Computational Design of Functionally Graded Materials from Sintered Powders
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A new computational method is presented for the efficient design of alloy systems in functionally graded materials (FGMs), optimized for manufacturability (sintering) as well as performance. The design methodology uses a multi-objective genetic algorithm (GA) integrated with computational thermodynamics and physics-based predictive models to optimize the composition of each alloy in the FGM. Thermodynamic modeling, using the CALPHAD method, is used to establish microstructural constraints and calculate the effective diffusivity in each alloy of the FGM. Physics-based predictive models are used to estimate performance properties. The model is verified by comparing results with data from the literature. A design exercise is also presented for an FGM that combines a ferritic and an austenitic stainless steel to demonstrate the capability of the methodology. It is shown that the mismatch in sintering rate between the two alloys, which causes processing defects during co-sintering, can be minimized while the solution hardening and corrosion resistance in the austenitic alloy can be optimized by independently controlling the composition of both alloys, the initial particle sizes and the sintering temperature.
KeywordsIntegrated Computational Materials Engineering (ICME) Functionally graded materials Design of alloys Sintering
G.B.S. conceived the initial idea, supervised the project, and contributed to writing the manuscript. T.T.M. extended the idea, developed the model, performed simulations, and wrote the manuscript. J.Z.L. provided critical comments and contributed to revisions of the manuscript.
This work was funded by The University of Melbourne.
Compliance with Ethical Standards
The authors declare that they have no competing interests.
- 3.Deschamps A, Tancret F, Benrabah I-E, De Geuser F, Van Landeghem HP (2018) Combinatorial approaches for the design of metallic alloys. Comptes Rendus Phys 19:737–754Google Scholar
- 5.Molla TT, Liu JZ, Schaffer GB (2018) An ICME framework for design of stainless steel for sintering. Integr Mater Manuf Innov 7:136–147Google Scholar
- 11.Mulser M, Baumann A, Ebert S, Imgrund P, Langer I, Petzoldt F (2014) Materials of high hardness and wear resistance joined to stainless steel by 2C-MIM. Adv Powder Metall & Part Mater 4:140–148Google Scholar
- 19.Perrut M (2015) Thermodynamic modeling by the calphad method and its applications to innovative materials. J AerospaceLab:1–11. https://doi.org/10.1276/212015.AL09.10
- 20.Rahaman MN (2008) Sintering of ceramics, Taylor and Francis Group, Boca RatonGoogle Scholar
- 24.McGuire MF (2008) Stainless steels for design engineers. ASM International, Materials ParkGoogle Scholar
- 25.Shukla PK, Deb K (2007) On finding multiple Pareto-optimal solutions using classical and evolutionary generating methods. Eur J Oper Res 181:1630–1652Google Scholar
- 26.Jamaludin KR, Muhamad N, Rahman MNA, Amin SYM, Ahmad S, Ibrahim MHI (2009) Sintering Parameter Optimisation of the SS316L metal injection molding (MIM) compacts for final density using Taguchi Method, 3rd South East Asian Tech. Univ Consort Symp:258–262Google Scholar