Simulation of the Peritectic Phase Transition in Fe-C Alloys.

In this work, a multi-phase cellular automaton (CA) model is extended for the quantitative simulation of peritectic phase transition. First, the effects of cooling rate/supersaturation and temperature on the peritectic transformation kinetics in Fe-C alloys are investigated by utilizing the present CA model. The CA simulations show that supersaturations in the parent phases (liquid and δ-ferrite) increase the L/γ interface growth velocity remarkably, but tinily for the δ/γ interface migration velocity. There exists a transition supersaturation for isothermal transformations, at which the growth rates of the two interfaces are equal. The transition supersaturation is found to increase with decreasing temperature. Microstructural evolution at different cooling rates during peritectic transformation is simulated using the experimental conditions. At low cooling rates, the δ/γ interface propagates at a higher velocity than the L/γ interface. At high cooling rates, however, the γ-phase grows more into the L-phase with a cellular morphology. Then, the proposed CA model is applied to simulate the microstructural evolution during peritectic reaction. It is observed that the γ-phase propagates along the L/δ interface and finally encircles the δ-phase. Meanwhile, the intervenient γ-phase grows in thickness through peritectic transformation. The CA simulations are compared reasonably well with the experimental data and analytical calculations.

Modeling of dendrite arm fragmentation and dendrite arm coarsening⋆.

A two-dimensional quantitative cellular automaton (CA) model is employed to simulate dendrite arm fragmentation and dendrite arm coarsening in mushy zones. The phenomenon of dendrite arm fragmentation of an Al-Cu alloy during heating is well represented by the CA simulation, and it is analyzed in detail by comparing the local actual concentration and local equilibrium concentration. The CA simulations for the dendritic microstructures of SCN-ACE alloys during isothermal holding in a mushy zone reproduce the typical dendrite coarsening features as observed in experiments. The effects of holding temperature and alloy composition on the microstructures and dendrite coarsening kinetics are investigated. It is found that the melting of small dendrite arms and interdendritic groove advancement are the two main mechanisms in dendrite coarsening. The mechanism of coalescence by joining arm tips is more likely to take place at a lower temperature or for a lower alloy composition, while the dendrite arm fragmentation mechanism tends to occur at a higher temperature. The coarsening rate constant is found to decrease with increasing holding temperature and alloy composition.

Cellular automaton modeling of peritectic transformation⋆.

A two-dimensional multiphase cellular automaton (CA) model is proposed for the prediction of growth kinetics and microstructural evolution during peritectic transformation of Fe-C alloys. The proposed model is validated by comparing the simulation results with the experimental measurements and analytical predictions for the growth kinetics of the [Formula: see text] -phase and the concentration distributions. The simulated time evolution of the [Formula: see text] -phase thickness and the concentration distribution in the [Formula: see text] -phase agree well with the experimental data, demonstrating the quantitative capabilities of the proposed model. The influences of the holding temperature and [Formula: see text] -phase thickness on the [Formula: see text] -phase growth behavior are analyzed based on the simulation results. The [Formula: see text] -phase growth velocity is found to decrease with increasing the [Formula: see text] -phase thickness and holding temperature. Simulations are also performed for the microstructural evolution during isothermal peritectic transformation of Fe-C alloys with the primary [Formula: see text] -phase being an equiaxed dendrite under different holding temperatures. It is found that the driving force for [Formula: see text] -phase growth increases with decreasing temperature.

Interaction of local solidification and remelting during dendrite coarsening - modeling and comparison with experiments.

The microstructural evolution of dendrite coarsening during isothermal holding is simulated using a quantitative cellular automaton (CA) model involving the mechanisms of both solidification and melting. The present model encompasses the essential aspects of thermodynamics and kinetics, particularly the evolution/influence of composition, temperature, and curvature, leading to valid simulations of simultaneous solidification and melting. Model validation is performed through a comparison of the CA simulations with analytical predictions for a liquid pool migrating in the mushy zone of a SCN-0.3 wt.% ACE alloy due to temperature gradient zone melting. The model is applied to simulate the microstructural evolution of columnar dendrites of a SCN-2.0 wt.% ACE alloy during isothermal holding in a mushy zone. The simulation results are compared with those of a previous CA model that does not include the melting mechanism under otherwise identical conditions. The role of melting for dendrite coarsening is quantified, showing how the melting influences the coarsening process. The present model effectively reproduces the typical dendrite coarsening features as observed in experiments reported in the literature. The simulations reveal how local solidification and melting stimulate each other through the complicated interactions between phase transformation, interface shape variation, and solute diffusion.

[The study on energy band structure of silicon nanowires with XPS].

Silicon nanowires were obtained via oxide-assisted method, which was operated in a high temperature furnace at 1250 degrees C under 1000 Pa for 5 h using Ar as carrier gas. The silicon nanowires were etched with 5% HF aqueous solution for 5 min, and reacted with 1 X 10(-3) mol X L(-1) AuCL3 solution, and Au-modified silicon nanowires were obtained. The crystal structure of the products was characterized with XRD, and both of the patterns of Si and Au were observed. The morphology checked with SEM and TEM indicated large scale uniform silicon nanowires and Au particles on the surface of silicon nanowires. The average diameter of Au nanoparticls was 8 nm. The energy band structures obtained with XPS showed that gold nanoparticles are in negative charge and exist both at donor and acceptor levels. The Fermi level moved towards the top of valence band due to oxygen.

Registration of medical images using an interpolated closest point transform: method and validation.

Image registration is an important procedure for medical diagnosis. Since the large inter-site retrospective validation study led by Fitzpatrick at Vanderbilt University, voxel-based methods and more specifically mutual information-based registration methods (see for instance [IEEE Trans. Med. Imag. 22 (8) (2003) 986] for a review on these methods) have been regarded as the method of choice for rigid-body intra-subject registration problems. In this study we propose a method that is based on the Iterative Closest Point algorithm and a pre-computed closest point map obtained with a slight modification of the fast marching method proposed by Sethian. Pre-computing the closest point map speeds up the process because at each iteration point correspondence can be established by table lookup. We also show that because the closest point map is defined on a regular grid it introduces a registration error and we propose an interpolation scheme that addresses this issue. The method has been tested both on synthetic and real images, and registration results have been assessed quantitatively using the data set provided by the Retrospective Registration Evaluation Project. For these volumes, MR and CT head surfaces were extracted automatically using a level-set technique. Results show that on these data sets this registration method leads to accuracy numbers that are comparable to those obtained with voxel-based methods.

Brain atlas deformation in the presence of small and large space-occupying tumors.

Brain atlases contain a wealth of information that could be used in radiation therapy or neurosurgical planning. Until now, however, when large space-occupying tumors and lesions drastically alter the shape of brain structures and substructures, atlas-based methods have been of limited use. In this work, we present a new technique that permits a brain atlas to be warped onto image volumes in which large lesions are present. First we show that a method previously used for atlas-based segmentation of normal brains can also be used for brains with small lesions. We then present an extension of this technique for brains with large lesions. This involves several steps: a global registration to bring the two volumes into approximate correspondence; a local registration to warp the atlas onto the patient volume; the seeding of the warped atlas with a tumor model derived from patient data; and the deformation of the seeded atlas. Global registration is performed using a mutual information criterion. The method we have used for atlas warping is derived from optical flow principles. Preliminary results obtained on real patient images are presented. These results indicate that the proposed method can be used to automatically segment structures of interest in brains with gross deformation. Potential areas of application for this method include automatic labeling of critical structures for radiation therapy and presurgical planning.