From the results of the three round-robin tests on electrochemical noise (EN) measurements with dummy cells performed between 2014 and 2017 by the European Cooperative Group on Corrosion Monitoring of Nuclear Materials, it was concluded that achieving valid EN measurements is jeopardized by a lack of theoretical knowledge as well as by software and hardware issues. This paper is aimed at guiding users of the EN technique by providing the minimum knowledge for EN measurements, including the necessary validation of the signals measured at different sampling frequencies by calculation of their power spectral densities. Two practical works performed with a commercial potentiostat are proposed. The first one is devoted to the measurement of the thermal noise of three resistors of equal value connected in a “star” arrangement and used in the conventional three-electrode EN measurement setup using a zero-resistance ammeter. This allows the instrumental noise of the equipment to be determined. The second practical work concerns pitting corrosion of two identical aluminum electrodes in potassium chloride to show that the noise impedance is equal to the modulus of the impedance of the electrodes, which is another way to validate the EN measurements. A bias voltage is then applied between the electrodes to obtain one anode and one cathode, which shows the difficulty of analyzing the measured EN in asymmetric systems.
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1 September 2019
SCIENCE SECTION|
June 02 2019
Electrochemical Noise—Guidance for Improving Measurements and Data Analysis
François Huet;
François Huet
*Sorbonne Université, CNRS, Laboratoire Interfaces et Systèmes Electrochimiques, F-75005 Paris, France.
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Kieu Ngo
Kieu Ngo
‡
*Sorbonne Université, CNRS, Laboratoire Interfaces et Systèmes Electrochimiques, F-75005 Paris, France.
‡Corresponding author. E-mail: [email protected].
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CORROSION (2019) 75 (9): 1065–1073.
Article history
Received:
March 09 2019
Revision Received:
June 02 2019
Accepted:
June 02 2019
Citation
François Huet, Kieu Ngo; Electrochemical Noise—Guidance for Improving Measurements and Data Analysis. CORROSION 1 September 2019; 75 (9): 1065–1073. doi: https://doi.org/10.5006/3211
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