Rita C. O. Sebastião

ARTIFICIAL NEURAL NETWORK APPLIED TO SOLID STATE THERMAL DECOMPOSITION

A multi-layer neural network is constructed to describe the thermal decomposition of rhodium acetate. Critical analysis of the residual, trained, interpolated and extrapolated errors, with the number of neurons, indicates the efficiency of the present approach. It was possible, within this framework, to improve the An model, with a better correlation between the results. A new value of the activation energy, Ea, and frequency factor, Z, are calculated for the decomposition process. Since the neural network is more precise than a particular model, the calculated values for these quantities are believed to be more precise. The computed values are Ea=194.0 kJ mol-1 and Z=5.23·1016 s-1. The neural network eliminates the step to decide, among the available models, the one that best fit the data. An agreement up to four significant figures can be achieved even for data not used in the training process, both in the interpolated and extrapolated regions. This method suggests, therefore, an important alternative tool for the experimentalists. The present approach can also be adapted to other systems and to data in two dimensions.

Probability density function from experimental positron annihilation lifetime spectra

Inversion of experimental positron annihilation lifetime spectra was carried out to obtain the probability density function. Apparatus resolution together with experimental noise was taken into consideration while solving this ill posed problem. The singular value decomposition approach, moving the boundary between the subspaces was the theoretical formulation to calculate the probability density function. For the system considered, the Al(dpm)3 complex, three peaks will be presented in the inverted spectra, indicating the presence of the para-Positronium, the free positron and the ortho-Positronium. The predicted positions were, 0.1042 ns, 0.3542 ns and 1.3958 ns, respectively. Since the present approach gives the distribution of the species, it was possible also to predict the relative importance of each species in the spectra. The areas found correspond to: 13%, 32%, 55%. Both these results, position of the peaks and the areas, together with the half-life distribution can provide important information for experimentalists.

Quantum second virial coefficient calculation for the 4He dimer on a recent potential

This paper focuses on the calculation of the quantum second virial coefficient, under a recently developed potential. This coefficient was determined to within 4-5 significant figures in the temperature range from 3 to 100 K. Our results are within experimental error. The three contributions to the overall value of the coefficient are the quantum scattering (continuum state contribution), the bound state (discrete state contribution) and the quantum ideal gas; we discuss these contributions separately. The most significant contribution is from the scattering states, whereas the smaller contributions are from the discrete states. A sensitivity analysis was performed as a function of temperature for one parameter in the short-range region of the potential and for three parameters in the long-range regions of the potential. For both temperatures considered, 10 and 100 K, the C6 dispersion coefficient was the most significant, and the C10 dispersion term was the least significant to the overall result. In general, the precision required to describe the potential decays as the temperature increases. The overall accuracy and the relationship of the parameters to the experimental errors are discussed.

Retrieval of GammaCell 220 irradiator isodose curves with MCNP simulations and experimental measurements

Gamma irradiator facilities can be used in a wide range of applications such as biological and chemical researches, sterilization of medical devices and products. Dose mapping must be performed in these equipments in order to establish plant operational parameters, as dose uniformity, source utilization efficiency and maximum and minimum dose positions. The isodoses curves are measured using dosimeters or computer simulations. This work evaluates the absorbed dose in the CDTN/CNEN GammaCell Irradiation Facility, using the Monte Carlo N-Particles (MCNP) code.

Potential energy function from second virial data using sensitivity analysis

Retrieving the potential energy function from second virial data, and using the sensitivity analysis approach is discussed in this work. A potential energy function, with an initial average error of 92%, in temperature range of 100–500 K, with respect to a reference potential, was considered as an initial guess. Within the present framework it was possible to produce another potential with an average error of 0.7 and 2.7%, using two regularization methods. Analysis of the sensitivity matrix has shown to be an important step while inverting the data. This preliminary analysis provides important informations about the optimal temperature and coordinate range to be used in the inversion process.

Kinetic study of anti-HIV drugs by thermal decomposition analysis: A multilayer artificial neural network propose

Kinetic study by thermal decomposition of antiretroviral drugs, efavirenz (EFV) and lamivudine (3TC), usually present in the HIV cocktail, can be done by individual adjustment of the solid decomposition models. However, in some cases, unacceptable errors are found using this methodology. To circumvent this problem, here is proposed to use a multilayer perceptron neural network, with an appropriate algorithm, which constitutes a linearization of the network by setting weights between the input layer and the intermediate one and the use of kinetic models as activation functions of neurons in the hidden layer. The interconnection weights between that intermediate layer and output layer determine the contribution of each model in the overall fit of the experimental data. Thus, the decomposition is assumed to be a phenomenon that can occur following different kinetic processes. In investigated data, the kinetic thermal decomposition process was best described by R1 and D4 models for all temperatures to EFV and 3TC, respectively. The residual error of adjustment over the network is on average 103 times lower for EFV and 102 times lower for 3TC compared to the best individual kinetic model. These improvements in physical adjustment allow detailed study of the process and therefore a more accurate calculation of the kinetic parameters such as the activation energy and frequency factor. It was found

Problemas inversos mal colocados em química

E_{\text{a}} = 75.230\,{\text{kJ}}\,{\text{mol}}^{ - 1}

Parametric sensitivity analysis for the helium dimers on a model potential

Ea=75.230kJmol-1 and