ArticleMaterials (Basel, Switzerland)2026
Electrical Resistance-Based Characterization of Carbon Steel Using Controlled Current Injection and Parameter Estimation.
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Abstract
Electrical resistance measurements can provide supplementary information for the characterization of carbon steels, since resistivity is influenced by composition, microstructure, geometry, processing history, and temperature. This work presents an experimental methodology for the electrical resistance-based characterization of AISI 1045 carbon steel specimens using controlled current injection and parameter estimation. The proposed system integrates a DC-modulated excitation stage, a four-terminal measurement configuration, voltage, current, and temperature acquisition, signal preprocessing, and offline resistance estimation using Python 3 scripts. Ten cylindrical specimens were evaluated through 10 repeated characterization experiments per sample, yielding 100 characterization records, each containing 100,000 voltage, current, and temperature measurements. The sample resistance is estimated using a least-squares formulation based on synchronized voltage-current data and is compared with a mean-based estimator derived from instantaneous resistance values. The results show that the least-squares estimator produced repeatable resistance values concentrated within a narrow interval, from approximately 443.43μΩ to 445.55μΩ, with interquartile ranges below 4.46μΩ for all specimens. In contrast, the mean-based estimator exhibited larger resistance values and substantially higher dispersion. The least-squares resistance-derived resistivity values ranged from 1.823×10-7 to 2.263×10-7Ω·m, which is consistent with the expected order of magnitude for AISI 1045 steel when compared with temperature-dependent theoretical reference values. The corresponding relative differences ranged from 1.94% to 11.00%, with most specimens remaining below 6%. These findings indicate that controlled current injection, combined with four-terminal sensing, signal preprocessing, and least-squares estimation, provides a reproducible framework for the low-resistance characterization of carbon steel specimens. Although the present study focuses on AISI 1045 steel, the methodology may be adapted to other metallic specimens, steel grades, heat-treated samples, or controlled thermal-cycle experiments, provided that geometry, temperature, calibration, and material-specific reference conditions are properly considered.
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