Study of the Relationships Between Optical and Physical Properties for Nanostructure TiO2 Thin Film

Pulsed Laser Deposition (PLD) technique was performed to deposit the pure Titanium oxide (TiO2) nanoparticles on the glass substrate of temp. (100 - 400°C), using the doubled frequency of Nd: YAG laser wavelength of 532nm at (10) Hz rate, 10 nanosecond duration pulses and a constant laser energy 800 mJ. The optical measurements obtained by UV-Vis transmittance on deposited TiO2 films indicate the highest transparency in the visible wavelength region with an average transmittance of 80%. Estimated the relationship between the refractive index of TiO2 thin films with substrate temperature was n = 2.49 at 400 oC. Moreover, the calculated empirical relation between the energy gap and refractive index have similar to the work results.

Estimation of divergent wind from OLR data for use in objective analysis over the Indian region

A scheme is formulated for the use of OLR data in the estimation of vertical velocity; divergence and then the divergent part of the wind over Indian region. In this scheme, ascending motion over cloudy region is estimated from an empirical relation between the cloud top temperature and descending motion over cloud-free region is estimated from the thermodynamic energy equation and both are blended. From this blended vertical velocity field, aivergence, velocity potential and divergent winds at all standard levels from 4 to 8 July 1979 at 00 UTC are computed. These fields are compared with satellite cloud pictures, rainfall etc and they are found to be realistic in depicting the synoptic conditions. Total wind is computed as the sum of the estimated divergent component and rotational component computed from observed wind field. For assessment of the scheme, this total wind field at 850 hPa is used as initial. guess field in univariate optimum interpolation scheme and analyses were made for the period 4 to 8 July 1979. Results show that scheme is able to produce realistic analyses which included divergent part of the wind.

Toward Precise n-Type Doping Control in MOVPE-Grown β-Ga2O3 Thin Films by Deep-Learning Approach

In this work, we train a hybrid deep-learning model (fDNN, Forest Deep Neural Network) to predict the doping level measured from the Hall Effect measurement at room temperature and to investigate the doping behavior of Si dopant in both (100) and (010) β-Ga2O3 thin film grown by the metalorganic vapor phase epitaxy (MOVPE). The model reveals that a hidden parameter, the Si supplied per nm (mol/nm), has a dominant influence on the doping process compared with other process parameters. An empirical relation is concluded from this model to estimate the doping level of the grown film with the Si supplied per nm (mol/nm) as the primary variable for both (100) and (010) β-Ga2O3 thin film. The outcome of the work indicates the similarity between the doping behavior of (100) and (010) β-Ga2O3 thin film via MOVPE and the generality of the results to different deposition systems.

A Phase-Field Study of Microstructure Evolution in Tungsten Polycrystalline under He/D Irradiation

Analyses in the present study focus on understanding the evolution of the tungsten microstructure under He/D irradiation. A fractal dimension analysis was utilized to characterize the structural pattern of the microstructure irradiated by both low (10–80 eV) and high (8–30 keV) irradiation energy. All examined W microstructures show a direct correlation between the fractal dimension and irradiation energy. Analyses establish an empirical relation expressing a change in the microstructure as a function of the irradiation energy based on the changes in the fractal dimension of the microstructures. The proposed relation was implemented in the phase-field model formulation with an account of the interfacial energy induced by the crystallographic mismatch between grains under irradiation. The current phase-field model captures the evolution of the void under irradiation, including nucleation and the growth of voids, and sink efficiency for vacancy annihilation in the vicinity of grain boundaries.

Design of hybrid narrow-band plasmonic absorber based on chalcogenide phase change material in the infrared spectrum

Structures absorbing electromagnetic waves in the infrared spectral region are important optical components in key areas such as biosensors, infrared images, thermal emitters, and special attention is required for reconfigurable devices. We propose a three-dimensional metal-dielectric plasmonic absorber with a layer of PCM’s (Phase Change Materials). The phase shift effects of PCMs are numerically analyzed, and it is possible to obtain a shifting control of the resonant absorption peaks between the amorphous and crystalline states using the Lorentz–Lorenz relation. By using this empirical relation, we analyzed the peak absorption shift at intermediate phases between the amorphous and the crystalline. The geometric parameters of the structure with the PCM layer in the semi-crystalline state were adjusted to exhibit strong absorption for normal incidence. The effects of the oblique incidence on the absorption for the TM and TE polarization modes were also analyzed. Our results demonstrate that PCMs have great potential for reconfigurable nanophotonic devices.

Evaluation of Empirical Relation between Compressive and Flexural Strength of Concrete Partially Using Alccofine and Nano-Silica

In this paper, the flexural strength of concrete using alccofine and nano-silica was investigated experimentally and analytically. 15% alccofine and 3% nano-silica by weight of cement was used as a binary and ternary blend in three concrete grades M40, M50, and M60. Compressive strength and flexural strength were obtained experimentally by curing the specimens in water for 28 days. The empirical equation between compressive strength and flexural strength in the form of fr =bfc’n was obtained using regression analysis. The proposed empirical relation was compared with relations given by a code of practices and the relations reported by other researchers for predicting flexural strength using the compressive strength of concrete. The accuracy of the proposed empirical relation was validated using various statistical equations. From the experimental results, it was found that the cubic compressive strength and flexural strength of ternary blended concrete mixes using alccofine and nano-silica was 20 to 29% and 32 to 39 % higher compared to the control mixes. From the values of statistical equations, the proposed relation was found accurate. It showed less error compared to other relations and can be used to determine flexural strength results based on compressive strength data.

Electrical conductivity of concentrated LiBr Ethylene-Glycol and water ternary system

LiBr/H2O as working pair in absorption chiller is widely used in the absorption refrigeration system, and the electrical conductivity is used as secondary properties as an empirical relation with temperature and concentration as a simple method to measure the concentration. In this paper, another working pair Carrol/H2O is chosen, more suitable for air-cooled cycles. Carrol contains ethylene glycol and LiBr with a mass ratio at 4.5:1 and has advantages of low risk of crystallization and reduce the LiBr charge. The working range for the LiBr/H2O solution is temperature 25-80°C, at concentration 50–64%, in term of Carrol/H2O system, the temperature range is 25-80°C, concentration range is 50%-75%. The electrical conductivity will be measured according to the working range and a typical used solution extracted from an absorption chiller prototype will also be measured to compare with the experimental result.

Low-Frequency 1/f Noise Characteristics of Ultra-Thin AlOx-Based Resistive Switching Memory Devices with Magneto-Resistive Responses

Low-frequency 1/f voltage noise has been employed to probe stochastic charge dynamics in AlOx-based non-volatile resistive memory devices exhibiting both resistive switching (RS) and magneto-resistive (MR) effects. A 1/fγ noise power spectral density is observed in a wide range of applied voltage biases. By analyzing the experimental data within the framework of Hooge’s empirical relation, we found that the Hooge’s parameter α and the exponent γ exhibit a distinct variation upon the resistance transition from the low resistance state (LRS) to the high resistance state (HRS), providing strong evidence that the electron trapping/de-trapping process, along with the electric field-driven oxygen vacancy migration in the AlOx barrier, plays an essential role in the charge transport dynamics of AlOx-based RS memory devices.

Prediction of Perforation Efficiency in Gas Well Using Machine Learning

The efficiency of perforation is an important aspect in gas well since it affects near wellbore pressure drop related to turbulent flow. The perforation efficiency is correlated with non-Darcy skin that is able to be distinguished by pressure transient analysis of isochronal test (Swift et al., 1962), or evaluated from multi-rate flow test data plot coefficients (Jones et al., 1976), or type curve of single build up test following constant-rate production (Spivey et al., 2004). A simple single rate pressure transient analysis which is supported by parameters derived from historical multi rate test data was also proven to differentiate skin damage and non-Darcy skin (Aminian et al., 2007). Unfortunately there are trade-offs between accurateness and analysis time in these aforementioned methods. Quick analysis of perforation efficiency is often needed during well completion and workover activities, to decide whether re-perforation job is required or not. To overcome the challenges of limited time for data acquisition and evaluation, an empirical relation between actual perforation length, skin damage, and laminar-turbulence flow coefficients that are obtained from short-time multi rate test is important to predict the perforation efficiency. The empirical relation will be developed using machine learning. A simple gas reservoir model is built and then run with variations of reservoir permeability, perforation interval length, near wellbore permeability, and vertical anisotropy to generate large numbers of hypothetical multi rate test data. The data set of laminar coefficient, turbulence coefficient, absolute open flow, skin damage, and perforation length will then be trained and tested to create empirical relation using supervised regression method which will afterwards be applied to several actual field cases. This study will elaborate the development of empirical relation of perforation efficiency with the distinct parameters obtained from simple short-time multi rate test data, what other factors will influence the empirical relation, as well as become the possible condition limit of the field application of the developed empirical relation.