Literature data on the physical properties of steels have been collected and put into a database. The resistivity of steels has been analyzed as a function of composition and microstructure. An overview over former studies is given. The steels have been investigated in two groups, ferritic steels and austenitic steels. A thermodynamic analysis with ThermoCalc has been performed. Regression analysis on the influence of composition on the resistivity was then carried out.The results for ferritic steels are: Si and Al have the highest elemental resistivity, followed by Mn, Cu, Ni, Mo, and Cr. C precipitated in cementite shows a high coefficient in the analysis when the amount of Fe bound in cementite is not considered separately. C in solution with ferrite shows no significant effect. Cr bound in cementite shows a significant effect but Mn, though present in cementite in comparable amounts, has no significant effect on the resistivity.N and C have the highest elemental resistivity in austenite, followed by the substitutional solutes Nb, Si, Ti, Cu, Ni, Mo, and Cr. The carbides NbC and TiC appear with a higher coefficient in the regression model than can be explained by phase-mixture models providing upper and lower bounds for the resistivity of two-phase alloys. Cr_(23)C_6 shows no significant effect.The regression results can be used to predict the resistivity of steels with known composition. The model predicts the resistivity of ferritic steels with a maximum deviation between experimental and computed value of 12 n#OMEGA#m and a standard deviation of 5.6 n#OMEGA#m. For austenitic steels, the model prediction shows a maximum deviation of 52 n#OMEGA#m and a standard deviation of 20 n#OMEGA#m.
展开▼
