Structure and microstructure behavior of iron doped potassium sodium niobate powders

In this paper, the synthesis and characterization of the potassium sodium niobate doped with iron powders have been studied. Solid-state oxide reaction sintering was used. The powders produced in this work exhibit no homogeneous microstructure, which introduced the growth of random cylindrical structures and will can contribute to the increased porosity ceramics. It was observed average particle size of 3μm, besides, also it was observed the formation of agglomerations and an increase in the size of these clusters with the increase in the amount of iron. The calcination temperature was 950 °C. This is slightly higher than other potassium sodium niobate powders systems. In addition to the physical and microstructural properties, structural properties are presented and analyzed for the first-time using Mössbauer spectroscopy as complementary technique in Fe 3+doped potassium sodium niobate powders. This work is important to state solid physics because establishes the influence of iron in the potassium sodium niobate system, and so the future obtaining of multifunctional materials that have piezoelectric and magnetic properties.

PORE PERCENTAGE ESTIMATION OF PIEZOELECTRIC CERAMICS USING CCANN AND IMAGE MADE WITH SEM

Авторами получены образцы пьезоэлектрической керамики ниобата калия натрия с концентрацией пор 10,25 и 40 объемных %. Разработана капсульная свёрточная искусственная нейронная сеть для определения процентного содержания пор по изображению. С помощью растрового электронного микроскопа получено обучающее множество примеров (фотографии поверхности и сколов подготовленных образцов). Разработка и апробация капсульной свёрточной искусственной нейронной сети осуществлена в несколько этапов. На первом проведено ее обучение с помощью метода обратного распространения ошибки. На втором - тестирование на проверочном множестве. На заключительном этапе проведено сравнение полученных результатов с результатами метода сравнения плотности материала. Показано, что данный метод можно использовать для решения задачи определения процентного содержания пор в KNN, поскольку полученные результаты сопоставимы с результатами, полученными другим методом. Установлено, что в образцах, в которых не были специально добавлены поры, также присутствуют поры (порядка 5 %). The authors synthesized samples of piezoelectric potassium sodium niobate ceramics of 10,25 and 40 pore percentage by volume. Capsule convolutional artificial neural network has been developed for estimation of the pore percentage in images. Using the scanning electron microscopy, f learning massive of examples was formed (photographs of surface and edges of so-synthesized samples). Development and approbation of the capsule convolutional artificial neural network was completed in a few stages. During the first stage, the network was trained using a backpropagation method. Secondly, it was tested by a testing set. At the final stage we made a comparison of the acquired results with the results of the density comparing method. The article shows that this method can be used the pore percentage estimation in sodium niobate ceramics because the acquired results are comparable with the results of other methods. It was found that the samples where the pores were not made also have some pore percentage (about 5 %).

Screen Printed Copper and Tantalum Modified Potassium Sodium Niobate Thick Films on Platinized Alumina Substrates

We show how sintering in different atmospheres affects the structural, microstructural, and functional properties of ~30 μm thick films of K0.5Na0.5NbO3 (KNN) modified with 0.38 mol% K5.4Cu1.3Ta10O29 and 1 mol% CuO. The films were screen printed on platinized alumina substrates and sintered at 1100 °C in oxygen or in air with or without the packing powder (PP). The films have a preferential crystallographic orientation of the monoclinic perovskite phase in the [100] and [−101] directions. Sintering in the presence of PP contributes to obtaining phase-pure films, which is not the case for the films sintered without any PP notwithstanding the sintering atmosphere. The latter group is characterized by a slightly finer grain size, from 0.1 μm to ~2 μm, and lower porosity, ~6% compared with ~13%. Using piezoresponse force microscopy (PFM) and electron backscatter diffraction (EBSD) analysis of oxygen-sintered films, we found that the perovskite grains are composed of multiple domains which are preferentially oriented. Thick films sintered in oxygen exhibit a piezoelectric d33 coefficient of 64 pm/V and an effective thickness coupling coefficient kt of 43%, as well as very low mechanical losses of less than 0.5%, making them promising candidates for lead-free piezoelectric energy harvesting applications.

Evaluation of Electromechanical Properties and Conversion Efficiency of Piezoelectric Nanocomposites with Carbon-Fiber-Reinforced Polymer Electrodes for Stress Sensing and Energy Harvesting

Wireless sensor networks are the future development direction for realizing an Internet of Things society and have been applied in bridges, buildings, spacecraft, and other areas. Nevertheless, with application expansion, the requirements for material performance also increase. Although the development of carbon-fiber-reinforced polymer (CFRP) to achieve these functions is challenging, it has attracted attention because of its excellent performance. This study combined the CFRP electrode with epoxy resin containing potassium sodium niobate piezoelectric nanoparticles and successfully polarized the composite sample. Furthermore, a three-point bending method was applied to compare the bending behavior of the samples. The peak output voltage produced by the maximum bending stress of 98.4 MPa was estimated to be 0.51 mV. Additionally, a conversion efficiency of 0.01546% was obtained. The results showed that the piezoelectric resin with CFRPs as the electrode exhibited stress self-inductance characteristics. This study is expected to be applied in manufacturing self-sensing piezoelectric resin/CFRP composite materials, paving the way for developing stable and efficient self-sensing structures and applications.