Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
<mark>Journal publication date</mark> | 12/2008 |
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<mark>Journal</mark> | Computational Materials Science |
Issue number | 2 |
Volume | 44 |
Number of pages | 12 |
Pages (from-to) | 678-689 |
Publication Status | Published |
<mark>Original language</mark> | English |
A computational method for the design of precipitation hardened stainless steel is presented which combines genetic algorithms and thermodynamic computations. The aim of the algorithm is finding compositional scenarios for stainless steels displaying yield strength values exceeding those of their existing commercial counterparts. Strengthening results from ensuring the presence of fine lath martensite and a variety of nanoprecipitates. Using no less than 13 alloying elements, constrained by realistic minimum and maximum levels, the model leads to the design of four alloys for which strengthening is the result of either MC carbides, Cu, Ni rich intermetallics, or a combination of all of them. The model predictions are also compared to a variety of existing commercial high-end engineering steels, showing that the design strategy presented here may potentially lead to significant improvements in strength, while at the same time keeping the Cr level in the matrix above the critical corrosion protection level of 12 wt%.