Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1 + 1966 word(s) 1966 2022-01-24 09:41:34 |
2 format done Meta information modification 1966 2022-01-27 09:56:01 |

Video Upload Options

We provide professional Video Production Services to translate complex research into visually appealing presentations. Would you like to try it?

Confirm

Are you sure to Delete?
Cite
If you have any further questions, please contact Encyclopedia Editorial Office.
Prosek, T. Corrosion Monitoring in Atmospheric Conditions. Encyclopedia. Available online: https://encyclopedia.pub/entry/18694 (accessed on 16 November 2024).
Prosek T. Corrosion Monitoring in Atmospheric Conditions. Encyclopedia. Available at: https://encyclopedia.pub/entry/18694. Accessed November 16, 2024.
Prosek, Tomas. "Corrosion Monitoring in Atmospheric Conditions" Encyclopedia, https://encyclopedia.pub/entry/18694 (accessed November 16, 2024).
Prosek, T. (2022, January 24). Corrosion Monitoring in Atmospheric Conditions. In Encyclopedia. https://encyclopedia.pub/entry/18694
Prosek, Tomas. "Corrosion Monitoring in Atmospheric Conditions." Encyclopedia. Web. 24 January, 2022.
Corrosion Monitoring in Atmospheric Conditions
Edit

A variety of techniques are available for monitoring metal corrosion in electrolytes. However, only some of them can be applied in the atmosphere, in which case a thin discontinuous electrolyte film forms on a surface. Traditional and state-of-the-art real-time corrosion monitoring techniques include atmospheric corrosion monitor (ACM), electrochemical impedance spectroscopy (EIS), electrochemical noise (EN), electrical resistance (ER) probes, quartz crystal microbalance (QCM), radio-frequency identification sensors (RFID), fibre optic corrosion sensors (FOCS) and respirometry.

atmospheric corrosion real-time corrosion monitoring atmospheric corrosion monitor electrochemical impedance spectroscopy electrochemical noise electrical resistance probes quartz crystal microbalance radio-frequency identification sensors fibre optic cor

1. Introduction

The atmospheric corrosion of metallic materials has huge financial, environmental and cultural implications. In 2016, the Association for Material Protection and Performance (AMPP) published the International Measures of Prevention, Application, and Economics of Corrosion Technologies (IMPACT) report, which estimated the global cost of corrosion to be equivalent to 3.4% of the global Gross Domestic Product. They calculated that by using the available corrosion control techniques, it would be possible to save between 15 and 35% of the total corrosion cost [1]. Alongside financial losses, undetected corrosion can cause sudden industrial and transport failures that may result in environmental catastrophes and hazards that endanger health and lives. Furthermore, corrosion is known to induce irreversible damage in, or even destruction of, unique cultural artefacts.
Atmospheric corrosion is a complex process of interaction between materials and the environment. Environmental corrosivity is dependent on various parameters, including relative humidity (RH), temperature (T) and air pollutant concentrations. Thus, understanding the corrosion of metallic materials requires detailed knowledge of these parameters and their effect on the underlying corrosion processes [2]. The main tools used to assess environmental corrosiveness, corrosion progression, material corrosion behaviour and the effects of coatings and inhibitors, involve cumulative or real-time monitoring of corrosion rates and environmental parameters, and frequent equipment inspections. This review is focused on real-time corrosion monitoring, which we define as a long-term instantaneous measuring of parameters directly linked to corrosion loss.
Many real-time corrosion monitoring techniques have been developed for monitoring of metal corrosion in electrolytes. However, their applicability is limited under atmospheric conditions, under which a thin electrolyte layer is formed on a metallic surface. This limitation particularly relates to electrochemical methods that require a conductive connection between the electrodes. Modified electrochemical and non-electrochemical real-time corrosion monitoring techniques have been developed for use in both indoor and outdoor atmospheres. Such techniques are designed to meet the requirements of easy measurement and data interpretation, direct corrosion rate determination, rapid responses to changes in corrosivity and wide applicability in environments with different influences on corrosivity [3]. In the last decade, these techniques have evolved, but no paper summarizing the developments has been published.

2. Comparison of Atmospheric Corrosion Monitoring Techniques

Studies applying the real-time atmospheric corrosion monitoring techniques described in the previous sections are summarised in Table 1 in terms of environments, sensing materials, ranges of detected corrosion rates and suitability for localised corrosion detection.
Table 1. Summary of studies applying real-time atmospheric corrosion monitoring.
Technique Environment * Sensing Metal ** Range of Measured Corrosion Rates ***, [µm·a−1] References Localised Corrosion Detection
ACM 1 Outdoor exposures Fe 1 × 10−1–1 × 102 [4][5][6][7][8][9][10][11][12]
Zn Not calculated [13]
ACTs Fe 1 × 102 [14]
Laboratory tests Fe 1 × 101–1 × 103 [15][16]
Zn 1 × 101–1 × 103 [15][16]
Cu 1 × 101–1 × 103 [15]
Al 1 × 101–1 × 103 [15]
ER Outdoor exposures Fe 1 × 10−1–1 × 103 [17][18][19] [3][20][21]
Zn 1 × 10−1–1 × 101 [18]
Cu 1 × 10−1–1 × 100 [22]
ACTs Fe 1 × 101–1 × 103 [2][23][24][18][25][26][27]
Zn 1 × 100–1 × 103 [2][23][24]
Cu 1 × 103 [2]
Al 1 × 10−1–1 × 101 [20]
Laboratory tests Fe 1 × 10−3–1 × 101 [2][3][28]
Cu 1 × 10−3–1 × 10−1 [2][29][30][28]
Ag 1 × 10−3–1 × 101 [29][30][31]
Zn 1 × 100–1 × 102 [2]
Pb 1 × 10−3–1 × 102 [32][33][34]
Indoor exposures Cu 1 × 10−3–1 × 10−1 [29][35][36][37][38][39]
Ag 1 × 10−3–1 × 10−1 [29][35][36][38][40]
Pb 1 × 10−2–1 × 101 [36][38][41]
EIS 2 Outdoor exposures Fe 1 × 10−1–1 × 101 [42][43] [44][45]
Cu 1 × 102–1 × 103 [22]
ACTs Fe 1 × 102–1 × 103 [46]
Laboratory tests Fe 1 × 10−1–1 × 104 [47][48][49][50][51]
Zn-coated steel 1 × 100–1 × 103 [52][53][54][55]
Zn 1 × 101 [56]
Cu 1 × 10−1–1 × 101 [57][58][22]
EN 3 Outdoor exposures Fe 1 × 10−1–1 × 101 [44][59] [44][59][45][60]
Cu 1 × 10−2–1 × 102 [61][60]
QCM 4 Laboratory tests Cu 1 × 10−1–1 × 100 [62]
Ag 1 × 10−3–1 × 10−2 [63][64][65][66][67][68]
Indoor exposures Cu 1 × 10−3–1 × 10−1 [36][69]
Ag 1 × 10−2–1 × 10−1 [36][40][69]
Co 1 × 10−2–1 × 10−1 [69]
RFID ACTs Fe 1 × 102–1 × 103 [70][71] [72][73]
Laboratory tests Zn 1 × 101 [72][74][73]
FOCS   Fe No data for atmospheric corrosion
Respirometry 5 Laboratory tests Fe 1 × 10−1–1 × 102 [75][76] [77][78]
Cu 1 × 10−2–1 × 10−1 [75]
Al 1 × 10−1–1 × 100 [77]
Mg 1 × 101–1 × 103 [77][78]
* Outdoor exposures–field exposures outdoors; ACTs–standardised accelerated corrosion tests; Laboratory tests–non-standardised tests in laboratories, e.g., wetting/drying cycles, thin electrolyte layers application, increased T and RH, pre-contamination; Indoor exposures–exposures in real indoor environments. ** Symbols Fe, Al, Zn, Cu and Mg refer to both pure metals and their alloys. Zn-coated Fe refers to zinc-coated steels. *** For easy orientation, and as exact values of minimum and maximum detected corrosion rates are often not given in the studies, they are summarised in orders of magnitude of µm·a−1 here. 1 In reference [6], the lowest detectable Fe corrosion rate of 7.7 µm a−1 was calculated. 2 Rp−1 (Rct−1) evolution in time is commonly used as a corrosion indicator instead of calculated corrosion rate as Tafel slopes are not usually known for systems under investigation, as, for example, for corrosion monitoring of Fe [79][80][81][82][83], Zn and Zn-coated steel [84][85], Cu [86][79][87][62], Al [88][89] and Sn [53]. 3 More frequently, Rn, ECN and/or EPN evolution in time is used as a corrosion indicator instead of corrosion rate, as, for example, for corrosion monitoring of Fe [90][91] and Al [92][45]. 4 Mass gain in time is frequently presented as a direct measurement output instead of thickness loss in time, as, for example, for corrosion monitoring of Ag [69][63][64][65][66][67][68], Cu [69][93][62][94][95], Pb [96][97] and Fe [95]. 5 For pre-corroded historical iron artefacts, when the corrosion mechanism is not known, ORR rate cannot be re-calculated to corrosion rate and oxygen consumption is used as a corrosion indicator [98][99][100][101][102].
 
 
 
A comparison of the techniques is given in Table 2. In the first column, current applications are described, whereas their potential applications are suggested in the second column based on the operation principle. The sensitivity is defined in general categories for a quick orientation. The number of suppliers of commercial products is an important indicator of the applicability in service. Finally, main advantages and drawbacks of the techniques are summarised in the last two columns.
Table 2. Comparison of atmospheric corrosion monitoring techniques.
Technique Current Applications Potential Fields of Application Sensitivity * Commercial Suppliers Main Advantages Main Drawbacks
Coupons Indoor and outdoor corrosivity classification according to standards
Verification of other techniques
Applicable in any environment High at long exposure times, otherwise medium Several Standardised technique
Easy data interpretation
No real-time data
Time-consuming
ACM Outdoor monitoring
TOW assessment
Outdoor and indoor at higher RH Medium 1 Not sensitive to temperature fluctuations
Suitable for harsh outdoor environments
Corrosion acceleration due to galvanic coupling
Unclear data interpretation during rainfall
Electrolyte presence required
EIS Laboratory tests at higher RH and under thin electrolyte layers
Assessment of protective coatings
Outdoor and indoor at higher RH Medium 0 Information about corrosion mechanism
Non-destructive assessment of coatings
Knowledge about investigated system needed for correct data interpretation
Electrolyte presence required
Unclear results under very thin electrolyte layers and in presence of thick corrosion products
EN Outdoor corrosion monitoring Outdoor and indoor at higher RH Medium 0 Localised corrosion detection
Corrosion mechanism determination
Complex and unclear interpretation
Electrolyte presence required
ER Indoor and outdoor corrosion monitoring, laboratory studies
Corrosivity classification
Applicable in any environment High 4 Universal technique
High sensitivity
Easy operation and data interpretation
Optimal for uniform corrosion monitoring
Sensitive to temperature fluctuations
Limited possibilities in monitoring of non-uniform corrosion
QCM Indoor corrosivity classification
Laboratory tests
Indoor at lower corrosivity High 2 High sensitivity and short response time
Electrolyte presence not required
Sensitive to temperature fluctuations, moisture and pollutants presence
Not suitable for harsh environments
RFID Laboratory tests Outdoor and indoor at higher corrosivity Low 0 Compact and wireless
Electrolyte presence not required
Further development needed
FOCS None for atmospheric corrosion Not clear yet, as the technique is at the development stage Not available 0 Not known for atmospheric corrosion yet
Respirometry Laboratory tests Not clear yet, as the technique is at the development stage High 0 High sensitivity
Information about corrosion mechanism
Electrolyte presence not required
Sensitivity to RH, temperature and pressure fluctuations
Further development needed
* Low sensitivity–corrosion detection in high-corrosive outdoor environments. Medium sensitivity–detection of corrosion rate in an order of 10 µm·a−1 and higher corresponding to outdoor corrosivity. High sensitivity–detection of corrosion rate in an order of 1 × 10−3 µm·a−1 and higher corresponding to indoor corrosivity.
 
Metallic coupons are used for both indoor and outdoor corrosivity classification according to several standards. The technique is universal and provides easy-to-interpret results, but the corrosivity assessment using coupons is time-consuming and does not allow for real-time monitoring.
ACM is suitable for outdoor corrosion monitoring and assessment of time of wetness (TOW). The data have been used as an input for prediction models. The measurement is not sensitive to temperature fluctuations and showed a good correlation to mass loss of corrosion coupons. The main disadvantages of the technique are the necessity for the electrolyte presence to provide connection between electrodes, corrosion acceleration of the less noble metal caused by galvanic coupling and unclear data interpretation during rainfall and condensation, when the current output increases steeply. Future development of the technique should aim at the improvement of data interpretation algorithms, particularly for the rainfall effect correction.
Similarly to ACM, EIS and EN techniques require a continuous layer of electrolyte to connect the electrodes to be present on the surface. EIS proved to be able to generate useful laboratory or short-term outdoor data in atmospheric exposure conditions. However, it is not considered to be fit for long-term monitoring due to the complex signal interpretation and insufficient stability. EN has been tested outdoors. The main advantage of this method is its potential for localised corrosion detection and corrosion mechanism assessment, but the interpretation of its data is complex, and there is no generally valid data treatment method allowing for a direct corrosion rate calculation from the measured EN signal. The further development of the EN data processing procedure is thus of great importance.
ER is a universal technique that can be recommended for both indoor and outdoor measurements, as a compromise between sensitivity and lifetime can be found by a correct choice of sensor thickness. Sensors made of a wide range of metals and alloys are available. The method is suitable for long-term monitoring of uniform corrosion, providing direct and easy-to-interpret corrosion loss data. The measurement sensitivity to rapid temperature fluctuations which cannot be fully compensated by the reference part may, however, require additional data processing. Along with thermal noise elimination and filtering, the ability of the technique to detect localized corrosion should be considered as beneficial rather than disadvantageous and quantified in future studies.
QCM is an extremely sensitive technique used for corrosivity classification indoors and for laboratory studies of corrosion mechanisms. Due to its sensitivity to moisture, pollutants’ presence and temperature fluctuations, it is not suitable for exposures in harsh environments.
RFID is a state-of-the-art technique currently under development. It is probable to be applicable for corrosion monitoring in service in the future, especially under conditions which require compact wireless solutions. However, there is no ready-to-use solution available yet, as a number of technical obstacles need to be solved first.
FOCS is a technique potentially feasible for monitoring of atmospheric corrosion, but so far it has been developed and applied only for corrosion monitoring in concrete.
Respirometry is a highly-sensitive method which can provide information about corrosion rate and mechanisms. For these purposes, it has been used within laboratory investigations. The technique was tested as an indicator of historical artefacts’ degradation. It can be difficult to use it for real-time corrosion monitoring due to its sensitivity to RH, temperature and pressure variations, and the necessity of placing the monitored object into a sealed box, or to attach a sealed container to the surface.

3. Conclusions

Techniques used for real-time corrosion monitoring of metallic materials have been reviewed and compared focusing on their use in atmospheric conditions. Based on their key characteristics, such as sensitivity, lifetime, availability and data interpretation complexity, the following conclusions can be drawn.
  • Electrochemical EIS, EN and ACM methods can be recommended for the use under outdoor conditions and in laboratory tests at higher RH when stable electric connection between electrodes in ensured.
  • QCM is a powerful technique for extremely low corrosion rate detection in indoor environments.
  • The ER technique is the most universal corrosion monitoring tool, which can be applied both in high and weakly corrosive environments, depending on the sensor’s thickness.
  • Further development of the state-of-the art RFID, FOCS and respirometric techniques in the field of atmospheric corrosion is expected. At the current stage, it is too early to evaluate their application potential.

References

  1. Koch, G.; Varney, J.; Thompson, N.; Moghissi, O.; Gould, M.; Payer, J. International Measures of Prevention, Application, and Economics of Corrosion Technologies Study; NACE International: Houston, TX, USA, 2016.
  2. Prosek, T.; Kouril, M.; Hilbert, L.R.; Degres, Y.; Blazek, V.; Thierry, D.; Hansen, M. Real time corrosion monitoring in atmosphere using automated battery driven corrosion loggers. Corros. Eng. Sci. Technol. 2008, 43, 129–133.
  3. Li, S.; Kim, Y.G.; Jung, S.; Song, H.S.; Lee, S.M. Application of steel thin film electrical resistance sensor for in situ corrosion monitoring. Sens. Actuators B Chem. 2007, 120, 368–377.
  4. Shinohara, T.; Motoda, S.; Oshikawa, W. Evaluation of corrosivity in atmospheric environment by ACM (Atmospheric Corrosion Monitor) type corrosion sensor. In Proceedings of the Pricm 5: The Fifth Pacific Rim International Conference on Advanced Materials and Processing, Pts 1–5, Beijing, China, 2–5 November 2004; Volume 475–479, pp. 61–64.
  5. Mizuno, D.; Suzuki, S.; Fujita, S.; Hara, N. Corrosion monitoring and materials selection for automotive environments by using Atmospheric Corrosion Monitor (ACM) sensor. Corros. Sci. 2014, 83, 217–225.
  6. Zibo Pei, X.C.; Xiaojia, Y.; Qing, L.; Chenhan, X.; Dawei, Z.; Xiaogang, L. Understanding environmental impacts on initial atmospheric corrosion based on corrosion monitoring sensors. J. Mater. Sci. Technol. 2020, 64, 214–221.
  7. Pei, Z.B.; Zhang, D.W.; Zhi, Y.J.; Yang, T.; Jin, L.L.; Fu, D.M.; Cheng, X.Q.; Terryn, H.A.; Mol, J.M.C.; Li, X.G. Towards understanding and prediction of atmospheric corrosion of an Fe/Cu corrosion sensor via machine learning. Corros. Sci. 2020, 170, 108697.
  8. Fuse, N.; Naganuma, A.; Fukuchi, T.; Tani, J.; Hori, Y. Methodology to Improve Corrosion Rate Estimation Based on Atmospheric Corrosion Monitoring Sensors. Corrosion 2017, 73, 199–209.
  9. Kainuma, S.; Yamamoto, Y.; Itoh, Y.; Oshikawa, W. Prediction method for mean corrosion depth of uncoated carbon steel plate subjected to rainfall effect using Fe/Ag galvanic couple ACM-Type corrosion sensor. Zair. Kankyo Corros. Eng. 2011, 60, 497–503.
  10. Kainuma, S.; Sugitani, K.; Itoh, Y.; Kim, I.T. Evaluation Method for Time-dependent Corrosion Behavior of Carbon Steel Plate using Atmospheric Corrosion Monitoring Sensor. Adv. Fract. Damage Mech. Viii 2010, 417, 417–420.
  11. Cao, X.L.; Xiao, Y.D.; Deng, H.D.; Cao, P.J.; Jia, B. Evaluation of Atmospheric Corrosivity by ACM Technique. In Materials Science Forum; Trans Tech Publications Ltd.: Freienbach, Switzerland, 2009; Volume 610, pp. 3–8.
  12. Huang, Y.L.; Yang, D.; Xu, Y.; Lu, D.Z.; Yang, L.H.; Wang, X.T. Field Study of Weather Conditions Affecting Atmospheric Corrosion by an Automobile-Carried Atmospheric Corrosion Monitor Sensor. J. Mater. Eng. Perform. 2020, 29, 5840–5853.
  13. Shi, Y.N.; Fu, D.M.; Zhou, X.Y.; Yang, T.; Zhi, Y.J.; Pei, Z.B.; Zhang, D.W.; Shao, L.Z. Data mining to online galvanic current of zinc/copper Internet atmospheric corrosion monitor. Corros. Sci. 2018, 133, 443–450.
  14. Ahn, J.H.; Jeong, Y.S.; Kim, I.T.; Jeon, S.H.; Park, C.H. A Method for Estimating Time-Dependent Corrosion Depth of Carbon and Weathering Steel Using an Atmospheric Corrosion Monitor Sensor. Sensors 2019, 19, 1416.
  15. To, D.; Shinohara, T.; Umezawa, O. Experimental Investigation on the Corrosivity of Atmosphere through the Atmospheric Corrosion Monitoring (ACM) Sensors. Atmos. Mar. Corros. 2017, 75, 1–10.
  16. Dara, T.; Shinohara, T.; Umezawa, O. Effects of Anion on the Corrosion Behaviors of Carbon Steel under Artificial Rainfall. In Proceedings of the 9th Pacific Rim International Conference on Advanced Materials and Processing (PRICM9), Kyoto, Japan, 1–8 August 2016; The Japan Institute of Metals and Materials: Sendai, Japan, 2016.
  17. Kouřil, M.; Prošek, T.; Scheffel, B.; Dubois, F. High sensitivity electrical resistance sensors for indoor corrosion monitoring. Corros. Eng. Sci. Technol. 2013, 48, 282–287.
  18. Msallamova, S.; Kouril, M.; Strachotova, K.C.; Stoulil, J.; Popova, K.; Dvorakova, P. Historical lead seals and the influence of disinfectants on the lead corrosion rate. Herit. Sci. 2019, 7, 18.
  19. Zajec, B.; Bajt Leban, M.; Kosec, T.; Kuhar, V.; Legat, A.; Lenart, S.; Fifer Bizjak, K.; Gavin, K. Corrosion monitoring of steel structure coating degradation. Teh. Vjesn. 2018, 25, 1348–1355.
  20. Diler, E.; Peltier, F.; Becker, J.; Thierry, D. Real-time corrosion monitoring of aluminium alloys under chloride-contaminated atmospheric conditions. Mater. Corros. 2021, 72, 1377–1387.
  21. Prošek, T.; Le Bozec, N.; Thierry, D. Application of automated corrosion sensors for monitoring the rate of corrosion during accelerated corrosion tests. Mater. Corros. 2014, 65, 448–456.
  22. AirCorr: Corrosion. Available online: https://nke-instrumentation.com/produit/aircorr-corrosion/ (accessed on 21 December 2021).
  23. Dubus, M.; Kouril, M.; Nguyen, T.P.; Prosek, T.; Saheb, M.; Tate, J. Monitoring Copper and Silver Corrosion in Different Museum Environments by Electrical Resistance Measurement. Stud. Conserv. 2010, 55, 121–133.
  24. Kouril, M.; Prosek, T.; Scheffel, B.; Degres, Y. Corrosion monitoring in archives by the electrical resistance technique. J. Cult. Herit. 2014, 15, 99–103.
  25. Van den Steen, N.; Simillion, H.; Thierry, D.; Terryn, H.; Deconinck, J. Comparing Modeled and Experimental Accelerated Corrosion Tests on Steel. J. Electrochem. Soc. 2017, 164, C554–C562.
  26. Kreislova, K.; Fialova, P.; Bohackova, T. Indoor corrosivity in Klementinum baroque library hall. In Prague Structural Studies, Repairs and Maintenance of Heritage Architecture XVII & Earthquake Resistant Engineering Structures XIII; WIT Press: Ashurst, UK, 2021; p. 123.
  27. Shan, W.; LIAO, B.-k.; DONG, Z.-h.; GUO, X.-p. Comparative investigation on copper atmospheric corrosion by electrochemical impedance and electrical resistance sensors. Trans. Nonferrous Met. Soc. China 2021, 31, 3024–3038.
  28. Dubus, M.; Prosek, T. Standardized Assessment of Cultural Heritage Environments by Electrical Resistance Measurements. e-PRESERVATIONScience 2012, 9, 67–71.
  29. Prošek, T.; Kouřil, M.; Dubus, M.; Taube, M.; Hubert, V.; Scheffel, B.; Degres, Y.; Jouannic, M.; Thierry, D. Real-Time monitoring of indoor air corrosivity in cultural heritage institutions with metallic electrical resistance sensors. Stud. Conserv. 2013, 58, 117–128.
  30. Faifer, M.; Goidanich, S.; Laurano, C.; Petiti, C.; Toscani, S.; Zanoni, M. Measurement Setup for the Development of Pre-Corroded Sensors for Metal Artwork Monitoring. In Proceedings of the 2019 IMEKO TC-4, Florence, Italy, 4–6 December 2019; pp. 1–6.
  31. Kosec, T.; Kuhar, V.; Kranjc, A.; Malnaric, V.; Belingar, B.; Legat, A. Development of an Electrical Resistance Sensor from High Strength Steel for Automotive Applications. Sensors 2019, 19, 1956.
  32. Msallamova, S.; Kouril, M.; Strachotova, K.C.; Stoulil, J.; Popova, K.; Dvorakova, P.; Lhotka, M. Protection of lead in an environment containing acetic acid vapour by using adsorbents and their characterization. Herit. Sci. 2019, 7, 76.
  33. Strachotova, K.C.; Kuchtakova, K.; Kouril, M.; Msallamova, S. Protection of Lead in Acetic Acid Containing Air by Means of Corrosion Inhibitors. In Proceedings of the 27th International Conference on Metallurgy and Materials (Metal 2018), Brno, Czech Republic, 23–25 May 2018; pp. 1045–1050.
  34. Van den Steen, N.; Simillion, H.; Thierry, D.; Deconinck, J. Modeling Film Thicknesses and Estimating Corrosion Depths Under Climate Control. In Proceedings of the ECS Meeting Abstracts, PRiME 2016/230th ECS Meeting, Honolulu, HI, USA, 2–7 October 2016; p. 1319.
  35. Yasri, M.; Lescop, B.; Diler, E.; Gallee, F.; Thierry, D.; Rioual, S. Fundamental basis of electromagnetic wave propagation in a zinc microstrip lines during its corrosion. Sens. Actuators B Chem. 2016, 223, 352–358.
  36. Prosek, T.; Taube, M.; Dubois, F.; Thierry, D. Application of automated electrical resistance sensors for measurement of corrosion rate of copper, bronze and iron in model indoor atmospheres containing short-chain volatile carboxylic acids. Corros. Sci. 2014, 87, 376–382.
  37. Kouřil, M.; Prošek, T.; Dubus, M.; Taube, M.; Hubert, V.; Scheffel, B.; Degres, Y.; Jouannic, M.; Thierry, D. Korozní monitoring v rukách restaurátorů a konzervátorů/Corrosion monitoring in the hands of restorers and conservators. Koroze Ochr. Mater. 2012, 56, 67–75.
  38. Bailey, G.; Brian, J.; Champion, C. An investigation into the impact of sealed wooden and acrylic showcases and storage cases on the corrosion of lead objects during long term storage and display. AICCM Bull. 2017, 38, 43–50.
  39. Morcillo, M.; Otero, E.; Chico, B.; de la Fuente, D. Atmospheric corrosion studies in a decommissioned nuclear power plant. In Nuclear Power; InTech: Rijeka, Croatia, 2010; pp. 243–265.
  40. SURVEYOR PLUS™. Available online: https://circul-aire.com/corrosion-monitoring/surveyor-plus/ (accessed on 21 December 2021).
  41. Svadlena, J.; Voracova, E.; Stoulil, J. Corrosion of silver in environment containing halides, pseudohalides, or thiourea. Mater. Corros. Werkst. Und Korros. 2020, 71, 1721–1728.
  42. Nishikata, A.; Suzuki, F.; Tsuru, T. Corrosion monitoring of nickel-containing steels in marine atmospheric environment. Corros. Sci. 2005, 47, 2578–2588.
  43. Nishikata, A.; Zhu, Q.J.; Tada, E. Long-term monitoring of atmospheric corrosion at weathering steel bridges by an electrochemical impedance method. Corros. Sci. 2014, 87, 80–88.
  44. Xia, D.H.; Song, S.Z.; Jin, W.X.; Li, J.; Gao, Z.M.; Wang, J.H.; Hu, W.B. Atmospheric Corrosion Monitoring of Field-exposed Q235B and T91 Steels in Zhoushan Offshore Environment Using Electrochemical Probes. J. Wuhan Univ. Technol. Mater. Sci. Ed. 2017, 32, 1433–1440.
  45. ASTM G96-90(2008)Standard Guide for Online Monitoring of Corrosion in Plant Equipment (Electrical and Electrochemical Methods), ASTM: West Conshohocken, PA, USA, 2008.
  46. Li, C.L.; Ma, Y.T.; Li, Y.; Wang, F.H. EIS monitoring study of atmospheric corrosion under variable relative humidity. Corros. Sci. 2010, 52, 3677–3686.
  47. Nishikata, A.; Yamashita, Y.; Katayama, H.; Tsuru, T.; Usami, A.; Tanabe, K.; Mabuchi, H. An Electrochemical Impedance Study on Atmospheric Corrosion of Steels in a Cyclic Wet-Dry Condition. Corros. Sci. 1995, 37, 2059–2069.
  48. Shi, Y.; Tada, E.; Nishikata, A. A method for determining the corrosion rate of a metal under a thin electrolyte film. J. Electrochem. Soc. 2015, 162, C135–C139.
  49. Nishikata, A.; Ichihara, Y.; Hayashi, Y.; Tsuru, T. Influence of electrolyte layer thickness and pH on the initial stage of the atmospheric corrosion of iron. J. Electrochem. Soc. 1997, 144, 1244.
  50. Thee, C.; Hao, L.; Dong, J.H.; Mu, X.; Ke, W. Numerical Approach for Atmospheric Corrosion Monitoring Based on EIS of a Weathering Steel. Acta Met. Sin. Engl. 2015, 28, 261–271.
  51. Angelini, E.; Grassini, S.; Corbellini, S.; Ingo, G.M.; De Caro, T.; Plescia, P.; Riccucci, C.; Bianco, A.; Agostini, S. Potentialities of XRF and EIS portable instruments for the characterisation of ancient artefacts. Appl. Phys. A Mater 2006, 83, 643–649.
  52. Katayama, H.; Tay, Y.-C.; AS, V.; Nishikata, A.; Tsuru, T. Corrosion monitoring of Zn and Zn–Al coated steels under wet-dry cyclic conditions using AC impedance method. Mater. Trans. JIM 1997, 38, 1089–1094.
  53. El-Mahdy, G.A.; Nishikata, A.; Tsuru, T. AC impedance study on corrosion of 555%Al-Zn alloy-coated steel under thin electrolyte layers. Corros. Sci. 2000, 42, 1509–1521.
  54. El-Mahdy, G.A.; Nishikata, A.; Tsuru, T. Electrochemical corrosion monitoring of galvanized steel under cyclic wet-dry conditions. Corros. Sci. 2000, 42, 183–194.
  55. Yadav, A.; Nishikata, A.; Tsuru, T. Electrochemical impedance study on galvanized steel corrosion under cyclic wet–dry conditions––influence of time of wetness. Corros. Sci. 2004, 46, 169–181.
  56. Ma, X.M.; Cheng, Q.L.; Zheng, M.; Cui, F.Y.; Hou, B.R. Monitoring Marine Atmospheric Corrosion by Electrochemical Impedance Spectroscopy under Various Relative Humidities. Int. J. Electrochem. Sci. 2015, 10, 10402–10421.
  57. Pan, C.; Lv, W.; Wang, Z.; Su, W.; Wang, C.; Liu, S. Atmospheric corrosion of copper exposed in a simulated coastal-industrial atmosphere. J. Mater. Sci. Technol. 2017, 33, 587–595.
  58. Wan, S.; Hou, J.; Zhang, Z.F.; Zhang, X.X.; Dong, Z.H. Monitoring of atmospheric corrosion and dewing process by interlacing copper electrode sensor. Corros. Sci. 2019, 150, 246–257.
  59. Xia, D.-H.; Ma, C.; Song, S.; Xu, L. Detection of atmospheric corrosion of aluminum alloys by electrochemical probes: Theoretical analysis and experimental tests. J. Electrochem. Soc. 2019, 166, B1000.
  60. Garcia-Ochoa, E.; Gonzalez-Sanchez, J.; Corvo, F.; Usagawa, Z.; Dzib-Peerez, L.; Castaneda, A. Application of electrochemical noise to evaluate outdoor atmospheric corrosion of copper after relatively short exposure periods. J. Appl. Electrochem. 2008, 38, 1363–1368.
  61. Li, J.; Kong, W.K.; Shi, J.B.; Wang, K.; Wang, W.K.; Zhao, W.P.; Zeng, Z.M. Determination of Corrosion Types from Electrochemical Noise by Artificial Neural Networks. Int. J. Electrochem. Sci. 2013, 8, 2365–2377.
  62. Schwind, M.; Langhammer, C.; Kasemo, B.; Zoric, I. Nanoplasmonic sensing and QCM-D as ultrasensitive complementary techniques for kinetic corrosion studies of aluminum nanoparticles. Appl. Surf. Sci. 2011, 257, 5679–5687.
  63. Kleber, C.; Wiesinger, R.; Schnoller, J.; Hilfrich, U.; Hutter, H.; Schreiner, M. Initial oxidation of silver surfaces by S2- and S4+ species. Corros. Sci. 2008, 50, 1112–1121.
  64. Wiesinger, R.; Kleber, C.; Frank, J.; Schreiner, M. A New Experimental Setup for in Situ Infrared Reflection Absorption Spectroscopy Studies of Atmospheric Corrosion on Metal Surfaces Considering the Influence of Ultraviolet Light. Appl. Spectrosc. 2009, 63, 465–470.
  65. Wiesinger, R.; Schreiner, M.; Kleber, C. Investigations of the interactions of CO2, O3 and UV light with silver surfaces by in situ IRRAS/QCM and ex situ TOF-SIMS. Appl. Surf. Sci. 2010, 256, 2735–2741.
  66. Wiesinger, R.; Schade, U.; Kleber, C.; Schreiner, M. An experimental set-up to apply polarization modulation to infrared reflection absorption spectroscopy for improved in situ studies of atmospheric corrosion processes. Rev. Sci. Instrum. 2014, 85, 064102.
  67. Wiesinger, R.; Martina, I.; Kleber, C.; Schreiner, M. Influence of relative humidity and ozone on atmospheric silver corrosion. Corros. Sci. 2013, 77, 69–76.
  68. Wan, S.; Ma, X.Z.; Miao, C.H.; Zhang, X.X.; Dong, Z.H. Inhibition of 2-phenyl imidazoline on chloride-induced initial atmospheric corrosion of copper by quartz crystal microbalance and electrochemical impedance. Corros. Sci. 2020, 170, 108692.
  69. Hosseinpour, S.; Schwind, M.; Kasemo, B.; Leygraf, C.; Johnson, C.M. Integration of Quartz Crystal Microbalance with Vibrational Sum Frequency Spectroscopy-Quantification of the Initial Oxidation of Alkanethiol-Covered Copper. J. Phys. Chem. C 2012, 116, 24549–24557.
  70. Alamin, M.; Tian, G.Y.; Andrews, A.; Jackson, P. Corrosion detection using low-frequency RFID technology. Insight 2012, 54, 72–75.
  71. Yasri, M.; Gallee, F.; Leseop, B.; Diler, E.; Thierry, D.; Rioual, S. Passive Wireless Sensor for Atmospheric Corrosion Monitoring. In Proceedings of the 8th European Conference on Antennas and Propagation (EuCAP 2014), The Hague, The Netherlands, 6–11 April 2014; pp. 2945–2949.
  72. Dyos, G. The Handbook of Electrical Resistivity: New materials and pressure effects; The Institution of Engineering and Technology: London, UK, 2012.
  73. Alamin, M. Passive Low Frequencey RFID for Detection and Monitoring of Corrosion under Paint and Insulation; Newcastle University: Newcastle upon Tyne, UK, 2014.
  74. Yasri, M.; Lescop, B.; Diler, E.; Gallee, F.; Thierry, D.; Rioual, S. Monitoring uniform and localised corrosion by a radiofrequency sensing method. Sens. Actuators B Chem. 2018, 257, 988–992.
  75. Watkinson, D.; Rimmer, M. Quantifying Effectiveness of Chloride Desalination Treatments for Archaeological Iron Using Oxygen Measurement. In Proceedings of the Metal 2013: Interim Meeting of the ICOM-CC Metal Working Group, Edinburg, Schotland, 16–20 September 2013; pp. 95–102.
  76. Emmerson, N.; Seifert, J.; Watkinson, D. Refining the use of oxygen consumption as a proxy corrosion rate measure for archaeological and historic iron. Eur. Phys. J. Plus 2021, 136, 546.
  77. Strebl, M.; Virtanen, S. Real-Time Monitoring of Atmospheric Magnesium Alloy Corrosion. J. Electrochem. Soc. 2018, 166, C3001–C3009.
  78. Matthiesen, H. A novel method to determine oxidation rates of heritage materials in vitro and in situ. Stud. Conserv. 2007, 52, 271–280.
  79. Nishikata, A.; Ichihara, Y.; Tsuru, T. Electrochemical impedance spectroscopy of metals covered with a thin electrolyte layer. Electrochim. Acta 1996, 41, 1057–1062.
  80. Thee, C.; Hao, L.; Dong, J.H.; Mu, X.; Wei, X.; Li, X.F.; Ke, W. Atmospheric corrosion monitoring of a weathering steel under an electrolyte film in cyclic wet-dry condition. Corros. Sci. 2014, 78, 130–137.
  81. Thee, C.; Dong, J.; Ke, W. Corrosion monitoring of weathering steel in a simulated coastal-industrial environment. Int. J. Environ. Ecol. Eng. 2015, 9, 587–593.
  82. Cruz, R.V.; Nishikata, A.; Tsuru, T. AC impedance monitoring of pitting corrosion of stainless steel under a wet-dry cyclic condition in chloride-containing environment. Corros. Sci. 1996, 38, 1397–1406.
  83. Cruz, R.V.; Nishikata, A.; Tsuru, T. Pitting corrosion mechanism of stainless steels under wet-dry exposure in chloride-containing environments. Corros. Sci. 1998, 40, 125–139.
  84. Yadav, A.P.; Nishikata, A.; Tsuru, T. Degradation mechanism of galvanized steel in wet–dry cyclic environment containing chloride ions. Corros. Sci. 2004, 46, 361–376.
  85. Somphotch, C.; Hayashibara, H.; Ooi, A.; Tada, E.; Nishikata, A. Corrosion behavior of zinc under thin solution films of different thicknesses. J. Electrochem. Soc. 2018, 165, C590.
  86. Liao, X.-N.; Cao, F.-H.; Chen, A.-N.; Liu, W.-J.; Zhang, J.-Q.; Cao, C.-N. In-situ investigation of atmospheric corrosion behavior of bronze under thin electrolyte layers using electrochemical technique. Trans. Nonferrous Met. Soc. China 2012, 22, 1239–1249.
  87. Liao, X.; Cao, F.; Zheng, L.; Liu, W.; Chen, A.; Zhang, J.; Cao, C. Corrosion behaviour of copper under chloride-containing thin electrolyte layer. Corros. Sci. 2011, 53, 3289–3298.
  88. El-Mahdy, G.; Kim, K.B. AC impedance study on the atmospheric corrosion of aluminum under periodic wet-dry conditions. Electrochim. Acta 2004, 49, 1937–1948.
  89. Van Tran, N.; Ooi, A.; Tada, E.; Nishikata, A. EIS Characteristics of Galvanic Couple of Aluminum Alloy and High-strength Steel under Thin Solution Films. J. Electrochem. Soc. 2020, 167, 131507.
  90. Ma, C.; Song, S.Z.; Gao, Z.M.; Wang, J.H.; Hu, W.B.; Behnamian, Y.; Xia, D.H. Electrochemical noise monitoring of the atmospheric corrosion of steels: Identifying corrosion form using wavelet analysis. Corros. Eng. Sci. Technol. 2017, 52, 432–440.
  91. Jamali, S.S.; Zhao, Y.; Gao, Z.M.; Li, H.J.; Hee, A.C. In situ evaluation of corrosion damage using non-destructive electrochemical measurements-A case study. J. Ind. Eng. Chem. 2016, 43, 36–43.
  92. Iverson, W.P. Transient Voltage Changes Produced in Corroding Metals and Alloys. J. Electrochem. Soc. 1968, 115, 617.
  93. Ehahoun, H.; Gabrielli, C.; Keddam, M.; Perrot, H.; Cetre, Y.; Diguet, L. Electrochemical quartz crystal microbalance corrosion sensor for solid metals and metal alloys—Application to the dissolution of 304 stainless steel. J. Electrochem. Soc. 2001, 148, B333–B336.
  94. Odlyha, M.; Jakiela, S.; Bergsten, C.J.; Slater, J.M.; Niklasson, A.; Svensson, J.; Cavicchioli, A.; de Faria, D.; Thickett, D.; Grøntoft, T. Dosimetry for monitoring in organ pipes and in microclimate frames for paintings. In Proceedings of the Metal 2010: Interim Meeting of the ICOM-CC Metal Working Group, Charleston, CA, USA, 11–15 October 2010; 2010; pp. 321–326.
  95. OnGuard Smart. Available online: https://www.purafil.com/products/monitoring/active-monitoring/onguard-smart/ (accessed on 21 December 2021).
  96. Odlyha, M.; Slater, J.M.; Grøntoft, T.; Jakiela, S.; Obarzanowski, M.; Thickett, D.; Hackney, S.; Andrade, G.; Wadum, J.; Christensen, A.H. A Portable Tool for the Evaluation of Microclimate Conditions within Museum Enclosures, Transit Frames, and Transport Cases. Stud. Conserv. 2018, 63, 407–410.
  97. Agbota, H.; Mitchell, J.E.; Odlyha, M.; Strlič, M. Remote assessment of cultural heritage environments with wireless sensor array networks. Sensors 2014, 14, 8779–8793.
  98. Matthiesen, H.; Stemann-Petersen, K. A fast and non-destructive method to document and quantify the efficiency of metals conservation. In Proceedings of the Metal 2013: Interim Meeting of the ICOM-CC Metal Working Group, Edinburgh, Scotland, 16–20 September 2013; pp. 16–20.
  99. Watkinson, D.; Emmerson, N.; Seifert, J. Matching Display Relative Humidity to Corrosion Rate: Quantitative Evidence for Marine Cast Iron Cannon Balls. In Proceedings of the Metal 2016: Interim Meeting of the ICOM-CC Metals Working Group, New Delhi, India, 26–30 September 2016; pp. 195–202.
  100. Watkinson, D.E.; Rimmer, M.B.; Emmerson, N.J. The influence of relative humidity and intrinsic chloride on post-excavation corrosion rates of archaeological wrought iron. Stud. Conserv. 2019, 64, 456–471.
  101. Emmerson, N.J.; Watkinson, D.E. Surface preparation of historic wrought iron: Evidencing the requirement for standardisation. Mater. Corros. 2016, 67, 176–189.
  102. Watkinson, D.; Emmerson, N. The impact of aqueous washing on the ability of βFeOOH to corrode iron. Environ. Sci. Pollut. Res. 2017, 24, 2138–2149.
More
Information
Contributor MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
View Times: 679
Revisions: 2 times (View History)
Update Date: 27 Jan 2022
1000/1000
ScholarVision Creations