New Trends in Corrosion Analysis of Al-Sn Alloy Duplex System

doi:10.4236/wjcmp.2011.12006

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World Journal of Condensed Matter Physics, 2011, 1, 33-36

doi:10.4236/wjcmp.2011.12006 Published Online May 2011 (http://www.SciRP.org/journal/wjcmp)

New Trends in Corrosion Analysis of Al-Sn Alloy

Duplex System

Chinedu Ekuma, Eziaku Osarolube, Ephraim O. Chukwuocha, Michael C. Onyeaju

Department of Physics, University of Port Harcourt, Port Harcourt, Nigeria.

Email: [email protected]

Received February 15th, 2011; revised March 18th, 2011; accepted March 20th, 2011.

ABSTRACT

The corrosion characterization of binary Al-Sn alloy systems has been statistically analyzed in the light of developed

model equations. It was observed that the modeled corrosion penetration rate values generated using the developed

model equations are in tandem with the experimental values.

Keywords: Al-Sn, Statistical Analysis, Corrosion, Model Equations, Correlation

1. Introduction

It has since been a worldwide problem for man to combat

the menace of material degradation. Many structural

failures and general loss of valuable engineering mate-

rials have been traced to be caused basically by analysis

and not synthesis [1] as over 313 failure cases studied [2]

have shown that well over 56.90% are due to corrosion.

The causes of materials degradation with the associated

environmental variables have been well explained in

many literatures [3-14].

A critical look at all forms of co rrosion show that th ey

are merely a statistical phenomenon hence, the yardstick

behind the adoption of statistics techniques in this

present study. However, even with the somewhat

semi-empirical nature of corrosion (as it show the rela-

tions between available data and measurements that do

not necessarily reveal any relation between cause and

effect), statistical models attempt to determine the fun-

damental relationship between sets of input data (predic-

tors) and targets (predictands) [15,16].

The adoption of statistical analysis in corrosion analy-

sis in metals has been predicted for years but, its usage

has been hampered primarily by the specialty skill

needed in applying this principle which, its impediment

lies basically on the lack of reference frame for its appli-

cation [16] .

In this present study, we will apply the non-linear re-

gression analysis technique to obtain model equations that

will be used to determine the corrosion parameter of in-

terest and other statistical parameters adequate for dis-

cussing and understanding the phenomenon of corrosion

(in this case, Al-Sn alloys of compositions 2.5% and 4.5%

by weight respectively of Sn) in selected media environ-

ments: HCl and NaCl of concentrations 0.5 M and 1.0 M

respectively, using the statistical software SPSS™.

The data of Idenyi et al. [17] has been used for this

analysis.

2. Results

The results of the corrosion penetration rate values for

the experimental and modeled values are as shown in

Tables 1 to 8, while Table 9 is the model equation of the

corrosion parameters of the various Al-Sn alloy systems

in the various concentrations of hydrochloric acid and

brine environments.

3. Discussion of Results

A cursory look at Tables 1-8 clearly reveals that the

modeled corrosion penetration values of the various bi-

nary alloy samples subjected to the varying concentra-

tions (0.5 M and 1.0 M) of hydrochloric acid and brine

environments respectively, are in tandem with the ob-

served experimental values. This is further confirmed by

the nearly perfect coefficient of correlations of all the

composites which is in the range

0.94 1.00R≤≤

(see

Table 9). The implication of this high positive coeffi-

cient of correlation is that the modeled values are in good

agreement with the experimental data. Thus, our model

can be of good usage in studying effect of the studied

environments on Al-Sn binary alloy system on expanded

time scale. In order to further confirm the dependence of

the corrosion penetration rate mainly on the exposure

New Trends in Corrosion Analysis of Al-Sn Alloy Duplex System

Table 1. CPR Data for Al – 2.5% Sn in 0.5 M HCl Envi-

ronment.

Time (Hrs) Experimental CPR

(mm/yr) Modeled CPR

(mm/yr)

12 2.08 1.763

24 1.25 1.334

0.90

1.083

0.73

0.905

60 0.62 0.767

0.55

0.654

84 0.51 0.559

0.47

0.477

108 0.44 0.404

120

0.43

0.338

132

0.42

0.28

144 0.39 0.226

Table 2. CPR Data for Al – 2.5% Sn in 1.0 M HCl Envi-

ronment.

Time (Hrs) Experimental CPR

(mm/yr) Modeled CPR

(mm/yr)

3.12

2.815

2.08

2.201

1.66

1.843

1.46

1.588

1.25

1.391

1.14

1.229

1.07

1.093

96 1.01 0.975

108 0.92 0.870

120 0.85 0.777

132 0.79 0.693

144

0.74

0.616

Table 3. CPR Data for Al – 2.5% Sn in 0.5 M NaCl Envi-

ronment.

Time (Hrs)

Experimental CPR

(mm/yr)

Modeled CPR

(mm/yr)

3.74

3.201

2.29

2.488

1.66

2.071

48 1.46 1.775

60 1.37 1.545

72 1.35 1.358

1.22

1.199

1.12

1.062

108

1.02

0.941

120

0.94

0.832

132

0.87

0.734

144

0.81

0.645

time (though alloy composition and other physical fac-

tors play a vital role in corrosion experiments), the coef-

ficient of determination of the various samples in their

different environments were also determined. It can be

verified (see Tabl e 9 ) that the range of the coefficients of

determination is 2

0.88 0.99R≤≤ . This shows that ap-

proximately 92.64% of the total variation in the corr osion

Table 4. CPR Data for Al – 2.5% Sn in 1.0 M NaCl Envi-

ronment.

Time (Hrs) Experimental CPR

(mm/yr) Modeled CPR

(mm/yr)

2.50

2.140

1.46

1.646

1.18

1.357

0.99

1.152

0.87

0.993

0.80

0.863

0.71

0.753

0.65

0.657

108

0.62

0.573

120

0.58

0.498

132

0.55

0.430

144

0.52

0.368

Table 5. CPR Data for Al – 4.5% Sn in 0.5 M HCl Envi-

ronment.

Time (Hrs) Experimental CPR

(mm/yr) Modeled CPR

(mm/yr)

12 3.12 2.549

24 1.66 1.890

36 1.18 1.505

0.94

1.231

0.79

1.019

0.73

0.846

0.64

0.699

0.60

0.573

108

0.54

0.461

120

0.5

0.360

132

0.46

0.270

144

0.43

0.187

Table 6. CPR Data for Al – 4.5% Sn in 1.0 M HCl Envi-

ronment.

Time (Hrs) Experimental CPR

(mm/yr) Modeled CPR

(mm/yr)

12 3.33 2.724

1.77

2.012

36 1.25 1.596

0.99

1.30

60 0.85 1.071

0.75

0.884

84 0.65 0.725

0.6

0.588

108 0.55 0.467

120

0.51

0.359

132 0.47 0.261

144

0.44

0.172

penetration rate in the whole environments is accounted

for by the corresponding variation in the exposure time.

The remaining 7.36% may be due to alloy composition

and other factors not incorporated in the model equations.

This is overwhelmingly significant and it further con-

firms that the developed model equations will be a good

New Trends in Corrosion Analysis of Al-Sn Alloy Duplex System

Table 7. CPR Data for Al – 4.5% Sn in 0.5 M NaCl Envi-

ronment.

Time (Hrs)

Experimental CPR

(mm/yr)

Modeled CPR

(mm/yr)

3.95

3.941

3.02

3.074

2.77

2.568

2.18

2.208

1.87

1.929

1.63

1.702

1.43

1.509

1.27

1.342

108

1.16

1.195

120

1.08

1.063

132

1.00

0.944

144

0.95

0.835

Table 8. CPR Data for Al – 4.5% Sn in 0.5 M NaCl Envi-

ronment.

Time (Hrs)

Experimental CPR

(mm/yr)

Modeled CPR

(mm/yr)

3.53

3.483

2.91

2.656

2.15

2.173

1.66

1.83

1.37

1.564

1.18

1.346

1.04

1.162

0.94

1.003

108

0.86

0.863

120

0.79

0.737

132

0.78

0.623

144

0.75

0.520

Table 9. The Modeled Corrosion Parameters for the Various Al-Sn Alloys in Different Media Concentration.

MEDIA CONCEN-

TRATION

COEFFICIENT OF CORRELA-

TION (R - VALUES)

COEFFICIENT OF DETERMINATION

- VALUES)

MODEL EQUATIO NS

Al – 2.5% Sn IN VARIOUS CONCE NTRATIONS OF HCl

0.5 M 0.94935 0.90126 3.299919 0.618580CPR In

= −

1.0 M 0.97840 0.95726

5.014043 0.885003CPR In

= −

Al – 4.5% Sn IN VARIOUS CONCE NTRATIONS OF HCl

0.5 M 0.93906 0.88183 4.910416 0.950385CPR In

= −

1.0 M 0.94087 0.88524

5.275761 1.026965CPR In

= −

Al – 2.5% Sn IN VARIOUS CONCENTRATIONS OF NaCl

0.5 M 0.95146 0.90527 5.757208 1.028719CPR In

= −

1.0 M 0.95772 0.91722

3.912334 0.713126CPR In

= −

Al – 4.5% Sn IN VARIOUS CONCE NTRATIONS OF NaCl

0.5 M 0.99582 0.99165 7.045895 1.249661CPR In

= −

1.0 M 0.98574 0.97168

6.445930 1.192448CPR In

= −

predictor of the corrosion trend in the various duplex

Al-Sn alloy systems being investigated.

3. Conclusion

The statistical analysis of the corrosion behaviour of

Al-Sn duplex alloy system has been investigated. It can

be observed that the modeled values of CPR obtained

from our model equations correlates well with the expe-

rimental data. This is attributed to the nearly p erfect pos-

itive coefficient of correlation that obtained in the analy-

sis which is consistent for all the alloy compositions.

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