Download full-text PDF

Experimental correlation between metallographic evaluation and electrochemical noise in intergranular corrosion tests of aluminium alloys

Article (PDF Available) inSurface and Interface Analysis 44(9) · September 2012with30 Reads
DOI: 10.1002/sia.5003
Abstract
In the present work, the correlation between the metallographic evaluation and electrochemical noise (EN) in intergranular corrosion (IGC) tests of aluminium alloy 2024-T3 has been analysed. For this purpose, the influence of temperature and hydrogen peroxide concentration on the IGC attack has been studied. Similar IGC was observed between 20 and 40 °C, showing a low dependence with temperature (at least in this range). Hydrogen peroxide was seen to have a strong effect, leading to IGC activation when raising its concentration. The results of the detailed metallographic evaluation of the samples after the tests were analysed together with the EN measured during the tests. The averaged noise resistance was inversely proportional to the depths of the attacks, whereas the average of the parameter so-called 'Statistical Noise Power' was directly related to the IGC degree. The metallographic evaluation and the EN showed a reasonable experimental correlation
Figures
Experimental correlation between
metallographic evaluation and electrochemical
noise in intergranular corrosion tests of
aluminium alloys
J. M. Sánchez-Amaya,
a,b
* L. González-Rovira,
c
M. R. Amaya-Vázquez
c
and
F. J. Botana
c
In the present work, the correlation between the metallographic evaluation and electrochemical noise (EN) in intergranular
corrosion (IGC) tests of aluminium alloy 2024-T3 has been analysed. For this purpose, the inuence of temperature and
hydrogen peroxide concentration on the IGC attack has been studied. Similar IGC was observed between 20 and 40 C,
showing a low dependence with temperature (at least in this range). Hydrogen peroxide was seen to have a strong effect,
leading to IGC activation when raising its concentration. The results of the detailed metallographic evaluation of the samples
after the tests were analysed together with the EN measured during the tests. The averaged noise resistance was inversely
proportional to the depths of the attacks, whereas the average of the parameter so-called Statistical Noise Powerwas directly
related to the IGC degree. The metallographic evaluation and the EN showed a reasonable experimental correlation. Copyright
© 2012 John Wiley & Sons, Ltd.
Keywords: aluminium alloys; intergranular corrosion; metallographic evaluation; electrochemical noise; noise resistance; noise power
Introduction
Intergranular corrosion (IGC) is the attack produced at the grain
boundaries and in the area surrounding them, without affecting
the bulk of the grains. In aluminium alloys, IGC usually appears as
a consequence of a selective precipitation of intermetallic particles
at the grain boundary during heat treatments.
[1,2]
The different
electrochemical behaviour of the precipitates (second phases)
and the aluminium matrix provokes the formation of a galvanic
coupling that encourages IGC.
[3]
Although this corrosion
mechanism does not provoke great losses of metal, the mechanical
properties of the alloy are strongly affected.
[4]
In addition, zones
affected by IGC can promote the formation of cracks, which can
lead to stress corrosion cracking or corrosion fatigue processes.
Therefore, the study of the susceptibility to IGC of aluminium alloys
is of high scientic interest and of a great technological importance
because the early detection of this type of corrosion will help avoid
catastrophic failures of structures in service.
[2]
Accordingly, important efforts have been devoted to study the
mechanisms of initiation and propagation of IGC in aluminium
alloys, specially 2XXX and 6XXX series. Mankowski
[5,6]
and
Svennigsen
[710]
reported that initiation of IGC depends on the cop-
per content of the aluminium alloy. In fact, the formation of
intermetallic particles containing copper in the grain boundaries
has proven to provoke the aforementioned galvanic coupling.
Regarding the phenomenon of the IGC propagation, some
authors
[11]
found that IGC rate is related to grain size and shape.
High strength aluminium alloys such as 2XXX series are often
elongated and anisotropic, with the fastest IGC growth rate in the
longitudinal direction or long transverse direction and the slowest
in the short transverse direction.
[11]
In the literature, several methods have been described to
evaluate the susceptibility to IGC of different alloys. In the case of
aluminium alloys, different eld tests can be used. In these tests,
the samples are exposed to the same medium in which they are
going to be exposed in service, as in sea water or in rural, industrial
or marine atmosphere.
[12]
As an example, Svenningsen et al.
[7]
used
eld test for detecting the susceptibility to IGC of 6XXX series alu-
minium alloys, based on the atmospheric exposure of the
samples, which lasted from 6 to 24 months.
Although the most reliable methods for determining the
susceptibility to IGC are the aforementioned eld tests, accelerated
immersion tests are usually employed. These latter methods have
the great advantage of being much faster than the eld tests
because they can estimate the susceptibility to IGC in only hours.
In these accelerated tests, very aggressive solutions are employed,
* Correspondence to: Titania, Ensayos y Proyectos Industriales S.L. (TITANIA).
Parque Tecnológico TecnoBahía, Edif. RETSE Nave 4. Ctra. Sanlúcar Km 7, El
Puerto de Santa María, Cádiz, Spain. E-mail: josemaria.sanchez@titania.aero
aTitania, Ensayos y Proyectos Industriales S.L. (TITANIA), Parque Tecnológico
TecnoBahía, Edif. RETSE Nave 4. Ctra. Sanlúcar Km 7, El Puerto de Santa María,
Cádiz, Spain
bDepartamento de Física Aplicada, Escuela Politécnica Superior de
Algeciras, Universidad de Cádiz, Avenida Ramón Pujol s/n, Algeciras
11202, Cádiz, Spain
cLaboratorio de Corrosión y Protección (LABCYP), Departamento de Ciencia
de los Materiales e Ingeniería Metalúrgica y Química Inorgánica, CASEM,
Universidad de Cádiz, Avda. República Saharaui s/n, Apdo. 40, Puerto Real
11510, Cádiz, Spain
Surf. Interface Anal. 2012,44, 12791286 Copyright © 2012 John Wiley & Sons, Ltd.
Research article
Received: 19 September 2011 Revised: 16 March 2012 Accepted: 20 March 2012 Published online in Wiley Online Library: 17 April 2012
(wileyonlinelibrary.com) DOI 10.1002/sia.5003
1279
such as sodium chloride and hydrochloric acid aqueous solu-
tions, which are used in method B of the British Standard BS
11846.
[13]
This method has been recently applied in the works of
Svenningsen.
[710]
Additionally, another accelerated test that can
be employed is the method recommended by the Standard ASTM
G11092 (2009),
[14]
recently used by Sánchez-Amaya et al.,
[1]
based
on the employment of sodium chloride and hydrogen peroxide
aqueous solutions. The evaluation of the damage suffered by the
samples during the tests is usually based on metallographic analysis
of cross sections, although other evaluation methods considering
mechanical properties
[10]
or, more recently, 3D images generated
by means of X-ray tomography can also be employed.
[15,16]
Although there is no established procedure based on
electrochemical techniques allowing the determination of the
susceptibility to IGC of aluminium alloys, some studies can be
found in the literature. Among them, the behaviour of 2XXX
aluminium alloys samples has been analysed by means of the
linear polarisation (LP) technique,
[2,17]
in which the breakdown
potentials are related to IGC or pitting processes. Even though
LP curves can be used to evaluate the behaviour of aluminium
alloys against IGC, this technique has the disadvantage of
severely damaging the samples. Thus, as LP is a destructive
technique, it is not possible to use it in subsequent studies
on the same samples. In this context, techniques such as
electrochemical noise (EN) show clear advantages and are very
promising because they are not intrusive and do not disturb
the natural corrosion processes taking place. Thus, the EN signals
obtained are spontaneously generated by the corrosion systems
and are not affected by the measurement procedure.
[18,19]
However, relatively few works oriented to the study of IGC by
means of EN have been found in the literature, with most of them
dealing with stainless steels. For example, Ritter et al.
[20]
studied
IGC phenomena by means of EN in austenitic stainless steel
samples (AISI 347) in acidic sodium tetrathionate (Na
2
S
4
O
6
)
solutions at 70 C. This solution has been seen to promote only
IGC in stainless steel and does not induce pitting corrosion. More
recently, Pujar et al.
[21]
employed EN to detect and quantify
IGC processes in AISI 316 samples with different degrees of
sensitization. Similarly, EN has been successfully applied to
determine the effect of varying the concentration and
temperatures of nitric acid on IGC of sensitised AISI 304
samples.
[22]
Other studies concerning the analysis of IGC
phenomena with EN in zirconium and titanium alloys
[23]
and in
lead
[24]
have been made.
In aluminium alloys, Sánchez-Amaya et al.
[1]
have recently
analysed, by means of EN and metallographic evaluation, the
susceptibility to IGC of 2024 and 7075 samples subjected to
different heat treatments. In this work,
[1]
normalised tests
(according to ASTM G 11092 (2009)) were performed, the
damage suffered by the samples being evaluated by
metallographic analysis and, in parallel, by the analysis of EN
generated during the tests. Although these results showed some
tendencies relating metallographic observations and EN data,
further investigations are required to prove this correlation.
Sánchez-Amaya et al.
[1]
also indicate that further work is
necessary to understand the effect of the different experimental
variables on the IGC attack produced in the aluminium alloy
samples subjected to the normalised test ASTM G 11092 (2009).
In the present paper, the inuence of the temperature of the so-
lution and the hydrogen peroxide concentration of the testing so-
lution are analysed. AA2024 samples were immersed in different
solutions promoting IGC, the assessment of the attack produced
in these tests being carried out by metallographic observations af-
ter tests and EN measured during the tests. The main objective of
the work has been to study the experimental correlation between
the results of both techniques. The analysis of this experimental
relationship is considered of high interest for the corrosion com-
munity as once this correlation is proven, EN can be used to eval-
uate the susceptibility to IGC of metallic alloys. A possible future
output of this research line may be the development of quality
control tests of susceptibility to IGC based on EN.
Experimental
In the present work, the behaviour against the IGC of AA2024
samples (whose composition is detailed in Table 1) has been
studied under different conditions. Immersion treatments in
solutions of sodium chloride 5.7 wt.% and hydrogen peroxide
0.3 vol.% at 30 C for 6 h were used as reference.
[14]
Tests were
carried out at three different temperatures 20, 30 and 40 C
and solutions with different concentrations of hydrogen peroxide
were employed 0, 0.06, 0.15, 0.3, 0.6 and 1.2vol.%. In all tests,
the concentration of sodium chloride has been 5.7 wt.%. Before
the immersion tests, the aluminium alloy samples were subjected
to the surface cleaning procedure recommended in,
[14]
following
four steps: (i) etching of the surface, in which samples are exposed
in an acid solution (5 ml HF 40 vol.% and 50 ml HNO
3
69 vol.% per
litre) for 1 min at 95 C; (ii) samples are rinsed with distilled
water; (iii) samples are exposed for 1 min in HNO
3
69 vol.%; and
(iv) samples are nally rinsed with distilled water.
To perform the EN measurements, a modication of the Parc
single cell was employed, which allows two working electrodes
to be exposed to the testing solution (Fig. 1). The exposed area
of each working electrode was always 0.79 cm
2
. The exposed area
was delimitated with an anticorrosive adhesive tape with a
central aperture, which reduces the crevice corrosion. To comply
with the normalised tests for the detection of susceptibility to
IGC
[14]
a minimum of 5 ml of solution per square centimetre of
metal surface exposed is required. This requirement has been
Table 1. Composition of the aluminium alloy 2024 (weight percentage values)
Si Fe Cu Mn Mg Zn Ni Cr Pb
0.103 0.252 4.42 0.62 1.46 0.182 <0.002 0.012 <0.002
Sn Ti Ag B Be Bi Ca Cd Na
0.009 0.018 0.000 0.001 0.000 <0.002 0.001 0.000 0.000
Sr Li Zr Co V Ga Al P
0.000 0.000 0.002 <0.001 0.011 0.009 92.893 0.002
J. M. Sánchez-Amaya et al.
wileyonlinelibrary.com/journal/sia Copyright © 2012 John Wiley & Sons, Ltd. Surf. Interface Anal. 2012,44, 12791286
1280
satised, as in each test 1.58 cm
2
of surface was exposed in
300 ml of solution. The EN current and voltage signals were
recorded simultaneously using a potentiostat 1287 of Solartron
Instruments (Farnborough, UK). To avoid aliasing, a digital lter
of 2 Hz was activated during the EN measurements. Following
the ASTM G-110 recommendations for IGC tests, the duration of
the tests was exactly 6 h. EN was continuously measured during
the tests at an acquisition rate of 2.16 Hz, the signals being stored
in records of 4096 points. Concerning the analysis of the
obtained EN signals, before calculating the standard deviation
of the potential (s
E
) and the standard deviation of the current
density (s
i
), the drift was removed from both current and
potential records by means of linear regression subtraction.
A detailed metallographic analysis of the metallic samples was
performed after the tests. All tested samples were cut, embedded
in resin, ground and polished. Finally, the mounted cross sections
were deeply analysed by optical microscope to evaluate the IGC
attacks.
Results and discussion
As the Standard ASTM G 11092 (2009) does not specify the
method to evaluate the IGC attacks, an internal criterion of
qualitative and quantitative analyses has been used on the
basis of the description of the attacksmorphology and the
measurements of the depth of the corroded zones, respectively.
In the qualitative analysis, six degrees of IGC has been taken into ac-
count to characterise the shape of the attack, in function of the
number of grain layers affected. These degrees range from pure pit-
ting corrosion (P) to extreme IGC (E), as shown in Table 2. It is impor-
tant to consider that one sample can show zones with different
intergranular (IG) degrees and depths of attack. Therefore, two
parameters have been dened to describe the characteristics of
the grade of damage: the average grade,G
A
and the maximum
grade,G
M
. For the quantitative analysis, two parameters have been
also employed to evaluate the depth of the attacks: the maximum
depth,D
M
, and the average depth,D
A
, both measured from the
ve deepest attacked zones found in the samples. The values of
these four parameters (G
A
,G
M
,D
M
and D
A
) were obtained for each
sample by a meticulous metallographic evaluation.
As IGC processes are relatively irreproducible (it is not possible
to predict accurately the moment and the place in which these
localised attacks are going to happen), EN was recorded during
the immersion of the same 2024 samples that were later evaluated
Figure 1. Electrochemical cell employed to perform the intergranular
corrosion tests, which allows the measurements of electrochemical noise.
Figure 2. Examples of potential electrochemical noise signals of AA2024
samples in the indicated solutions.
Table 2. Degrees of intergranular corrosion dened to evaluate the damage suffered by the samples
Type of attack Code Description of the attacked zones
Pure pitting corrosion P No signs of intergranular corrosion. Only pits.
Degree A of IGC A Grains partially affected. Whole grains not attacked.
Degree B of IGC B Whole grains revealed in the outer layer of grains exposed.
Degree C of IGC C Two layers of grains affected.
Degree D of IGC D Three layers of grains corroded.
Degree E of IGC E Extreme intergranular corrosion. More than three layers of grains dened.
Intergranular corrosion tests of aluminium alloys
Surf. Interface Anal. 2012,44, 12791286 Copyright © 2012 John Wiley & Sons, Ltd. wileyonlinelibrary.com/journal/sia
1281
with the metallographic analysis. This methodology enables us to
correlate the characteristics of the EN signals with the degree of
IGC observed in the metallographic analysis.
Some examples of the EN signals obtained are included in Figs 2
and 3. Potential noise values (Fig. 2) range between 0.600
and 0.565 V versus Ag/AgCl 3M KCl, whereas current noise values
(Fig. 3) fall in the range between 0.1 mA cm
2
. From these noise
signals, it is difcult to observe individual transients related to loca-
lised corrosion events, as the transients overlap. Although accurate
calculations of standard deviations of both Eand Inoise signals are
performed later, peak to peak distances can be taken as rst
approximation to estimate this statistical parameter. Thus,
according to,
[18]
the peak to peak distance (difference between
maximum and minimum values) of a signal with Gaussian distribu-
tion is approximately six times the standard deviation of the signal.
This approximation has been checked to be valid for the EN signals
obtained in the present work. The differences between maximum
and minimum values of E(ΔE)andI(ΔI) noise signals of Figs 2
and 3 have been measured, being 13, 9, 8, 8 and 13mV and 65,
70, 65, 40 and 175 mA, respectively (values from upper to lower
signals of Figs 2 and 3). ΔEvalues always ranged between 8 and 13
mV and do not seem to be inuenced by the temperature or H
2
O
2
concentration. In contrast, ΔIvalues presented some differences,
increasing their values with increasing H
2
O
2
concentration.
Two parameters were used to analyse in detail the EN signals:
the classical noise resistance(R
n
) and a new parameter so-called
statistical noise power(P
n
).
Rn¼
sE
si
(1)
Pn¼sEsi(2)
s
E
and s
i
being the standard deviation of the potential (E) and
current density (i) noise signals.
R
n
is the most employed parameter for analysing EN data
because it is easy to calculate and interpret. R
n
is generally related
to the corrosion activity of the systems (strictly corrosion rate only
in the case of uniform corrosion under activation control), showing
low values when the studied system has a high activity.
[2529]
In the
present work, the averaged R
n
values of all records of each test
have been estimated. Later, the experimental relationship between
these R
n
values and the depths of IG attacks has been explored.
Under uniform corrosion, the relationship between R
n
and the
depth of attack is clear, as a system with high uniform corrosion
rates leads to high material lost (high corrosion penetration),
leading to low R
n
values (assuming uniform corrosion under
activation control, R
p
=R
n
). Unfortunately, the systems studied here
undergo localised corrosion; therefore, the relationship between R
n
and the depth of attack has to be analysed. This correlation is
experimentally explored in this work.
Although the activity of the corrosive systems can be generally
estimated by means of R
n
, consolidated parameters to distinguish
between different corrosion mechanisms cannot be found in the
literature.
[25]
In the present paper, a new parameter so-called
statistical noise power,P
n
, as simple to estimate as R
n
, has been
used to distinguish between different IGC degrees. The name of
this parameter is adopted by the analogy of the noise resistance
(resistance, E/I, obtained by EN) with noise power (power, E*I,
obtained by EN). P
n
is expected to have good differentiation ability
because (i) it takes into account the uctuations of both potential
and current noise signals and (ii) it is generally observed that both
s
E
and s
i
increase as the corrosion processes are more localised.
Consequently, P
n
may be related to the localisation degree of the
corrosion processes. In our study, P
n
are expected to provide
differentiation between IGC degrees. The actual relationship
between P
n
and the IGC degree is explored in the present work.
Note that P
n
is related to the characteristic charge, q,shot
noise parameter giving successful results when applied to
discriminate between corrosion mechanisms.
[1,25,3032]
P
n
is only
mathematically proportional to qif (i) qis estimated by statistical
parameters (q=s
E
s
i
A/Bb),
[3032]
(ii) the SternGeary constant (B)
is assumed to be equal in all tests (not expected, as it may depend
on the corrosion rate and mechanism) and (iii) the exposed area of
specimens (A) does not change (neither expected, as it increases
with the progress of IGC). For simplicity reasons, P
n
has been the
parameter employed in this work.
The authors are conscious of the fact that the area of samples
does increase as IGC progresses with time. The real value of the
samples area is nearly impossible to estimate at each time from
a practical point of view. Therefore, for the EN analyses, the
samplesarea has been considered to be constant within
the tests. This assumption can lead to divergences between
metallographic evaluation and EN analysis, but still, this
methodology allows a relatively easy practical approach to
study the experimental correlation between both techniques.
Inuence of the test temperature
Figure 4 shows cross-section metallographic images of the samples
immersed for 6 h in sodium chloride 5.7% and hydrogen peroxide
0.3% at 20, 30 and 40 C. The results of the metallographic
evaluation are summarised in Table 3. It can be appreciated in this
table that a change in the temperature of 10 Cdoesnotmodify
much the type and the depths of attack. A relevant fact observable
from the images of Fig. 4 is that when the testing temperature is
20 C, the lines dened by the IG attacks are narrower and deeper
Figure 3. Examples of current electrochemical noise signals of AA2024
samples in the indicated solutions.
J. M. Sánchez-Amaya et al.
wileyonlinelibrary.com/journal/sia Copyright © 2012 John Wiley & Sons, Ltd. Surf. Interface Anal. 2012,44, 12791286
1282
than the l ines developed at 30 or 40 C. As can be seen, the widths
of the attacked grain boundaries at 40 C are relatively wider,
meaning that more metal is released from the more supercial
grain boundaries. These results indicate that at low temperature,
the IG attack mainly takes place through new inner grain
boundaries whereas at high temperature, the attack seems to be
promoted over grain frontiers already formed. This effect is thought
to be due to the different reactivity and stability of the hydrogen
peroxide of the testing solution. The rate of the hydrogen peroxide
consumption is probably lower at 20 C because the hydrogen
peroxide is less reactive and decomposes slower. This leads to a
selective attack to new deeper grain boundaries, generating
consequently longer and narrower IG attacks. In contrast, when
the temperature increases, the hydrogen peroxide surely becomes
more reactive and decomposes faster. As a consequence, the high
reactivity increases the attack on the outer grain boundaries,
whereas the fast decomposition prevents the hydrogen peroxide
from reaching the inner layers of grains. At higher temperatures,
the most supercial grain frontiers were mainly attacked.
As reported in Table 3, G
A
,G
M
,D
A
and D
M
do not vary strongly
when the temperature is modied in the range between 20 and
40 C. Only a smooth increase of the IG degree is observed at 20
and 40 C, and slightly higher depths of attacks are measured
at 20 C. Despite this, it can be stated that in this range, the
Figure 4. Metallographic images of AA2024 samples after 6 h of exposure in sodium chloride 5.7% and hydrogen peroxide 0.3% solutions at different
temperatures.
Table 3. Metallographic evaluation of samples after the intergranular corrosion tests. Inuence of the temperature
Qualitative analysis (codes dened in Table 2) Quantitative analysis (depths of attacks in mm)
Temperature (C)
G
A
(average grade) G
M
(maximum grade) D
A
(average depth) D
M
(maximum depth)
20 B D 143 173
30 A B 133 163
40 B B 132 153
Intergranular corrosion tests of aluminium alloys
Surf. Interface Anal. 2012,44, 12791286 Copyright © 2012 John Wiley & Sons, Ltd. wileyonlinelibrary.com/journal/sia
1283
temperature of the IGC test has relatively low inuence on the level
ofdamage.Thisfactisreected in the averaged R
n
and cumulative
P
n
values plotted in Figs 5 and 6. The averaged R
n
is expected
to be related with the depth of attacks, whereas cumulative P
n
with the IG degree. Averaged R
n
values are similar at the three
temperatures (Fig. 5), providing the similar values of D
A
and D
M
.
The smooth increase of the depths observed at 20Cissosmall
that it is not observable in the averaged R
n
values. The averaged
R
n
values and D
A
have been plotted together in Fig. 7. It is clear
from this gure that the values of both parameters are very close
in this range of temperature. The low R
2
value (practically zero)
obtained from the tting is a consequence ofthe fact that all values
obtained in this temperature range are statistically similar. On the
other hand, a slight increase in the cumulative P
n
values at 20
and 40 C is observable in Fig. 6, correlating well with the
relatively higher G
A
and G
M
values measured at these temperatures.
The correlation between the cumulative P
n
values and G
A
can be
better seen in Fig. 8. It can be seen in this gure that the lowest
cumulative P
n
values coincide with the lowest G
A
values, whereas
the highest G
A
values lead to the highest cumulative P
n
values. This
tendency suggests that these two parameters are correlated, as a
higher R
2
value (0.63) is obtained from the tting. Although small
differences of both parameters are observed when changing the
temperature, high cumulative P
n
values are seen to be related to
high G
A
values.
The correlation between the averaged R
n
and D
A
(or D
M
)and
between the cumulative P
n
and G
A
(or G
M
) is better visualised in
the analysis of the inuence of the hydrogen peroxide concentra-
tion, where higher differences between values are found.
Inuence of the hydrogen peroxide concentration
Table 4 reports the results obtained from the metallographic
analysis performed on the samples immersed for 6 h at 30 Cin
the indicated solutions. From the parameters D
A
and D
M
of Table 4,
it can be clearly observed that the depth of attack drastically
increases as the concentration of hydrogen peroxide is higher.
Indeed, the D
A
values vary from 21.7 mm, when no hydrogen
peroxide is added to the solution, to 318.5 mm, when 1.2% of
hydrogen peroxide is used. Concerning the type of attack,
described in Table 4, the IG degree does not vary at concentrations
of hydrogen peroxide below 0.3%, with G
M
=B andG
A
=A. In the
test without hydrogen peroxide, the surface suffers damages only
in some specic areas with very low depths, whereas most of the
surface remained unaffected. It can be also observed that an
increase in the hydrogen peroxide concentration above 0.3%
makes the solution much more aggressive, provoking a signicant
increase of both the degree and the depth of attack. Thus, at 1.2%
of hydrogen peroxide, extreme IG degree can be found in the
samples, presenting both G
M
and G
A
parameters Edegree.
The averaged R
n
values (Fig. 9) and the cumulative P
n
values
(Fig. 10) conrm the tendencies seen in Table 4. Thus, the higher
Figure 5. Averaged R
n
values of samples subjected to intergranular
corrosion tests at different temperatures.
Figure 6. Cumulative P
n
values of samples subjected to intergranular
corrosion tests at different temperatures.
Figure 7. Relationship between D
A
and averaged R
n
values at different
temperatures.
Figure 8. Relationship between G
A
and cumulative P
n
values at different
temperatures.
J. M. Sánchez-Amaya et al.
wileyonlinelibrary.com/journal/sia Copyright © 2012 John Wiley & Sons, Ltd. Surf. Interface Anal. 2012,44, 12791286
1284
the amount of hydrogen peroxide in the testing solution, the lower
the averaged R
n
value. It is worth recalling that R
n
is inversely
related to the corrosion activity. Averaged R
n
values between
10
+4
and 10
+5
Ωcm
2
are observed when no hydrogen peroxide is
added to the testing solution. The values decrease down to around
10
+2
Ωcm
2
as the hydrogen peroxide concentration is increased.
The relationship between the averaged R
n
and D
A
can be clearly
observed in Fig. 11, where the averaged R
n
decreases as the
depth of the IG attacks increases. The best t line for these data is
plotted on this gure, which reveals a correlation between these
parameters (R
2
= 0.84). This relationship between R
n
and D
A
permits
the use of R
n
to estimate the depth of IGC attacks in these tests
because as the depth increases, the R
n
value decreases.
Meanwhile, the cumulative P
n
values (Fig. 10), expected to be
related to the localisation degree of corrosion processes, are
Figure 9. Averaged R
n
values of samples subjected to intergranular cor-
rosion tests with different hydrogen peroxide concentrations.
Figure 10. Cumulative P
n
values of samples subjected to intergranular
corrosion tests with different hydrogen peroxide concentrations.
Table 4. Metallographic evaluation of samples after the intergranular corrosion tests. Inuence of the hydrogen peroxide concentration
Qualitative analysis (codes dened in Table 2) Quantitative analysis (depths of attacks in mm)
Test solution
G
A
(average grade) G
M
(maximum grade) D
A
(average depth) D
M
(maximum depth)
NaCl 5.7% P B 21.7 36
NaCl 5.7% + H
2
O
2
0.06% A B 65.3 80
NaCl 5.7% + H
2
O
2
0.15% A B 109.6 141
NaCl 5.7% + H
2
O
2
0.3% A B 133 163
NaCl 5.7% + H
2
O
2
0.6% C D 181 193
NaCl 5.7% + H
2
O
2
1.2% E E 318.5 374
Figure 11. Relationship between D
A
and averaged R
n
values at different
hydrogen peroxide concentrations.
Figure 12. Relationship between G
A
and cumulative P
n
values at
different hydrogen peroxide concentrations.
Intergranular corrosion tests of aluminium alloys
Surf. Interface Anal. 2012,44, 12791286 Copyright © 2012 John Wiley & Sons, Ltd. wileyonlinelibrary.com/journal/sia
1285
observed to increase proportionally to the hydrogen peroxide
concentration. Thus, values around 10
9
AVcm
2
are measured
without hydrogen peroxide and gradually increase up to 10
6
AV
cm
2
at 1.2% of hydrogen peroxide. In Figure 12, the cumulative
P
n
values have been represented as a function of their
corresponding G
A
values. As depicted, a clear relationship between
P
n
and the IG degree is observed (R
2
= 0.85). Therefore, the higher
the degree of attack, the greater the values of cumulative P
n
obtained. The correlation between P
n
and G
A
allows one to use P
n
to determine the degree of IGC attacks in these tests because as
the IGC degree increases, the P
n
value increases.
To sum up, the concentration of hydrogen peroxide has a great
inuence on the results of the IGC tests performed on AA2024-T3
samples. Thus, it could be veried that raising the hydrogen
peroxide concentration provokes an increase in both the degree
and the depth of attack. Therefore, it can be deducted that in
the standard IGC tests (where a concentration of 0.3% hydrogen
peroxide is required), a proper control of the concentration of this
reactive is strongly recommended if the reproducibility of these
tests is intended to be guaranteed.
Finally, the aim of the present paper has been achieved,
because a reasonable correlation between the EN measurements
and the metallographic observations has been observed. These
results indicate that EN technique may be useful to distinguish
between different degrees of IGC of aluminium alloys samples.
The averaged R
n
is seen to be related to the depth of
attacks, whereas the cumulative P
n
to the IG degree. Thus, high
correlation degrees between averaged R
n
and D
A
and between
cumulative P
n
and G
A
were observed. Therefore, R
n
can be used
to determine the depth of attacks and P
n
to estimate the degree
of attacks in ICG tests.
Conclusions
In this paper, the inuence of temperature and hydrogen peroxide
concentration on IGC tests of AA2024-T3 samples is reported. The
evaluation of the depths and degree of attacks is performed with
an internal criterion based on metallographic measurements of
the samples after the tests and the analysis of EN measured during
the tests.
The obtained results indicate that similar depths and IG degrees
are rea ched b etween 20 and 40 C. Among the little differences
found, the lines dened by the IG attacks are seen to be narrower
and deeper at 20 C. At 30 C, the IG degree is slightly lower than
at 20 an d 40 C. It could be also evidenced that the hydrogen
peroxide concentration has a strong inuence on IGC tests. Both
the depth of attack and the IG degree rapidly increase when raising
the concentration of hydrogen peroxide.
The results obtained from the metallographic evaluation have
been compared with analytic parameters estimated from EN
measurements. In general terms, a good correlation between
both techniques has been found. Thus, the averaged R
n
is seen
to be inversely proportional to the depths of the attacks, whereas
the cumulative P
n
is observed to be directly related to the IGC
degree. Although further investigation is necessary, the obtained
results suggest that EN could be used to detect the susceptibility
to IGC of aluminium alloys.
Acknowledgements
The authors would like to thank the nancial support of
Ministerio de Ciencia e Innovación (project LENTEC, Reference
PTQ-09-01-00629) and Junta de Andalucía.
References
[1] J. M. Sánchez-Amaya, M. Bethencourt, L. González-Rovira, F. J.
Botana, Electrochim. Acta 2007,52, 6569.
[2] W. Zhang, G. S. Frankel, Electrochim. Acta 2003,48, 1193.
[3] D. A. Jones, Principles and Prevention of Corrosion, 2nd Edition, Pren-
tice Hall, Upper Saddle River, New Jersey, 1996, 307.
[4] B. Davó, A. Conde, J. J. de Damborenea, Corros. Sci. 2005,47, 1227.
[5] V. Guillaumin, G. Mankowski, Corros. Sci. 1999,41, 421.
[6] C. Augustin, E. Andrieu, C. Blanc, G. Mankowski, J. Delfosse, J.
Electrochem. Soc. 2007,154, C637.
[7] G. Svenningsen, J. E. Lein, A. Bjorgum, J. H. Nordlien, Y. Yu, K.
Nisancioglu, Corros. Sci. 2006,48, 226.
[8] G. Svenningsen, M. H. Larsen, J. H. Nordlien, K. Nisancioglu, Corros.
Sci. 2006,48, 3969.
[9] G. Svenningsen, M. H. Larsen, J. H. Nordlien, K. Nisancioglu. Corros.
Sci.,2006,48, 258.
[10] G. Svenningsen, M. H. Larsen, J. Walsmley, J. H. Nordlien, K.
Nisancioglu, Corros. Sci. 2006,48, 1528.
[11] S. Zhao, D. A. Wolfe, T.-S. Huang, G. S. Frankel, J. Statist. Plann.
Inference,2007,137, 2405.
[12] T. D. Burleigh, E. Ludwiczak, R. A. Petri, Corrosion 1995,51, 50.
[13] Standard BS 11846:1995, Determination of resistance to IGC of
solution heat-treatable aluminium alloys, British Standards
Institution, 1995.
[14] ASTM G-110-92, Practice for evaluating intergranular corrosion
resistance of heat-treatable aluminum alloys by immersion in
sodium chloride + hydrogen peroxide solution, American Society
for Testing and Materials, 2009.
[15] S. P. Knight, M. Salagaras, A. M. Wythe, F. De Carlo, A. J. Davenport, A.
R. Trueman, Corros. Sci. 2010,52, 3855.
[16] S. P. Knight, M. Salagaras, A. R. Trueman, Corros. Sci. 2011,53, 727.
[17] J. R. Galvele, S. M. De Micheli, Corros. Sci. 1970,10, 795.
[18] S. Turgoose, R. A. Cottis, Corrosion Testing Made Easy: Electrochemical
Impedance and Noise, Ed. B. C. Syrett, NACE International, Houston,
U.S.A., 1999,1149.
[19] J. M. Sánchez-Amaya, M. Bethencourt, L. González-Rovira, F. J.
Botana, Rev. Metal. Madrid 2009,45, 143.
[20] S. Ritter, T. Dorsch, R. Kilian, Mater. Corros. 2004,55, 781.
[21] M. G. Pujar, N. Parvathavarthini, R. K. Dayal, S. Thirunavukkarasu,
Corros. Sci. 2009,51, 1707.
[22] S. Girija, U. K. Mudali, H. S. Khatak, B. Raj, Corros. Sci. 2007,49, 4051.
[23] G. S. Duffó, S. B. Farina, Corros. Sci. 2005,47, 1459.
[24] E. M. Lehockey, A. M. Brennenstuhl, G. Palumbo, P. Lin, Brit. Corros. J.
1998,33, 29.
[25] J. M. Sánchez-Amaya, R. A. Cottis, F. J. Botana, Corros. Sci. 2005,
47, 3280.
[26] R. A. Cottis, Corrosion 2001,57, 265.
[27] F. Mansfeld, H. Xiao, J. Electrochem. Soc. 1993,140, 2205.
[28] Y. J. Tan, S. Bailey, B. Kinsella, Corros. Sci. 1996,38, 1681.
[29] J. Zhang, W. Zhao, Surf. Interface Anal. 2011,43, 1018.
[30] K.-H. Na, S.-I. Pyun, H.-P. Kim, Corros. Sci. 2007,49, 220.
[31] M. G. Pujar, N. Parvathavarthini, R. K. Dayal, Mater. Chem. Phys. 2010,
123, 407.
[32] G. Meng, L. Wei, T. Zhang, Y. Shao, F. Wang, C. Dong, X. Li, Corros. Sci.
2009,51, 2151.
J. M. Sánchez-Amaya et al.
wileyonlinelibrary.com/journal/sia Copyright © 2012 John Wiley & Sons, Ltd. Surf. Interface Anal. 2012,44, 12791286
1286
Project
The main objective of this project is to help achieving various social challenges, mainly in the field of sustainable transport and in particular, on two related aspects. First, to facilitate the u…" [more]
Project
LUI is a Project to lay the groundwork for the implementation of the Physical Internet. (LUI is the acronym in Spanish of the Universal Logistic Integrated - Logística Universal Integrada). RedEP…" [more]
Article
July 2007 · Electrochimica Acta · Impact Factor: 4.50
    In the present paper, the effect of heat treatment on the susceptibility to intergranular corrosion (IGC) of aluminium alloys is analysed. Samples of aluminium alloys AA2024 and AA7075 were first subjected to different heat treatments. Then the susceptibility of these samples to IGC was determined by means of normalized tests, based on the immersion of the samples in an aggressive medium and... [Show full abstract]
    Article
    October 2014
      The effect of artificial aging on the corrosion properties of 6063 Al alloy was investigated by optical microscope, field emission scanning electron microscope (FE-SEM) and accelerated corrosion test. Accelerated corrosion test revealed that the corrosion resistance of the alloy strongly depended on artificial aging times, and the corrosion weight gain curve of the aged alloy was greatly in... [Show full abstract]
      Article
      November 2013
        The effect of artificial aging on the corrosion properties of 6063 Al alloy was investigated by optical microscope, field emission scanning electron microscope and accelerated corrosion test. Accelerated corrosion test revealed that the alloy was susceptible to intergranular corrosion (IGC) in the artificial aged conditions according to the surface corrosion morphology, and the IGC resistance... [Show full abstract]
        Discover more