Atomic layer deposition (ALD) processes for HfO2 and HfxSi1−xO2 high-k dielectric thin films using liquid precursors and ozone were evaluated. Tetrakis(ethylmethylamino)hafnium (TEMAHf) precursor provides HfO2 films with superior quality as compared to Hf(t-butoxide)4 precursor in terms of deposition rate, purity, and electrical properties of the films. ALD processes for hafnium silicate films have been developed by co-injection of TEMAHf and tetrakis(ethylmethylamino) silicon precursors. Alternating pulses of the Hf/Si precursor vapor mixture and ozone allow process temperatures below 400 °C to grow HfxSi1−xO2 film. The Hf and Si precursors can be converted to vapor for delivery to the deposition chamber either by bubbling an inert carrier gas separately through each liquid or by using a liquid vaporization unit. The co-injection process enables the formation of homogeneous single-layer hafnium silicate films as deposited.

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The thickness growth characteristics of flowing lava are investigated using a heat balance model and a two‐dimensional model for flow of a Bingham plastic fluid down an inclined plane. It is found that yield strength plays a crucial role in the thickening of a lava flow of given flow rate. To illustrate this point, downstream thickness profiles and yield strength distributions were calculated for flows with mass flow rates of 104 and 105 kg/m‐sec. Higher flow rates led to slow cooling rates which resulted in slow rate of increase of yield strength and thus greater flow lengths.

This paper concentrates on the system that controls the femur-tibia joint in the legs of the stick insect, Carausius morosus. Earlier investigations have shown that this joint is subject to a mixture of proportional and differential control whereby the differential part plays a prominent role. Experiments presented here suggest another interpretation: single legs of a stick insect were systematically perturbed using devices of different compliance and compensatory forces and movements monitored. When the compliance is high (soft spring), forces are generated that return the leg close to its original position. When the compliance is low (stiff spring), larger forces are generated but sustained changes in position occur that are proportional to the force that is applied. Selective ablation of leg sense organs showed that the leg did not maintain its position after elimination of afferents of the femoral chordotonal organ. Ablation of leg campaniform sensilla had no effect. These data support the idea that different control strategies are used, depending upon substrate compliance. In particular, what we and other authors have called a differential controller, is now considered as an integral controller that "intelligently gives up" when the correlation between motor output and movement of the leg is low.

In this study, the exchange current density and the transfer coefficient of uranium in LiCl-KCl molten salt were obtained precisely by using a Tafel plot and linear polarization. The exchange current density for the U 0 /U 3+ redox couple was determined to be 185.4 ± 3.7 A/m 2 at 500 • C and 1 wt% of UCl 3 . The cathodic transfer coefficient was measured as 0.22 ± 0.01 for the U 0 /U 3+ reaction, showing a different value from the input value assumed in many modeling programs. The temperature and concentration dependency of the exchange current density were investigated as well.

Various power saving and contrast enhancement (PSCE) techniques have been applied to an organic light emitting diode (OLED) display for reducing the power demands of the display while preserving the image quality. In this paper, we propose a new deep learning-based PSCE scheme that can save power consumed by the OLED display while enhancing the contrast of the displayed image. In the proposed method, the power consumption is saved by simply reducing the brightness a certain ratio, whereas the perceived visual quality is preserved as much as possible by enhancing the contrast of the image using a convolutional neural network (CNN). Furthermore, our CNN can learn the PSCE technique without a reference image by unsupervised learning. Experimental results show that the proposed method is superior to conventional ones in terms of image quality assessment metrics such as a visual saliency-induced index (VSI) and a measure of enhancement (EME). 1 Index Terms-Convolutional neural network, deep learning, energy efficiency, image enhancement.