L. E. Ramírez-Vidaurri

Bio: L. E. Ramírez-Vidaurri is an academic researcher from Instituto Tecnológico de Saltillo. The author has contributed to research in topics: Eutectic system & Intermetallic. The author has an hindex of 3, co-authored 3 publications receiving 181 citations.

Transactions of the Indian Institute of Metals

Abstract: Transactions of The Indian Institute of Metals is devoted to the publication of selected reviews on contemporary topics and original research articles that contribute to the advancement of ferrous and non-ferrous process metallurgy, materials engineering, physical, chemical and mechanical metallurgy, welding science and technology, surface engineering and characterisation, materials development, thermodynamics and kinetics, materials modelling and to other allied branches of metallurgy and materials engineering.

Effect of cooling rate and Fe/Mn weight ratio on volume fractions of α-AlFeSi and β-AlFeSi phases in Al-7.3Si-3.5Cu alloy

Abstract: The crystallization behavior of iron intermetallic compounds in Al−7.3Si−3.5Cu alloy was investigated using thermal analysis, metallography, and a thermodynamic simulation performed with the Scheil module of ThermoCalc®. We observed that β-AlFeSi disappeared when both high (>3.5°C/s) and low cooling rates (<0.1°C/s) were used. The elimination of β-AlFeSi at low cooling rates may be attributable to a decrease in the magnitude of microsegregation associated with low cooling rates. The disappearance of β-AlFeSi at high cooling rates may be related to growth difficulties when this phase precipitates during solidification of eutectic Al−Si: β-AlFeSi precipitation approaches the solidification onset of eutectic Al−Si when the cooling rate is increased. Moreover, the cooling rate at which the β-AlFeSi phase is suppressed should depend on the chemical composition of the alloy. According to thermodynamic simulations, the alloy composition determines the precipitation onset temperature of both β-AlFeSi (Tβ) and eutectic Al−Si (Teut). The cooling rate at which the β-AlFeSi phase disappears may be even higher as the difference betweenTβ andTeut increases.

Predictions of effective physical properties of complex multiphase materials

Abstract: Theoretical prediction of effective properties for multiphase material systems is very important not only to analysis and optimization of material performance, but also to new material designs. This review first examines the issues, difficulties and challenges in prediction of material behaviors by summarizing and critiquing the existing major analytical approaches dealing with material property modeling. The focus then shifts to some recent advances in numerical methodology that are able to predict more accurately and efficiently the effective physical properties of multiphase materials with complex internal microstructures. A random generation-growth algorithm is highlighted for reproducing multiphase microstructures, statistically equivalent to the actual systems, based on the geometrical and morphological information obtained from measurements and experimental estimations. Then a high-efficiency lattice Boltzmann solver for the corresponding governing equations is described which, while assuring energy conservation and the appropriate continuities at numerous interfaces in a complex system, has demonstrated its numerical power in yielding accurate solutions. Various applications are provided to validate the feasibility, effectiveness and robustness of this new methodology by comparing the predictions with existing experimental data from different transport processes, accounting for the effects due to component size, material anisotropy, internal morphology and multiphase interactions. The examples given also suggest even wider potential applicability of this methodology to other problems as long as they are governed by the similar partial differential equation(s). Thus, for given system composition and structure, this numerical methodology is in essence a model built on sound physics principles with prior validity, without resorting to ad hoc empirical treatment. Therefore, it is useful for design and optimization of new materials, beyond just predicting and analyzing the existing ones.