Electrochemical Noise Analysis in Passivated Martensitic Precipitation-Hardening Stainless Steels in H₂SO₄ and NaCl Solutions

Abstract

Precipitation-hardenable stainless steels (PHSS) are widely used in various applications in the aeronautical industry such in as landing gear supports, actuators, and fasteners, among others. This research aims to study the pitting corrosion behavior of passivated martensitic precipitation-hardening stainless steel, which underwent passivation for 120 min at 25 °C and 50 °C in citric and nitric acid baths before being immersed in solutions containing 1 wt.% sulfuric acid (H₂SO₄) and 5 wt.% sodium chloride (NaCl). Electrochemical characterization was realized employing electrochemical noise (EN), while microstructural analysis employed scanning electron microscopy (SEM). The result indicates that EN reflects localized pitting corrosion mechanisms. Samples exposed to H₂SO₄ revealed activation–passivation behavior, whereas those immersed in NaCl exhibited pseudo-passivation, indicative of an unstable oxide film. Current densities in both solutions ranged from 10⁻³ to 10⁻⁵ mA/cm², confirming susceptibility to localized pitting corrosion in all test conditions. The susceptibility to localized attack is associated with the generation of secondary oxides on the surface.

1. Introduction

In the aerospace industry, a variety of components such as actuators, landing gear supports, and fasteners are manufactured from stainless steel because these materials offer good mechanical strength and corrosion resistance in the presence of aggressive atmospheres. In different industry sectors, corrosion causes significant economic losses. In the aeronautical industry, costs vary and are associated with various factors such as industry regulations, preventive maintenance practices, and technological advances [1,2,3,4].

Stainless steels are alloys containing [Fe-Cr] (at least 11% chromium) with nickel additions and have a variety of applications. Stainless steels can be classified based on their microstructure and precipitates, as ferritic, austenitic, martensitic, duplex, and precipitation hardening (PH) [5,6]. The aeronautical industry relies on precipitation-hardenable (PH) steels for their superior properties, including low weight, high mechanical strength, and excellent corrosion resistance. PH stainless steels (PHSS) fall into two categories: semi-austenitic, known for high ductility and corrosion resistance, and martensitic, valued for their strength-to-weight ratio [7,8,9,10,11]. Key industrial stainless steels like 17-4PH, 17-7PH, and 15-7Mo were introduced by Armco (USA) in 1948, followed by semi-austenitic AM350 and AM355, and martensitic Custom 630, 455, and 450, produced by Carpenter Technology Corporation and ATI Materials. These steels serve in turbine blade, rotor, and shaft manufacturing. Additionally, 15-5 PH steel from Penn Stainless Products, Inc., is used in aircraft structural components [12,13,14].

Alloys such as stainless steels have high corrosion resistance performance due to the protective film of chromium oxide (Cr₂O₃) that forms on the surface and is characterized by being a thin, invisible, and compact film. The chemical treatment that allows the growth of the oxidation film is known as passivation and improves corrosion resistance. Passivation treatment was discovered by chemist Christian Friedrich Schönbein in the mid-19th century, and is commonly performed on stainless steels using an oxidizing agent such as nitric acid [15,16,17,18,19,20,21]. The addition of elements such as Cr with Mo decreases pitting corrosion. Also, elements such as N and Cu can help reduce these problems. The passive film of Cr plays a crucial role in reducing the corrosion rate; however, SS has transitioned from a single passivation trend to exhibiting pitting corrosion [22,23]. Surface factors (heterogeneity, roughness, microstructure, etc.) are important to determine the corrosion behavior of material; defects in the atomic layer, the difference in phases, and roughness will reduce the corrosion resistance [24,25,26]. Factors such as reducing gases, alkaline solutions, mechanical wear, or non-oxidizing acids can disrupt the oxide film, accumulating corrosion products in specific zones [27,28].

Different studies [29,30,31,32] propose that citric acid could serve as an environmentally friendly alternative to nitric acid, which is widely used for anti-corrosion treatments. Adjusting specific parameters, such as duration, temperature, and electrolytic baths during passivation has enhanced the passive layer’s properties. It is also crucial to recognize that anodic reactions involving iron dissolution lead to chromium and iron oxide films forming, which create the passive layer characteristic of stainless steel, ensuring corrosion resistance [33].

Research on the corrosion behavior of stainless steels has focused on accelerated corrosion testing (salt spray chamber) and localized corrosion, pitting nucleation, and passive, pseudopassive, and transpassive zones to understand the corrosion mechanisms of these steels. Corrosion studies have been conducted using electrochemical techniques such as potentiodynamic (PP) and galvanodynamic (PG) polarization, cyclic potentiodynamic polarization (CPP), electrochemical impedance spectroscopy (EIS), and electrochemical noise (EN). The latter technique has allowed for data analysis in time, time-frequency, and frequency, respectively [14,15,16,17,18,19,20,21]. However, the literature on the corrosion of PH steels is limited, and it is necessary to determine the corrosion mechanism and the behavior of the passive layer that forms.

Some of the stainless steel passivation studies using electrochemical techniques are summarized as follows: the electrochemical noise technique used by Suresh and Mudali in 2014 [34] analyzed the corrosion behavior of austenitic 304 stainless steel immersed in ferric chloride (FeCl₃), finding an important relationship between the frequency analysis through power spectral density (PSD) and time analysis (statistical study, noise resistance (Rn) and localization index (IL)) to find the localized pitting corrosion mechanism. In 2018, Lara et al. [35], investigated precipitation-hardenable steels, having as reference an austenitic 304 steel; the corrosion kinetics were studied by electrochemical noise in the current and potential mode, potentiodynamic polarization tests were reported, and the passivation process was carried out using citric acid as an environmentally friendly option; the results indicated that the passivation films formed were different in the different passivation acids, as the evaluations were carried out in sulfuric acid and sodium chloride. In other investigations, potentiodynamic polarization and electrochemical impedance spectroscopy were used to study the oxide film through charge transfer processes in authentic passivated stainless steels such as 304 [36]. The electrochemical characteristics of SS have also been studied by varying the pH concentrations in aerated solutions, resulting in a decrease in the pH of the oxidizing solution that promotes the formation of protective films, improving the corrosion resistance of the substrates [37,38,39,40,41]. Pei-de Han et al., in 2022–2023, studied superaustenitic steel S31254 by potentiodynamic polarization and electrochemical impedance spectroscopy to see the effect of boron on the dissolution and repair of the passive films of these steels, in the presence of sulfuric acid; they resulted in better corrosion resistance with the addition of boron [42,43].

Recent investigations on PHSS, such as CUSTOM450 (martensitic) and AM350 (austenitic) steels, have focused on hydrogen diffusion, fatigue behavior, and microstructural characterization [44,45,46,47]. Samaniego et al. [4,8,20] studied the corrosion behavior of CUSTOM450- and AM350-passivated PHSS steels using electrochemical noise and electrochemical impedance spectroscopy in acid baths. The CUSTOM 450 PHSS showed the best results in corrosion behavior in acid baths. The primary research for this type of alloy has been conducted using potentiodynamic polarization and spectroscopy impedance. Therefore, this research will utilize EN to investigate the transient behavior and its correlation with corrosion.

This study analyzed the pitting corrosion of martensitic precipitation-hardening stainless steel that had been passivated for 120 min at 25 and 50 °C using citric and nitric acid baths and then immersed in solutions containing 1 wt.% sulfuric acid and 5 wt.% sodium chloride. The electrochemical technique was electrochemical noise based on ASTM G199-90. [48,49] The EN technique was analyzed, employing methods of classic statistics and recurrence plots (RP). The RP is used for chaotic signals, as are the corrosion signals. Few researchers used that method to study. The microstructural analysis was performed by scanning electron microscopy (SEM) after the samples had been tested for corrosion. Corrosion studies on stainless steels in recent years have focused on austenitic steels. PHSS steels have few studies; these steels are used in components that require a combination of excellent mechanical properties, as well as corrosion resistance due to aircraft exposure in harsh environments. So, it is important to know the electrochemical corrosion in electrolytes where aircraft commonly work, so that they can simulate marine, industrial (acid rain), and urban atmospheres.

2. Materials and Methods

2.1. Materials

The commercial martensitic precipitation-hardening stainless steel used is equivalent to CUSTOM 450 (AMS 5773, AMS Aerospace Material Specifications) in the shape of rolled and heat-treated cylindrical bars. Stainless steel was employed and tested in the as-received condition; the nominal chemical composition of these stainless steels is shown in

Table 1. Chemical composition of the martensitic PHSS (wt.%).

Element	Martensitic PHSS
Cr	14.0–16.0
Ni	5.0–7.0
Mo	0.50–1.0
Mn	1.00 max
Cu	1.25–1.75
Nb	0.35–0.75
N	≤0.1
Si	1.00 max
S	0.030
C	≤0.05
Fe	Balance

[50].

The metallography technique was used to prepared martensitic stainless steel samples using silicon carbide sandpaper of varying grades (240, 400, 500, 600, and 800). For corrosion tests the surface samples were roughened and polished using diamond paste, and then cleaned with deionized water and ultrasound in ethanol for 10 min [51,52]. The microstructure of martensitic PHSS was assessed using optical microscopy (OM, Olympus, Hamburg, Germany). Using the metallography technique (roughing was performed from 240 to 4000 grit, and the polishing of the samples with a diamond paste), to reveal the microstructure with a chemical agent called Fry’s, which was composed of 5 g CuCl, 40 mL HCl, 30 mL H₂O, and 25 mL of ethanol.

2.2. Microstructure of Martensitic PHSS

Figure 1 displays the microstructure of martensitic precipitation-hardening stainless steel using optical microscopy. It shows the martensitic phase (α’) and remnants of retained austenite (γ), respectively.

Martensitic precipitation-hardening stainless steel offers moderate mechanical strength and outstanding corrosion resistance. When annealed, it achieves a yield strength exceeding 100 ksi (689 MPa); but through a single-stage heat hardening process it further enhances toughness, ductility, and mechanical strength. The chosen aging temperature affects the mechanical characteristics [52].

2.3. Chemical Passivation Treatment

The chemical passivation treatment on stainless steel was carried out based on the ASTM A967-17 standard [15]. The procedure was carried out based on the stages mentioned in the following experimental diagram (Figure 2) [53,54,55]:

To identify each of the samples, the nomenclature in

Table 2. General characteristics of the martensitic precipitation-hardening stainless steel samples.

Electrolyte	Temperature (°C)	Time (min)	Passivation Baths	Nomenclature
H2SO4 (1)	25	120	Citric Acid C6H8O7 (25% w/v)	1/C/25
	50			1/C/50
	25	120	Nitric Acid HNO3 (45% v/v)	1/N/25
	50			1/N/50
NaCl (2)	25	120	Citric Acid C6H8O7 (25% w/v)	2/C/25
	50			2/C/50
	25	120	Nitric Acid HNO3 (45% v/v)	2/N/25
	50			2/N/50

was used (time and material are omitted as they are constant parameters): The electrolytes are identified as 1 for H₂SO₄ and 2 for NaCl, the passivation baths C for citric acid and N for nitric acid, and the temperature values are 25 and 50 °C, respectively. The description of all the parameters of each of the samples tested is indicated in Table 2.

2.4. Corrosion Measurement

Electrochemical corrosion measurements were performed to determine martensitic precipitation-hardening stainless steel pitting corrosion using the electrochemical technique of electrochemical noise. Martensitic PHSS samples had an area of 1.0 cm² and were immersed in two solutions: 1 wt% sulfuric acid and 5 wt% sodium chloride at room temperature (25 ± 2 °C) [4,8,14]. For each experiment, two nominally identical specimens were used as the working electrodes (WE1 and WE2) and a saturated calomel electrode as the reference electrode (RE). Electrochemical current noise (ECN) was measured with a galvanic coupling current between two identical working electrodes; simultaneously, electrochemical potential noise (EPN) was measured linking one of the working electrodes and a reference electrode. The electrochemical equipment was a potentiostat/galvanostat/ZRA (produced by Solartron 1287A, Bognor Regis, UK). Electrochemical corrosion tests were performed in triplicate.

Electrochemical noise measurements were based on ASTM G199-09 [56], acquiring 1024 data points at 1 data/second speed. A program created with MATLAB 2018a software from Math Works (Natick, MA, USA) was used to process the EN data [56,57,58].

2.5. Microstructural Characterization

The surface analysis after corrosion testing was conducted with a scanning electron microscope (SEM, JEOL-JSM-5610LV, Tokyo, Japan) equipped with a secondary electron (SE) detector. The SEM operated at a beam energy of 20 kV and a working distance of 11–13 mm.

3. Results and Discussion

3.1. Corrosion Measurements

Electrochemical Noise

Electrochemical noise (EN) refers to spontaneous, low-level fluctuations in potential and current during electrochemical processes. This technique is particularly effective for monitoring localized corrosion, as its analysis depends on the signal type within the system. A major advantage of EN is its ability to assess localized corrosion through a non-invasive approach [59,60,61,62].

EN analysis is divided into time-domain, frequency-domain, frequency-time, and chaotic systems. Initially, signals underwent statistical evaluation, with researchers such as Mansfeld, Cottis, Turgosse, Eden, and Bertocci investigating the correlation between corrosion types and statistical metrics like localization index (LI) and pitting index, derived from standard deviations of ECN and EPN. Additionally, the noise resistance (Rn) parameter was introduced as an Rp equivalent, linking it to kinetic properties. Later studies incorporated kurtosis and skewness to refine LI for improved corrosion classification [63,64,65,66,67,68,69,70].

EN signals comprise DC, stationary, and random components. Separating DC from the stationary and random components is essential to analyze EN data effectively, as DC can distort statistical, visual, and power spectral density (PSD) evaluations by introducing artificial frequencies. Once DC is removed, low-frequency corrosion data remain unaffected. EN can be mathematically represented, as shown in Equation (1), where x(t) is the EN time series, m_t is the DC component, st is the random component, and Y_t is a stationary component. The last two are functions that define the corrosion system [71,72,73,74,75,76]:

$$x\left(t\right)=m_t+s_t+Y_t$$

(1)

To calculate noise resistance (R_n), the standard deviation from time series data must be determined. These statistical parameters offer insights into corrosion mechanisms and kinetics. Research by Turgoose and Cottis [63] revealed that higher corrosion rates correspond to variance and standard deviation increases. Use Equation (2) to compute the standard deviation (σ), standard deviation of the potential data (σ_v), standard deviation of the potential data (σ_I), working electrode area (A), and derive Rn (Equation (3)), utilizing EN time series information (EPN and ECN) as the foundation:

$${\sigma }_x=\sqrt{\overline{x^2}}=\sqrt{{\displaystyle \frac{\sum _1^N{(x_i-\overline{x})}^2}{N}} }$$

(2)

$$R_n={\displaystyle \frac{{\sigma }_v}{{\sigma }_I}}\times A$$

(3)

This study employed kurtosis and skewness to classify corrosion types. However, the localization index (LI) was excluded, as Mansfeld and Sun [71] concluded in 1995 that it has limitations and requires cautious application. A patent created by Reid and Eden in 2001 [77] proposed that statistical moments, including skewness and kurtosis, can be utilized to determine the corrosion type. These correspond to the third and fourth statistical moments [77,78]. The following table shows the relationship between the values obtained by kurtosis and skewness to determine the corrosion type of material (

Table 3. Corrosion types are evaluated by kurtosis and skewness.

Corrosion Type	Potential		Current
	Skewness	Kurtosis	Skewness	Kurtosis
Uniform	<±1	<3	<±1	<3
Pitting	<−2	>>3	>±2	>>3
Transgranular (SCC)	4	20	−4	20
Intergranular (SCC #1)	−6.6	18 to 114	1.5 to 3.2	6.4 to 15.6
Intergranular (SCC #2)	−2 to −6	5 to 45	3 to 6	10 to 60

).

Figure 3 shows the time series of passivated martensitic precipitation-hardening stainless steel exposed to H₂SO₄. Figure 3a shows how the sample 1/N/50 presented higher amplitudes with values of 4 × 10⁻⁴ V, but the potential begins to be reduced. All the signals presented a high transitory number. Figure 3b shows the time in the current series; it presents a high transitory number with an amplitude higher for samples 1/C/50 and 1/N/50. The high number of transmissions indicates much pitting on the material surface. That behavior is reflected in

Table 4. Parameters obtained by EN for martensitic precipitation-hardening stainless steel in 1 wt.% H₂SO₄ and 5 wt% NaCl solutions.

Electrolyte	Parameters	Samples
		1/C/25	1/C/50	1/N/25	1/N/50
H2SO4	Rn (Ω·cm2)	4060 ± 9	7027 ± 5	4734 ± 4	22146 ± 6
	LI	0.07 ± 0.002	0.1 ± 0.002	0.2 ± 0.002	0.4 ± 0.002
	Kurtosis	258 ± 3	240 ± 2	116 ± 2	83 ± 2
	Skewness	15 ± 2.1	−3.7 ± 0.5	9.9 ± 0.6	8.1 ± 0.2
NaCl	Rn (Ω·cm2)	716 ± 7	1716 ± 11	2102 ± 13	44985 ± 16
	LI	0.06 ± 0.002	0.02 ± 0.001	0.1 ±0.001	0.06 ± 0.001
	Kurtosis	12 ± 0.01	13 ± 0.004	8 ± 0.005	49 ± 0.006
	Skewness	—1.5 ± 0.04	1.1 ± 0.01	—1.5 ± 0.05	3.2 ± 0.04

, where the LI of samples 1/C/50 and 1/N/50 are associated with localized corrosion.

On the other hand, 1/C/25 presented a mixed corrosion process with a value of 0.07, indicating that both processes are occurring on the surface. In the kurtosis and skewness evaluation, all samples presented values related to pitting corrosion. The sample 1/N/50 exhibited a higher Rn value (22146 Ω·cm²). Additionally, the sample passivated at 50 °C in citric acid showed the second-highest Rn value of 7027 Ω·cm², indicating that when passivation temperature increases, the corrosion resistance of passivated steel increases. The samples specified at 25 °C presented 4000 Ω·cm² values with less corrosion resistance.

Figure 4 shows the time series of martensitic precipitation-hardening stainless steel exposed to NaCl. Figure 4a shows the potential time series, where 1/25/N presents a high amplitude with values o 14 × 10⁻² V at the beginning but with a decrease in amplitude; that behavior is presented by the rest of the samples, indicating that a reduction of ionic transference occurs due to a stabilization of the material’s surface. The current in time series (Figure 4b) shows that sample 1/N/50 presented a lower amplitude than the other samples; that behavior is associated with a lower corrosion kinetic, so 1/N/50 presented the highest Rn with 44,965 Ω·cm². In this medium, the samples passivated in citric acid presented the lower corrosion rate resistance with 700 and 1700 Ω·cm^2,, respectively. However, the samples exposed to citric acid LI values related to the mixed corrosion process and 1/N/50. All the kurtosis results indicated to localized corrosion occurs; however, skewness shows how 1/C/50 has a value of uniform corrosion. The rest of the values are related to localized corrosion; however, the values are very close to the division of localized to uniform corrosion.

Non-linear (chaotic) systems can be analyzed using recurrence plots (RPs), which identify whether processes follow deterministic recurrence patterns. If a system is deterministic (D), it corresponds to localized processes, whereas recurrence in its domain suggests uniform behavior [61,62].

A recurrence plot (RP) is a two-dimensional binary diagram illustrating temporal patterns in a single observable time series, such as current (I) in this study. It represents trajectory recurrences (xiin Rm) at specific time points (i, j) within an (m)-dimensional phase space and a defined threshold (ε). The RP consists of a square matrix with black and white dots along time axes (ti, tj), where black dots mark state recurrences at position (ti, tj); The matrix formulation is provided in Equation (4) [78,79]:

$$R_{ij}=\mathsf{\Theta }\left(\epsilon -‖\overrightarrow{x_i}-\overrightarrow{x_j}‖\right), i, j=1,\dots . N$$

(4)

Figure 5 shows the recurrence plots of samples exposed to H₂SO₄. Figure 5a shows the behavior of 1/C/25. This sample exhibited a localized process trend, similar to Figure 5b, where the samples were transitory. However, the number of vertical and horizontal lines indicate that the localized process occurs periodically; therefore, for that reason, the determinism value (DET) from

Table 5. Parameters obtained by recurrence plot analysis for martensitic precipitation-hardening stainless steel in 1 wt.% H₂SO₄ and 5 wt% NaCl solutions.

Electrolyte	Parameters	Samples
		1/C/25	1/C/50	1/N/25	1/N/50
H2SO4	RR	0.606 ± 0.006	0.211 ± 0.005	0.5 ± 0.01	0.295 ± 0.006
	Det	0.937 ± 0.003	0.827 ± 0.002	0.871 ± 0.002	0.856 ± 0.008
	L	7.72 ± 0.004	4.682 ± 0.006	4.468 ± 0.005	4.204 ± 0.004
	LAM	0.962 ± 0.005	0.902 ± 0.002	0.932 ± 0.002	0.924 ± 0.005
	TT	12.5 ± 0.01	7.14 ± 0.01	6.85 ± 0.01	6.34 ± 0.01
NaCl	RR	0.196 ± 0.002	0.255 ± 0.001	0.113 ± 0.004	0.096 ± 0.004
	Det	0.992 ± 0.006	0.992 ± 0.008	0.986 ± 0.005	0.386 ± 0.004
	L	20.82 ± 0.05	20.46 ± 0.02	24.61 ± 0.03	2.33 ± 0.02
	LAM	0.996 ± 0.002	0.996 ± 0.001	0.993 ± 0.002	0.493 ± 0.004
	TT	30.905 ± 0.002	32.635 ± 0.002	31.327 ± 0.002	2.576 ± 0.002

, of all the samples, is between 0.93 and 0.87, and the recurrence (RR) with values are from 0.2 to 0.60. Also, trapping time (TT), the value associated with the repeatability time, is between 6 and 12, indicating that the process is repeated too periodically. That suggests that a pitting uniform corrosion process is probably occurring on the surface. Also, the breaking and passivation of a passive layer is associated with this behavior.

Figure 6 shows the recurrence plots of samples exposed to NaCl. The behaviors of samples 1/C/25, 1/C/50, and 1/N/25 are similar, with localized processes before the second 1000 and the lack of transience. This behavior is related to localized corrosion with a low frequency; hence, the TT value is lower. On the other hand, sample 1/N/50 presented multiple lines vertically and horizontally, with values associated with linearity (L), indicating uniform corrosion on the surface. It can be associated with a passivation process.

3.2. SEM Characterization of PHSS After Electrochemical Corrosion Measurements

Following electrochemical corrosion measurements, the surface morphology of each sample was examined using SEM to study the reaction of materials against corrosion. SEM analysis revealed that localized pitting corrosion occurred on all passivated stainless steel surfaces, with some conditions only showing pit nucleation, while others demonstrated severe localized attack.

The martensitic PHSS passivated at 25 and 50 °C (Figure 7a–d) was exposed to H₂SO₄ and presented pit nucleation with pits measuring approximately 10 microns in size.

For the martensitic precipitation-hardening stainless steel immersed in NaCl under similar passivation conditions (Figure 8a–d), pitting corrosion was observed with pit sizes exceeding 100 microns.

In previous studies, precipitation-hardening martensitic stainless steels displayed distinctive profiles due to different electrochemical behavior in NaCl and H₂SO₄ test solutions, indicating passivation during the anodic reaction, along with variability in pitting potentials. When martensitic stainless steel is immersed in H₂SO₄ solution, a passivation layer forms on the surface of the chromium-rich alloy, improving corrosion resistance and initiating protective mechanisms. Iron and chromium oxides play a critical role in creating the passive film in stainless steels by interacting with hydroxyl ions. High current densities in martensitic stainless-steel samples result in transpassivation and secondary passivation. On the other hand, samples immersed in NaCl solution exhibit pseudo-passivation, reflecting the presence of an unstable protective layer. This defense system forms a passive Cr-rich oxide and oxyhydroxide film that protects the substrate from chloride ions (Cl⁻) while preventing oxygen penetration into the inner layer [30,31,80].

According to various authors [31,32], unstable passivation layers increase current density in stainless steels exposed to NaCl, thus altering corrosion kinetics. In contrast, austenitic stainless steels in H₂SO₄ solutions displayed transient phenomena linked to transpassivation, characterized by passive film disruption, and secondary passivation, associated with passive layer regeneration.

The passive region is the formation site for iron oxide and chromium oxide coatings, often identified in martensitic stainless steel [32,81,82,83,84]. The selective dissolution of Cr³⁺ from the stainless-steel surface results in the chromium trihydroxide complex, Cr(OH)₃ (Equation (5)). Subsequently, Cr(OH)₃ reacts to develop a continuous chromium oxide passive layer, Cr₂O₃, on the surface (Equation (6)) [32,85]:

$${\mathrm{C}\mathrm{r}}^{3+}+3{\mathrm{O}\mathrm{H}}^{-}\to {\mathrm{C}\mathrm{r}\left(\mathrm{O}\mathrm{H}\right)}_3+3{\mathrm{e}}^{-}$$

(5)

$$\mathrm{C}\mathrm{r}{\left(\mathrm{O}\mathrm{H}\right)}_3+\mathrm{C}\mathrm{r}+{3\mathrm{O}\mathrm{H}}^{-}\to {\mathrm{C}\mathrm{r}}_2{\mathrm{O}}_3+3{\mathrm{H}}_2\mathrm{O}+3{\mathrm{e}}^{-}$$

(6)

As mentioned before, iron and chromium oxidation mainly cause anodic reactions during the passivation film development stage. The iron oxidation processes are illustrated in Equations (7)–(9) [32,86,87]:

$$3\mathrm{F}\mathrm{e}+8{\mathrm{O}\mathrm{H}}^{-}\to {\mathrm{F}\mathrm{e}}_3{\mathrm{O}}_4+4{\mathrm{H}}_2\mathrm{O}+8{\mathrm{e}}^{-}$$

(7)

$$2{\mathrm{F}\mathrm{e}}_3{\mathrm{O}}_4+2\mathrm{O}{\mathrm{H}}^{-}+2{\mathrm{H}}_2\mathrm{O}\to 6\mathrm{F}\mathrm{e}\mathrm{O}\mathrm{O}\mathrm{H}+{2\mathrm{e}}^{-}$$

(8)

$$2{\mathrm{F}\mathrm{e}}_3{\mathrm{O}}_4+2{\mathrm{O}\mathrm{H}}^{-}\to 3{\mathrm{F}\mathrm{e}}_2{\mathrm{O}}_3+{\mathrm{H}}_2\mathrm{O}+2{\mathrm{e}}^{-}$$

(9)

Passivated martensitic precipitation-hardening stainless steel samples immersed in sulfuric acid under both passivation conditions exhibit pseudo-passivation, characterized by an unstable oxide layer alongside distinct secondary passivation. Research suggests that the Cr(OH)₃ film’s formation may be connected to this pseudo-passivation behavior [88,89].

The samples passivated in nitric acid performed better at 50 °C than at 25 °C. The diffusion process of passivation in nitric acid is more straightforward and generates a more stable passive layer due to the exothermic properties of nitric acid. On the other hand, citric acid is an endothermal chemical, and the properties of the oxide layer generated at 50 °C decreased the corrosion resistance [88].

The electrochemical noise results show that samples exposed to H₂SO₄ presented a lower value of TT, indicating that pitting attack occurs recurrently. That behavior means that the pitting attack is uniform. That is, pitting nucleation occurs (as SEM shows). On the other hand, when the sample is exposed to NaCl, it presents a localized attack. That behavior is related to Cl⁻ ions’ preference to attack the sample surface in specific zones, generating the localization of corrosion.

Various researchers have applied recurrence plots (RP) to classify corrosion types [32,61,81,82,83,90,91,92]. Valavanis et al. [93] propose that RP is useful for identifying dynamic states, transitions, and complex physicochemical processes such as passivity, pitting, and uniform corrosion. Garcia-Ochoa [92] highlights RP’s role in analyzing non-linear systems and electrochemical processes, emphasizing its necessity for scientific disciplines requiring such assessments. Since corrosion behaves as a chaotic or non-linear system [94,95], RP and recurrence quantification analysis (RQA) provide valuable insights into the corrosion process.

EN showed the types of corrosion and the stability of the passive layer; however, some transients were present. It occurs due to the instability of the oxide passive layer created in the sample. This will be dissolved when an oxide soluble in an aqueous solution is generated. However, the presence of multiple alloying elements such as Ni, Mo, Mn, Cu, and hydroxides facilitates the generation of other oxides that can be unstable under aqueous media. As a secondary oxide layer is generated, the corrosion process begins to occur in those specific zones. Figure 9 shows how localized attacks occur on another passive layer. Also, information obtained from SEM-EDS shows how elements such as Ni, Cu, and Fe are present on the surface. Hence, the corrosive ions attack the more susceptible oxides (solubility, porosity, and/or cracking conditions) [92,93,94,95,96].

The literature highlights that stainless steels develop a protective passive film enriched with oxides and hydroxides, distinct from films formed in natural conditions. Chemical passivation treatments typically remove surface contaminants, producing a cleaner and more protective passive film on stainless steel surfaces [97,98].

Using different techniques to characterize EN signals is important, and several authors have demonstrated that the statistical approach indicates that corrosion classification is largely inconsistent. This is attributed to LI variability; researchers like Eden and Mansfeld have pointed out the constraints of statistical evaluation, noting that Eden originally introduced LI years earlier to define corrosion types. Consequently, LI should be applied at the discretion of corrosion identification. Additionally, the signal examined using statistical methods must avoid a DC component to minimize standard deviation and yield a more precise outcome [99,100,101]. For that reason, in this research, recurrence plots were employed, and in this way, the results obtained by LI, kurtosis, and skewness were validated. It is important to mention that fact. The results obtained by recurrence plots helped to determine that if a well-localized process occurs on the surface, some samples will be passivated again. Conventional statistical methods cannot obtain that interpretation.

4. Conclusions

The present research investigates the passive state of passivated martensitic precipitation-hardening stainless steel in citric and nitric acid baths at 25 and 50 °C for 120 min and immersed in 1 wt.% H₂SO₄ and 5 wt.% NaCl solutions; considering the current results of experiments, the following can be concluded:

• The electrochemical noise results indicated that the martensitic precipitation-hardening stainless steel samples exposed to H₂SO₄ presented uniform pitting corrosion attacks.
• The samples exposed to NaCl presented pitting corrosion attacks. It is due to the susceptibility of PHSS to pitting generated by Cl⁻ ions in preference zones due to the presence of two phases.
• The passivation of martensitic PHSS samples increased the corrosion resistance; however, the susceptibility to localized corrosion increased for passivated samples.
• Localized attacks occurred due to secondary oxide formation that facilitated surface differences, attacking in preference zones.
• Surface morphologies obtained by SEM indicate that the passivated martensitic precipitation-hardening stainless steel samples exhibit pitting corrosion, which is more intense when the steels are exposed to NaCl solution due to the aggressivity of Cl⁻ ion.
• The best performance of passivation in nitric acid at 50 °C relates to the exothermic properties of the solution.
• The citric acid passivation process on stainless steels could be an environmentally friendly alternative to the frequently used nitric acid passivation process; however, it is necessary to increase research. The corrosion resistance increases, but the efficiency in comparison to nitric acid is lower.