Evaluation of the electrical resistivity of steels

Literature data on the physical properties of sleets have been collected an d put into a database. The resistivity of steers has been analyzed as a fun ction of composition and microstructure. An overview over former studies is given. The steels have been investigated in two groups, ferritic steels an d austenitic steels. A thermodynamic analysis with ThermoCalc has been perf ormed. Regression analysis on the influence of composition on the resistivi ty was then carried out. The results for ferritic steels are: Si and Al have the highest elemental r esistivity, 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 ce mentite is not considered separately. C in solution with ferrite shows no s ignificant effect. Cr bound in cementite shows a significant effect but Mn, though present in cementite in comparable amounts, has no significant effe ct on the resistivity. N and C have the highest elemental resistivity in austenite, followed by th e substitutional solutes Nb, Si, Ti, Cu, Ni, Mo, and Cr. The carbides NbC a nd 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. Cr23C6 shows no significant effect. The regression results can be used to predict the resistivity of steels wit h known composition. The model predicts the resistivity of ferritic steels with a maximum deviation between experimental and computed value of 12 n Om egam and a standard deviation of 5.6 n Omegam. For austenitic steels, the m odel prediction shows a maximum deviation of 52 mu Omegam and a standard de viation of 20 n Omegam.