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Review

Advances in Magnetic and Electrochemical Techniques for Monitoring Corrosion and Microstructural Degradation in Steels

by
Polyxeni Vourna
1,*,
Pinelopi P. Falara
2,
Aphrodite Ktena
3,
Evangelos V. Hristoforou
4 and
Nikolaos D. Papadopoulos
5
1
Institute of Nanoscience and Nanotechnology, National Centre for Scientific Research “Demokritos”, 15341 Agia Paraskevi, Greece
2
School of Chemical Engineering, National Technical University of Athens, 9 Iroon Polytechniou Str., Zografou, 15772 Athens, Greece
3
General Department, National and Kapodistrian University of Athens, 15784 Athens, Greece
4
Institute of Communication and Computer Systems, 15773 Athens, Greece
5
Department of Research and Development, BFP Advanced Technologies G.P., 11633 Athens, Greece
*
Author to whom correspondence should be addressed.
Metals 2026, 16(3), 352; https://doi.org/10.3390/met16030352
Submission received: 26 February 2026 / Revised: 18 March 2026 / Accepted: 20 March 2026 / Published: 21 March 2026
(This article belongs to the Special Issue Novel Insights into Corrosion and Electrochemical Behavior of Metals and Alloys)
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Abstract

Steels remain among the most widely used structural and engineering materials in modern infrastructure, energy systems, and industrial facilities. Their long-term reliability depends critically on the early detection of corrosion damage and microstructural degradation. This review surveys recent advances in two complementary families of non-destructive evaluation (NDE) methods: magnetic techniques, including magnetic Barkhausen noise (MBN), magnetic flux leakage (MFL), eddy current testing (ECT), and magnetic hysteresis analysis; and electrochemical methods including electrochemical impedance spectroscopy (EIS), linear polarization resistance (LPR), scanning vibrating electrode technique (SVET), and electrochemical noise (EN). Recent progress in sensor miniaturization, signal processing algorithms, and multi-technique integration is reviewed. Particular attention is given to the sensitivity of these methods to microstructural changes reported in the literature, including carbide dissolution, phase transformations, temper embrittlement, and sensitization in stainless steels, as well as to the conditions under which such sensitivity has been demonstrated. The potential synergy between magnetic and electrochemical monitoring is discussed as a possible pathway toward more robust, condition-based maintenance frameworks. Challenges related to field deployment, environmental interference, calibration, and data interpretation are identified, and future directions—including machine learning-assisted analysis and multi-physics sensor arrays—are outlined.

1. Introduction

Steels constitute the backbone of civil, mechanical, and energy infrastructure worldwide. Despite their mechanical robustness and versatility, steels are highly susceptible to corrosion and microstructural degradation under service conditions, particularly in harsh chemical, thermal, or electrochemical environments [1,2]. Corrosion-induced losses are estimated to represent 3–4% of GDP in industrialized nations, with a significant fraction attributable to inadequate or delayed monitoring of structural components [3].
The degradation of steel in service is rarely a simple surface dissolution process. Rather, it is intimately coupled to microstructural evolution: grain boundary sensitization, carbide precipitation, temper embrittlement, hydrogen embrittlement, and phase transformations all alter the electrochemical reactivity as well as the magnetic domain structure of the material [4]. This coupling creates an opportunity for cross-disciplinary monitoring strategies that exploit both the magnetic and electrochemical fingerprints of microstructural change.
Non-destructive evaluation (NDE) methods are essential for assessing damage without removing or impairing the component under test [5,6,7]. Among the available NDE toolbox, magnetic methods are considered particularly well-suited for ferromagnetic steels, since their domain structure has been shown to respond sensitively under appropriate measurement conditions to stress, plastic strain, and phase composition [8,9]. Simultaneously, electrochemical techniques can provide direct kinetic and thermodynamic information about the metal–electrolyte interface, including insights into passive film stability, pitting susceptibility, and general corrosion rate [10].
Despite the complementary nature of these two method families, reviews that treat them in a unified framework are relatively scarce. The present article aims to address this gap by: (i) providing a concise account of the physical and electrochemical principles underlying each technique; (ii) reviewing recent experimental and field-deployment advances; (iii) discussing how combined magnetic–electrochemical protocols may enhance detection sensitivity and diagnostic specificity; and (iv) identifying open challenges and future research directions.
It should be noted that several important NDE technique families are not covered in this review. Acoustic emission (AE) and guided ultrasonic wave (GUW) methods are widely used in conjunction with magnetic NDE for pipeline and structural inspection, and represent a significant complementary toolbox. Their omission here is deliberate: the unique contribution of this review is the synthesis of the magnetic–electrochemical pairing, which has not been comprehensively treated elsewhere and constitutes a distinct monitoring paradigm. Readers interested in AE and GUW methods are directed to dedicated recent reviews [11,12,13]. Similarly, radiographic and thermographic methods, while capable of corrosion imaging, are outside the scope of this review.
Two recent review articles from our group address complementary but distinct aspects of MBN technology: Vourna et al. [14] provided a comprehensive treatment of MBN sensor design and signal processing across material characterization applications, while Vourna et al. [15] focused on MBN sensitivity to crystallographic texture and stress–microstructure coupling in steels. The present review is distinguished by its focus on corrosion and microstructural degradation monitoring and by its integration of electrochemical techniques alongside magnetic methods. No text, figures, or data are reproduced from References [14] or [15].

2. Magnetic Techniques for Corrosion and Microstructural Monitoring

The magnetic properties of ferritic, martensitic, and duplex steels depend on their microstructure through the coupling between magnetic domains and crystal defects, phase boundaries, and residual stress fields. This coupling makes magnetic methods sensitive to a wide range of damage mechanisms, from surface pitting to deep-seated phase transformations [8,16].

2.1. Magnetic Barkhausen Noise (MBN)

When a ferromagnetic steel is exposed to a cyclic magnetic field, domain walls undergo discontinuous, irreversible jumps—a phenomenon known as Barkhausen emission. The resulting voltage pulses (Barkhausen noise, MBN), detected by a pickup coil (Figure 1a), carry information about domain wall pinning sites, which include dislocations, precipitates, grain boundaries, and stress concentrations [14,15,17,18]. The MBN coil geometry, MFL leakage field configuration, and PEC probe design depicted in Figure 1 are based on the configurations described in [19], [20], and [21], respectively.
Corrosion-induced microstructural changes have been reported to systematically alter the MBN signal. Studies on low-alloy pipeline steels have suggested that selective dissolution of pearlite colonies increases the MBN amplitude due to the progressive reduction in cementite pinning sites [22,23,24,25]. Conversely, the formation of iron oxide layers has been associated with the suppression of high-frequency MBN components, an effect attributed to the surface oxide layer acting as a magnetic shunt [26,27,28,29,30]. Residual tensile stresses introduced by corrosion pitting have been reported to produce a characteristic shift of the MBN peak position toward lower applied fields [31,32,33,34].
Recent advances in signal processing—including wavelet decomposition and power spectral analysis—have improved the depth-selectivity of MBN, enabling the independent assessment of surface and subsurface regions [35]. Portable MBN instruments with permanent magnet excitation are now commercially available, facilitating the in situ inspection of pipelines, pressure vessels, and structural welds [36].
Compared with other magnetic NDE techniques, MBN offers the best sensitivity to near-surface microstructural state and residual stress, but its shallow penetration depth (<1 mm) and dependence on surface condition make it complementary to—rather than a replacement for—bulk methods such as magnetic hysteresis analysis or volumetric methods such as MFL. Its main competitive advantage over ECT lies in its direct coupling to the ferromagnetic domain structure, which provides microstructural information (dislocation density, phase fraction) that ECT cannot resolve.

2.2. Magnetic Hysteresis Analysis

The quasi-static magnetic hysteresis loop (B–H curve) encodes fundamental material parameters: coercivity (Hc), remanence (Br), and saturation magnetization (Ms). Each parameter responds differently to microstructural changes [37,38,39]. Coercivity is sensitive to domain wall pinning and increases with dislocation density and fine precipitate concentration; saturation magnetization tracks the ferrite volume fraction and decreases as austenite or non-magnetic phases form [40,41].
In the context of thermal aging and the sensitization of martensitic stainless steels, hysteresis measurements have been used to track carbide coarsening during tempering at 500–700 °C, which progressively reduces Hc as pinning sites are consumed [42,43,44]. For duplex stainless steels (DSSs), changes in the ferrite/austenite ratio due to spinodal decomposition at 280–500 °C are directly reflected in Ms [43,45,46]. First-order reversal curve (FORC) diagrams, which provide a 2D representation of the reversible and irreversible magnetization components, have recently been applied to steels to resolve overlapping phase contributions in complex microstructures [47].
Magnetic hysteresis analysis provides bulk-averaged information unavailable to surface-sensitive methods such as MBN or MFL. Its primary limitation relative to other magnetic NDE techniques is the requirement for laboratory sample extraction: it cannot be applied in situ. In this regard, it is best used as a reference calibration tool—establishing the magnetic signature of a known microstructural state—against which field measurements from portable MBN or permeability sensors can be interpreted. VSM and FORC offer higher information content rather than single-parameter coercimetry, but at a significantly greater cost and measurement time.

2.3. Magnetic Flux Leakage (MFL)

MFL is one of the most widely deployed NDE methods for in-service pipeline inspection. A strong permanent magnet or electromagnet saturates the steel wall; at regions of wall thinning, pitting, or cracks, the magnetic flux leaks out of the surface and is detected by Hall sensors or fluxgate magnetometers [20,48,49,50,51,52,53] (Figure 1b).
Modern MFL tools (inline inspection, ILI) can detect corrosion defects with axial extents as small as 10 mm; under controlled, low-speed laboratory conditions, depth sizing accuracies of ±0.1 mm have been reported at pipe wall thicknesses up to 20 mm [52,54,55]. However, in-service performance is more variable: at tool travel speeds above approximately 1 m/s, velocity-induced signal distortion degrades the depth sizing accuracy substantially unless dedicated correction algorithms are applied [20], and practical ILI depth tolerances per API 1163 are typically cited as ±10% of wall thickness (i.e., ±2 mm for a 20 mm wall). Finite element modeling (FEM) of the flux leakage signature has enabled the inverse reconstruction of defect geometry from sensor signals [56]. Recent developments include tri-axial sensor arrays that improve angular sensitivity and the use of pulsed MFL to extend inspection frequency bandwidth, thus enhancing depth discrimination [20,53,57].
MFL is uniquely suited to the full-wall-thickness screening of large ferromagnetic structures such as pipelines and storage tanks, a capability that MBN (surface-only) and ECT (limited penetration) cannot match at comparable inspection speeds. Its principal disadvantage relative to ECT is the requirement for magnetic saturation of the component, which demands high-field electromagnets or strong permanent magnets and limits applicability to wall thicknesses below approximately 20 mm without signal degradation. Against SQUID magnetometry, MFL is orders of magnitude less sensitive but orders of magnitude more field-practical and cost-effective.

2.4. Eddy Current Testing (ECT)

When a coil carrying an alternating current is brought close to a conducting material, eddy currents are induced in the surface region. The impedance change of the coil reflects variations in electrical conductivity, magnetic permeability, and specimen geometry [58,59,60,61]. ECT is sensitive to surface and near-surface defects and has been extensively applied to detect corrosion thinning and stress corrosion cracking (SCC) in heat exchanger tubes, aircraft components, and nuclear structures [62,63].
In corrosion monitoring applications, pulsed eddy current (PEC) testing (Figure 1c) is increasingly preferred over single-frequency ECT because the transient response contains information across a range of depths simultaneously, enabling wall-thickness profiling through insulation without direct contact [62,64,65,66]. Array ECT probes with up to 64 sensing elements provide C-scan corrosion maps with millimeter-scale lateral resolution [67].
ECT occupies a unique position among magnetic NDE techniques in being applicable to both ferromagnetic and non-ferromagnetic materials (the latter inaccessible to MBN, MFL, and hysteresis methods). Its sensitivity to near-surface geometry changes (cracks, wall thinning) is comparable to MBN, but it yields no direct microstructural information because eddy current impedance reflects electrical conductivity and permeability rather than domain wall pinning. Pulsed ECT extends the depth advantage over standard single-frequency ECT substantially, approaching MFL-class penetration without requiring magnetic saturation.

2.5. SQUID-Based and Flux-Gate Magnetometry

Superconducting quantum interference device (SQUID) magnetometers offer unmatched sensitivity (∼10−15 T/√Hz) and have been applied to map stray magnetic fields arising from deeply buried corrosion products and residual stress distributions in steel structures [68]. In corrosion-specific applications, SQUID-based passive magnetic anomaly mapping has been reported to detect localized corrosion clusters in reinforced concrete at cover depths exceeding 50 mm, where the paramagnetic-to-ferrimagnetic transformation of iron corrosion products (formation of magnetite, Fe3O4, and maghemite, γ-Fe2O3) generates a measurable stray field anomaly [69]. The technique requires no active magnetization of the component, making it particularly suited to structures where the application of external magnetic fields is impractical or where residual magnetization would interfere with subsequent measurements.
The principal practical limitation of conventional low-Tc SQUID systems is the requirement for liquid helium cooling (4.2 K), which severely restricts field deployment. High-temperature superconducting (HTS) SQUID systems operating at liquid nitrogen temperature (77 K) have partially addressed this constraint and have been demonstrated in the laboratory-scale corrosion mapping of steel plates [70]. More recently, optically pumped magnetometers (OPMs) operating at room temperature have emerged as a promising alternative, offering field sensitivity in the range of 10−14–10−13 T/√Hz—approaching low-Tc SQUID performance without cryogenic requirements [71]. OPM-based systems have been proposed for pipeline corrosion monitoring and buried structure inspection, though field validation on in-service infrastructure remains limited.
Fluxgate magnetometers, which operate at room temperature and provide a field resolution of ∼10−10 T, represent the most field-practical option in the high-sensitivity magnetometry family. They have been applied to detect corrosion-associated magnetic anomalies in structural steel components and buried pipelines by mapping the passive remanent field distribution without active excitation [72]. Compared with MBN and MFL, SQUID and fluxgate magnetometry occupy a distinct operational niche: they are passive techniques sensitive to the intrinsic magnetic signature of corrosion products and residual stress fields rather than to defect-induced perturbations of an applied field. This makes them uniquely suited to detecting deeply buried or inaccessible corrosion where active magnetization is not feasible, but it also means that they provide no direct information on wall thickness loss or domain wall pinning state. Their spatial resolution is fundamentally limited by the sensor-to-target distance, which degrades rapidly with depth. Table 1 summarizes and compares the key performance metrics of all five magnetic NDE techniques reviewed in this section.

3. Electrochemical Techniques for Corrosion Monitoring

Electrochemical methods probe the metal–electrolyte interface directly and can provide quantitative information on corrosion rates, passivity, and localized dissolution mechanisms. They range from simple potential measurements to advanced scanning probe techniques with micrometer spatial resolution [73,74].

3.1. Electrochemical Impedance Spectroscopy (EIS)

EIS involves the application of a small-amplitude sinusoidal voltage perturbation (typically 5–20 mV RMS) over a frequency range of 10−3–105 Hz and measurement of the resulting current response [75]. The technique is inherently non-destructive: the small-amplitude perturbation does not alter the electrode surface or passive film, permitting repeated measurements on the same specimen over time and making EIS particularly suited to in situ and long-term corrosion monitoring. The impedance spectrum is fitted to an equivalent circuit model that is intended to represent the physical elements of the corroding interface: solution resistance (Rs), double-layer capacitance (Cdl), charge transfer resistance (Rct), and diffusion elements [1,4,76]. A schematic illustration of the three-electrode cell configuration and measurement workflow is provided in Figure 2.
EIS has been widely applied to investigate the protective properties of passive films on stainless steels and to follow their degradation upon chloride exposure [77,78,79,80,81] (Figure 3). The high-frequency loop in the impedance plane reflects the compact oxide layer, while a low-frequency capacitive loop is associated with defect-mediated ion transport. The time evolution of Rct has been reported to provide a semi-quantitative measure of the corrosion rate without the need for direct current (DC) polarization [82]. Increasing chloride concentration is thought to destabilize the passive film through competitive adsorption of Cl− at oxide surface sites, reducing the charge transfer resistance Rct and manifesting as a progressive decrease in the diameter of the semicircle in the Nyquist plot (Figure 3).
In the context of microstructural monitoring, EIS has been applied to follow sensitization in austenitic stainless steels (ASTM A262) [83] and to correlate impedance parameters with chromium depletion at grain boundaries [84,85]. The decrease in passive film resistance (Rpf) upon sensitization provides a direct electrochemical proxy for the degree of carbide precipitation.
Cross-study comparability of EIS results remains a practical challenge, as key sources of variability include electrode area, electrolyte composition and temperature, immersion time prior to measurement, and frequency range. ASTM G106 [86] provides standard practice guidance for EIS in corrosion studies, while ISO 16773 (Parts 1–4) [87,88,89,90] addresses terminology and measurement validation for coated specimens. It is important to note a fundamental limitation of EIS equivalent circuit analysis: the non-uniqueness problem. Multiple circuit topologies can produce identical or near-identical fits to the same impedance spectrum, particularly in systems with overlapping time constants. For example, a two-time-constant spectrum arising from a bilayer passive film (inner barrier oxide + outer hydrated layer) is mathematically indistinguishable from a spectrum produced by a film with a single time constant and a distributed Warburg diffusion element. Physical interpretation of circuit elements therefore requires independent corroboration from surface analysis techniques such as X-ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM), or scanning electrochemical microscopy (SECM). This limitation is discussed further in Section 6.2 in the context of calibration and standardization challenges.

3.2. Linear Polarization Resistance (LPR)

The Stern–Geary method is used to relate the polarization resistance Rp, measured from the slope of the E–I curve in a ±20 mV window around Ecorr, to the instantaneous corrosion current density icorr via icorr = B/Rp, where B is a constant (typically 26 mV for active dissolution) [91,92]. LPR sensors have been permanently embedded in pipelines, concrete, or process streams for real-time corrosion rate monitoring.
Recent developments include multielectrode array (MEA) sensors that simultaneously measure localized and general corrosion rates on a single probe, providing statistical information on the distribution of pitting events [93]. Wireless LPR transmitters with onboard data loggers have been deployed in offshore and nuclear environments, enabling condition-based maintenance strategies [92].

3.3. Potentiodynamic and Potentiostatic Polarization

Polarization curves obtained by sweeping the electrode potential at a controlled scan rate reveal the kinetics of anodic dissolution, passive film formation, and breakdown (pitting potential, Epit). Critical pitting temperature (CPT) measurements under potentiostatic conditions are standardized methods for ranking the pitting resistance of stainless steels and duplex alloys [94].
In the study of microstructural effects, potentiodynamic polarization has been used to quantify the impact of δ-ferrite content on the pitting resistance of super-duplex stainless steels [95,96,97,98,99,100], to evaluate the intergranular corrosion susceptibility of sensitized alloys, and to characterize the galvanic coupling between martensite and austenite in dual-phase steels [101,102].

3.4. Scanning Electrochemical Techniques (SVET, LEIS, SECM)

The scanning vibrating electrode technique (SVET) maps the local current density above a corroding surface by measuring the AC potential gradient generated by the vibrating probe. SVET has been widely used in visualizing the spatial distribution of anodic and cathodic sites on coated steels, weld heat-affected zones (HAZs), and galvanically coupled assemblies [103,104,105] (Figure 4).
Local electrochemical impedance spectroscopy (LEIS) combines the spatial resolution of scanning techniques with the mechanistic information of impedance analysis, yielding maps of local Rct and Cdl [106,107]. Scanning electrochemical microscopy (SECM) uses a redox mediator to image local electrochemical activity with submicron resolution and has been applied to investigate early-stage pitting nucleation on Type 304 and 316L stainless steels [108,109,110,111,112,113].

3.5. Electrochemical Noise (EN)

Electrochemical noise refers to the spontaneous fluctuations in corrosion potential and current that arise from the stochastic nature of anodic dissolution, passive film formation, and pit nucleation events (Figure 5). EN signals are acquired passively (no perturbation) from a pair of nominally identical electrodes [114,115,116]. Statistical parameters such as noise resistance (Rn), skewness, and kurtosis, as well as time–frequency analysis via wavelet transforms, are used to distinguish corrosion mechanisms [117].
EN has been reported to provide indications of pitting initiation on 316L stainless steel in chloride solutions before any significant mass loss occurs [118,119,120,121] and to follow the onset of SCC in sensitized alloy 600 under BWR conditions [122]. The combination of EN with EIS in a sequential protocol improves the reliability of mechanism assignment, particularly when multiple corrosion processes are active simultaneously. Table 2 provides a structured comparison of the five electrochemical techniques reviewed in this section.
A key practical challenge in EN interpretation that must be acknowledged is the problem of drift and signal stationarity. EN time series typically exhibit low-frequency drift arising from gradual changes in the corrosion potential and film state, which violates the stationarity assumption underlying many statistical descriptors (noise resistance Rn, skewness, kurtosis). Failure to remove this drift prior to analysis can lead to gross overestimation of Rn and erroneous mechanism classification. Common drift removal approaches include linear detrending (subtracting a least-squares straight-line fit) and high-pass digital filtering; each approach introduces artifacts at different frequency ranges and can affect the estimated noise resistance by up to an order of magnitude, as discussed by Bertocci et al. [117]. This framework for EN analysis remains an unresolved methodological controversy: no consensus standard for drift removal exists, and different laboratories applying different procedures to the same dataset may reach different mechanistic conclusions. This limitation is discussed further in Section 6.2.

4. Combined Magnetic–Electrochemical Monitoring Strategies

Magnetic and electrochemical techniques probe fundamentally different physical manifestations of steel degradation, and it is precisely this complementarity that makes their combined deployment powerful. Magnetic methods (MBN, MFL, magnetic hysteresis) are sensitive to changes in the ferromagnetic domain structure arising from stress, plastic strain, dislocation accumulation, and phase transformations—all of which alter the energy landscape for domain wall motion. Electrochemical methods (EIS, LPR, EN) probe the metal–electrolyte interface directly, reflecting passive film stability, charge transfer kinetics, and local dissolution activity. Because the most industrially critical failure modes—stress corrosion cracking (SCC), hydrogen embrittlement, and sensitization—simultaneously produce both a microstructural or mechanical signature (detectable magnetically) and an interfacial electrochemical signature (detectable electrochemically), the combined approach enables earlier detection and more definitive mechanism assignment than either method family can achieve alone. For example, in SCC initiation, the electrochemical breakdown of the passive film (rising EIS phase angle loss, EN transients) typically precedes the development of a detectable crack-tip stress field (MBN amplitude increase); monitoring both signals in parallel therefore extends the detection window into the pre-cracking stage. This mechanistic synergy is the central argument for the integrated monitoring strategies reviewed in this section. Specific examples of this synergy are presented in the following subsections: SCC monitoring via combined MBN and EIS (Section 4.1), phase transformation tracking via magnetic hysteresis and polarization methods (Section 4.2), and spatial corrosion mapping via MFL and SVET (Section 4.3)

4.1. Coupling MBN with EIS for Stress Corrosion Cracking Assessment

Stress corrosion cracking (SCC) combines mechanical loading, electrochemical dissolution, and microstructural embrittlement [123,124,125,126,127,128]. The integrity of protective coatings is a critical factor in SCC management, since coating degradation creates occluded microenvironments with elevated chloride activity and reduced pH that accelerate crack initiation. Recent studies on biocide-free antifouling coatings applied to naval steels under simulated and natural seawater conditions [124,125,126,127] illustrate how coating performance directly influences the local electrochemical conditions governing SCC susceptibility. MBN has been shown to be sensitive to the crack-tip stress field and the plastic zone damage, while EIS has been used to follow the dissolution kinetics at the crack tip and the integrity of the passive film. The complementary use of both methods on sensitized austenitic stainless steels has revealed that a reduction in Rpf (from EIS) precedes the increase in MBN amplitude associated with crack-tip plasticity, suggesting that electrochemical film breakdown may represent the initiating step [129].
This temporal offset between the electrochemical and magnetic signatures provides a basis for early-warning algorithms that flag SCC initiation before macroscopic cracking occurs. Miniaturized sensor probes integrating a fluxgate pickup coil and a three-electrode electrochemical cell have been prototyped for deployment on pressure vessel welds [130].

4.2. Tracking Phase Transformations with Magnetic Hysteresis and Polarization

In duplex stainless steels, sigma-phase precipitation at ferrite/austenite boundaries between 700 and 900 °C dramatically increases intergranular corrosion susceptibility while simultaneously reducing Ms (due to the loss of ferromagnetic δ-ferrite) [131]. The correlation between the decrease in Ms from vibrating sample magnetometry (VSM) and the increase in intergranular dissolution current density from double-loop electrochemical potentiokinetic reactivation (DL-EPR) testing has been demonstrated for both Type 2205 and 2507 DSS [132,133].
This dual magnetic–electrochemical fingerprinting is now being extended to in-service monitoring scenarios through portable permanent-magnet-based susceptibility measurements and embedded electrochemical probes, enabling phase fraction estimation without sample extraction.

4.3. Corrosion Mapping with MFL and SVET

MFL and SVET operate on different principles but both produce spatially resolved maps of corrosion activity. By overlaying MFL-derived wall-thickness profiles with SVET-derived local current density maps on the same coupon or pipe section, researchers have established correlations between the depth of metal loss (magnetic) and the local dissolution rate (electrochemical), which allow for the extrapolation of damage evolution rates [49,134,135,136].
This approach has been validated on API 5L X65 pipeline steel in CO2/H2S environments and shows promise for predicting remaining useful life (RUL) under dynamic flow conditions.

4.4. Multi-Sensor Arrays and Data Fusion

The integration of multiple sensors on a single platform—combining eddy current, MBN, EIS, and temperature sensors—enables a multi-physics assessment of steel components without repositioning [137,138,139] (Figure 6). Data fusion algorithms, including principal component analysis (PCA) and independent component analysis (ICA), have been applied to disentangle overlapping signals from different degradation mechanisms [140,141].
Machine learning approaches have recently demonstrated strong performance in corrosion classification from electrochemical signals. Homborg et al. [142] treated electrochemical noise time–frequency spectra as an image classification problem, applying a CNN to continuous wavelet transform representations of EN transients from AISI 304 stainless steel in HCl and AA2024-T3 aluminum in NaCl; the combined feature set achieved a classification accuracy of 0.97, though the training dataset comprised only 11 raw EN signals expanded to 480 images through data augmentation. Signal fusion approaches have similarly shown promise on the magnetic NDE side: Efremov et al. [141] demonstrated that multifrequency data fusion in eddy current inspection markedly improved the detection of small cracks in multi-layer structures by suppressing structural noise. The integration of such ML and data fusion strategies with combined magnetic–electrochemical sensor arrays represent a natural next step, though validation on large, field-acquired datasets from in-service steel structures remains to be demonstrated.

5. Microstructural Degradation Mechanisms and Their Signatures

This section summarizes the specific microstructural degradation modes in steels and the magnetic/electrochemical signatures by which they can be identified.

5.1. Sensitization in Austenitic and Duplex Stainless Steels

Sensitization refers to the precipitation of chromium-rich M23C6 carbides at grain boundaries during heating in the 425–870 °C range, creating Cr-depleted zones susceptible to intergranular attack. The DL-EPR (Double-Loop Electrochemical Potentiokinetic Reactivation) ratio Ir/Ia is widely considered the electrochemical benchmark for quantifying sensitization, where Ir is the reactivation current peak density measured during the reverse potential scan, and Ia is the activation current peak density from the forward scan; a higher Ir/Ia ratio indicates a greater degree of sensitization and more extensive Cr depletion at grain boundaries [143]. MBN provides a complementary signal: the loss of paramagnetic austenite grain boundary carbides has a measurable effect on the domain wall pinning landscape in duplex grades [36,144,145,146,147,148].

5.2. Hydrogen Embrittlement and Hydrogen-Induced Cracking

Hydrogen absorbed during cathodic protection, acid pickling, or electroplating segregates to trap sites (dislocations, carbide interfaces, grain boundaries), increasing the local coercivity due to enhanced domain wall pinning [149]. EIS under cathodic polarization reveals hydrogen evolution kinetics and can quantify the hydrogen permeability through thin steel membranes using a modified Devanathan–Stachurski cell configuration [150]. The combination of Hc measurements and hydrogen permeation data provides a comprehensive picture of hydrogen damage accumulation.

5.3. Temper Embrittlement and Carbide Evolution

Martensitic steels subjected to service temperatures in the range 350–550 °C undergo temper embrittlement due to impurity (P, Sb, As) and carbide segregation at prior austenite grain boundaries. The coercive field Hc tracks the dissolution and re-precipitation of transition carbides during tempering [151,152,153]. The EIS of tempered martensitic steels in NaCl solution shows a systematic decrease in Rct with increasing carbide density, reflecting enhanced micro-galvanic coupling [154,155].

5.4. Pipeline Steel Corrosion in H2S/CO2 Environments

Sour service environments containing H2S and CO2 promote both electrochemical corrosion (sweet/sour corrosion) and sulfide stress cracking (SSC). MBN and FORC measurements on API 5L grade steels exposed to simulated sour media have documented progressive increases in domain wall pinning correlated with hydrogen trapping and sulfide scale formation [156]. EIS and EN monitoring in autoclave-based sour service simulators have characterized the impedance evolution of FeCO3/FeS2 scale layers and their influence on pitting susceptibility [157,158].

6. Challenges and Future Directions

Despite considerable progress, several challenges limit the widespread adoption of combined magnetic–electrochemical monitoring systems.

6.1. Field Deployment and Environmental Interference

Magnetic measurements in field environments are affected by stray magnetic fields from nearby electrical equipment, magnetized ground, and residual magnetization of the component itself. Effective shielding and active compensation algorithms are required [159]. Electrochemical methods require direct contact with an electrolyte, which limits their applicability to dry environments without special protective housings or gel electrolyte systems [70].

6.2. Calibration and Standardization

The quantitative interpretation of MBN and magnetic hysteresis signals requires reference calibration specimens with known microstructural states, which are rarely available for in-service components with complex processing histories [24,160]. Similarly, EIS equivalent circuit fitting is inherently non-unique, and physical interpretation of circuit elements requires independent validation by surface analysis (XPS, TEM), as discussed in detail in Section 3.1. Analogously, the interpretation of electrochemical noise signals is hampered by the absence of a consensus standard for drift removal: as noted in Section 3.5, different detrending procedures applied to the same dataset can alter the estimated noise resistance by up to an order of magnitude, leading to divergent mechanistic conclusions across laboratories. Progress toward standardized calibration protocols and benchmark datasets shared across research groups is essential.

6.3. Machine Learning and Digital Twins

The availability of large corrosion sensor datasets has enabled the application of deep learning to feature extraction and failure prediction. Recurrent neural networks (RNNs) and long short-term memory (LSTM) architectures have been applied to time-series analysis of electrochemical impedance data; for example, Ma et al. [161] demonstrated LSTM-based prediction of ionic concentrations in soil from electrical impedance spectral inputs. Direct prediction of EIS spectral evolution from LPR time-series data for steel corrosion monitoring has not yet been demonstrated and represents an open research direction. Digital twin frameworks that couple physics-based corrosion models with real-time sensor data streams have been proposed as the next frontier for predictive maintenance of steel infrastructure [162,163]. Recent implementations have demonstrated real-time convergence between physical pipeline condition data and virtual model states, enabling damage detection, quantification, and remaining useful life prediction within a unified probabilistic framework [162].

6.4. Miniaturization and Wireless Sensing

The miniaturization of both magnetic (giant magnetoresistance, GMR; tunneling magnetoresistance, TMR) and electrochemical (microfabricated three-electrode cells) sensors has enabled the development of wireless sensor nodes that can be permanently installed in confined structures such as concrete-embedded rebars and subsea pipelines [164,165,166,167]. Energy harvesting from mechanical vibration or fluid flow is being explored to power autonomous sensor nodes in inaccessible locations [168].

7. Conclusions

This review surveyed recent advances in magnetic and electrochemical techniques for monitoring corrosion and microstructural degradation in steels, with emphasis on the growing convergence of these two method families. The key conclusions are as follows:
  • Magnetic techniques (MBN, MFL, ECT, magnetic hysteresis) can provide non-contact, depth-sensitive information on microstructural changes, residual stress, and wall-thickness loss that is directly relevant to structural integrity assessment.
  • Electrochemical techniques (EIS, LPR, EN, SVET) can offer mechanistic insight into corrosion kinetics, passive film stability, and localized attack, enabling quantitative corrosion rate determination and improved sensitivity to pitting and SCC initiation.
  • The combined use of magnetic and electrochemical monitoring exploits the complementary sensitivity of the two method families to mechanical and chemical degradation, respectively, and has been demonstrated to improve diagnostic specificity for complex failure modes such as SCC, hydrogen embrittlement, and phase transformation-induced corrosion.
  • Machine learning-assisted data fusion of multi-sensor signals holds significant promise for automated defect classification and remaining useful life prediction.
  • Future progress requires standardized calibration protocols, miniaturized wireless sensor platforms, and digital twin frameworks that seamlessly integrate sensor data with physics-based degradation models.
In conclusion, the complementarity between magnetic NDE and electrochemical monitoring constitutes a powerful and underexploited paradigm for the comprehensive structural health management of steel infrastructure.

Author Contributions

Conceptualization, P.V. and N.D.P.; methodology, P.V. and N.D.P.; investigation, P.V.; formal analysis, A.K. and E.V.H.; validation, A.K. and E.V.H.; data curation, P.P.F., A.K., E.V.H. and P.V.; writing—original draft preparation, P.V. and P.P.F.; supervision, N.D.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Acknowledgments

The authors acknowledge precious help and technical assistance from colleagues working on nanotechnology processes for the solar energy conversion and environmental protection lab of INN/NCSRD.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
ACAlternating Current
AMRAnisotropic Magnetoresistance
APIAmerican Petroleum Institute
ASTMAmerican Society for Testing and Materials
BWRBoiling Water Reactor
CNNConvolutional Neural Network
CPTCritical Pitting Temperature
DCDirect Current
DL-EPRDouble-Loop Electrochemical Potentiokinetic Reactivation
DSSDuplex Stainless Steel
ECTEddy Current Testing
EISElectrochemical Impedance Spectroscopy
ENElectrochemical Noise
FEMFinite Element Modeling
FORCFirst-Order Reversal Curve
GDPGross Domestic Product
GMRGiant Magnetoresistance
HAZHeat-Affected Zone
ICAIndependent Component Analysis
ILIInline Inspection
ISOInternational Organization for Standardization
LEISLocal Electrochemical Impedance Spectroscopy
LPRLinear Polarization Resistance
LSTMLong Short-Term Memory
MBNMagnetic Barkhausen Noise
MEAMultielectrode Array
MFLMagnetic Flux Leakage
MLMachine Learning
MsSaturation Magnetization
NDENon-Destructive Evaluation
NDTNon-Destructive Testing
PCAPrincipal Component Analysis
PECPulsed Eddy Current
RMSRoot Mean Square
RNNRecurrent Neural Network
RULRemaining Useful Life
SCCStress Corrosion Cracking
SECMScanning Electrochemical Microscopy
SQUIDSuperconducting Quantum Interference Device
SSCSulfide Stress Cracking
SVETScanning Vibrating Electrode Technique
TEMTransmission Electron Microscopy
TMRTunneling Magnetoresistance
VSMVibrating Sample Magnetometry
XPSX-ray Photoelectron Spectroscopy
XRDX-ray Diffraction

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Figure 1. Schematic illustration of the main magnetic NDE monitoring techniques: (a) Magnetic Barkhausen Noise (MBN) setup with pickup coil and excitation yoke; (b) Magnetic Flux Leakage (MFL) inline inspection concept showing leakage field at a corrosion pit; (c) Pulsed Eddy Current (PEC) probe configuration. Original schematic drawn by the authors. Original schematic drawn by the authors.
Figure 1. Schematic illustration of the main magnetic NDE monitoring techniques: (a) Magnetic Barkhausen Noise (MBN) setup with pickup coil and excitation yoke; (b) Magnetic Flux Leakage (MFL) inline inspection concept showing leakage field at a corrosion pit; (c) Pulsed Eddy Current (PEC) probe configuration. Original schematic drawn by the authors. Original schematic drawn by the authors.
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Figure 2. Schematic illustration of the three-electrode electrochemical cell configuration used for the EIS measurements. The working electrode (WE, steel specimen), reference electrode (RE, Ag/AgCl or saturated calomel electrode), and counter electrode (CE, platinum mesh or graphite rod) are connected to a potentiostat/frequency response analyzer (FRA). The sinusoidal perturbation (5–20 mV RMS, 10−2 to 105 Hz) applied at open-circuit potential produces impedance spectra displayed as Nyquist and Bode plots, from which equivalent circuit parameters (Rs, Rct, CPE) are extracted. Original schematic drawn by the authors.
Figure 2. Schematic illustration of the three-electrode electrochemical cell configuration used for the EIS measurements. The working electrode (WE, steel specimen), reference electrode (RE, Ag/AgCl or saturated calomel electrode), and counter electrode (CE, platinum mesh or graphite rod) are connected to a potentiostat/frequency response analyzer (FRA). The sinusoidal perturbation (5–20 mV RMS, 10−2 to 105 Hz) applied at open-circuit potential produces impedance spectra displayed as Nyquist and Bode plots, from which equivalent circuit parameters (Rs, Rct, CPE) are extracted. Original schematic drawn by the authors.
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Figure 3. (a) EIS Nyquist plots for AH 36 structural steel in NaCl solution at three chloride concentrations: 0.01 M (Low), 0.1 M (Medium), and 0.6 M (High). Specimens were ground to 1200-grit SiC finish and immersed for 1 hour prior to measurement to allow passive film stabilization. Data were acquired at open-circuit potential with a sinusoidal perturbation of 10 mV RMS over a frequency range of 100 kHz–10 mHz. The progressive decrease in semicircle diameter with increasing [Cl−] reflects the systematic reduction in charge transfer resistance (Rct) due to the competitive adsorption of Cl− at the oxide surface sites and progressive passive film destabilization. (b) Randles-type equivalent circuit (Rs in series with parallel Rct and CPE) used for spectral fitting. All data are original unpublished experimental work by the authors, generated specifically for illustrative purposes in this review.
Figure 3. (a) EIS Nyquist plots for AH 36 structural steel in NaCl solution at three chloride concentrations: 0.01 M (Low), 0.1 M (Medium), and 0.6 M (High). Specimens were ground to 1200-grit SiC finish and immersed for 1 hour prior to measurement to allow passive film stabilization. Data were acquired at open-circuit potential with a sinusoidal perturbation of 10 mV RMS over a frequency range of 100 kHz–10 mHz. The progressive decrease in semicircle diameter with increasing [Cl−] reflects the systematic reduction in charge transfer resistance (Rct) due to the competitive adsorption of Cl− at the oxide surface sites and progressive passive film destabilization. (b) Randles-type equivalent circuit (Rs in series with parallel Rct and CPE) used for spectral fitting. All data are original unpublished experimental work by the authors, generated specifically for illustrative purposes in this review.
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Figure 4. Representative SVET-derived local current density map over a weld heat-affected zone (HAZ), showing the spatial distribution of anodic (positive) and cathodic (negative) current density. Original unpublished experimental data acquired by the authors; steel specimen in NaCl solution, vibrating probe frequency 70–300 Hz.
Figure 4. Representative SVET-derived local current density map over a weld heat-affected zone (HAZ), showing the spatial distribution of anodic (positive) and cathodic (negative) current density. Original unpublished experimental data acquired by the authors; steel specimen in NaCl solution, vibrating probe frequency 70–300 Hz.
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Figure 5. Representative electrochemical noise current transients recorded during pit initiation on carbon steel (ZRA configuration, two nominally identical electrodes, 1 M NaCl, open-circuit potential, 1 Hz sampling rate). The characteristic asymmetric transients indicate individual pitting events. Original unpublished data acquired by the authors.
Figure 5. Representative electrochemical noise current transients recorded during pit initiation on carbon steel (ZRA configuration, two nominally identical electrodes, 1 M NaCl, open-circuit potential, 1 Hz sampling rate). The characteristic asymmetric transients indicate individual pitting events. Original unpublished data acquired by the authors.
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Figure 6. Conceptual design of a multi-sensor monitoring platform combining magnetic (MBN pickup, eddy current coil array) and electrochemical (three-electrode EIS cell) elements for in situ pipeline inspection. This is an original conceptual schematic prepared by the authors for this review; it is not based on any specific commercial device or patented design. The figure was created using Microsoft PowerPoint 365 (Microsoft Corporation, Redmond, WA, USA) with custom vector graphics.
Figure 6. Conceptual design of a multi-sensor monitoring platform combining magnetic (MBN pickup, eddy current coil array) and electrochemical (three-electrode EIS cell) elements for in situ pipeline inspection. This is an original conceptual schematic prepared by the authors for this review; it is not based on any specific commercial device or patented design. The figure was created using Microsoft PowerPoint 365 (Microsoft Corporation, Redmond, WA, USA) with custom vector graphics.
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Table 1. Comparison of key magnetic NDE techniques for corrosion and microstructural monitoring.
Table 1. Comparison of key magnetic NDE techniques for corrosion and microstructural monitoring.
TechniqueMin. Detectable Defect SizeDepth Sensitivity/PenetrationSpatial ResolutionTypical Frequency RangeKey ApplicationsPrincipal LimitationsApproximate Relative Cost
Magnetic Barkhausen Noise (MBN)Surface pit ≥ 0.1 mm; stress change ≈ 10 MPa0.01–1 mm (frequency-dependent; higher freq. = shallower)0.5–5 mm lateral (coil size-dependent)Excitation: 1 Hz–100 kHz; signal: 1–200 kHzResidual stress mapping; hardness/microstructure; weld HAZ; fatigue damage; phase fractionSurface-sensitive only; calibration specimen required; sensitive to roughness and lift-off; ferromagnetics onlyLow–Moderate (€5k–€50k); portable units widely available
Magnetic Hysteresis Analysis (VSM/FORC)Phase fraction change ≈ 1 vol%; coercivity shift ≈ 10 A/mBulk (full sample volume); no depth profilingBulk average; no spatial mapping (standard VSM)Quasi-static (DC–1 Hz); AC susceptibility up to ≈1 kHzPhase transformation monitoring; carbide coarsening; sigma-phase/spinodal decomposition; temper embrittlementLaboratory instrument; destructive sampling; no field deployment; slow; no spatial resolutionModerate–High (€30k–€200k for VSM/FORC systems); laboratory only
Magnetic Flux Leakage (MFL)Axial defect ≥ 10 mm; depth ≥ 0.1 mm (±10% wall)Up to 10–15 mm (full-wall at saturation)5–20 mm (sensor pitch-dependent)DC–100 Hz; pulsed MFL up to ≈1 kHzInline pipeline inspection (ILI); corrosion pit/wall-thinning detection; storage tank floors; weld screeningRequires magnetic saturation; ferromagnetics only; geometry-sensitive (bends, welds); speed-dependent signalHigh (€100k–€1M+ for ILI tools); high operational cost per run
Eddy Current Testing (ECT/PEC)Surface crack: 0.1–0.5 mm; wall thinning: ±0.2 mmECT: 0.5–5 mm; PEC: up to 30 mm (through insulation)1–5 mm (array probes); sub-mm (high-freq. pencil probes)ECT: 100 Hz–10 MHz; PEC: DC–100 kHz (broadband pulse)Heat exchanger tubes; SCC in nuclear/aircraft structures; corrosion under insulation (PEC); weld inspectionGeometry-dependent calibration; surface preparation required; edge effects; permeability variation complicates ferromagnetic inspectionLow–Moderate (€5k–50k for probes/instruments); PEC systems higher (€50k–€150k)
SQUID Magnetometry/FluxgateSQUID: ≈10 pT field anomaly; Fluxgate: ≈0.1 nTSQUID: mm–cm (passive field mapping); Fluxgate: cm–m (buried pipelines)SQUID: sub-mm (scanning mode); Fluxgate: cm–dmSQUID: DC–1 kHz; Fluxgate: DC–10 kHzDeeply buried corrosion product mapping; CP current monitoring; stress anomaly detection; weak-signal NDESQUID requires cryogenic cooling (LN2/LHe), complex setup; fluxgate lower sensitivity; both need magnetically quiet environmentsSQUID: Very High (€200k–€1M+; cryogenic running costs); Fluxgate: Low–Moderate (€1k–10k per sensor)
Table 2. Summary of the electrochemical techniques for corrosion monitoring.
Table 2. Summary of the electrochemical techniques for corrosion monitoring.
TechniqueFrequency Range/Time ResolutionMeasurable ParameterApplicable Corrosion TypesKey ApplicationsPrincipal Limitations
Electrochemical Impedance Spectroscopy (EIS)10−3–105 Hz; single spectrum: minutes to hoursImpedance spectra; Rs, Rct, CD1, RpeGeneral, pitting, crevice, intergranular, passive film degradationPassive film characterization; corrosion inhibitor evaluation; coating assessment; sensitization monitoring (DL-EPR corr.)Non-uniqueness of equivalent circuit models (multiple topologies fit same spectrum; requires XPS/TEM validation); requires stable interface; slow at low frequencies; not valid for rapidly changing systems
Linear Polarization Resistance (LPR)DC–1 Hz (quasi-static scan); measurement: 1–10 minPolarization resistance Rp; icorr(via Stern–Geary)Uniform/general corrosionReal-time embedded corrosion rate monitoring; pipeline/concrete/process stream sensors; offshore and nuclear environmentsNot valid for localized corrosion (pitting, SCC); Stern–Geary constant B uncertainty (±30%); requires electrolytic contact
Potentiodynamic/Potentiostatic PolarizationDC (scan rate: 0.1–1 mV/s); duration: tens of minutesEcorr, icorr (A cm−2), EpIt, passive current densityGeneral, pitting, intergranular, galvanic couplingPitting resistance ranking; passive film stability; galvanic coupling assessment; critical pitting temperature (CPT); DL-EPR sensitization testingDestructive/ex situ; perturbs the surface irreversibly; scan rate dependent; not suitable for in-service monitoring
Scanning Techniques (SVET/LEIS/SECM)SVET: AC vibration at 70–300 Hz; LEIS: 10−2–104 Hz per pixel; full map: hoursLocal current density (SVET); local Z(ω) map (LEIS); redox mediator current (SECM)Localized corrosion, galvanic coupling, coating defects, early-stage pitting nucleationWeld HAZ corrosion mapping; coating defect detection; pitting nucleation on stainless steels (SECM, sub-µm resolution); galvanic couple visualizationConfined to solution environments; slow (full map: hours); tip–surface distance control critical; limited to lab scale; not field-deployable
Electrochemical Noise (EN)DC–1 Hz acquisition (broadband); statistical analysis in time/frequency domain; measurement: continuous or 10–60 min windowsPotential and current fluctuations; noise resistance Rn; skewness; kurtosis; wavelet coefficientsPitting initiation, SCC, crevice corrosion, general dissolution, passive film breakdownPassive in situ monitoring (no perturbation); pitting initiation detection before mass loss; SCC onset monitoring; long-term embedded sensingDrift removal critical (no consensus standard); stationarity assumption often violated; signal interpretation ambiguous without complementary data; electrode symmetry assumption rarely met in practice
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MDPI and ACS Style

Vourna, P.; Falara, P.P.; Ktena, A.; Hristoforou, E.V.; Papadopoulos, N.D. Advances in Magnetic and Electrochemical Techniques for Monitoring Corrosion and Microstructural Degradation in Steels. Metals 2026, 16, 352. https://doi.org/10.3390/met16030352

AMA Style

Vourna P, Falara PP, Ktena A, Hristoforou EV, Papadopoulos ND. Advances in Magnetic and Electrochemical Techniques for Monitoring Corrosion and Microstructural Degradation in Steels. Metals. 2026; 16(3):352. https://doi.org/10.3390/met16030352

Chicago/Turabian Style

Vourna, Polyxeni, Pinelopi P. Falara, Aphrodite Ktena, Evangelos V. Hristoforou, and Nikolaos D. Papadopoulos. 2026. "Advances in Magnetic and Electrochemical Techniques for Monitoring Corrosion and Microstructural Degradation in Steels" Metals 16, no. 3: 352. https://doi.org/10.3390/met16030352

APA Style

Vourna, P., Falara, P. P., Ktena, A., Hristoforou, E. V., & Papadopoulos, N. D. (2026). Advances in Magnetic and Electrochemical Techniques for Monitoring Corrosion and Microstructural Degradation in Steels. Metals, 16(3), 352. https://doi.org/10.3390/met16030352

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