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Fe-Ni alloys of meteoritic composition were solidified by a plane front solidification technique. Distribution coefficients of Ni, P, Ir, Ge, and Cu were determined from the composition data of the plane front solidified alloys. Equations that describe the distribution coefficients (P, Ni, Ir, Ge, and Cu) as a function of S and P content as well as S to P ratio were used to calculate solute partitioning between solid and liquid during the solidification of IIAB, IIIAB, and IVA parent bodies. The calculated P versus Ni, Ir versus Ni, Ge versus Ni, and Cu versus Ni trends are in good agreement with the observed meteorite data for each chemical group. It is concluded that each chemical group formed as a single molten pool in a parent body and that solute partitioning that occurred during solidification is responsible for the observed compositional trends within a single meteorite group.

A directional solidification technique was developed and applied to the problem of fractional crystallization of an iron meteorite parent body. Samples of Fe-Ni alloys close to meteorite compositions and containing S, P, and C were made. The solidified structures contain secondary phases such as sulphides within the proeutectic single crystal austenite (taenite). As a result of these experiments, we propose that the secondary phases observed in iron meteorites were formed during primary solidification of austenite (taenite). The measured composition profiles of Ni, P and C in the alloys were used to explain the elemental distribution within a chemical group of iron meteorites. An analytical procedure was applied to determine the equilibrium distribution coefficients as a function of fraction solidified for Ni and P from the composition profiles. The distribution coefficients of Ni and P agree with previous values. These distribution coefficients are of particular interest in the determination of the elemental distributions in iron meteorites.

Olivine and metal compositions of pallasitic meteorites by electron microprobe measurements, obtaining cooling rates

A model has been developed that can account for both front and back "autodoping" effects during epitaxial growth as well as impurity redistribution during further high-temperature processing. The model incorporates three dopant fluxes, i.e., (i) the flux from the solid into the gas phase at the rear of the wafer, (ii) the flux from the solid to the front surface of the wafer, and (iii) the flux from the bulk gas phase into the boundary layer near the front surface of wafer in which transport of dopant occurs by diffusion only. The redistribution of impurities both within the solid semiconductor and in the gas phase are investigated from a theoretical viewpoint. Numerical solutions are obtained using the method. Implications of differences between this approach and previous work are discussed. Calculated results are presented to illustrate the variety of problems that may be solved using this mathematical approach. The distribution of impurities in epitaxially grown silicon layers plays a major role in the operation of diodes, transistors, and integrated circuits. The impurity redistribution that occurs during silicon epitaxial processing and semiconductor device fabrication is dependent upon processing times and temperatures, diffusivities, evaporation rates, and segregation coefficients of the dopants in the solid and gaseous phases. A model for the redistribution process wou]d enable one to assess the critical steps in the fabrication sequence and predict the effect of process changes on the impurity distribution in the semiconductor. A typical device processing sequence may consist of fifteen discrete high-temperature steps that affect the impurity redistribution. Since the results of the prior step form the initial conditions for the present step, analytical solutions to the diffusion or transport equations are not available. Therefore, a sequential numerical technique is the obvious choice to solve this type of processing problem. At present only fragmentary parts of this problem have been solved and no complete model exists.