.88 a 3.6% were collected from supermarkets in Natal-Brazil, and NIR spectra were acquired in the 714 2500 nm range. A comparison of several multivariate calibration techniques with respect to several pre-processing data and variable selection algorithms, such as interval Partial Least Squares (iPLS), genetic algorithm (GA), successive projections algorithm (SPA) and ordered predictors selection (OPS), was performed. Validation models for SSC, pH and titratable acidity had a coefficient of correlation (R) of 0.95 0.90 and 0.80, as well as a root mean square error of prediction (RMSEP) of 0.45ºBrix, 0.07 and 0.40%, respectively. From these results, it can be concluded that NIR spectroscopy can be used as a non-destructive alternative for measuring the SSC, pH and titratable acidity in plums
Resumo:
In this work have been studied the preparation, characterization and kinetic study of decomposition of the polymerizing agent used in the synthesis under non-isothermal condition ceramics PrMO3 of general formula (M = Co and Ni). These materials were obtained starting from the respective metal nitrates, as a cations source, and making use of gelatin as polymerizing agent. The powders were calcined at temperatures of 500°C, 700°C and 900°C and characterized by X-ray Diffraction (XRD), Thermogravimetric Analysis (TG / DTG/ DTA), Infrared Spectroscopy (FTIR), Temperature Programmed Reduction (TPR) and Scanning Electron Microscopy (SEM). The perovskite phase was detected in all the X-rays patterns. In the infrared spectroscopy observed the oxide formation as the calcination temperature increases with the appearance of the band metal - oxygen. The images of SEM revealed uniform distribution for the PrCoO3 and particles agglomerated as consequence of particle size for PrNiO3. From the data of thermal analysis, the kinetics of decomposition of organic matter was employed using the kinetics methods called Model Free Kinetics and Flynn and Wall, in the heating ratios 10, 20 and 30° C.min-1 between room temperature and 700°C. Finally, been obtained the values of activation energy for the region of greatest decomposition of organic matter in samples that were determined by the degree of conversion (α)
Resumo:
The main objective of this study is to apply recently developed methods of physical-statistic to time series analysis, particularly in electrical induction s profiles of oil wells data, to study the petrophysical similarity of those wells in a spatial distribution. For this, we used the DFA method in order to know if we can or not use this technique to characterize spatially the fields. After obtain the DFA values for all wells, we applied clustering analysis. To do these tests we used the non-hierarchical method called K-means. Usually based on the Euclidean distance, the K-means consists in dividing the elements of a data matrix N in k groups, so that the similarities among elements belonging to different groups are the smallest possible. In order to test if a dataset generated by the K-means method or randomly generated datasets form spatial patterns, we created the parameter Ω (index of neighborhood). High values of Ω reveals more aggregated data and low values of Ω show scattered data or data without spatial correlation. Thus we concluded that data from the DFA of 54 wells are grouped and can be used to characterize spatial fields. Applying contour level technique we confirm the results obtained by the K-means, confirming that DFA is effective to perform spatial analysis
Resumo:
In recent years, the DFA introduced by Peng, was established as an important tool capable of detecting long-range autocorrelation in time series with non-stationary. This technique has been successfully applied to various areas such as: Econophysics, Biophysics, Medicine, Physics and Climatology. In this study, we used the DFA technique to obtain the Hurst exponent (H) of the profile of electric density profile (RHOB) of 53 wells resulting from the Field School of Namorados. In this work we want to know if we can or not use H to spatially characterize the spatial data field. Two cases arise: In the first a set of H reflects the local geology, with wells that are geographically closer showing similar H, and then one can use H in geostatistical procedures. In the second case each well has its proper H and the information of the well are uncorrelated, the profiles show only random fluctuations in H that do not show any spatial structure. Cluster analysis is a method widely used in carrying out statistical analysis. In this work we use the non-hierarchy method of k-means. In order to verify whether a set of data generated by the k-means method shows spatial patterns, we create the parameter Ω (index of neighborhood). High Ω shows more aggregated data, low Ω indicates dispersed or data without spatial correlation. With help of this index and the method of Monte Carlo. Using Ω index we verify that random cluster data shows a distribution of Ω that is lower than actual cluster Ω. Thus we conclude that the data of H obtained in 53 wells are grouped and can be used to characterize space patterns. The analysis of curves level confirmed the results of the k-means
Resumo:
This master thesis aims at developing a new methodology for thermochemical degradation of dry coconut fiber (dp = 0.25mm) using laboratory rotating cylinder reactor with the goal of producing bio-oil. The biomass was characterized by infrared spectroscopy with Fourier transform FTIR, thermogravimetric analysis TG, with evaluation of activation energy the in non-isothermal regime with heating rates of 5 and 10 °C/min, differential themogravimetric analysis DTG, sweeping electron microscopy SEM, higher heating value - HHV, immediate analysis such as evaluated all the amounts of its main constituents, i.e., lignin, cellulose and hemicelluloses. In the process, it was evaluated: reaction temperature (450, 500 and 550oC), carrier gas flow rate (50 and 100 cm³/min) and spin speed (20 and 25 Hz) to condensate the bio-oil. The feed rate of biomass (540 g/h), the rotation of the rotating cylinder (33.7 rpm) and reaction time (30 33 min) were constant. The phases obtained from the process of pyrolysis of dry coconut fiber were bio-oil, char and the gas phase non-condensed. A macroscopic mass balance was applied based on the weight of each phase to evaluate their yield. The highest yield of 20% was obtained from the following conditions: temperature of 500oC, inert gas flow of 100 cm³/min and spin speed of 20 Hz. In that condition, the yield in char was 24.3%, non-condensable gas phase was 37.6% and losses of approximately 22.6%. The following physicochemical properties: density, viscosity, pH, higher heating value, char content, FTIR and CHN analysis were evaluated. The sample obtained in the best operational condition was subjected to a qualitative chromatographic analysis aiming to know the constituents of the produced bio-oil, which were: phenol followed by sirigol, acetovanilona and vinyl guaiacol. The solid phase (char) was characterized through an immediate analysis (evaluation of moisture, volatiles, ashes and fixed carbon), higher heating value and FTIR. The non-condensing gas phase presented as main constituents CO2, CO and H2. The results were compared to the ones mentioned by the literature.