Effect of Sintering Atmosphere on Phase Evolution of Hydroxyapatite Nanocomposite Powders

In the present work, pure hydroxyapatite, hydroxyapatite-20 wt% alumina and hydroxyapatite-20 wt% titanium mixtures were pressed and sintered in air, moist, and reduction atmospheres at 1200 C for 2 h. XRD investigations of sintered samples showed that, pure hydroxyapatite is stable in all three atmospheres. But, moist and reduction atmospheres were preferred to suppress the hydroxyapatite decomposition in hydroxyapatite -alumina and hydroxyapatite – titanium nanocomposites, respectively. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/3494

Microstructure Development and Phase Evolution of Alumina- mullite Nanocomposite

In this work, alumina-mullite composites (5-15 vol.%) were prepared using sol-gel derived alumina composite nanopowders. The results revealed the formation of intragranular and intergranular mullites inside and between the alumina grains, respectively. Accordingly, the intragranular mullites (average grain size, 0.3 ?m) were smaller than the intergranular mullites (average grain size, 0.5 ?m). Moreover, the alumina grains (average grain size, 1.0 ?m) are larger than the mullites. Meanwhile, the mullites showed positive results in the prevention of the alumina grains growth and the retardation of densification. The relative density of alumina-15 vol.% mullite that was sintered at 1650?C for 2 h, was obtained as 98.7 %. After sintering at 1750?C for 2 h, the mullite was decomposed

Integration of Gravitational Torques in Cerebellar Pathways Allows for the Dynamic Inverse Computation of Vertical Pointing Movements of a Robot Arm

Several authors suggested that gravitational forces are centrally represented in the brain for planning, control and sensorimotor predictions of movements. Furthermore, some studies proposed that the cerebellum computes the inverse dynamics (internal inverse model) whereas others suggested that it computes sensorimotor predictions (internal forward model).This study proposes a model of cerebellar pathways deduced from both biological and physical constraints. The model learns the dynamic inverse computation of the effect of gravitational torques from its sensorimotor predictions without calculating an explicit inverse computation. By using supervised learning, this model learns to control an anthropomorphic robot arm actuated by two antagonists McKibben artificial muscles. This was achieved by using internal parallel feedback loops containing neural networks which anticipate the sensorimotor consequences of the neural commands. The artificial neural networks architecture was similar to the large-scale connectivity of the cerebellar cortex. Movements in the sagittal plane were performed during three sessions combining different initial positions, amplitudes and directions of movements to vary the effects of the gravitational torques applied to the robotic arm. The results show that this model acquired an internal representation of the gravitational effects during vertical arm pointing movements.This is consistent with the proposal that the cerebellar cortex contains an internal representation of gravitational torques which is encoded through a learning process. Furthermore, this model suggests that the cerebellum performs the inverse dynamics computation based on sensorimotor predictions. This highlights the importance of sensorimotor predictions of gravitational torques acting on upper limb movements performed in the gravitational field

Modern microwave methods in solid state inorganic materials chemistry: from fundamentals to manufacturing

No abstract available