Parameters Of Evaporation Process Research Articles

Optimization of Electron-Beam Evaporation Process Parameters for ZrN Thin Films by Plasma Treatment and Taguchi Method

This study presents the optimal process parameters of zirconium nitride (ZrN) thin films prepared by ion-assisted deposition (IAD) technology combined with electron-beam evaporation based on plasma surface treatment and the Taguchi method. We use Minitab statistical software (Version 20.2.0) and L9 orthogonal array parameter design combined with the response surface method (RSM). The quadratic polynomial regression equation was optimized by the RSM. Based on the control factor screening test of the Taguchi method, we determined the most critical factor combination for the process and derived the optimized process parameters of the ZrN thin films. In the coating experiments, we successfully achieved the optimal combination of good refractive index, adequate residual stress, and lower surface roughness on B270 glass substrates. These results indicate that the optimized preparation process can simultaneously achieve several desirable properties, improving the performance and application of ZrN thin films. Furthermore, our research method not only reduces the number of experiments and costs but also improves the efficiency of research and development. By screening key factors and optimizing process parameters, we can find the best process parameter more rapidly, reduce the demand for expenses given materials and equipment costs, and contribute to improving the electron-beam evaporation process. According to the experimental results, it can be observed that under certain conditions, the properties of ZrN thin films reached optimal values. These results are highly useful for optimizing the process parameters of ZrN thin films and provide a basis for further improvement of the thin film properties.

Evaporation generation in the vehicle fuel tank. Canister feed strategy optimization

Introduction (problem statement and relevance). In addition to the toxic substances generated during fuel combustion in the engine, the vehicle generates a significant amount of hydrocarbons in the form of fuel vapors generated as a result of evaporation from the fuel tank and fuel system components. The evaporation process parameters and the amount of fuel evaporations are determined by dynamics of fuel heating in the tank in various vehicle operation modes. Modern requirements for the limit level of emissions caused by evaporation become much stricter. Therefore, the solution of the task of fuel evaporation minimization and prevention of ingress thereof into the atmosphere is relevant and practically significant. The purposes of the studies are to develop a model of the processes of evaporation generation in the vehicle fuel tank based on the analysis of mathematical modeling and experimental research results as well as to develop the optimum strategy and algorithm of the canister feed.Methodology and research methods. In the study, a combination of analytical methods of the classical thermodynamics with modeling in the Simcenter Amesim integrated program platform environment is used.Scientific novelty and results. It has been found that transition from feeding the canister with an open vapor space to evaporation in a fixed-volume space allows significant reduction of the amount of hydrocarbons delivered to the canister.Practical significance. It has been found and proved that accumulation of hydrocarbons in a closed tank with discrete cyclic feed of the canister allows significant reduction of evaporation generation and lowering of the requirements for the canister parameters. An algorithm of optimum canister feed is suggested.

Dynamic correction of soft measurement model for evaporation process parameters based on ARMA.

To address the significant soft measurement errors in traditional static models for evaporation process parameters, which are characterized by continuity and cumulativity, this paper proposes a dynamic correction method for soft measurement models of evaporation process parameters based on the autoregressive moving-average model (ARMA). Initially, the Powell's directional evolution (Powell-DE) algorithm is utilized to identify the autoregressive order and moving average order of the ARMA model. Subsequently, the prediction error of a mechanism-reduced robust least squares support vector machine ensemble model is utilized as input. An error time series prediction model, which compensates for the errors in the autoregressive moving average model, is then applied for dynamic estimation of the prediction error. Finally, an integration strategy using the entropy method is employed to combine the static soft measurement model, based on the mechanism-reduced robust least squares support vector machine, with the dynamic correction soft measurement model, which is based on the error time series compensation of the ARMA model. The new model is analyzed and validated using production data from an alumina plant's evaporation process. Compared to traditional models, the new model demonstrates significantly improved prediction accuracy and is capable of dynamic prediction of evaporation process parameters.

Theoretical and experimental researches of the liquid evaporation during thermal vacuum influences

The mathematical model of the evaporation process of model liquid with the free surface boundary conditions of the "mirror" type under thermal vacuum influence and the numerical estimates of the evaporation process parameters are developed. An experimental stand, comprising a vacuum chamber, an experimental model tank with a heating element is designed; the experimental data are obtained. A comparative analysis of numerical and experimental results showed their close match.

Parameter prediction based on Improved Process neural network and ARMA error compensation in Evaporation Process

The traditional model of evaporation process parameters have continuity and cumulative characteristics of the prediction error larger issues, based on the basis of the process proposed an adaptive particle swarm neural network forecasting method parameters established on the autoregressive moving average (ARMA) error correction procedure compensated prediction model to predict the results of the neural network to improve prediction accuracy. Taking a alumina plant evaporation process to analyze production data validation, and compared with the traditional model, the new model prediction accuracy greatly improved, can be used to predict the dynamic process of evaporation of sodium aluminate solution components.

Thermoelectric Properties of Sb<SUB>2</SUB>Te<SUB>3</SUB> Thin Films by Electron Beam Evaporation

This study applies the thermoelectric grains of Sb2Te3 on conductive glass to evaporate Sb2Te3 thin films by the electron beam evaporation method. Through experimental tests with different evaporation process parameters and film annealing conditions, thin films with better Seebeck coefficient, resistivity (p) and power fact (PF) can be obtained. Experimental results show that when thin films are annealed, their defects can be decreased accordingly, and carrier mobility can be enhanced to further elevate the conductivity of thin films. When the substrate temperature is set at 200 degrees C to fabricate Sb2Te3 thin films by the evaporation process and by annealing at 220 degrees C for 60 minutes, the Seebeck coefficient of Sb2Te3 thin films increase from 87.6 microV/K to 177.7 microV/K; resistivity falls from 6.21 m ohms-cm to 2.53 m ohms-cm and PF can achieve the maximum value of 1.24 10(-3) W/K2 m. Finally, this study attempts to add indium (In) to Sb2Te3 thin films. Indium has been successfully fabricated In3SbTe, thin films. This study also analyzes the effects of In on the thermoelectric properties of In3SbTe2 thin films.

The Identification of TP Chromatic Aberration by Using Nearly Equivalent NN Model

This paper presents the chromatic aberration identification of touch panel (TP) decoration film by using nearly equivalent neural network (NN) model. This model is expected to adequately catch the complex relationship between the chromatic aberration and its possible influencing factors during the evaporation process of TP decoration film. Then, an intelligent estimator for the chromatic aberration of TP film could be developed automatically. Based on this estimator, the technician could set the control parameters of evaporation process in advance and make the quality of chromatic aberration of TP could meet the customer’s required.

The Estimation of TP Chromatic Aberration by Using Neural Network

In this paper, the chromatic aberration estimator of touch panel (TP) decoration film by using neural network is presented. Through the training of neural network, the complex relationship between the chromatic aberration and the parameters of evaporation process of TP decoration film is expected to be found. Thus, an intelligent decision mechanism for the chromatic aberration of TP film on its evaporation process could be developed. Based on this mechanism, the technician could set the control parameters of evaporation in advance so that the quality of chromatic aberration of TP could meet the customer’s request.

Electron-beam Evaporation의 증착 방법에 따른 MgO Layer의 표면 특성에 관한 연구

A MgO layer is used as electrode protective film in the alternating current plasma display panel (AC PDP). The properties of MgO layer are thought to be one of the most important factors that affects the panel reliability through the firing voltage variation. In this study, we investigated the relations between the surface characteristics and e-beam evaporation process parameters such as deposition rate, temperature of substrate and distance between the MgO pellet and substrate. To produce the MgO layer of (200) crystal orientation, we suggest the high temperature of the substrate, the long distance between the pellet and substrate and the high deposition rate.

Process-parameter optimization of Sb2O3 films in the ultraviolet and visible region for interferometric applications

The influence of different evaporation process parameters on the optical properties and constants of thin Sb2O3 films in the ultraviolet and visible region from 250 to 800 nm has been investigated. The most dominant parameters, namely the substrate temperature, rate of evaporation, and ambient oxygen pressure used during the deposition process and the post-annealing temperatures were optimised which resulted in low loss, dense and homogeneous Sb2O3 films. The optical constants and band gaps of these films were evaluated using their interference modulated transmittance spectra in case of both homogeneous and inhomogeneous conditions. Optimized films have been successfully used in developing multilayer high reflecting coatings for Fabry-Perot etalons along with the cryolite (Na3AlF6) films.

The theory of heating and evaporation of a spherical particle exposed to optical radiation

A theoretical investigation into the processes of heating and evaporation of a spherical particle under strong optical radiation is carried out. A system of equations is formulated which describe the process of particle evaporation in diffusional regime. Based on numerical solution of this system of equations, the evaporation of air-suspended water droplets under the i.r. optical radiation is investigated in detail. The timedependent and stationary values of the evaporation process parameters have been obtained for a wide range of the initial problem parameters. The calculated results are compared with the experimental data. A simple model of particle evaporation is considered, analytical and numerical solutions have been obtained.