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This work reports, for the first time, the sintering of the thermally decomposable lead dioxide at a temperature lower than 290 °C. Such low-temperature processing is necessary to avoid the transformation of the conductive lead dioxide to the non-conductive lead oxides via the well-known thermal decomposition processes of lead oxides. Such sintering process provides an important opportunity to find a way toward an efficient and cost-effective alternative for platinum electrodes for the electrochemical applications. It has been found that 90% of the theoretical density can be achieved, for lead dioxide body, via cold sintering process with the help of minor additives of saturated lead nitrate solution and 2 M hydrochloric acid solution. The different characterization analyses could not detect any undesirable phase, while the cyclic voltametery, BET, and the contact angle tests confirmed the suitability of the synthesized body for the electrochemical applications.

Barium titanates are widely used in the electronics industry because of their high dielectric constant and ferroelectric and piezoelectric properties. These properties are related to the physical properties of the material; thus, the optimization of these properties is crucially important. The aim of the current work is to control the values of the processing parameters to produce the optimum density, porosity, firing shrinkage, and green density of BaTiO3. A genetic algorithm was used to fulfill this aim. The modified pechini method was used to prepare barium titanate powders with five different particle size distributions. Eighty samples were prepared using different processing parameters including the pressing rate, pressing pressure, heating rate, sintering temperature, and soaking time. A genetic algorithm (GA) approach has been applied in order to obtain the optimum processing parameters. The results showed that the best value of the density that can be achieved is 6.02 g/cm3, which is equal to the theoretical density of BaTiO3 using a pressing rate of 3 KN/S, a pressing pressure of around 370–385 Mpa, a sintering temperature of not less than 1400 °C, a soaking time of around 6–8 h, and a heating rate of 2.5 °C/min. The same upper and lower boundary conditions, used to obtain the optimum density, were also employed for the investigation of the porosity, firing shrinkage, and green density. The optimum achieved values were of geometric mean of 6.89%, 3.48 g/cm3, and 17.01% for the porosity, green density, and firing shrinkage, respectively.

Barium titanate is one of the most important ceramics amongst those that are widely used in the electronic industry because of their dielectric properties. These properties are related to the physical properties of the material, namely, the density and the porosity. Thus, the prediction of these properties is highly desirable. The aim of the current work is to develop models that can predict the density, porosity, firing shrinkage, and the green density of barium titanate BaTiO3. An artificial neural network was used to fulfill this aim. The modified pechini method was used to prepare barium titanate powders with five different particle size distributions. Eighty samples were prepared using different processing parameters including the pressing rate, pressing pressure, heating rate, sintering temperature, and soaking time. In the artificial neural network (ANN) model, the experimental data set consisted of these 80 samples, 70 samples were used for training the network and 10 samples were employed for testing. A comparison was made between the experimental and the predicted data. Good performance of the ANN model was achieved, in which the results showed that the mean error for the density, porosity, shrinkage, and green density are 0.02, 0.06, 0.04, and 0.002, respectively.