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The effects of continuous heating on the crystallisation kinetics and the phase transformation behaviour of electroless nickelphosphorus deposits plated on mild steel substrates, with high phosphorus contents of 12 and 16 wt.%, were studied. Both the deposits exhibited an amorphous X-ray profile in the as-deposited condition. The crystallisation temperatures of the deposits increased with decreasing phosphorus content, and increasing heating rate. The activation energies during the crystallisation processes were calculated from the differential scanning calorimetry (DSC) curves of the deposits at heating rates ranging from 5 to 508C / min. It was found that the activation energy is slightly higher in the deposit with lower phosphorus content. X-ray diffraction (XRD) analyses were also conducted on the deposits after heating processes in the DSC apparatus to 300-8008C at 208C / min. The sequence of phase transformations was found to be: amorphous phase→intermediate metastable phases1stable Ni P phase (1f.c.c. nickel)→stable Ni P phase (1f.c.c. nickel). 3 3 Electron microprobe analysis was carried out on the 16 wt.% P deposit and showed that the iron content in the deposit was affected by heating processes. Film growth in the 16 wt.% P deposit has been shown by scanning electron microscopy (SEM) and electron microprobe analysis on the cross-sections of the deposit after heating to 400 and 8008C (at 208C / min).

The relationship between heat-treatment parameters and microstructure in titanium alloys has so far been mainly studied empirically, using characterization techniques such as microscopy. Calculation and modeling of the kinetics of phase transformation have not yet been widely used for these alloys. Differential scanning calorimetry (DSC) has been widely used for the study of a variety of phase transformations. There has been much work done on the calculation and modeling of the kinetics of phase transformations for different systems based on the results from DSC study. In the present work, the kinetics of the ␤ ⇒ ␣ transformation in a Ti-6Al-4V titanium alloy were studied using DSC, at continuous cooling conditions with constant cooling rates of 5 ЊC, 10 ЊC, 20 ЊC, 30 ЊC, 40 ЊC, and 50 ЊC/min. The results from calorimetry were then used to trace and model the transformation kinetics in continuous cooling conditions. Based on suitably interpreted DSC results, continuous cooling-transformation (CCT) diagrams were calculated with lines of isotransformed fraction. The kinetics of transformation were modeled using the Johnson-Mehl-Avrami (JMA) theory and by applying the "concept of additivity." The JMA kinetic parameters were derived. Good agreement between the calculated and experimental transformed fractions is demonstrated. Using the derived kinetic parameters, the ␤ ⇒ ␣ transformation in a Ti-6Al-4V alloy can be described for any cooling path and condition. An interpretation of the results from the point of view of activation energy for nucleation is also presented.

A model is developed for the analysis and prediction of the correlation between processing (heat treatment) parameters and mechanical properties in titanium alloys by applying arti®cial neural network (ANN). The input parameters of the neural network (NN) are alloy composition, heat treatment parameters and work (test) temperature. The outputs of the NN model are nine most important mechanical properties namely ultimate tensile strength, tensile yield strength, elongation, reduction of area, impact strength, hardness, modulus of elasticity, fatigue strength and fracture toughness. The model is based on multilayer feedforward neural network. The NN is trained with comprehensive dataset collected from both the Western and Russian literature. A very good performance of the neural network is achieved. Some explanation of the predicted results from the metallurgical point of view is given. The model can be used for the prediction of properties of titanium alloys at di erent temperatures as functions of processing parameters and heat treatment cycle. It can also be used for the optimization of processing and heat treatment parameters. Graphical user interface (GUI) is developed for use of the model. Ó