Liquid-crystalline organic semiconductors exhibit unique properties that make them highly interesting for organic optoelectronic applications. Their optical and electrical anisotropies and the possibility to control the alignment of the liquid-crystalline semiconductor allow not only to optimize charge carrier transport, but to tune the optical property of organic thin-film devices as well. In this study, the molecular orientation in a liquid-crystalline semiconductor film is tuned by a novel blading process as well as by different annealing protocols. The altered alignment is verified by cross-polarized optical microscopy and spectroscopic ellipsometry. It is shown that a change in alignment of the liquid-crystalline semiconductor improves charge transport in single charge carrier devices profoundly. Comparing the current-voltage characteristics of single charge carrier devices with simulations shows an excellent agreement and from this an in-depth understanding of single charge carrier transport in two-terminal devices is obtained. Finally, p-i-n type organic light-emitting diodes (OLEDs) compatible with vacuum processing techniques used in state-of-the-art OLEDs are demonstrated employing liquid-crystalline host matrix in the emission layer.
An analytical expression for the charge density distributions is derived based on the use of occupation numbers of the states and the single particle wave functions of the harmonic oscillator potential with size parameters chosen to reproduce the observed root mean square charge radii for all considered nuclei. The derived expression, which is applicable throughout the whole region of shell nuclei, has been employed in the calculations concerning the charge density distributions for odd- of shell nuclei, such as and nuclei. It is found that introducing an additional parameters, namely and which reflect the difference of the occupation numbers of the states from the prediction of the simple shell model leads to obtain a remarkabl
... Show MoreThe effect of different doping ratio (0.3, 0.5, and 0.7) with thickness in the range 300nmand annealed at different temp.(Ta=RT, 473, 573, 673) K on the electrical conductivity and hall effect measurements of AgInTe2thin film have and been investigated AgAlxIn(1-x) Te2 (AAIT) at RT, using thermal evaporation technique all the films were prepared on glass substrates from the alloy of the compound. Electrical conductivity (σ), the activation energies (Ea1, Ea2), Hall mobility and the carrier concentration are investigated as a function of doping. All films consist of two types of transport mechanisms for free carriers. The activation energy (Ea) decreased whereas electrical conductivity increases with increased doping. Results of Hall Effect
... Show Morethin films of se:2.5% as were deposited on a glass substates by thermal coevaporation techniqi=ue under high vacuum at different thikness
The effects of gamma irradiation on the structure of ZnS films , which preparing by flash evaporation method, are studied using XRD. Two peaks of (111), (220) orientations are appeared in X ray chart indicating the cubic phase of the films .The lattice parameter, grain size, average internal stress, microstrain, dislocation density and degree of preferred orientation in the film are calculated and correlated with gamma irradiation.
In this research PbS thin film have been prepared by chemical bath deposition technique (CBD).The PbS film with thickness of (1-1.5)μm was thermally treated at temperature of 100°C for 4 hours. Some Structural characteristics was studied by using X-ray diffraction (XRD)and optical microscope photograph some of chemical gas sensing measurements were carried out ,it shown that the sensitivity of (CO2) gas depend on the grain Size and deposition substrate. The grain size of PbS film deposited on on glass closed to 21.4 nm while 37.97nm for Si substrate. The result of current-voltage characterization shwon the sensitivity of prepared film deposited on Si better than film on glass.
In this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual output of the system & to find the jacobain of the system. Which appears to be of critical importance parameter as it is used for the feedback controller and the second stage is learned on-line to modify the weights of the model in order to control the variable parameters that will occur to the system. A back propagation neural network is appl
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