Understanding solidification of near eutectic alloy using Cellular Automata (CA)

Indranil Roy, Matt Rolchigo, John Coleman, Shuanglin Chen, Alex Plotkowski, Ying Yang

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The solidification microstructure of an alloy strongly influences the mechanical properties. Dendritic and eutectic solidification are two important pathways of alloy solidification. The formation of phases, and their size and distribution depend on which pathway to take. In contrast to the Scheil model that has been widely used in describing the solidification pathways of alloys manufactured from conventional casting approach, more sophisticated solidification models are required to describe the state-of-the art manufacturing processes, such as additive manufacturing where distinctly different phase morphology, size and distribution than conventional casting can form, due to the vast difference in cooling conditions. Therefore, this work is to develop a computational Cellular Automata framework which includes the modeling of nucleation and growth of dendritic and eutectic solidification, as well as their competition as a function of alloy composition, undercooling and cooling rate. After individual solidification models were validated against analytical solutions, the models were then combined to predict the competition between dendritic and eutectic solidification in alloys with off-eutectic compositions. This work predicts increased cooling rates suppress the dendritic solidification and promote eutectic solidification. Although quantitative validation is needed, this finding is consistent with qualitative observation in literature.

Original languageEnglish
Article number112835
JournalComputational Materials Science
Volume236
DOIs
StatePublished - Mar 2024

Funding

This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE) . The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan ( https://www.energy.gov/doe-public-access-plan ). This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (https://www.energy.gov/doe-public-access-plan).Research was sponsored by the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office, Propulsion Materials Program. This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. Research was sponsored by the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office , Propulsion Materials Program. This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy .

Keywords

  • Cellular Automata
  • Dendritic growth
  • Eutectic transformation
  • Microstructure modeling
  • Solidification simulation
  • Solute segregation

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