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Available online at www.sciencedirect.com SCIENCE ELECTROCHIMICA DIRECT° 4 ELSEVIER Electrochimica Acta 49 20042787-2793 www.elsevier.com/locate/electacta A practical evaluation of electrochemical noise parameters as indicators of corrosion type H.A.A. Al-Mazeedi, R.A. Cottis Corrosion and Protection Centre, UMIST,P.O. Box 88, Sackville Sfree4 ManchesterM6O JQD, UK Received 3 May 2003; accepted 6 January 2004 Available online 30 April 2004 Abstract While electrochemical noise EN measurement has been used in corrosion monitoring for many years, the true capabilities of the technique and the optimal methods for extracting useful information from the collected data are only now becoming clear. This paper examines the information that can be obtained from EN measurement, both from a theoretical and a practical perspective. 2004 Elsevier Ltd. All rights reserved. Keywords: Electrochemical noise; Corrosion monitoring; Linear polarization resistance; Corrosion inhibition; CO2 corrosion 1. Introduction Conventional electrochemical convsion monitoring using the linear polarization rnsistance LPR method is well es tablished for the determination of average cormsion rate. The method is rnlatively simple to implement and reliable, except in a few well-debned cases where the requirnd con ditions are not met. Morn rncently the electrochemical noise EN method has been studied by many rnseaith groups and implemented as a pmctical cormsion monitoring system by a few pioneers see 1I for a rncent review. In many appli cations though not all the electrochemical noise rnsistance Rn, determined as the standard deviation of the potential noise divided by the standard deviation of the cuntnt noise, has been found to be compamble to the linear polarization rnsistance Rn, determined by LPR. However, Rn tends to be mther more variable thanR, and it offers littleadvantage it might be claimed that Rn requirn less complex measumment equipment, but this is barely signibcantwith the low cost of modem electronics. Whern EN does offer the pmspect of signibcant benebts compared to LPR is in the detection of localized corrosion. The noise is pmduced by fluctuations in the electrochemical pmcess, and larger fluctuations will typically be indicative of a morn localized process. A num 0Corresponding author. Tel.: + 44-161-236-3311; fax: + 44-161-228-7040. E-mail address: [email protected] R.A. Cottis. 0013-4686/S - see front matter 2004 Elsevier Ltd. All rights reserved. doi: 10. 1016/j.electacta.2004.01.040 ber of parameters have been proposed for the identibcation of localized corrosion; these are described below. They have been subjected to theoretical analysis, and to experimental tests, but none of these tests have been comprnhensive. The oretical analyses necessarily make a number of assumptions about the noise genention pmcess, while most experimen tal studies have examined only one or two of the pmposed pammeters or have been based on mther limitedthtasets. In this paper, a statistical approach is used to compare the dis crimination ability of some of the pammeters that have been proposed for the identibcationof the mte or especially the type of the corrosion pmcess. A relatively large dataset is used appmximately 3500 points, corrnsponding to 1000 h of testing, and each point corrnsponding to a 1024 sample time rncord, based on studies of two cormsion systems. 2. Electmchemical noise measurement The conventional EN measurement method uses thne electrodes. Two of these me working electmdes, between which the electmchemical currnnt noise ECN is measurnd using a zero-resistance ammeter ZRA, so that the two working electrodes me at the same potential. At the same time the electmchemical potential noise, EPN, is measurnd as the fluctuationin the potential of the working electrode pair relative to a reference electrode. In labontory work the refernnce electmde is typically a tme reference electmde 2788 H.A.A. Al-Mazeedi, R.A. Coil/s /ElectrochiniicaActa 492004 2787-2 793 such as the satunted calomel electmde, SCE, while in cor rosion monitoring applications the reference electrode may be nominally identical to each of the two working electmdes. The latter conbguntion modibes the behaviour since the reference electrode is also producing noise, but this can be corrected for if the thite electmdes can be assumed to be similar 2I. frequency, is being calculated fmm a measurement made at a low frequency. For a detailed explanation maders are re ferred to or to standard shot noise texts, but an analogy may help readers to appreciate how the analysis works: Consider the Bow of trathc down a mad, with a bxed av enge rate of carriage of people. if the number of peo ple passing a bxed point each minute is measumd many times, and the properties of the distribution of the ob served number of people is studied, it will be reasonably obvious that the standard deviation will be larger if all the people alt in buses canying 50 people, nther than cars with one person each car. This is a shot noise pmcess, as suming that the movements of each vehicle a unaffected by other vehicles, and it can be shown that the avenge number of passengers can be determined from an analysis of the observed mean and standard deviation. 2.]. EN analysis methods Having measured the ECN and EPN, the next problem is how to interpmt the data obtained. Them is, as yet, no general theoretical description of the chancteristics of EN data, but an analysis is available for the special case of a shot noise process. Shot noise is pmduced when the current takes the form of a series of statistically independent packets of charge, with each packet having a short duntion.1 The total charge passing in a given sample interval is then a sample fmm a binomial distribution,which, ifthe avenge number of pulses in the sample interval is masonably large, approximates to a normal distributionwith known properties. if this theory is applied to EN, thne pammeters can be obtained: 1corr the avenge cormsion current, q the avenge charge in each event, and f the fmquency of events. Only two of these pammeters are independent, since I corr = CJfn It is not possible to measure Icorr, q and f directly, but it is possible to estimate them from the measumd ECN and EPN: BBr - corr n = q Bb n - ‘corr - - - - q 82b whem Iii isthe standard deviation of current, LIE the standard deviation of potential and b the bandwidth of measumment. It should be noted that f, q and similar statistical pa rameters pmvide an avenge value over the period the term ‘calculation sample interval’ is used hem to indicate thispe riod, which may or may not be the same as the measurement sample interval, depending on how the calculation is per formed for which they have been calculated. Furthermom, f is essentially an estimate of the number of events occur ring withinthe calculation sample interval. The derivation of the theory assumes that high fmquencies have been excluded fmm the measurement. Some commentators have been con fused by the fact thatfn, which typically has a relatively high 1 In this context, short means short relative to the period of the frequencies being used in the analysis, so if we conbne ourselves to frequencies of the order of 0.01 Hz, events lasting for 10 s can still be considered to be short In the case of electrochemical noise, it is necessaiy to infer the number of events occuning each second, since we cannot measum it directly, but otherwise the analysis is exactly equivalent to that for the road analogy. The theomtical analysis assumes that them are a reason ably large number of events occurring in each calculation interval since this is necessaiy for the distribution to be appmximated by a normal distribution, so the calculation sample interval is ideally reasonably long, i.e. the measure ment should cormspond to a low fmquency. For this mason, a better method of estimating the shot noise pammeters is probably to use estimates of the low fmquency power spec tral density PSD of potential and curmnt, as this permits mom precise selç9tion of the fmqueny of the meas.yrement. In this case. 97/ his mplaced by Wand lIE’ hisre placed by W, where ‘‘i and are the PSD of curmnt and potential Having obtained ‘corr’ q and fn, the next question is how they mlate to the nature of the cormsion pmcess. As only two of the pammeters a independent, we only need to consider two of them, and for most purposes it is most relevant to consider ‘corr and fn clearly describes the avenge corrosion nte in a way that will be familiar to all corrosion engineers. fn describes the frequency of events. In general, it is ex pected that high fmquency events will tend to occur all over the surface, and the cormsion will therefom be ma sonably uniform. In contmst low fmquency events must be removing mlatively large amounts of material at indi vidual locations, and the corrosion willtypically be rather localized. Thus fn pmvides an indicator of the localization of corrosion, with a small fn indicating localized corro sion, and a large f indicating uniform corrosion. * ‘corr * Other pammeters that have been used for the identibcation of localized corrosion typically have a less well-debned the oretical basis. One of the brstpammeters proposed was the coethcient of variation of curmnt-the standard deviation of cuntnt dividedby the mean curmnt. The coefkient of varia ____ _____ H.A.A. Al-Mazeedi, R.A. Coals /ElectrochiniicaActa 492004 278 7-2 793 tion is a standard statistical term, and it isused to indicate the mlative variability of a distribution. The problem with using it for the interpretation of EN data is that itis only validfor a single-sided distributioni.e. a distributionwhere every point can only be positive or every point can only be negative-an example might be the number of peas in each packet of a batch of frozen peas. In the case of EN as normally mea sured, the measured curmnt is expected to be centred on zero, and the distributionis denitely not single-sided. Con sequently the coefcient of variation is an unwliable pamm eter it can be shown 141 that for ideal data the coefcient of variation is expected to be pmportional to the number of samples used in the measurement, and independent of any mal electrochemical properties of the system being studied. An obvious limitation of the coefcient of variation of curmnt is that it is iniiite in the event that the mean current happens to be exactly zem. In order to overcome this lim itation, the localization index sometimes called the pitting index was introduced. This is dened as the standard devia tion of current divided by the rm.s. curmnt. As the expected value of the rm.s. current is, Iean + I oise this results in the localization index tending to the coefcient of variation when the latter is much less than 1, and to 1 when the co efcient of variation is gmater than 1. In other words it is effectively the coefcient of variation limited to a maximum value of 1. Consequently it suffers the same limitations as the coefcient of variation. A valid form of the coefcient of variation is obtained by dividing by ‘corr rather than the mean current, since the measumd curmnt noise is arguably a noise in 1corr, and 1corr is clearly single-sided. if it is assumed that Icorr can be de rived from Rn, then the "tme coefcient of variation" can be obtained: 1J tme coefcient ofvariation 11/ = - I corr = B A similar pammeter, described as the Pitting Factor, has been used by Eden and Bmene In this case ‘corr was obtained by another method harmonic analysis, and a form of specimen aita normalization was used see below for further discussion of this, but the nal msult is ex pected to behave in a similar way to the tme coefcient of variation. Furthermore, both of these pammeters ait pro portional to the standard .eviation of potential, and hence inversely pmportional to 7. For this mason they alt not considemd further-other than questions associated with area and bandwidth normalization, they can be considered as equivalent to fn. 3. Area and bandwidth normalization Cormsion scientists and other electmchemists am used to the idea that curmnts in electrochemical systems can be nor malized for specimen size by using the current divided by 2789 the specimen ama-the current density. Probably because of the familiarity of this approach, them is a tendency to as sume that is also correct to normalize the standard deviation of curmnt by dividing by the specimen area. Similarly, elec tmchemical potential is genenlly independent of specimen ama, and it is therefom assumed that this also applies to the standard deviation of potential. Both of these assumptions am incormct-if the noise fmm individual areas of the spec imen can be assumedobe independent, then !I is expected to be pmportional to A, whem A is the specimçp area and A. if this 1E is expected to be inversely pmportional to behaviour is obtained, then the cormct area normalization for the shot noise pammeters is as might be expected; q is independent of area, and fn is proportional to ama, so can be reported as events per second per unit area. For the other localization indicators that have been pmposed, the cormct area normalization is rather counter in tuitive. As an example, the tme coefcient of variation has been dened above in terms of the standard deviation of current divided by the cormsion current. It is tempting to as sume that this dimensionless msu4is correct. However, Ili is expected to be pmportional to A, while Icorr is pmpor tional to A, so the tme coefcieijt of variation is expected to be inversely pmportional to A, and should therefore be reported with units of cm. In addition, it should be appreciated that the measumd standard deviation is a function of measumment bandwidth. This is properly handled in the shot noise analysis, but ig nomd in most other pammeters. While these factors should be understood when analysing EN data, it should also be appreciated that the effects of specimen ama and measumment bandwidth am only of ma jor signicance when they are changed. As most measum ments includingthose reported here use constant specimen ama and measurement bandwidth, the mnking of msults will generally be cormct. 4. Experimental The experimental work pmsented in this paper had the objective of understanding the tmnsient corrosion processes that occur during the depletion of an inhibitor. Two sys tems wem used, steel in mixtures of nitrite and chloride, and steel in CO2 satunted solution with thioacetamide as an inhibitor In both cases the steel used was a mild steel to B5970:080A15. The nitrite-chloride solutionswem based on distilledwater, to which varying amounts of sodium chlo ride and/or sodium nitrite wem added. The C02 system was based on 3% NaC1, saturated with CO at ambient pressum the satuntion with C02 also sewed to deaente the solu tion, and with the pH adjusted to 5.5 with HC1 or NaOH. In order to examine the effect of changes in the com position, one solution was mplaced by another at intervals thmugh the test. This was achieved by pumping solution into and out of the test vessel using a two-channel peristaltic 2790 H.A.A. Al-Mazeedi, R.A. Coil/s /ElectrochiniicaActa 492004 2787-2 793 Table 1 Experimental sequences Experiment Solution Duration h Corrosion type Label la lb ic lOOppmNO2°+ l000ppmCl0 l000ppm NO20 + l000ppm Cl0 l0000ppm NO20 + l000ppm Cl0 25 25 25 Pitting Pitting changing to inhibition Inhibition P1 2a 2b 100 ppm NO2 lOOppmNOi°+ l000ppmCl0 25 167 Inhibition Pitting 12 P2 3a 3b l000ppm Cl0 lOOppmNOi°+ l000ppmCl0 25 168 Uniform corrosion Pitting Ui P3 4 3% NaC1 saturated with CO2 pH 5.5 136 Uniform corrosion U2 Sa Sb 3% NaC1 saturated with CO2 pH 5.5 3% NaC1 saturated with CO2 pH 5.5 lppm thioacetamide 50 192 Inhibition Pitting changing to uniform corrosion 13 U4 6a 6b 3% NaC1 saturated with CO2 pH 5.5 + lppm thioacetamide As above, but CO2 bubbling stopped, and exposed to the air 50 117 Inhibition Pitting/uniform corrosion * + pump. This msulted in an exponential decay in composition, with a time constant of approximately 500 s. The sequences of solutions used, together with the corm sion behaviour observed, am summarized in Table 1. The cormsion type indicated in Table 1 was inferred from visual observation of the sample, coupled with the behaviour of these systems as reported by earlier workers especially in the case of the chloride/nitrite system and visual inter pmtation of the electrochemical noise time records. The La bel given in Table 1 am used in the gums to indicate the various test sequences, sections labelled ‘*‘ have not been plotted, in one case because the type ofcorrosion varied sig nicantly over the period of the test, and in the other case because the test duplicated other data Electmchemical noise thta wem obtained using the con ventional thite electrode technique A saturated calomel reference electmde was used to measure the potential of a pair of mild steel working electmdes. The sampling quency was 1 Hz. In a practical monitoring situation it seems probable that two pammeters will be derived fmm EN measumments: 1. A measure of the average corrosion nte. This will almost inevitably be based on Rn. 2. A measure of the tendency to localization of the corro sion. A range of pammeters, including those indicated above, have been proposed for this purpose. Thus a key test for any localization indicator is its ability to discriminate between different types of corrosion. In order to evaluate thisfor the data obtained inthis work, a statistical C 10000 100000 1000000 10000000 R11 ohm/cm2 -uniform corrosion fit 5. Analysis pmcedurcs a 1000 Ii U3 -c 100 * -pitting -inhibition Fig. 1. Cumulative probability plot for R11 for all of the corrosion systems tested see Table 1 for an explanation of the labels used. H.A.A. Al-Mazeedi, R.A. Coals /ElectrochiniicaActa 492004 278 7-2 793 0.8 j06 0.4 It = E = C- 0.2 0 1 001J f, Hz/mY Fig. 2. Cumulative probability plot forfn for all of the corrosion systems tested. -M 0 0 0 ci > It = E = C 0,01J1 0,001 0,01 0,1 1 10 q nC Fig. 3. Cumulative probability plot for q for all of the corrosion systems tested. 0.8 0.6 = E 0.4 8 0.2 Ccv Fig. 4. Cumulative probability plot for coef cient of variation of current for all of the corrosion systems tested. 2791 2792 H.A.A. Al-Mazeedi, R.A. Cottis /ElectrochimicaActa 492004 2787-2 793 -M 0 0 ci > It = E= 0 0.J1 0.01 0.1 LI Fig. 5. Cumulative probability plot for localization index for all of the corrosion systems tested. approach has been used. To test the ability of individual pammeters to discriminate the type or nte of corrosion, the cumulative probability has been plotted for each set of conditions. This is determined by the following algorithm using q as an example: two conditions, if the plots overlap, then there is no ability to discriminate between them this is, of course, correct if the corrosion behaviours am similar, while if there is no overlap, then there is a good discrimination ability. As we can obtain two independent pammeters from a conventional EN measumment, then it is potentially possible to use them in combination to impmve the discrimination. This situation has been tested by plotting all of the data as individual points in a plot of one pammeter against the other. This pmduces ‘clusters’ of points for each set of conditions, and in this case it is possible to assess qualitatively whether or not clusters can be discriminated by looking at the overlap between them. 1. Sort all of the values of q for a given environment into ascending order. 2. Then the cumulative probability for each value is n/’N + 1, where n is the position in the sorted list, and N is the total number of entries in the list. By comparing the cumulative probability plots for two different conditions, we can determine the effectiveness with which the pammeter can distinguish between the 1 J0J00 1 00J00 x EC., E 1 00J0 x xx - xx QZ I. U * 0 U 1 0J0 * _s 100 . _I 1 J0 1 10 100 1000 10000 ioooo iodoooo U U 10000000 100000000 fI Hz cm2 Fig. 6. Plot of R11 vs. corrosion. f for all of the systems tested open circles correspond to inhibition, closed squares to uniform corrosion and crosses to pitting H.A.A. Al-Mozeedi, R.A. Coals /ElectrochiniicoActo 492004 278 7-2 793 The resultsthat have been obtained me shown in Figs. 1-5. It can be seen thatfn pmvides a rnlatively good discrim ination of localized cormsion, with a boundary of about 3000 Hz cm. As the tme coef dent ofvariation and pitting factor me essentially equivalent to f other than the com plications of area and bandwidth normalization discussed above, they will have the same discrimination ability. In contmst the conventional coef cient of variation and lo calization index have relatively poor discrimination ability with signi cant overlap between differnnt types of cormsion. Note, for example that the rightmost four traces in Figs. 4 and 5 corrnspond to two systems that were pitting, and two that wern suffering uniform corrosion, so these pammeters cannot discriminate between these two types of corrosion. Similarly, q appears to discriminate between inhibition and cormsion whether uniform or localized, with a small charge less than about 0.01 nC being indicative of inhibi tion. In Fig. 6, Rn is plotted as a function Offn. It is clif cult to distinguish the various systems in this monochrome plot a colour version of the plot is available fmm RAC, but it can be seen that the three types of cormsion occupy differnnt legions: * Pitting corrosion has a low value of fn. * Passive/inhibited samples have a high value of Rn and a highvalue Offn note thatthe thioacetamide inhibited CO2 system has a rnlatively low inhibitionef ciency, so R for this system is much lower than for the nitrite inhibited system, giving the cluster of inhibited points to the right of the plot. * Geneml cormsion has a high value offn and a low value of Rn. Thus these pammeters allow a useful and reasonably in tuitive categorization of the rate and type of cormsion, par ticularly when used together 2793 Similar plots can be pmduced for Rn and q and Rn and the other pammeters. Owing to the relationship between Rn and q this plot is just a tmnsformation of the Rn versus fn plot as is a plot of fn against q, and does not provide any additional information. 6. Conclusions EN measurnment pmvides useful information about the rate of cormsion through Rn and localization of cormsion through a mnge of pammeters, including the chancteristic frnquency, fe. Other measures for the identi cation of localization of corrosion notably the localization index me unduly in u enced by the mean current, and they me consequently less reliable thanfn. Cumulative pmbability plots pmvide a useful indicator of the effectiveness of the various pammeters at discriminating between different types of cormsion. Acknowledgements Ms Al-Mazeedi has been supported by the Kuwait Insti tute for Scienti c Reseaith. References [1 R.A. Cottis, Corrosion 27 3 2001 265. [21 U. Bertocci, F. Huet, R.P. Nogueira, Corrosion 59 7 2003 629. [31 R.A. Cottis, S. Turgoose, Mater. Sci. Forum 192-194 2 1995 663. [41 R.A. Cottis, in: J.D. Sinclair, E. Kalman, M.W. Kendig, W. Plieth, W.H. Smyrl Eds., Electrochemical Society Proceedings PV2001-22 on Corrosion and Corrosion Protection, 2001. [51 D.A. Eden, B. Breene, Corrosion/2003, Paper 361, NACE, 2003.