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Electrochemical noise for corrosion monitoring

Robert A. Cottis , in Techniques for Corrosion Monitoring, 2008

4.1.1 What is electrochemical noise?

Electrochemical noise (EN) is a generic term used to describe the fluctuations in potential and current that occur on a corroding electrode. EN is produced by the processes causing the corrosion (or other electrochemical reactions), and it has been a hope of corrosion researchers that its interpretation would provide an understanding of the corrosion process that cannot be obtained by other means. So far this hope has not been completely realised, but some progress has been made, and the method has been used for corrosion monitoring. This chapter will review the development of our current understanding of EN, and the methods that have been used in corrosion monitoring.

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Corrosion Monitoring

Y. He , in Reference Module in Materials Science and Materials Engineering, 2016

3.8 EN

EN monitoring technique records the natural fluctuation in the corrosion potential and current. EN has been utilized to identify localized corrosion and to differentiate conditions where general and localized corrosion may occur. Attempts have also been made to determine the corrosion rate using the fluctuations in potential and current. Since EN requires monitoring very small signal fluctuation, it may be prone to extraneous sources of signal noise if improperly used. Thus, EN is most commonly utilized in combination with other techniques such as LPR and EIS. Examples include the use of multiple probes to monitor dew point problem areas and multiphase environments. The technical basis for this technique is still under investigation.

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Management and Control of Corrosion

C.F. Britton , in Shreir's Corrosion, 2010

Electrochemical noise (EN)

The EN technique involves the analysis of spontaneous potential or current transients that arise on or between corroding metal electrodes. The EN technique was first identified by Iverson ²⁵ and there is now an extensive literature on applications in corrosion monitoring. ^26,27 The theoretical background and development of EN are described elsewhere in this book. In the last edition of this book in 1994, EN applications in power generation plant, cooling water systems, and reinforcement in concrete were reported. Also, it was noted that probes containing combination elements utilizing several electrochemical techniques (AC and DC) had been developed and used for measurements in condensing acid environments.

The development of EN has progressed rapidly particularly due to developments in the electronic equipment that is able to discriminate between natural electrode current/voltage transients and electronic background noise. The interest in the technique derives partly from the prospect of a more reliable and flexible way of measuring corrosion rate but particularly from its unique sensitivity to localized corrosion processes such as pitting crevice corrosion and stress corrosion cracking (SCC) that is not available from other electrochemical techniques. EN is also much more responsive to system changes and upsets than any other monitoring technique, electrochemical or otherwise, which makes it a strong contender for corrosion/process control.

The technique does not perturb the electrodes as is the case with electrochemical techniques involving polarization but detects the natural voltages and currents that are generated on the electrode surfaces in the environment. Measurements can be made in a wider range of environmental resistivity compared with LPR. In the usual configuration, the potential noise and/or the current noise between two identical electrodes is measured. Currents are measured with a zero-resistance ammeter. Data analysis is used to determine the corrosion rate and/or the corrosion mechanism. In theory, corrosion rates can be estimated from EN measurements in a manner analogous to LPR measurements. Corrosion rates are calculated using the so-called noise resistance, R _n, which is equivalent to the LPR polarization resistance, R _p, and is determined using the relationship:

$R_{\text{n}}=\text{σ}{V}_{\text{n}}/\sigma i_{\text{n}}$

where σV _n and σi _n are the standard deviations of the EN potential and current signals respectively. A variety of techniques can be used to analyze the data including the time basis of the data obtained, statistical analysis, which can provide mechanistic information, frequency domain transformation to characterize localized corrosion, fractal and neural analysis. ²⁸

An advantage of the technique is that it can be deployed in operating plants using standard, commercially available LPR probes with associated conventional access systems. However, the complex instrumentation can be expensive, and as with EIS, specialized knowledge is required for the verification of instrument/computer outputs and the interpretation and analysis of results. The technique is generally provided by specialized companies/contractors unless there is in-house expertise available in a larger company.

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Corrosion in Liquids, Corrosion Evaluation

R.A. Cottis , in Shreir's Corrosion, 2010

2.30.5.9.2 Measurement

Electrochemical noise is almost invariably measured as digitized time records. Thus, the measurement process consists of a number of steps, illustrated in Figure 20 . Potential noise typically has a low amplitude, and it is therefore common to amplify it – this is done as the first step in order to minimize the effects of other processes on the instrument noise. If the potential is measured with respect to a reference electrode, it will typically have a relatively large dc value, and the voltage amplifier may also incorporate a dc offset to allow a larger gain to be used without exceeding the output voltage range of the amplifier.

Figure 20. Three electrode EN measurement configuration.

Current noise is normally converted to a voltage signal using a current amplifier. It is not usually necessary to provide for a current offset as the current noise normally has an expected mean of zero.

Following amplification, the voltage and current noise signal should be filtered to remove unwanted frequency components (although the amplifier and filter circuits may be combined in a practical instrument). In particular, a low-pass antialiasing filter should be included to remove frequency components that could give rise to aliasing in the sampling process. A high-pass filter may also be incorporated to remove the dc level (as an alternative to the use of a fixed dc offset), although it is difficult to produce good analog filters with a very low frequency, and even good quality filters present 'issues' associated with the filter settling time when first switching on.

The continuous analog signal must then be sampled to convert it to a regular sequence of samples, and these sampled values must be converted from analog to digital values. These two processes may be combined if certain types of analog to digital convertor are used. Most electrochemical noise information is present at low frequencies (typically below about 10   Hz), and hence EN measurement systems do not have particularly stringent sampling rate requirements, and it is more important to have a high resolution. Most computer data acquisition systems are optimized for high-speed, relatively low-resolution sampling, and they are therefore unsuitable for EN measurements. Conventional digital multimeters or electrometers usually provide more suitable measurement capabilities, and they may also provide some of the required signal conditioning (although for the best results separate signal conditioning systems are normally required).

Finally the sampled digital time series is either recorded for subsequent processing (this is typically done for research purposes) or processed online to produce summary parameters (typically used for corrosion monitoring).

The measurement of electrochemical noise requires care in order to avoid sources of noise other than true electrochemical noise. Some of the more likely sources of error are:

•

Instrument noise – electrochemical noise often has a very low amplitude, and high-quality current and potential measuring systems are necessary in order to minimize the addition of electronic noise from the instrument. Instrument noise levels should be checked to ensure that the level of such noise is significantly below that of the measured signals. Instrument noise levels are influenced by the impedance of the system being measured, and a dummy cell with a similar impedance to that of the corroding system should be used in the calibration process ( Figure 21 , based on Ritter et al. ²⁵ ).

Figure 21. EN Measurement System (ADC   =   Analog to Digital Convertor) (from Cottis ⁸ ).

•

Quantization noise – virtually all electrochemical noise analysis methods involve converting the analog noise signal to a sampled digital time record. If the resolution of the analog to digital convertor is inadequate, steps will be observed in the time record ( Figure 22 ). These add a form of noise, known as quantization noise, to the data; providing the measured signal is changing sufficiently rapidly, the contribution of the quantization noise is to add white noise (noise with a constant PSD) to the signal. (If the signal is changing slowly compared with the quantization step size, the measured value may be constant for long periods, and in this case the effect of the quantization may be to reduce the apparent noise.)

Figure 22. Dummy cell for determination of instrument noise levels (from Schottky ²⁴ ).

•

Aliasing – during the sampling process, signals with a frequency above half the sampling frequency are transformed into samples that appear to have a lower frequency ( Figure 23 ). (Some digital-to-analog conversion methods reduce the sensitivity to aliasing by averaging the measured signal over the sample period. However, this does not completely prevent aliasing, and it is good practise to use antialiasing filters for all EN measurements.) It is important to use antialiasing filters to remove these frequencies before sampling occurs, as it is impossible to distinguish the resultant sampled data from real low-frequency signals. It should also be appreciated that aliasing does not just occur within electronic devices; it can also be created in software. Thus, if the sampling frequency of a signal is reduced by decimation (selecting every nth sample), this will also produce aliasing, and a low-pass software filter should be applied to the original data before decimation. (As software filters can be constructed to have essentially ideal properties, this can be a useful approach. Indeed there are arguments that the most effective approach to the development of instrumentation for EN is to sample at a fixed, relatively high frequency and then deliver data at the required rate by filtering and decimation. Besides avoiding expensive, low-frequency analog filters, this tends to reduce the amplitude of quantization noise (this process is known as oversampling in the electronics literature).)

Figure 23. EN time record showing quantization noise in the current signal (from Cottis ⁸ ). The quantization can be seen as the 'banding' in the plot, illustrated by the two dotted lines superimposed on the plot at two adjacent quantization levels. This level of quantization is tolerable, and is not going to have a very large impact on the analysis.

•

Interference – electromagnetic interference from a number of sources may be picked up and amplified by the EN measurement system. This leads to two main types of error: mains frequency (power-line) noise (50 or 60   Hz depending on location) and relatively rapid transients (duration of the order of ms) due to inductive effects associated with the switching of high currents (the laboratory refrigerator is a common source of the latter). While both of these types of interference can be identified relatively easily, it may be more difficult to do this once the data have been sampled. Thus, mains frequency noise will typically be aliased to a much lower frequency, and transients will appear to be at least one sample period long. Thus, it is always best to prevent such interference from getting into the measurement system. This is normally achieved by careful shielding and earthing.

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Corrosion monitoring under coatings

Feng Gui , Brossia C. Sean , in Techniques for Corrosion Monitoring, 2008

18.2.2 Electrochemical Noise (EN)

The impedance technique, although powerful and capable of detection under coating delamination via several parameters, can be complicated. Compared to the impedance technique, electrochemical noise does not introduce any perturbing signal to the system of interest. Instead, the current and voltage fluctuations are obtained at the open circuit potential. ³⁰ Many efforts have been made to use electrochemical noise for coating evaluations. ³⁰⁻³⁷

Although many different parameters could be determined from the analysis of impedance data, in general the analysis of electrochemical noise only generates the electrochemical noise resistance (R_n ), defined as:

[18.7] $R_n={\mathrm{\sigma }}_V/{\mathrm{\sigma }}_I$

where σ _V and σ _I are the standard deviation of the potential noise and the current noise, respectively. Many authors have demonstrated that the electrochemical noise usually decreases with increases in exposure time, which is very similar to that observed from EIS. ^{30 , 34−37} Skerry and Eden also found that good paints exhibited relatively large voltage noise and relatively small current noise compared to poor paint coatings. ³⁷ However, many also agreed that although the general trend of noise resistance change with time is similar to the parameters (e.g. R_t ) determined from impedance, the numerical values were considerably different. As a result, most of the published work has been using EN techniques in conjunction with electrochemical impedance techniques. Further research and theoretical work still needs to be conducted to build more confidence in using electrochemical noise to monitor corrosion under coating.

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Petroleum Products Transporting Pipeline Corrosion—A Review

N. Muthukumar , in The Role of Colloidal Systems in Environmental Protection, 2014

5.3 Monitoring

Development of an integrity management program to control the internal corrosion of such pipelines depends on our ability to monitor the efficiency of the inhibitor performance. Controlling the electrode potential in low-conductivity solutions was a major difficulty because of the drift of the corrosion potential that progressively polarized the electrode. Papavinasam et al. (2003) studied the comparison of techniques for monitoring corrosion inhibitors in oil and gas pipelines. The reliability of weight loss, linear polarization resistance (LPR), electrochemical impedance spectroscopy (EIS), electrochemical noise (EN), and externally mounted hydrogen probes for monitoring inhibitor performance in oil and gas pipelines were investigated. Reliable EIS measurements could not be obtained with regularity in operating oil and gas pipelines. Electrochemical noise was a reliable method of monitoring the effects of corrosion inhibitors on general corrosion rates in oil and gas pipelines. Noise parameters, pitting index, pitting factor, and pit indicator may be used with caution to obtain information regarding pitting corrosion. EN appears to be a promising monitoring method in oil and gas pipelines, but better theoretical understanding is still required. Chen et al. (2004) investigated monitoring of corrosion and flow characteristics in oil/brine mixtures of various compositions. The feasibility of monitoring corrosion processes by means of electrochemical impedance and noise measurements in paraffin oil/brine mixtures of various compositions between 0 and 80 vol% of oil were done. Hence many investigators evaluated the various electrochemical techniques in oil–water systems.

In contrast, electrolyte resistance (ER) measurements, performed with a homemade device delivering an analog signal allowing the mean value as well as the fluctuations of the ER to be measured in real time, were not sensitive to the corrosion potential drift. Bouazaze et al. (2005) reported a new approach for monitoring corrosion and flow characteristics in oil-brine mixtures. Monitoring of the corrosion process of various compositions between 0 and 80% in a volume of oil was investigated by means of electrochemical impedance and noise measurements. Hong et al. (2000, 2001) studied the monitoring of corrosion in multiphase pipelines. They investigated the corrosion inhibition efficiency of carbon steel in multiphase flow by electrochemical impedance spectroscopy (EIS) and electrochemical noise methods. They found that EIS and EN (electrochemical noise) techniques are good methods to study the corrosion and inhibition of pipeline steel under multiphase flow conditions.

Caunter (1999) investigated the remote corrosion monitoring of pipelines and plant sites. A newly developed remote corrosion monitoring system was used in monitoring oil and gas pipelines in remote and hostile environments, as well as process plants in hazardous locations. Silva et al. (2004) studied the effect of flow on the corrosion mechanism of different API pipeline steels grades in NaCl solutions containing CO₂. Electrochemical results were obtained during study of the corrosion of X52, X60, X65, and X70 pipeline steel samples, immersed in a 3 wt% NaCl solution saturated with CO₂ at 20°C under static and controlled turbulent flow conditions. Electrochemical techniques (e.g., linear polarization resistance) and polarization curves were also used to determine the effect of turbulent flow on the corrosion kinetics of the different steels studied. Dougherty et al. (1999) reported the criteria for selecting corrosion inhibitors for arctic and subsea high-velocity flow lines. They also described the different methodologies for evaluating corrosion inhibitors such as the flow loop test, rotating cylinder electrode (RCE), and emulsion tendency test. Becerra et al. (2000) studied the corrosion of carbon steel in oil–water emulsions under controlled hydrodynamic conditions. They found that the effect of the oil content on the electrochemical activity of carbon steel varies with the internal phase relationship (IPR). For emulsion with low IPR (oil contents up to 20 wt%), the electrochemical activity was slightly higher than that of the base surfactant solution. Schiapparelli et al. (1980) conducted their electrochemical study by employing contaminated water. In the present study, electrochemical behavior has been investigated by using contaminated water. Impedance and polarization techniques were employed. The study focuses on biodegradation of diesel/inhibitor and its effect on corrosion. Generally, water and bacteria contribute to corrosion. Hence, to find the mechanism whereby corrosion occurs, the contaminated water was used for electrochemical studies.

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Activity and passivity of magnesium (Mg) and its alloys

E. Ghali , in Corrosion of Magnesium Alloys, 2011

2.5.4 Metallurgically influenced corrosion

It has been observed that the corrosion resistance of diecast Mg alloys is a function of the polishing depth of the specimen. Effectively, removing certain surface layers during mechanical polishing expose the surface of the interior skin with less contaminants and somewhat different microstructure that can lead to an improvement in the active and passive behaviors of the specimen. The corrosion resistance of diecast and freely solidified or electromagnetically stirred thixocast AZ91D alloy has been studied using EN technique and EIS in dilute chloride solution saturated with atmospheric oxygen to assess the influence of the microstructure on corrosion kinetics and morphology. At depths between 10 and 50   μm (skin), all specimens showed general non-uniform corrosion with the lowest corrosion resistance. Between 100 and 200   μm (interior skin), the observed corrosion was accompanied by superficial undefined pits due to metastable pitting (Lafront et al., 2008). There is then an advantage to removing the superficial skin since the interior provides the best possibility for better passive performance. Hot- or grit-blasted surfaces often exhibit poor corrosion performance not from induced cold work but from embedded contaminants. Acid pickling to a depth of 0.01 to 0.05   mm can be used to remove reactive contaminants, but re-precipitation of the contaminant should be avoided such as steel shot residues (Shaw, 2003).

The corrosion behavior of the skin of diecast AZ91   Mg alloy has been examined as a function of the thickness of the cast alloy in 3.5%   NaCl solution saturated with Mg(OH)₂ at room temperature. It was found that the corrosion resistance of cast specimens with relatively more important thicknesses was higher than that of the less thick ones. This was explained in terms of the increasing amount of Al and β phase (Mg₁₇ Al₁₂) in their skins (Aghion and Lulu, 2009). It has been also stated that the morphology, the level of porosity and the composition of the passive layer especially in this passive alkaline medium were showing a better corrosion resistance.

A hot-chamber diecast AZ91D thin plate with a die chill skin on its surface was severely corroded in 5   wt% chloride solution (I _corr  ~   1600   μA/cm²), whereas a plate with a die skin layer etched in an HF/H₂SO₄ aqueous solution to remove interdendritic phases had a substantially lower corrosion rate (3 to ~   16   μA/cm²). The die-chill skin was composed of a thin layer of chill zone and a thick layer composed of interdendritic Al-rich α-Mg/Al₁₂Mg₁₇ β-phase particle/α-Mg grain composite. The chill zone (4   ±   1 (im in thickness) had fine columnar and equiaxed grains and contained a distribution of submicron Mg–Al–Zn intermetallic particles. The removal of the primary β-phase from the diecast sample surface did not improve the corrosion performance of the specimen (Uan et al., 2008).

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Corrosion monitoring in concrete

Peter Schießl , Christoph Dauberschmidt , in Techniques for Corrosion Monitoring, 2008

16.3.5 Corrosion rates

Potential measurements just give information whether active corrosion is actually probable or not. To get more detailed information on corrosion behaviour than from simple potential mapping, on-site corrosion rate measurement methods have been developed, like anodic pulse measurements, linear polarisation resistance measurements, AC impedance and electro-chemical noise measurement. Most of these methods have this in common: the potential of the steel (reinforcement) changes electrochemically by using an external current; and it monitors the electrochemical response of the reinforcement.

The anodic pulse measurements use a galvanic direct current pulse over a period of a few seconds to the reinforcement and the influence on the potentials of the reinforcement is monitored. This potential change consists of the IR-drop occurring immediately after applying the pulse (which enables the resistivity to be determined) and later on of a further increase of the potential describing the polarisation behaviour of the steel. Altogether three parameters are determined by anodic pulse measurements: the potential, the resistivity and the polarisation behaviour of the reinforcement. However, the determination of the exact corrosion rate under practical conditions is normally not possible, because the calculation models (suitable equivalent electrical circuits) are only rough approximations. Furthermore the measurement is influenced by the ratio between the reinforcement surface and the concrete surface, which can vary widely. Additionally galvanic effects in the case of macro-cell corrosion (localised corrosion) cannot be determined, i.e. only an average corrosion rate is measured (CEB, 1998).

Similar to the anodic pulse measurements linear polarisation measurements can be carried out to determine the potential and polarisation behaviour of the reinforcement and the resistivity of the concrete. Instead of an anodic pulse a small voltage variation (±   10 to ±   20   mV) is applied sinusoidally to polarise the reinforcement slightly. The induced electrical current is measured and evaluated allowing the determination of the IR-drop and polarisation behaviour. Assuming a linear relationship between potential and current near the free corrosion potential, a so-called linear polarisation resistance (LPR) (see Chapter 3 for more details) can be calculated from the measured data. This LPR is often used to calculate a corrosion current for the reinforcement.

A further improvement is a commercially available special device for LPR measurements: the so-called guard-ring. This confines the area of measurement on the reinforcement if placed around the counter electrode used for applying external voltage. When interpreting data from the LPR measurement it should also be noted that the corrosion rate of the reinforcement can only be estimated because some parameters cannot be quantified as a ratio between reinforcement and concrete surface and macro-cell corrosion effects. The limit values according to RILEM (2004) are given in Table 16.4.

Table 16.4. Limit values for LPR-measurements often used as evaluation criteria (RILEM, 2004)

Current densities [μA/cm2]	Corrosion rates
0.1 to 0.2	Passive condition
0.2 to 0.5	Low to moderate
0.5 to 1.0	Moderate to high
>   1.0	High

Similarly to the case of potential measurements, the corrosion rate may be measured by means of either external devices (cathode, reference electrode) for existing structures, or internal probes to be positioned inside the structure at the casting stage.

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Passivity and Localized Corrosion

G.T. Burstein , D Sazou , in Reference Module in Materials Science and Materials Engineering, 2016

12.1 Metastable Pitting

Metastable pitting events have been attracted considerable interest and numerous studies for many metals and alloys have shown that current fluctuations resulting from randomly created metastable pits at potentials below E _pitt can influence nucleation of future events and pit stabilization. ^233–235 The frequency of transients seem to be a function of potential scan rate, ²³⁶ chloride concentration and potential. ^237,238 Specific electrochemical techniques have been developed to record current and potential transients (noise). ^239–241 Electrochemical noise analysis has been conducted by using many statistical and spectral methods in order to extract relevant information on corrosion processes. ²²⁹

According to recent studies an alternative definition of E _pitt is that the E _pitt signifies high corrosion rates due to spatial and temporal interactions among metastable pits leading to clustering in time. ²⁴² Such spatiotemporal cooperative events exemplified by current transients of a stochastic nature within the range E _br<E<E _pitt were investigated on homogeneous metal surfaces, i.e. surfaces without any preferred sites for local corrosion, like sulfide inclusions in stainless steel surfaces. ^243,244

Interactions between metastable pitting events occur via local changes in concentration, ohmic potential drop and oxide film damage all of which influence the nucleation rate of subsequent pits. These factors constitute the pre-history of a specific location at the surface, which is governed by a memory effect resulting in enhanced generation rate of metastable pits, thereby, increasing the pitting probability at that location. Experimental observations and simulations of postulated spatiotemporal model demonstrated an explosive increase in the number of metastable pits accompanied with a sudden rise in the total current at E _pitt due to a cooperative effect. This model was used to characterize metastable pitting, the cooperative behavior of the pitting events and the explosive increase of pitting activity beyond E _pitt assigned to an autocatalytic growth of pits.

The idea of cooperative interactions between metastable pits and enhance generation of pits at E _pitt was further applied to heterogeneous surfaces with randomly distributed inclusion sites in an otherwise passive alloy surface. ^245,246 The inclusions formed a random sublattice of pit sites that were given a higher probability of pitting due to damage caused by corrosion products from adjacent pitting events. It was shown that there is a critical value of inclusion density, above which a transition to an autocatalytic explosive growth of metastable pits, associated with high rates of corrosion, will occur at E _pitt under otherwise fixed conditions. Critical factors affecting the sudden rise to high pitting activity depends on the inclusion density, the boundary layer thickness controlled by changes in stirring, intrinsic susceptibility of inclusions, and the applied potential. Below the E _pitt, a low pitting activity occurs since cooperative interactions exist between isolated metastable metastable pitting events. A smaller effective diffusion length than the inclusion spacing suppresses the cooperative spread of pitting. Heterogeneous surfaces with inclusions that induced a lower population of metastable events exhibit a higher E _pitt.

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Nitric Oxide, Part G Oxidative and Nitrosative Stress in Redox Regulation of Cell Signaling

Tal Nuriel , ... Steven S. Gross , in Methods in Enzymology, 2008

3.1 Materials

3-Nitrotyrosine, sodium octanesulfonate, acetonitrile, proteinase K, sodium hydrosulfite, and all other reagents are purchased from Sigma-Aldrich in the best available grade (minimum 95% purity; HPLC grade where available). An isocratic HPLC system with autosampler, pump, tubings, and fittings, as well as a multichannel electrochemical CoulArray detector and EC cell, are from ESA, Inc. HPLC mobile phase and all buffers and standard solutions are prepared using 18   MΩ resistance water, either purchased or prepared using a Milli-Q water purification system (Waters Inc.) or equivalent. The HPLC mobile phase is vacuum degassed and filtered through a 0.2-μ m nylon membrane (Whatman) to reduce background electrochemical noise, prolonging the electrochemical cell lifetime and enhancing the 3-NT detection of sensitivity. 3-NT detection sensitivity can be enhanced progressively by continuous recirculation of the mobile phase through the EC cell to attenuate background oxidizable species. Centrifugal molecular weight cutoff filters (Microcon Ultracel YM-10; 10 kDa) are from Millipore Corporation. Polypropylene microcentrifuge tubes (2  ml) are from Sorenson Biosciences, ultracentrifuge tubes (1.5   ml) are from Beckman Instruments, and autosampler vials are from Fisher Scientific. Any reversed-phase C18 column may be used for 3-NT analysis; however, columns with smaller particle sizes (3 μm, or less) and longer column lengths (>100   mm) will enhance resolution, except at the expense of analysis time. We often use a relatively inexpensive Microsorb-MV 100   mm C18 (5-μm particle size) HPLC column from Varian Instruments. Also required for this protocol is a handheld homogenizer (Branson Scientific), microultracentrifuge (e.g., Beckman Optima TLX and TLA100.3 rotor), and a Speed-Vac concentrator (Savant).

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