Papers by Keyword: Diffusivity

Abstract: The study is aimed at comparing the changes which occur in the microstructure and thermo-physical properties of pure copper (99.9%) and when copper alloyed with chromium and zirconium subjected to severe plastic deformation (SPD). The plastic deformation techniques employed were hydrostatic extrusion (HE), equal channel angular pressing (ECAP), and a combination of these two processes. The materials thus obtained had an ultra-fine-grained structure with the thermo-physical properties differing from those of the untreated materials. It appeared that there is a correlation between the deformation method employed and the thermo-physical properties of the materials, such as diffusivity and specific heat.

Abstract: Cement composites are vulnerable to harsh environments in which the chloride ions can ingress into concrete and thus cause corrosion of steel. In this study, the barrier effect of adding 2-D nanoparticles on the transport properties of cement-based materials was investigated. Graphene nanoplatelet (GNP), which comprises of a few layers of graphene stacked together, is chosen as a candidate in this study due to its impermeability and also its electrical conductivity which can be exploited for self-sensing functionality. Due to the large aspect ratio of the GNP, it is expected that the dispersion of these 2-D nanobarriers can contribute to the reduced permeability and diffusion of harmful agents. Experiments were carried out on cement mortar with 0%, 2.5%, 5.0% and 7.5% of GNP by weight of cement. The water penetration depth, chloride diffusion coefficient and chloride migration coefficient were reduced by 64%, 70% and 31% respectively with the addition of as little as 2.5% of GNP. This reduction can be attributed to the barrier effect of GNP which increases the tortuosity against water and chloride ions penetration, and also the refinement of the capillary pores which was revealed from the MIP tests. At GNP content exceeding 5%, the nanoparticles agglomerate, causing weak pockets which compromises the benefits of adding GNP to impede the ingress of fluids.

Abstract: A new atomic mobility database for Fcc_A1, L1₂, Bcc_A2, Bcc_B2, and liquid phases in the Al-Cu-Fe-Mg-Mn-Ni-Si-Zn system has been established via a hybrid approach of experiment, first-principles calculations and DICTRA (DIffusion Controlled TRAnsformation) software, focusing on the atomic mobility parameters in ternary systems. Various diffusivities can be computed as a function of temperature and composition. The reliability of this diffusivity database is further validated by comparing the calculated and measured diffusion properties in a series of ternary and quaternary diffusion couples, including concentration profiles, diffusion paths, interdiffusion fluxes, and so on. The effect of the diffusivity database on microstructure evolution during solidification is demonstrated by the phase field simulation of primary (Al) grains in Al356.1 alloy. The simulation results indicate that such accurate diffusivity database is highly needed for the quantitative simulation of microstructural evolution during solidification.

Abstract: The motion of interstitial atoms (one of the point defects) in material is random under certain temperature. However, the diffusion of interstitial atoms has priority along some certain directions to the others, so it is necessary to reveal the phenomenon (the phenomenon also can be called anisotropic). In order to illustrate the anisotropic and reveal the magnitude of probability of the micro crack formation along crystal axes, some formulae derived from former literatures have been adopted, and the values of diffusion probability and diffusivity of interstitial atoms-Ti or Al along 〈110〉and〈100〉have been calculated. The conclusion that the diffusion of interstitial atoms along different crystal axis has different diffusivity is verified by the comparison of the results of calculations.

Abstract: Temperature being one of the most important parameters of Spark plasma sintering (SPS) and its effects on the microstructures as well as on the physical properties of copper diamond composites fabricated by mechanical mixing of copper with 70 vol.% diamond powders, precoated with 1 wt% chromium has been studied. Experiments were performed at 900°C, 1000°C and 1100 °C for 10 minutes under 50 MPa. The results reveal that sintering temperature highly influences the copper/diamond interface bonding and microstructures. The composite’s properties like thermal conductivity (T.C), specific heat (Cp), diffusivity (Dff) and relative density (ρr) were also highly influenced by temperature variations. Except the relative density, all the other properties increased respectively with increasing sintering temperature.

Abstract: A mathematical model for predicting the permeability of natural gas in polymer nanocomposites was developed and tested using experimental data. The model takes into account the effects of pressure, temperature, crystallinity and nanoparticle loading. Three model parameters (, and) were obtained. The parameter is a measure of the activation energy, described the effect of nanocomposite loading, and can be used to describe the effect of gas concentration on the. Polymer nanocomposites were prepared using high density polyethylene as polymer matrix and Cloisite 15A as nanoclay. The proposed model was used to predict the permeability of the nanocomposites to pure CH₄ and mixed CH₄/CO₂ gases (containing 80 mol% CH₄) at pressures up to about 106 bar and temperatures between 30 to 70°C. Predicted results show that the developed model provides an excellent description of natural gas permeation in pure HDPE and its nanocomposites.

Abstract: Numerical simulation of a mass-diffusion analysis requires several parameters in order to comply with experimental method of gas – carburizing of iron powder compacts. Among the known parameters of mass-diffusion process, the diffusivity is an uncertain parameter in terms of its value. Different formulas can be found in literature but most of them are empirical determined since different results of carbon content are obtained by numerical mass-diffusion analysis. For iron powder compacts with rectangular shape subjected to gas – carburizing – sintering process it was determined the average carbon content in several layers. Based on these determinations and on the characteristics of mass diffusion analysis using Abaqus software it was empirically determined the diffusivity dependency on the carburizing time.

Abstract: The thermal diffusion behavior of ion-implanted Arsenic (As) in SiGeC alloy has been investigated and modeled. This paper introduces an empirical model consisting of physics-based and process-based parameters for evaluating the effective diffusivity of Arsenic in SiGeC accurately. The different process parameters that were found to affect the diffusivity were – Germanium content (x), diffusion temperature (T) and Carbon content (y). Germanium content taken into account was 7% and 12.3% for compressive strain in the structure with a Carbon content of 0.2%. The model incorporates all the effects associated with the change in the process parameters which affect the diffusivity of As in compressively strained-Si_1-x-yGe_xC_y. The model was found to be extremely accurate in predicting the exact dependencies of As diffusivity on physics-based and process parameters. The proposed empirical process model may find suitable application in the prediction of thermal diffusion behavior of As in Si_1-x-yGe_xC_y process-flow as well as in improving the existing model in Silvaco’s TCAD suite.

Abstract: The thermal diffusion behavior of ion-implanted Arsenic (As) in SiGe alloy has been investigated and modeled. This paper introduces a neural network based model consisting of physics-based and process-based parameters for evaluating the effective diffusivity of Arsenic through SiGe accurately. The parameters that served as the input to the neural network included Ge content, diffusion temperature and anneal time. The model was validated for the germanium content of up to 45% with the reported data and the existing simulation models in Silvaco. The model incorporates all the effects associated with the change in the process parameters which affect the diffusivity of As in relaxed-SiGe. The model was found to be extremely accurate in predicting the exact dependencies of As diffusivity on physics-based and process parameters. The proposed empirical process model may find suitable application in prediction of thermal diffusion behavior of As in SiGe process-flow with emphasis on reduced computational time.

Abstract: Titanium carbide particulate reinforced composites were fabricated by vibrational moulding sand casting technique. Titanium carbide particulate added as a reinforcement phase in the LM6 alloy matrix and the percentage of addition varied from 0.2, 0.6, 1 and 2% on weight fraction basis. The thermal conductivity and diffusivity of TiC composites were determined. Increasing frequency of vibration and TiC content helps to improve density, thermal conductivity, thermal diffusivity and purification of the grain boundaries. The dispersed particles increased the thermal conductivity and diffusivity according to an effective media theory.