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Anti-corrosion Properties of Ethanol Extract of Cardiospermum halicacabum Leaf on Steel Pipelines in Acidic Environment

  • I. Y. SuleimanEmail author
  • A. Kasim
  • S. R. Ochu
Article
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Abstract

In the continuation of the possibility of using green corrosion inhibitor, Cardiospermum halicacabum (CH) leaf extract as corrosion inhibitor for steel pipeline in 0.5 M hydrochloric acid using both gravimetric and potentiodynamic polarization techniques was investigated. The leaves were characterized by both quantitative and qualitative analyses and Fourier Transform Infrared Spectroscopy. Characterization of the substrates before and after corrosion tests were investigated by scanning electron microscope equipped with energy dispersive X-ray spectroscopy. The inhibitor concentration, time and temperature were varied in the range of 5–25% v/v, 1–12 days and 30–60 °C at 5% v/v, 2 days, and 10 °C interval,, respectively. Linear regression equation and analysis of variance (ANOVA) were employed to investigate the influence of process parameters (temperature, inhibitor concentration and time). Corrosion rate increased with the increasing temperature and decreased with increases in both inhibitor concentrations and time,, respectively. Maximum inhibition efficiency of 98.56% occurred at the optimal value of 20% v/v of the inhibitor concentration. The CH results revealed phytoconstituents such as tannins, alkaloids, saponins, flavonoids with their contents and azoddicarbonnamide, trphenyl phosphine oxide, etc. which were responsible for the protection of steel pipelines in acidic environment. The coupons without green inhibitor were rough, and severe pits and cracks occurred, while the surface of steel pipeline with green inhibitor was smooth. The adsorption of the molecules of the green inhibitor on adsorbate’s surface obeyed Langmuir adsorption isotherm. The potentiodynamic polarization results showed that the green inhibitor acted as mixed-type inhibitor. The ANOVA results also showed that inhibitor concentration was the most important and followed over time for the anti-corrosion of the steel pipeline by the green inhibitor.

Keywords

Cardiospermum halicacabum Steel pipeline Weight loss Polarization ANOVA 

1 Introduction

Steel pipeline is an important material being used in chemical industries, petrochemical, oil and gas, nuclear, for the construction of vessels, storage tanks and pipelines because of its easy availability, fabrication, low cost and good tensile strength besides various other desirable properties [1]. Steel pipeline suffers from severe corrosion when it comes into contact with acid solutions either during acid cleaning, transportation, de-scaling, storage of acids and exposure to other chemical processes [2].

However, pickling solution is quite corrosive, and the use of inhibitors is one of the most common methods for protection of the metal surface against corrosion, which are added in small amounts to retard the corrosiveness of the environments [3]. Inorganic inhibitors such as chromates, phosphates, and nitrates and organic inhibitors having heteroatoms and/or π-bonds compounds are the most commonly used metal corrosion inhibitors. The inorganic compounds have been observed to oxidize metal surface by forming impervious film that denies aggressive agents in the environment access to the surface [4]. However, inorganic inhibitors are very expensive and not degradable, and their disposals create pollution problems which make them harmful to the environment [5]. The organic inhibitors inhibit through the mechanism of adsorption onto metal surface using their heteroatoms and/or π-electrons as adsorption centres [6, 7]. Organic inhibitors have become widely accepted as effective corrosion inhibitors in various media. Most of the organic inhibitors containing nitrogen, oxygen, sulphur atoms and multiple bonds in their molecules facilitate adsorption onto the metal surfaces [8]. The adsorption ability and efficiency of the inhibitors are based on their chemical composition, molecular structure, type of functional groups and their attractions towards the coupon surface [9]. Recently, research works had been carried out and published on the use of natural inhibitors such as plant extracts on the corrosion inhibition of steel pipeline in different environments. These plant extracts are not only cost effective but environment friendly, bio-degradable, non-toxic, easily available, potentially with low cost and can be easily extracted by simple procedures [10, 11, 12, 13, 14, 15].

This work is designed to carry out the possibility of using Cardiospermum halicacabum, commonly known, as balloon plant as green corrosion inhibitor, which is a non-toxic, cheap, environmental friendly for steel pipeline in 0.5 M HCl solution. The objectives of this research work were to characterize the coupons before and after corrosion tests using Scanning Electron microscopy with energy dispersive spectroscopy (SEM/EDS). The extract was also characterized by quantitative and qualitative analyses and Fourier Transform Infrared Spectroscopy (FT-IR). Mathematical model was also used to determine which corrosion parameters (temperature, inhibitor concentration and exposure time) were statistically significant using analysis of variance (ANOVA).

2 Experimental Procedures

2.1 Materials

The chemical composition analysis conducted on steel pipeline coupon used for this study was carried out at Ajaokuta Steel Company Limited, Nigeria and the results are presented in Table 1.
Table 1

Chemical composition of steel pipeline coupon

Element

Fe

C

Si

Mn

P

S

Ni

Al

% Wt

Reminder

0.17

0.16

0.42

0.014

0.013

0.182

0.003

2.2 Extract and Solution Preparations

Fresh leaves of cardiospermum halicacabum (CH) were obtained from biological garden of University of Nigeria, Nsukka and are shown in Fig. 1 below. The leaves were washed with clean water and dried at room temperature (30 °C) for 72 h. The dried leaves were ground into powder and extracted via Soxhlet extractor using 70 percent ethanol and 30 percent distilled water. The extract was allowed to cool to room temperature, filtered, evaporated, and the concentrations of the extract were obtained. The corrosive solution of 0.5 M HCl was prepared by dilution of analytical (AR) grade 37% HCl with double distilled water. The concentration range of CH leaves extract were 5, 10, 15, 20 and 25% v/v,, respectively.
Fig. 1

Cardiospermum halicacabum (CH) leaf

2.3 Determination of Phytoconstituents of the Leaf Extract

The phytochemical constituents were determined by quantitative and qualitative methods. The analyses were carried out at the Energy Centre, University of Nigeria Nsukka.

2.3.1 Characterization of Leaf Extract by FT-IR Spectroscopy

Prepared small quantity of CH powdered sample was then exposed to infrared radiation. The sample molecules selectively absorb radiation of specific wavelength which causes the change of dipole moment of the sample molecules [16]. The commonly used region for infrared absorption spectroscopy was from 4000 to 400 cm−1. This is because the absorption radiation of within this region. The FT-IR was carried out using Perkin Elmer 2000 Model at the Energy Centre, University of Nigeria, Nsukka. The spectra obtained were then interpreted using Standard Library [17].

2.4 Corrosion Measurement Methods

2.4.1 Gravimetric Measurements

The weight loss experiments were carried out in accordance with the methods reported elsewhere [18, 19, 20]. Coupon specimens with dimensions of 3.0 cm × 2.5 cm × 0.50 cm were abraded with various grades of wax coated emery papers from 600 to 1600 grit. Specimens were degreased in absolute ethanol, dried in acetone, accurately weighed and stored in moisture-free desiccators prior to use to avoid reaction with atmospheric air. In gravimetric experiments, pre-weighed coupons were immersed in 0.5 M HCl solution without and with inhibitor concentrations of 5, 10, 15, 20 and 25% v/v of CH leave extracts for 12 days at an interval of 2 days for withdrawal. The experiments were carried out using calibrated thermostat at temperatures 30, 40, 50 and 60 °C, respectively. After the time elapsed, the specimens were removed, washed with distilled water, dried with acetone and re-weighed accurately. To ensure the reproducibility of the weight loss results, each experiment was performed in triplicate and mean values are used. From the weight loss obtained, corrosion rate, inhibition efficiency (IE%) and the surface coverage (θ) were computed using the following relationships according to Eqs. (1)–(3) [2, 21]:
$${\text{Corrosion}}\,{\text{Rate}}\,\left( {\text{CR}} \right)\, = \,\frac{KW}{DAT},$$
(1)
where CR is corrosion rate in mm/year, W is weight loss in (gm), D is the density (gcm−3), A is the area (cm2) and T is time, K a constant equal to 87500. Here, W is the weight loss (gm), i.e. the difference between initial (Wi) and final (Wf) of the coupons.
$${\text{Inhibition}}\,{\text{efficiency}}\,\left( {{\text{IE}}\% } \right)\, = \,\frac{{C_{\text{Ra}} }}{{C_{\text{Rp}} }}\, \times \, 100$$
(2)
$$\theta = \frac{{C_{\text{Ra}} - C_{\text{Rp}} }}{{C_{\text{Ra}} }},$$
(3)
where CRa and CRp are the corrosion rates in the absence and the presence of the extract, respectively.

2.4.2 Electrochemical Measurements

The electrochemical studies were made using a three-electrode cell assembly in a 0.5 M HCl static solution at 30 °C. The steel pipeline of 1.23 m2 served as the working electrode; platinum electrode was used as an auxiliary/counter electrode, and the standard calomel electrode (SCE) was used as the reference electrode. Before each electrochemical experiment, the working electrode was immersed in the test solution for 30 min, in order to attain a stable open circuit potential (OCP). Polarization was measured at the sweep rate of 1.0 mV s −1 from −250 to + 250 mV of OCP. Corrosion current density (Icorr) values were calculated using Tafel extrapolation method and by taking an extrapolation interval of 100 mV around Ecorr value once it becomes stable. The inhibition efficiencies (IE%) were calculated as per Eq. (4) given elsewhere [21, 22].
$${\text{IE}}\% \, = \, \frac{{i_{\text{corr}} \, - \, i^{\prime}_{\text{corr}} }}{{i_{\text{corr}} }}\, \times \,100\%,$$
(4)
where icorr and \(i^{\prime}_{\text{corr}}\) are the corrosion current densities of steel pipeline in the absence and the presence of the inhibitor,, respectively.

2.5 Surface Analysis

Surface analysis was carried out by immersing the coupon samples in the test solution in the absence and the presence of optimal concentration of 20% v/v of CH at 303 K for 2 days. The samples were retrieved after 2 days of immersion, rinsed with distilled water, dried in nitrogen, and then submitted for SEM/EDS analyses for analysis. The scanning electron microscope equipped with energy dispersive spectroscopy (SEM/EDS) was used to investigate the morphologies of the coupons before and after corrosion tests. The instrument model used for the studies was JOEL JSM 5900LV operating at 5 kV accelerating voltage with a magnification of 5000.

2.6 Development of Mathematical Model

The standard L8 orthogonal array was adopted in the design of the experiment in order to investigate which corrosion control parameters significantly affect the corrosion rate. The independent process parameters considered for the investigation are inhibitor concentration, exposure time and temperature. Two levels of each of the three factors were used for the statistical analysis. The levels for the three factors are shown in Table 2, and the treatment combinations for the two levels and three factors are found in Table 3. The model equation was obtained by representing the corrosion rate value by CR, which is a function of three variables as expressed in Eq. (5) [23]:
$${\text{CR}}\, = \,f\left( {K,\,L,\,M} \right),$$
(5)
where K is the temperature, L is the inhibitor concentration and M is the exposure time. The model selected includes the effects of first-order main variables and second-order interactions of all variables. Hence, the general model is written in the form of Eq. 6 [23].
$${\text{CR}}\, = \,\beta_{0} \, + \,\beta_{1} K\, + \,\beta_{2} L\, + \,\beta_{3} M\, + \,\beta_{4} KL\, + \,\beta_{5} KM\, + \,\beta_{6} LM\, + \,\beta_{7} KLM,$$
(6)
where β0 is average response of CR, and β1, β2, β3, β4, β5, β6, β7 are the coefficients associated with each variable K, L, M and interactions. The test results are recorded against the standard order of sequence as shown in Table 4. The sum of squares for main and interaction effects was calculated using Yates algorithm. The significant factors (main and interaction) were identified using analysis of variance (ANOVA) technique [24, 25].
Table 2

Statistical design of the corrosion process

Factors

Low level

High level

Temperature (K)

303 K

333 K

Inhibitor concentration (L)

0

25% v/v

Exposure time (M)

1 day

12 days

Table 3

Factorial design of the corrosion process showing treatment combination

Exptal. number

Temperature level

Concentration level

Time level

1

− 1

− 1

− 1

K

+1

− 1

− 1

L

− 1

+1

− 1

KL

+1

+1

− 1

M

− 1

− 1

+1

KM

+1

− 1

+1

LM

− 1

+1

+1

KLM

+1

+1

+1

Coded = − 1(low level), + 1(upper level or high)

Table 4

Factorial design of the corrosion process showing treatment combination

Exptal. number

Temperature level

Concentration level

Time level

1

303

0

1

K

333

0

1

L

303

10

1

KL

333

10

1

M

203

0

12

KM

333

0

12

LM

303

10

12

KLM

333

10

12

Coded = − 1(low level), + 1(upper level or high)

3 Results and Discussion

3.1 Chemical Composition of the Coupon

The chemical composition of the steel pipeline was determined using sparked method at the Ajaokuta Steel Company. The results from the test are presented in Table 1.

3.1.1 Determination of Phytoconstituents of the CH Leaves

The phytochemical constituents of the leaves were determined by both quantitative and qualitative analyses, after being washed, dried and ground using mortar and pestle. The results indicated that the leaves contain alkaloids, tannins, flavonoids, glycosides, saponins, etc. Tables 5 and 6 show the results of the analyses, respectively.
Table 5

Quantitative analysis of Cardiospermum halicacabum (CH) leaf

S/No

Leaf

Alkaloids (%)

Tannins (mg/100 g)

Saponins (%)

Flavonoids (%)

Glycosides (mg/100 g)

Volatile oil (%)

1

CH

9.04

1296

5.98

5.32

889

3.01

Table 6

Qualitative analysis of Cardiospermum halicacabum (CH) leaf

S/No

Leaf

Alkaloids

Tannins

Saponins

Flavonoids

Glycosides

Volatile oil

1

CH

++

+++

++

+

+++

+

3.1.2 Characterization of Leaf Extract by FT-IR Spectroscopy

Fourier Transforms Infrared (FT-IR) Spectroscopy was used to identify the active ingredients (chemical bonding and functional groups). The spectra were recorded, and the interpretations were done using Standard Library. The prominent peaks obtained from the FT-IR spectroscopy analysis for the extract are presented in Table 7. Figures 3, 4 show the IR absorption spectra of the extract and their functional groups.
Table 7

Prominent peaks obtained from reflectance FTIR spectroscopy for CH extract

S/No

Frequency range (cm−1)

Band assignments

1.

3416.87

N–H stretching of amines

2.

2923.33

CH2 symmetric mainly lipids

3.

2855.19

CH2 symmetric stretching of amino acid

4.

1649.87

N–H– in-plane bending mainly proteins

C–Br stretching of halogen derivatives

5.

583.56

6.

1545.21

C=O stretching mainly proteins

7.

1463.01

N–H in plane of lactans

C=S stretching mainly sulphur compounds

8.

1407.68

9.

1243.84

CH2 out-of-plane bending of alkanes

10.

1112.33

Symmetric stretching of amino acids

11.

1023.56

SO3 symmetric stretching of amino acids

12.

668.49

C–Br stretching of halogen derivatives

13.

613.20

C–I stretching of iodo compounds

14.

465.39

S–S stretching mainly sulphur compounds

3.1.3 Weight Loss and Potentiodynamic Polarization Measurements

The results of the weight loss/corrosion rate are presented in Fig. 2. Table 8 shows the corrosion rate, inhibition efficiency (% IE), and surface coverage (θ) for steel pipeline in 0.5 M HCl solution without and with the concentration of CH extract at 303 K for 12 days. The effects of temperature on inhibition efficiency of the leaves are presented in Fig. 5. The potentiodynamic polarization results are being presented in Fig. 6 and Table 9,, respectively.
Fig. 2

Variation of inhibition efficiency (% IE) with inhibitor concentration at 303 K

Table 8

Corrosion rates, inhibition efficiencies (% IE), and surface coverages (θ) for steel pipeline in 0.5 M HCl solution without and with the concentration of CH extract at 303 K for 12 days

Inhibitor concentration  % v/v

Corrosion rate (mmpy)

Inhibition efficiency (% IE)

Surface coverage (θ)

Blank (0)

25.561

5

6.052

76.34

0.76

10

2.881

88.72

0.89

15

1.508

94.12

0.94

20

0.870

98.56

0.99

25

0.383

98.42

0.98

Table 9

Potentiodynamic polarization parameters of steel pipeline in 0.5 M HCl in the absence and the presence of CH extract at 303 K

Concentrations (% v/v)

βa V/Dec

βC V/Dec

Ecorr V/SCE

Icorr, A/cm2

% IE

Blank

100

98

− 0.7323

1.44E−03

5

94

123

− 0.3497

5.41E−04

62.43

10

95

120

− 0.3255

8.76E−05

93.92

15

93

118

− 0.6233

8.13E−06

99.44

20

92

109

− 0.6322

1.19E−06

99.92

25

91

104

− 0.6766

1.09E−06

99.92

3.1.4 Adsorption Consideration

The adsorption of cardiospermum halicacabum (CH) extract onto steel pipeline surface in 0.5 M HCl solution was determined by fitting the experimental data obtained from gravimetric method in Table 8 into different adsorption isotherm models such as El-Awady, Freundlich, Temkin and Langmuir isotherms. Langmuir plot of C/θ against inhibitor concentration C for steel pipeline in 0.5 M HCl containing different concentrations of (CH) at different temperature is presented in Fig. 7. Table 10 shows thermodynamic parameters for the adsorption of inhibitor on steel pipeline in 0.5 M HCl at optimal concentration (20% v/v) of inhibitor at 303–333 K.
Table 10

Thermodynamic parameters for the adsorption of inhibitor on steel pipeline in 0.5 M HCl at optimal concentration (20% v/v) of inhibitor at 303–333 K

Inhibitor

Temp.

Langmuir isotherm

(K)

\(- \Delta G^{\text{o}}_{\text{ads}}\), KJ/mol

Slope

R 2

K ads

Cardiospermum halicacabum (CH)

303

73.74

1.3437

0.998

73.6

313

67.68

1.0356

0.999

39.1

323

57.91

0.9919

0.999

12.3

333

47.70

0.967

0.999

10.8

3.1.4.1 Activation Parameters
Figure 8 shows the Arrhenius plots of the corrosion rates (CRs) of steel pipeline in 0.5 M HCl in the absence and the presence of optimal concentration of CH. Effective activation energy (Ea) values of steel pipeline dissolution in 0.5 M HCl in the absence and the presence of CH at 303 K are presented in Table 11.
Table 11

Effective activation energy (Ea) values of steel pipeline dissolution in 0.5 M HCl in the absence and the presence of CH at 303 K

Concentration of CH

Ea (kJ mol−1)

Blank (0)

11.71

5% v/v CH

34.22

10% v/v CH

34.43

15% v/v CH

64.12

20% v/v CH

67.79

25% v/v CH

95.26

3.1.5 Surface Morphological Studies

Figure 9a–c shows the SEM/EDS morphology of steel pipeline in (a) the as-received polished state, (b) in the presence of 0.5 M HCl solution and (c) after exposure to 0.5 M HCl solution + optimal concentration of 20% v/v.

3.1.6 Analysis of Variance and the Effects of Parameters on the Corrosion Rate

Table 12 showed the analysis of variance (ANOVA) for corrosion rate in the presence of CH extract. Effect of the variables at 95% confidence level for CH extract was presented in Table 13. Comparison of the actual with the predicted results for steel pipeline using CH was presented in Table 14. Figure 10 showed the variation of actual and predicted values with standard order of the experiment in the presence of CH. Orthogonal diagrams of corrosion rate of CH, temperature, inhibitor and time are presented in Fig. 11.
Table 12

Analysis of variance (ANOVA) for corrosion rates in the presence of CH extract

Source of variation

Sum of squares

Degree of freedom (DF)

Mean square

\(F_{\text{cal}} \, = \,\frac{\text{Ms}}{{{\text{Error}}\,{\text{Ms}}}}\)

F value

F (%)

Main effect

 A

433.80

1

1115.33

183.03

0.005

7.78

 B

4447.66

1

433.80

71.19

0.0138

79.76

 C

658.66

1

4447.66

729.88

0.0014

11.81

Interaction

 AB

29.76

1

29.76

4.88

0.1577

0.53

 AC

6.75

1

6.75

1.11

0.4029

0.12

 Residual

12.19

2

6.09

  

0.22

 Cor. total

5576.64

7

   

100

Table 13

Effects of the variables at 95% confidence level for CH extract

Factor

Coefficient estimate

Degree of freedom

Standard error

95% CI low

95% CI high

Intercept

43.05

1

0.87

39.30

46.81

A-temp. 1.00

7.36

1

0.87

3.61

11.12

B-inhibitor 1.00

− 23.58

1

0.87

− 27.33

− 19.82

C-time 1.00

− 9.07

1

0.87

− 12.83

− 5.32

AB 1.00

− 1.93

1

0.87

− 5.68

1.83

AC 1.00

− 0.92

1

0.87

− 4.67

2.84

Table 14

Comparison of the actual with the predicted results for steel pipeline using CH

Standard order of the experiment

Temp. (K)

Inhibitor (% v/v)

Time (mins)

Corrosion rate (mpy × 10−3)

Actual

Predicted

Residual

S11

− 1

− 1

− 1

67.24

65.50

1.74

S12

+ 1

− 1

− 1

85.96

85.92

0.042

S13

− 1

+ 1

− 1

20.45

22.19

− 1.74

S14

+ 1

+ 1

− 1

34.86

34.90

− 0.043

S15

− 1

− 1

+ 1

47.44

49.19

− 1.75

S16

+ 1

− 1

+ 1

65.89

65.93

− 0.043

S17

− 1

+ 1

+ 1

7.63

5.88

1.75

S18

+ 1

+ 1

+ 1

14.96

14.92

0.043

3.2 Discussions

3.2.1 Effect of Concentrations

Weight loss measurements were performed on steel pipeline immersed in 0.5 M HCl solution with and without (CH) leaves extract for 12 days. Gravimetric analyses in the absence and the presence of the inhibitor with various concentrations are presented in Table 8 and Fig. 2,, respectively. Figure 2 shows that the inhibition efficiency increases with the increasing inhibitor concentration, which is due to the increases in the mass and charge transfer to the steel pipeline surface leading to the adsorption of inhibitor molecules and reduction in the metal dissolution. Further, increasing the inhibitor concentration causes little or negligible change in the inhibition efficiency values, and 20% v/v was taken as optimal concentration of the inhibitor. The inhibitor showed an effective anti-corrosion potential, and the results clearly indicated that the inhibition mechanism involved blockage of the steel pipeline surface by the inhibitor molecules via adsorption. Owing to the acidity of the corrosive medium, the extract which contains the phytochemical constituents could not remain in solution in its free base state. It may exist as neutral species or in its cationic form which are given in Figs. 3, 4 and Table 7, respectively. This assertion also agrees with the findings of the previous studies [26, 27].
Fig. 3

FT-IR transmittance spectra of Cardiospermum halicacabum (CH)

Fig. 4

FT-IR showing the functional groups/structures present in CH extract

The inhibition is possibly due to the fact that Cl−1 is hydrated in HCl and would be poorly adsorbed onto the metal surface leaving more active sites for the adsorption of the inhibitor—neutral species—and thus inhibition efficiency is increased with the increasing concentrations of inhibitor in HCl medium. Hence, it can be concluded that while adding the inhibitor to HCl solution the anions like COOH, OH present in the inhibitor solution, and the unshared pair of electrons present on the various hetero atoms present in the functional groups like C=O, O–H, N–H, NH2 gets adsorbed on the steel pipeline. This is similar the findings of [28].

3.2.2 Effect of Temperature on Inhibition Efficiency

The effect of temperature on inhibition efficiency was also investigated and the results obtained at the temperature range of 30–60 °C were shown in Fig. 5. It can be seen that the inhibition efficiency decreases with the increasing temperature because at high temperature, the hydrogen evolution increases on the metal surface and this leads to desorption of the adsorbed inhibitor film from the metal surface [29, 30]. This could also be attributed to the increasing rates of ionization and diffusion of active species in the corrosion process. Similar observation has been made by various workers on the corrosion of metals in both HCl and H2SO4 solutions at high temperatures [31, 32].
Fig. 5

Variation of inhibition efficiency (% IE) with concentration of inhibitor at different temperatures (303–333 K)

3.2.3 Potentiodynamic Polarization

The corrosion kinetics of both cathodic and anodic reactions of steel pipeline in 0.5 M HCl in absence and presence of different concentration of CH inhibitor at 303 K were presented in Fig. 6 and Table 9. The figure shows that both the cathodic and anodic reactions were suppressed with the addition of CH, and this resulted in a protective film formed on the metal surface, decreasing the corrosion current values (Icorr) as shown in Table 9. Table 9 reveals that the corrosion current density (icorr) in the presence of inhibitor is quite less, 8.361 μAcm−2 for 5% v/v, 6.352 μAcm−2 for 10% v/v compared to blank of 35.61 μAcm−2. The minimum reduction in corrosion current density of 0.716 μAcm−2 occurred at optimal concentration of 20% v/v with  % IE of 97.99 suggesting that the inhibitor had been adsorbed at the steel pipeline/solution interface and reduce the corrosion process greatly. There was significant decrease in the value of icorr with increasing CH concentrations from 5 to 25% v/v. The decrease in the current densities can be explained by the fact that the addition of the inhibitor reduces the hydrogen evolution and the dissolution of steel pipeline at both cathodic and anodic reactions,, respectively. However, the displacement of EOCP towards more negative values by the extract may imply greater effect of the extract on steel pipeline oxidation reaction than on hydrogen ions reduction reaction. The actual characterization of an inhibitor as anodic, cathodic, or mixed-type depends on the difference between Eocp of the uninhibited and inhibited solutions. In the previous works [33, 34, 35], the benchmark was fixed at ± 85 mV. If the displacement in Ecorr is > 85 mV, the inhibitor is either cathodic or anodic in nature and if the displacement of Ecorr is < 85 mV, the inhibitor is seen as mixed type and from the result, Ecorr is < 85 mV and said to be mixed-type inhibitor with predominant cathodic behaviour [36, 37].
Fig. 6

The Tafel curves for steel pipeline in 0.5 M HCl in absence and presence of CH extract concentrations at 303 K

3.2.4 Adsorption Consideration

It has been established in the previous findings that adsorption of organic inhibitor onto corroding metal surface does attain real equilibrium but tend to attain an adsorption steady state. As the corrosion rate appreciably decrease to minimum, the adsorption steady state attains a state of quasi-equilibrium [10]. The adsorption of the inhibitor molecules is always governed by the quasi-substitution process between the adsorbed water molecules on the metal surface and the inhibitor in the aqueous phase.

In this work, the adsorption of cardiospermum halicacabum (CH) extract onto steel pipeline surface in 0.5 M HCl solution was determined by fitting the experimental data obtained from gravimetric method in Table 8 into different adsorption isotherm models such as El-Awady, Freundlich, Temkin and Langmuir isotherms as described elsewhere [21, 25] and the correlation coefficient (R2) values were used to determine the best fit isotherms.

The best fitting was found to obey the Langmuir adsorption isotherm given in Eq. 7, which is based on the assumption that all adsorption sites are equivalent and that particle binding occurs independently from nearby sites being occupied or not [33, 34].
$$\frac{\theta }{1 - \theta }\, = \,K_{\text{ads}} C\,{\text{or}}\, \frac{{C_{\text{inh}} }}{\theta }\, = \,\frac{1}{{K_{\text{ads}} }}\, + \,C_{\text{inh}}$$
(7)
where Cinh is the inhibitor concentration, Kads is the adsorptive equilibrium constant and θ is the surface coverage.
Figure 7 shows the graph of \(\frac{C}{\theta }\) against C at 303–333 K for steel pipeline corrosion in 0.5 M HCl solution containing different concentrations of CH leaves extract. From the graph, Kads values decreases from 73.6 to 10.8 and were calculated from the intercepts of the straight line. However, the Kads values denote the strength of adsorbed inhibitor layer on metal surface as reported by [1, 39]. This implies that the higher the Kads value the stronger the bond between the adsorbent and the adsorbate and Kads is also related to free energy of adsorption (∆Gads) represented in Eq. 8 [38].
Fig. 7

Langmuir plot of C/θ against inhibitor concentration C for steel pipeline in 0.5 M HCl containing different concentrations of (CH) at different temperature

$$\Delta G_{\text{ads}} \, = \, 2. 30 3RT\,{ \log }\left( { 5 5. 5\,K_{\text{ads}} } \right),$$
(8)

where R is the molar gas constant 8.314 JK−1mol−1 and T is the absolute temperature. The value of 55.5 is the concentration of water in solution in mol L−1. Table 10 shows the results of ∆Gads, Kads, R2 and the slope of the graph. The values of ∆Gads are − 73.74 kJ mol−1 at 303 K and 47.70 kJ mol−1 at 333 K. The negative values of ∆Gads signified spontaneity of the adsorption process and the stability of the adsorbed (CH) extract on steel pipeline surface and similar to the findings of [39, 40].

Gads values around − 20 kJ mol−1 or lower are interpreted to be indicative of physical adsorption (i.e. electrostatic interaction between charged metal surfaces and charged inhibitor species), while that around − 40 kJ mol−1 or higher are consistent with chemical adsorption which has to do with the sharing or charge transfer between metal surface and inhibitor molecule. The calculated ∆Gads values are higher than − 40 kJ mol−1; hence, the adsorption of CH extract onto steel pipeline surface in 0.5 M HCl solution was mainly through chemical adsorption mechanism [23, 41].

3.2.5 Activation Parameters

The effective activation energy (Ea) was calculated using the Arrhenius in Eq. 9 as reported by [43, 44]:
$${\text{LogCR}}\, = \,{\text{logA}}\, - \,{\text{Ea}}/ 2. 30 3RT,$$
(9)
where Ea is the apparent effective activation energy, R is the general gas constant and A is Arrhenius pre-exponential factor. A plot of log of corrosion rate (CR) obtained by weight loss measurement versus \(\frac{1}{T}\) gave a straight line with a slope of − Ea/2.303R in Fig. 8. The values of activation energy corresponding to the extract concentrations are then presented in Table 11 showing that steel pipeline dissolution in the presence of inhibitor was reduced by forming the iron–inhibitor complex. The activation energy of the system in the presence of inhibitor is higher than that in the absence and conforms to the other work [42].
Fig. 8

Arrhenius plots of the corrosion rate (CR) of steel pipeline in 0.5 M HCl in the absence and the presence of optimal concentration of CH

3.2.6 Surface Morphological Studies

Figure 9a–c shows the SEM/EDS morphology of steel pipeline in (a) the as-received polished state, (b) in the presence of 0.5 M HCl solution and (c) after exposure to 0.5 M HCl solution + optimal concentration of 20% v/v. The surface of the coupon in Fig. 9a was relatively smooth and only revealed the polished surface. The EDS of the as-received coupon indicates the presence of Fe (wt% = 99.83 and carbons (wt% 0.15). Figure 9b shows the coupon being exposed to the corrodent and seriously damaged. The deposits of corrosion products can be seen clearly in the SEM. The EDS of Fig. 9b reveals the weight percentage of Fe to be 29.5 with other elements and oxides as a result of corrosion. Figure 9c showed the coupon exposed to corrodent in the presence of optimal concentration of 20% v/v CH. It could be seen that the surface of SEM was less rough and the most elements present were enhanced. This confirms that the adsorption of CH extract onto steel pipeline surface increases the heterogeneity of the surface. Comparing EDS spectra of Fig. 9a–c, the prominent peaks for Fe, Mn, and C with weight percentages (wt%) of 99.83%, 0.03%, and 0.17% are evident. On exposure to 0.5 M HCl solution, the intensity of Fe peak decreased and the wt% decreased to 29.5%, while other elements such as Ca, Mg, P, Na, Al were revealed in their oxides. This implies that steel pipeline lost some of its component elements to corrosion in 0.5 M HCl solution. In Fig. 9c, the wt% of Fe increased from 29.5 to 99.5%, with the alloying elements such as Mn, Si, etc. being enhanced. The difference could be indicative of oxygen-bearing active components in the extract being adsorbed onto the metal surface and seems to be a confirmation to the earlier assertion that the extract’s active components compete for direct adsorption onto steel pipeline surface. The adsorption of components of CH extract onto steel pipeline surface could be attributed to their functional groups obtained from FTIR results. The CH can be considered to be good and effective corrosion inhibitor of material in acid and similar to the previous findings [43, 44].
Fig. 9

a SEM/EDS of the as-received coupon. b SEM/EDS of steel pipeline in acid in the absence of CH extract for 12 days. c SEM/EDS of steel pipeline in the presence of optimal 20% v/v CH extract for 12 days

3.2.7 Analysis of Variance and the Effects of Parameters on the Corrosion Rate

The design parameters that were significantly influencing the corrosion rate (responses) were investigated by ANOVA. The results were presented in Table 12. It was evaluated for a confidence level of 95%, that is, for significance level of α = 0.05. The results obtained indicated that inhibitor was the most significant parameter having the highest statistical influence of 79.76% followed by time (11.81%) and temperature (7.78%). The F value for the model was less than 0.05 implying that the parameters or interactions were considered to be statistically significant [25]. The coefficient of determination (R2) was defined as the ratio of the explained variation to the total variation and a measure of the degree of fitness. From the results, as R2 was approaching unity, better response model results were indicated showing it fits the actual data. The value of R2 was 0.9651 (96.51%), high correlations with the experimental values were established and the model was obtained from Eq. (5).

A multiple linear regression analysis attempts to model the relationship between two or more variables and a response variable by fitting a linear equation to the observed data [23]. Based on the experimental results, a multiple linear regression model was developed, and the effects of 95% confidence levels for the extract are presented in Table 13. A regression equation thus generated establishes correlation between the significant terms obtained from ANOVA, namely, temperature, inhibitor concentration and time. Therefore, it was concluded that the influences of temperature, inhibitor concentration and time on the corrosion rate were statistically significant. The model equation was obtained after calculating each of the coefficients using Eq. 6. The developed model’s equation for the corrosion behaviour of the steel pipeline in the acidic environment in the presence of the green inhibitor is presented in Eq. 10:
$${\text{CR}}\,\left( {\text{CH}} \right)\,{ = }\, 4 3.0 5\, + \, 7. 3 6K\, - \, 2 3. 5L\, - \, 9.0 7M\, - \, 1. 9 3 {\text{KL}}\, - \,0. 9 2 {\text{KM}}$$
(10)

Substituting the coded values of the variables for any experimental conditions in Eq. 10, the corrosion rates values for the corrosion control behaviour of the steel pipeline were then calculated. The above equation was used to predict the corrosion rate of the steel pipeline under the studied condition. The results of linear regression model in Table 13 for the extract of CH show that the inhibitor (L) appears to be the most important variable with the main effect of − 23.58 mmpy, followed with time (M) with effect of − 9.07 mmpy and temperature (K) with main effect of 7.36 mmpy.

Still from Table 13, it is seen that increasing the concentrations from 0 to 25% v/v would lead to decrease in the corrosion rates by 23.58 mmpy, increasing the time from 1 to 12 days would decrease the corrosion rates by 9.07 mmpy and raising the temperature from 303 to 333 K would result in corrosion rate’s increase by 7.36 mmpy,, respectively. The interaction effects of the variables, namely, temperature, inhibitor concentration and time were also significant and must be taken into account for predicting the combined effect of temperature, inhibitor and time on the corrosion rate of any material. The interaction effects occur between temperature and inhibitor concentration (KL), temperature and time (KM), while inhibitor concentration and time (LM) have no effects on the system as shown in Eq. 10. This means that raising temperature and inhibitor concentration (KL) concurrently would result in decreasing the corrosion rate by 1.93 Mmpy, while increasing the temperature and time (KM) would lead to a decrease in the corrosion rate by 0.92 mmpy. Similar results have been observed by other researchers [24, 25]. This model enables one to predict the corrosion behaviour of material as a function of temperature, inhibitor concentration and time for any value of these parameters within their ranges specified in the present work.

3.2.7.1 Confirmation for Regression Equation
In order to validate the regression model, confirmation test was conducted with parameter levels that were used for the analysis. The difference in parameter levels chosen for the confirmation tests are shown in Table 14. Residual variation estimated in the Eq. 10 showed that the corrosion rate is in the range of − 1.74 to 1.75. The results of the confirmation test were obtained and comparison was made between the experimental corrosion rate values and the computed or predicted values obtained from the regression models as shown in Table 13 and represented in Fig. 10. The residual (error) values associated with the relationship between the experimental values and the computed values from the regression models for steel pipeline were very less (less than 4% error). This is in line with previous findings [23, 25]. Hence, the regression model developed demonstrated a feasible and an effective way to predict the corrosion rates of the steel pipeline in acidic environment—HCl.
Fig. 10

Variations of actual and predicted values with standard order of the experiment in presence of CH

Figure 11 shows the 3D surface plots for corrosion rates of steel pipeline in acidic environment. It shows the effects of temperature, inhibitor concentration and time on the, response of corrosion rate. It is clear from the figure that upon increasing the temperature from A to A+, the corrosion rate will increase from 65.50 to 85.92 mmpy, increasing the inhibitor concentration from B to B+ will decrease the corrosion rate from 65.50 to 22.19 mmpy and increasing the time from C to C+ will decrease the corrosion rate from 85.92 to 65.93 mmpy, respectively. The 3D orthogonal plots also confirmed that the inhibitor is very effective and reduces the corrosion rate to its minimum and also conforms to the findings of other studies [23, 24].
Fig. 11

Orthogonal diagrams of corrosion rates of CH temperature, inhibitor and time

4 Conclusions

The following conclusions can be drawn from the results obtained:
  1. 1.

    Cardiospermum halicacabum (CH) extract acted as an efficient anti-corrosive agent for steel pipeline in HCl solution. At the optimal point of concentration, it can increase the lifespan of the material by over 90%, and this can be utilized in industries.

     
  2. 2.

    The gravimetric weight loss technique showed the inhibiting effect of CH with percentage inhibition efficiency of 98.56 at 20% v/v but decrease with the increasing temperature. The adsorption of CH on steel pipeline surface obeys Langmuir adsorption isotherm.

     
  3. 3.

    Potentiodynamic polarization results showed that Cardiospermum halicacabum (CH) extract acted as mixed-type inhibitor.

     
  4. 4.

    The FT-IR revealed some major constituents such as Cyclohexane, Azodicarbonnamide (NH2 group), Trphenyl phosphine oxide and Ethyl methyl sulphide, which were adsorbed onto steel pipeline surface in 0.5 M HCl solution.

     
  5. 5.

    The SEM/EDS morphology of the adsorbed protective films on the steel pipeline surface confirmed the high performance of inhibitive effect of the active components of Cardiospermum halicacabum (CH).

     
  6. 6.

    ANOVA results revealed that the inhibitor concentration (L) is the most important variable with the main effect of − 23.58 mmpy, followed with time (M) with an effect of − 9.07 mmpy and temperature (K) with the main effect of 7.36 mmpy.

     

Notes

Acknowledgements

The authors are thankful to the staff of the university, who one way or the other contributed to the completion of this work.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Metallurgical and Materials EngineeringUniversity of Nigeria NsukkaNsukkaNigeria
  2. 2.Department of Metallurgical and Materials EngineeringAhmadu Bello University ZariaZariaNigeria
  3. 3.Department of ChemistryAhmadu Bello University ZariaZariaNigeria

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