Toward continuous amperometric gas sensing in ionic liquids: rationalization of signal drift nature and calibration methods
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Sensor signal drift is the key issue for the reliability of continuous gas sensors. In this paper, we characterized the sensing signal drift of an amperometric ionic liquid (IL)-based oxygen sensor to identify the key chemical parameters that contribute to the signal drift. The signal drifts due to the sensing reactions of the analyte oxygen at the electrode/electrolyte interface at a fixed potential and the mass transport of the reactant and product at the electrode/electrolyte interface were systematically studied. Results show that the analyte concentration variation and the platinum electrode surface activity are major factors contributing to sensing signal drift. An amperometric method with a double potential step incorporating a conditioning step was tested and demonstrated to be useful in reducing the sensing signal drift and extending the sensor operation lifetime. Also, a mathematic method was tested to calibrate the baseline drift and sensing signal sensitivity change for continuous sensing. This study provides the understanding of the chemical processes that contribute to the IL electrochemical gas (IL-EG) sensor signal stability and demonstrates some effective strategies for signal drift calibration that can increase the reliability of the continuous amperometric sensing.
KeywordsGas sensors Ionic liquid Continuous sensing Signal drift Calibration
Detection and quantification of gases are important in many applications, particularly in workplace safety and environmental health . The concentrations of gas analytes vary in both time and space depending on the time of day as well as locations relative to the contaminants and/or in environments where hazardous gaseous substances are not a factor in daily activities (e.g., offices and on the streets). Thus, measuring the gaseous analytes in ambient conditions requires gas sensors that can measure the concentrations of the gaseous analytes in real-time or continuously throughout some defined time period. Although many hand-held portable gas sensors have been developed, none meet the challenging set of cost/utility/capability requirements that prevent the pervasive use of personal, continuous-use gas monitors in many real-world applications. We have demonstrated a room temperature ionic liquid (RTIL) electrochemical gas sensor technology that could potentially solve many prevailing problems with existing gas sensor technologies [2, 3, 4, 5, 6, 7, 8, 9]. We have shown that the accuracy, selectivity, and detection limits of IL-based electrochemical gas (IL-EG) sensors are suitable for the real-time monitoring of key gases in work safety applications (e.g., O2, CH4, H2). One of the major challenges of chemical sensors for real-time sensing applications is sensor stability and/or sensor drift . As yet, it has not been possible to fabricate drift-free chemical sensors for long-term continuous sensing [11, 12, 13, 14]. Sensor signal drift is a very fundamental problem for real-time and continuous sensing in a dynamic gaseous environment. The prevailing IL-EG sensors also exhibit signal drift during long-term sensing in real-world gas mixtures [3, 15, 16].
Typically, there are two main signal drift sources for a general chemical sensor [10, 17, 18]. The first source is due to the chemical and physical interaction processes of the chemical analytes, occurring at the sensing film microstructure, such as aging (e.g., the reorganization of the sensor surface over long periods of time) and poisoning (e.g., irreversible binding due to external contamination) . The second source is due to measurement system drift, produced by the external and uncontrollable alterations of the experimental operating system, including but not limited to: changes in the environment (e.g., temperature and humidity variations), measurement delivery system noise (e.g., tubes condensation, sample conditioning, etc.), and thermal and memory effects (e.g., hysteresis or remnants of previous gases) . The second source of signal drift can often be eliminated with engineering approaches (e.g., packing of the sensor with a water-resistant filter) and calibration methods. In this work, we focus on understanding the nature of the first source of signal drift in the IL-EG sensor as it is directly related to the fundamental chemical sensing processes and mechanisms. Owing to the chemical and thermal stability of the IL sensing material, the aging of the sensing films can be minimized or eliminated. Thus, signal drift of the IL-EG sensor predominately results from the analyte mass transport at the IL/electrode interface and the interface sensing reactions under an applied potential. We selected an IL-EG oxygen sensor as our model system because the sensing mechanism of the oxygen sensor is based on the oxygen reduction . It has been shown that the directional polarizability of ILs facilitates the formation of an ordered interface structure, which has been used in making a proton-conducting gelatinous electrolyte and nanostructure anatase TiO2 monoliths [19, 20]. This unique IL/electrode interface structure and the high viscosity of an IL could result in the accumulation of reaction by-product leading to baseline drift. The by-product can also be adsorbed at the electrode surface, which can result in the change of the sensing sensitivity. We systematically studied the nature of the signal drift focusing on analyte mass transport at IL/electrode interface and the electrode reactivity, and demonstrated the advantage of applying a double potential step chronoamperometry to minimize the signal drift using an oxygen IL-EG sensor that our lab previously reported as an example . The understanding of the drift nature of the amperometric sensing signal of the IL-EG sensor and the calibration methods developed here serve as an important step toward the development of IL-EG sensors for reliable real-time and continuous monitoring of the gas analytes in real-world applications.
Chemicals and instruments
IL 1-Butyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)-imide ([Bmpy][NTf2], Io-LiTec Inc. 99%) was used in all electrochemical measurements. Both pyrrolidinium-based cation and NTf2 anion of [Bmpy][NTf2] have relatively high electrochemical stability [4, 21] and were also used in our early IL-EG oxygen sensor development by Wang et al. . Fifty μL of the IL was added to the electrochemical cell. The electrochemical cell structure is shown in Fig. S1 in the Electronic Supplementary Material (ESM). Based on the dimensions of the electrochemical cell, the IL thickness on the working electrode was ~637 μm. The electrochemical cell was purged with continuous nitrogen (PRAXAIR compressed nitrogen) via Tygon PVC gas tubing (ϕ = 1 mm) for a minimum of 12 h until no visible infrared peak from water was observed by FTIR transmission mode . All cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and chronoamperometry measurements were performed using AMETEK VersaSTAT MC 4-channel electrochemical workstation.
Our experimental set-up and protocol are designed to allow for the investigation of the signal drift source from (electro)-chemical reactions at the electrolyte/electrode interface rather than environmental variables such as humidity and temperature. All measurements in this work were performed in a lab condition with a constant temperature (25 °C) and humidity (RH=30%). The analyte oxygen gas and the background gas are dry. The outlet of the gas flow system was connected to a vacuum hood to avoid the buildup of gas in the testing system. The gas flow was controlled using MKS (MKS Instruments, Inc.) type 247 4-channel readout (bundled with Mass-Flo Controller). Two mass-flow controllers were used to adjust the volume ratio to reach the target gas concentration. One of the mass flow controllers was used to control the background gas (nitrogen) flow and the second was used to control the analyte gas (oxygen) flow. Oxygen UHP cylinder (Specialty Gases of America, 99.993%) was used as the source of oxygen. The gases were purged into the electrochemical sensor directly via a GPM.
Results and discussion
The principle of amperometric sensing oxygen in the IL
We are aware that both temperature and humidity changes will result in signal drifts. The variation of temperature will affect the solubility of the gas analyte in the ILs. This can lead to signal drift as the sensing signal correlates the concentration of the target gas in the IL in our IL-EG sensor. The trace water in the IL electrolyte can be a proton source. The presence of trace water can lead to signal drift since it can change the sensing reactions. As detailed in our Experimental section, all experiments were done at lab condition with constant temperature. IL [Bmpy][NTf2] is hydrophobic with little trace water and gases (N2 and O2) used are all dry. This allows us to systematically study the effects of the interfacial reactions and processes on the analytical performance of the amperometric sensor. If the products of sensing reaction are sensor poisons (e.g., change the IL/electrode microenvironment and/or electrode poison), the sensor lifetime or response characteristics will be severely limited and will exhibit a signal drift with time. Our early work shows that superoxide generated from sensing reactions at the electrode interface affects the signal stability for the continuous amperometric sensor . As the superoxide radical O2∙- is negatively charged, it could interact with the cations of the IL (i.e., [Bmpy]+ in this case) and form ion-pairs . Superoxide radical O2∙- and/or the ion-pair complex [Bmpy]+[O2∙-] could adsorb and/or accumulate at the electrode interface, which would hinder the continuous sensing of oxygen . In the following section, we systematically studied the sensing reactions and how they impact the signal stability. The mechanisms of the sensing signal drift allow for the testing of several strategies to calibrate and improve the sensing accuracy and precision using the IL amperometric oxygen sensor as a model system.
Sensing signal drift causes
Following our early IL-EG oxygen sensor method , the amperometric oxygen sensor was set at –1.2 V, in which oxygen was reduced to the superoxide radical that resulted in a reductive current proportional to the oxygen concentration. In a nonaqueous electrolyte, a quasi-reference electrode is commonly used as the reference electrode. If the absolute potential of the quasi-reference electrode is not stable, the sensor signal will drift since the stepped potential will not be the same. We studied the potential stability of the quasi-reference electrode by using the Fc+/Fc redox probe. As shown in ESM Fig. S3, the quasi-reference electrode is stable within our measurement time period. The uncertainty of the concentration of gas samples could also prompt the signal drift in addition to the sensing reactions. A gas sampling system using mass flow controllers was employed in our study to continuously and reproducibly provide controlled known concentrations of the gas sample. A systematic investigation of gas sampling flow rates (ESM Fig. S4) suggested the optimum flow rate was 100 sccm, which minimized IL/electrode interface perturbation while providing quicker mass transport of the gas molecules from the gas phase to the sensing electrode interface. Thus, 100 sccm was the gas sampling flow rate setup in the rest of this work.
Sensing signal drift cause: oxygen concentration change
Therein, in a separate measurement (Fig. 1b), a smaller oxygen concentration variation (±1%) was conducted when the sensing signal was stabilized at constant 5% oxygen concentration. Results indicated that the sensing signal was able to return to the value of 5% oxygen baseline, either by increasing [O2%] from 4% to 5% or decreasing [O2%] from 6% to 5%, which supported our hypothesis that smaller anlayte concentration changes exhibit better sensing signal stability. In this measurement, the sensor was exposed to a step-wise oxygen concentration change of ±1% and then returned back to the baseline oxygen concentration of 5%. This experiment mimics the real-world dynamic oxygen concentration change. The sensing responses of ±1% [O2%] variation from a-b, b-a’, a’-c, and c-a’ were 7.64 μA, 7.92 μA, 8.23 μA, and 8.24 μA, respectively. The RSD value was ±0.34%.
Compared with a previous measurement presented in Fig. 1a, after the removal of oxygen for 900 s (i.e., time scale 1800~2700 s), the new baseline current was –29.05 μA. This value was closer to the corresponding original baseline current than the measurement in Fig. 1a, implying a better restoration of the IL/electrode interface double layer initial condition. In both measurements, we picked the periods when oxygen was present (i.e., time scale 350–1100 s of the measurement in Fig. 1a, and time scale 600–1800 s of the measurement in Fig. 2a), integrated the total charge values, and found that IL/electrode interface double layer could better return to its initial condition in meausurements where less amount of O2∙- species was produced. According to Faraday’s Law (Q = nFN, in which Q is the total charge in the unit of C, n is the number of moles of the analyte, F is the Faraday’s constant, and N is the amount of electron transferred in the redox reaction), the total charge directly reflects the amount of analyte reacted. The total charge of both measurements were 0.1178 C (measurement in Fig. 1a) and 0.1056 C (measurement in Fig. 2a). This result further validated our hypothesis that the measurement in Fig. 2a, having smaller total charge and less amount of O2∙- species, exhibited less baseline signal drift.
In summary, better sensing signal stability could be approached with smaller [O2%] change, which was also validated by the measurement presented in Fig. 2b. The measurement started recording after the oxygen concentration was stabilized at 15.75%. The oxygen concentration was first increased stepwise to 19.95%, then decreased stepwise back to 15.75%, completing one measurement cycle. This cycle was repeated four times continuously. The oxygen concentration change was 1.05% at each step. The plot of sensing signal as the function of oxygen concentration (ESM Fig. S7) and the summary of the corresponding sensing signal sensitivity and the linearity coefficient (ESM Table S1) indicated that the sensing signals were quite repeatable and there was nearly no sensing signal sensitivity loss over the course of the entire measurement. It is noteworthy that the sensing sensitivy value when [O2%] increased (1.778 ± 0.045 μA/%) was slightly less than that of when [O2%] decreased (1.800 ± 0.034 μA/%), due to the slow diffusion of the oxygen molecules from the bulk electrolyte to the IL/electrode interface. Nevertheless, in this measurement of small [O2%] change, the slow mass transport effect of both the reactant and product was not significantly observed.
Sensing signal drift cause: electrode reactivity
Although small [O2%] changes influence the sensing signal stability slightly, the increased trend of the sensor functioning time to maintain stable sensing signals in Fig. 1b drew the reactivity of the working electrode to our attention. In our study, platinum gauze was used as the working electrode as a platinum electrode generally exhibits excellent stability under polarized potentials that may be corrosive to other metal electrodes. Platinum metals are also excellent catalysts for many analyte reactions. Our group previously reported the formation of the Au-O2-∙ adsorbate in the oxygen reduction process on a gold surface in [Bmpy][NTf2] . Similar interactions may occur on a platinum electrode as it exhibits similar physicochemical properties to gold [e.g., platinum has an electron affinity value of 205 kJ/mol, which is close to that of gold (223 kJ/mol)]. In the IL, the negatively charged superoxide radical O2∙- could have interactions with the platinum electrode and the cation of the IL, [Bmpy]+ (Eq. 3) when a cathodic potential is applied . These interactions not only influence the ion arrangement in the inner and outer Helmholtz planes near the electrode surface but also impair the reactivity of the platinum surface, as is illustrated in Scheme 1. We hypothesized that these interface interactions are one of the causes of the sensing signal drift of the continuous oxygen sensor.
Amperometric methods for signal drift minimization
Above discussions show that the drift of an IL-EG oxygen sensor predominately results from the electrode surface reactivity and the oxygen concentration change relating to the slow mass transport of both the reactant and the product, which is attributable to the presence of the O2∙- species. Since O2/O2∙- is a redox couple in an aprotic IL (see the CV in ESM Fig. S2), applying a double potential step method can be an effective way to remove the O2∙- species via oxidization to oxygen, which can maintain the stability of IL/electrode interface double layer condition. In this work, we programmed the double potential step amperometric measurement to alternate between 0 V and –1.2 V. The 0 V potential is sufficient to oxidize the O2∙- species, as the oxidation peak of O2∙- occurs at –0.9 V (Fig. S2). Moreover, as Jewell reported, the alternating reduction and oxidation of a species at the platinum surface could function to enhance platinum reactivity . Thus, the double potential step method should be effective to not only remove the O2∙- species but to also maintain the electrode reactivity for the purpose of continuous sensing.
Signal drift calibration with mathematic tools
Figure 4 shows an example of how both the differential and relative signal manipulation methods were applied to calibrate the amperometric sensing signal when the sensor was exposed to alternating 0% and 20% oxygen concentrations (see the test parameter profile in Fig. 4d). After calibration, the sensing drift was reduced from ±3.05% to ±0.19%. The detailed calibration procedure was as follows: the amperometric curve was corrected according to a baseline correction line (marked as the purple dash line in Fig. 4b) in the calibration equation of y = 5.14e-4 x -11.67. According to Wenzel et al. , applying a difference measurement between the steady-state signal and the conditioning signal can minimize the influence of baseline drift in analyte quantification. Thus, the baseline calibration curve was picked by aligning the mean current value of the last 50 data points in the conditioning steps in segments 1 and 2 (marked by the star symbols in Fig. 4b). After the baseline subtraction, the sensing signal was further manipulated by means of the relative signal manipulation (Eq. 5). The final outcome of this offline calibration is presented in Fig. 4c.
Viewing the importance of sensing signal drift compensation to enhance the reliability of the IL-EG sensors, we use an established oxygen sensor as a model system to investigate the fundamental chemical causes of the sensing signal drift. Analyte concentration variations and the electrode surface reactivity were studied to understand the influences toward sensor signal drift. Analyte concentration variation influences the sensing signal baseline as it modifies the IL/electrode interface double layer condition, whereas electrode surface reactivity causes the decrease of the sensing sensitivity.
Aiming to address the sensor signal drift, we reported a double potential step chronoamperometric method and demonstrated its effectiveness in mitigating the sensor signal drift while extending the sensor operation lifetime. In additional, two mathematical models (differential signal manipulation and relative signal manipulation) were employed to calibrate both the baseline drift and the sensor sensitivity change for continuous constant potential amperometric sensing of oxygen.
This is the first systematic study in identifying the chemical sensing drift issue in IL-EG sensors. Although it is impossible to eliminate the sensor signal drift, we are setting some perspective starting points to address, minimize, and calibrate the sensing drift so that both the sensing accuracy/precision and sensitivity can be improved for real-world applications, which demand the reliable continuous sensing and monitoring of important gaseous analytes with extended life-time. It is envisaged that these studies form the foundation toward improving the reliability of the IL-based electrochemical gas sensors by establishing the calibration methods to compensate for both short-term (hours) and long-term (days, months) signal drift to increase the reliability of the IL-EG sensor performance for continuously monitoring many gas analytes in real-world conditions.
X. Zeng acknowledges grant support from the National Institute of Environmental Health (R01ES022302) and the Alpha Foundation AFC518-2 for this research. The authors thank Dr. Xiaojun Liu and Dr. Jessica Koppen for helpful comments and proofreading.
Compliance with Ethical Standards
Conflict of interest
The authors declare no conflict of interest of this work.
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