An investigation of CO2 splitting using nanosecond pulsed corona discharge: effect of argon addition on CO2 conversion and energy efficiency

Plasma Sources Science and Technology PAPER • OPEN ACCESS An investigation of CO2 splitting using nanosecond pulsed corona discharge: effect of argon addition on CO2 conversion and energy efficiency To cite this article: M S Moss et al 2017 Plasma Sources Sci. Technol. 26 035009 View the article online for updates and enhancements. You may also like The catalytic role of tungsten electrode material in the plasmachemical activity of a pulsed corona discharge in water Petr Lukes, Martin Clupek, Vaclav Babicky et al. - Experimental study on toluene removal by a two-stage plasma-biofilter system Hao HUANG, , Lihao HE et al. - Ultraviolet radiation from the pulsed corona discharge in water Petr Lukes, Martin Clupek, Vaclav Babicky et al. - This content was downloaded from IP address 150.214.182.234 on 15/01/2024 at 20:07 An investigation of CO 2 splitting using nanosecond pulsed corona discharge: effect of argon addition on CO 2 conversion and energy efficiency M S Moss 1 , K Yanallah 1 , R W K Allen 1 and F Pontiga 2 1 Department of Chemical and Biological Engineering, University of Sheffield, United Kingdom 2 Departamento de Física Aplicada II, Universidad de Sevilla, Spain E-mail: MMoss1@sheffield.ac.uk Received 20 June 2016, revised 20 December 2016 Accepted for publication 20 January 2017 Published 22 February 2017 Abstract The plasma chemical splitting of carbon dioxide (CO 2 )to produce carbon monoxide (CO)in a pulsed corona discharge was investigated from both an experimental and a numerical standpoint. High voltage nanosecond pulses were applied to a stream of pure CO 2 and its mixture with argon, and the gaseous products were identified using Fourier transform infrared spectroscopy. Due to the shape of pulses, the process of CO 2 splitting was found to proceed in two phases. The first phase is dominated by ionization, which generates a high electron density. Then, during the second phase, direct electron impact dissociation of CO 2 contributes to a large portion of CO production. Conversion and energy efficiency were calculated for the tested conditions. The conversions achieved are comparable to those obtained using other high pressure non-thermal discharges, such as dielectric barrier discharge. However, the energy efficiencies were considerably higher, which are favorable to industrial applications that require atmospheric conditions and elevated gas flow rates. Keywords: CO 2 splitting, corona discharge, nanosecond pulses (Some figures may appear in colour only in the online journal) 1. Introduction Carbon dioxide mitigation technologies are at the forefront of most governments’minds in order to limit the global temperature rise to 2 °C above pre-industrial levels [1]. In the recent past, carbon dioxide has been seen as an unwanted waste product with an associated cost and energy penalty to deal with. However, newer technologies are emerging which envision the ample quantity of CO 2 available from waste gas streams as a feedstock for the synthesis of green chemicals. Unfortunately, CO 2 is a highly stable molecule and to achieve its thermal reduction to carbon monoxide requires temperatures in excess of 3000 K. Non-thermal plasmas can be beneficial to solve this problem since only the electron temperature in the gas is elevated. Furthermore, it is known that cumulative vibrational excitations of the CO 2 molecule can result in a highly energy efficient stepwise dissociation, as explained by Fridman [2]. Therefore, carbon dioxide splitting using non-thermal plasmas is nowadays being considered as a possible pathway to produce synthetic fuels via a CO intermediate. Many different approaches to non-thermal plasma splitting of CO 2 have been followed, but most research has been focused on dielectric barrier discharges (DBD), microwave plasmas and gliding arc discharges [2]. In this work, pulsed corona discharge using a wire-to-cylinder reactor will be considered. The design of the reactor is simple and it operates at atmospheric pressure, making it suitable for upscaling. Indeed, corona discharges have already demonstrated Plasma Sources Science and Technology Plasma Sources Sci. Technol. 26 (2017)035009 (18pp)https://doi.org/10.1088/1361-6595/aa5b1d Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s)and the title of the work, journal citation and DOI. 0963-0252/17/035009+18$33.00 © 2017 IOP Publishing Ltd1 their applicability on an industrial level in electrostatic precipitators for particulate removal in waste gas streams. The majority of past works on pulsed corona discharge have been focused on gas cleaning technologies for NO x , SO x , VOCs and H 2 S removal. These studies have shown that a significant percentage of the undesired molecules can be destroyed with a high efficiency. For example, in the work of Yamamoto et al [3], wire-to-cylinder microsecond pulsed corona discharge was applied for toluene, methylene chloride and CFC-113 removal with excellent results. Helfritch [4] employed a similar approach for H 2 S removal, again with a great efficiency. The use of pulsed corona to reduce NO x and SO 2 emissions in flue gases from a coal thermal plant has also tested by Dinelli et al [5]. The application of corona discharge for the decomposition of CO 2 has been less investigated, and even less the utilization of pulsed corona discharge. This latter technique wasappliedbyMaliket al [6]to decompose a mixture of CO 2 and methane (CH 4 )(1:1 ratio)using a wire-to-cylinder reactor. They applied 4 μs width pulses with maximum amplitude of 45 kV, and they achieved decompositions of 38% for CO 2 and 46% for CH 4 ,ataflow rate of 10 cm 3 min −1 . However, under these conditions, the energy efficiency was low (2.5%). The authors also investigated the decomposition of pure CO 2 with some success, obtaining a maximum reduction of 16.8%. Similarly, Bak et al [7] appliednanosecondpulsedhighvoltagebetweentheflat ends of two cylindrical electrodes separated by a short distance. The experiments were carried out in pure CO 2 under pressurized conditions (2.4 atm–5.1 atm)and they achieved the maximum conversion rate of CO 2 into CO at the highest tested pressure, with a value of 7.3%, while the best energy efficiency (11.5%)was obtained at the lowest pressure. The authors explained this result through the reduced electric field, being lower at higher pressures. Moreover, they performed an energy balance of reactions in the CO 2 plasma and concluded that the dominant dissociation pathway goes through electronic excitation of CO 2 (10.5 eV)followed by autodissociation into CO and O. Using DC wire-plate corona discharge, Xu et al [8] reported a maximum CO 2 decomposition of 10.91% for a gas flow rate of 30 cm 3 min −1 , although the energy efficiency was, at most, about 6.73%. The authors concluded that higher flow rates and lower discharge powers increase the energy efficiency at the cost of a lower conversion. Similarly, Mikoviny et al [9]investigated CO 2 reduction in pure CO 2 and in its mixture with O 2 with a flow rate of 100 cm 3 min −1 . They used a wire-to-cylinder reactor operated at negative polarity, in the range 4.5–6.5 kV. The conversion of CO 2 to CO was very small, but they observed an increase of CO production by rising the percentage of oxygen in the gas mixture. Horváth et al [10]also investigated the application of positive and negative DC corona to pure CO 2 using a wireto-cylinder reactor, but they carried out the experiment in a static regime, that is, under stopped-flow conditions. Their results showed that negative DC corona yield a better conversion to CO (over10%at7.5kV). The decomposition of CO 2 in mixtures with N 2 under flow-stopped conditions was studied by Pontiga et al [11]. They used negative wireto-cylinder corona discharge, and they also simulated the problem using a chemical model of 37 chemical species. The amount of CO formed during the operation of the reactor was of the order of a few percent, while O 3 formation was in the range of fractions of one percent. The authors observed that the formation of NO x inhibits the generation of O 3 and prevent the growth of CO over time. In a later work [12], they extended that investigation to positive corona using the same reactor. They found that in CO 2 -rich gas mixtures (>90%), the corona discharge became unstable and extinguished after running the discharge for some time. Then, voltage needed to be increased to stabilize the discharge. Moreover, they found that the electrical discharge exhibited two current regimes, depending on the ratio CO 2 :N 2 .Ingas mixtures with a high percentage of CO 2 (60%–80%),the corona current level was high and NO x , and particularly NO, was readily produced. In contrast, for low percentages of CO 2 (20 to 40%), the corona current level was much lower, and O 3 and N 2 O was easily detected. Numerical modeling is of great importance to increase the understanding of processes which take place inside plasmas, and it constitutes a valuable tool to determine the fundamental mechanisms leading to CO 2 splitting. Models can also provide a description of quantities which are difficult, if not impossible, to measure in experiments, such as time and spatial dependence of reaction rates. However, deciding which reactions must be included in the numerical simulation is a difficult task. In early modeling of CO 2 lasers, where the laser medium usually consists of a flowing CO 2 –N 2 –He mixture, hundreds of reactions have been proposed to participate in the plasma chemistry [13,14]. Therefore, the selection of reactions that are relevant to the target system is crucial to yield accurate predictions of experimental measurements. Of course, there is always a trade-off between accuracy and time efficiency in numerical simulations, since including more reactions and species increases the computational time. One of the most comprehensive comparative studies between plasma modeling and experiments in CO 2 has been undertaken by the PLASMANT research group, mainly for DBD [15,16]. They have carried out numerous 0D kinetic studies using the GlobalKin code of Kushner and co-workers, both for studying CO 2 reduction in pure CO 2 and its admixtures with argon/helium [17], and for dry-reforming of methane [18]. Particularly notable are their investigations of the role of vibrational states on CO 2 splitting [19,20]. They concluded that this pathway constitutes the dominant mechanism for CO 2 dissociation in microwave discharges, while it is of secondary importance in DBD. Focusing on pure CO 2 , their modeling gave excellent correlation with experimental results for specific energy inputs (SEI)below 100 J cm −3 . The maximum conversion achieved experimentally was 35%, with an energy efficiency of 2% [15]. However, energy efficiencies up to 8% were obtained at the expense of reducing CO 2 2 Plasma Sources Sci. Technol. 26 (2017)035009 M S Moss et al conversion to a few percent. More recently, Snoeckx et al [21]have carried out numerical modeling and experiments in CO 2 /N 2 mixtures. Their motivation was the DBD treatment of impure CO 2 streams, with N 2 as the main industrial impurity. They found that CO 2 conversion and energy efficiency increases more or less exponentially with rising N 2 .In gas mixtures with a large nitrogen fraction (∼90%), the reported CO 2 conversion was about 18%, with an energy efficiency of 20%, approximately. However, lowering the nitrogen content quickly reduces conversion and efficiency. Regarding corona discharge, Yanallah et al [22,23]have simulated positive and negative DC corona discharge in carbon dioxide for a wire-to-cylinder electrode configuration. In these studies, the experimental voltage and current were used as inputs for the numerical simulation. However, in the present work, only the experimental voltage is required. They computed the distribution of species using a 2D model, and compared their findings with the experimental concentrations of CO and O 3 for gas flow rates of 20 and 100 cm 3 min −1 and different applied voltages. The production of CO was below 1%, and the agreement between modeling and experiments was excellent. In this work, an experimental and modeling study on CO 2 splitting using pulsed corona discharge is presented, both in pure CO 2 and its mixtures with Ar. The main aim of this research is twofold: (1)to maximize the conversion of CO 2 into CO and (2)to minimize the energy required to achieve this transformation. The experiments have been carried out for different gas flow rates and gas compositions, and the results are analyzed and compared with the predictions from the numerical simulation. The computational model is a combination of a one-dimensional and a zero-dimensional model, so that the complex plasma chemistry of CO 2 can be successfully dealt, including the vibrational levels of the CO 2 molecule. The 1D model treats a single pulsed discharge, and their results are used in the 0D model to simulate the plasma chemistry of corona discharge over long times. From the results of this combined technique, the mechanism of CO 2 splitting in a pulsed corona discharge can be hypothesized and compared to those of other non-thermal plasmas. 2. Description of the work 2.1. Experimental setup Figure 1shows a schematic diagram of the experimental equipment. All experiments were carried out at atmospheric pressure and ambient temperature. The wire-to-cylinder corona discharge reactor was formed by a stainless steel cylinder as the outer electrode, with radius R=17 mm, and a thin tungsten wire as the inner electrode, with radius r 0 =125 μm. The length of the reactor was 30 cm. A high voltage pulse generator (NPG18-3500N Megaimpulse Ltd [24])was used to energize the inner wire. The connection between the pulse generator and the corona wire was made by means of a 75 Ωcoaxial cable. The voltage signal applied to the wire was measured using a high voltage probe (Tektronix P6015A)connected to the live electrode. Regarding the corona current, a wide band current transformer (Pearson 6595)was used. The current transformer was fitted around the cable that connects the cylinder to ground. The voltage signals from both the high voltage probe and the current transformer Figure 1. Schematic of experimental system. Figure 2. Oscillogram of the voltage applied to the reactor for pure CO 2 . 3 Plasma Sources Sci. Technol. 26 (2017)035009 M S Moss et al were recorded in a high resolution oscilloscope (6404c Picotech). In order to minimize the time delay between the two signals, coaxial cables of similar lengths were used for the high voltage probe and the current transformer. A typical oscillogram of the voltage signal applied to the reactor, as measured with the high voltage probe, is shown in figure 2. It consists of a train of pulses, in which a first pulse, of high amplitude and short rise time, is followed by a series of pulses of smaller amplitude. Hereinafter, the term ‘pulse’will be used to denote the entire voltage signal, while the term ‘sub-pulse’will be used to refer to each distinct pulse within the voltage signal. The characteristic width of sub-pulses is about 40 ns and the total duration of a complete pulse is of about one microsecond. The short duration of pulses remove the need for a dielectric layer, prevent gas heating (thus increasing the efficiency of CO 2 splitting)and reduce the possibility of plasma arc development. The repetition frequency of pulses could be adjusted in the range 50–1700 Hz. As shown in figure 2, the applied peak voltage across the electrodes had a potential up to 17 kV. However, the amplitude and the voltage waveform are strongly affected by the impedance matching between the reactor and the power supply. During experiments, a mixture of pure CO 2 (99.999%) and Ar (99.9%)was fed into the reactor in the axial direction. A mixing chamber was installed before the reactor entrance, in order to ensure a homogeneous gas mixing. The gas flow rates were controlled by means of mass flow controllers (Bronkhorst), and the total gas flow rate was varied in the range 100–800 cm 3 min −1 . After passing through the discharge reactor, gaseous products were analyzed by means of a Fourier transform infrared spectrometer (FTIR)(Varian 660IR Agilent)ex situ. A typical spectrum, corrected with the background of the initial gas mixture, is shown in figure 3. The positive values of absorbance in the wavelength range 2025–2225 cm −1 corresponds to the formation of CO. The presence of ozone is also observed around 1054 cm −1 .In contrast, the negative values of the absorbance indicate the decomposition of CO 2 . 2.2. Computational model Atmospheric pressure corona discharges can be modeled using the so-called fluid approximation, which consists in solving continuity equations for every species produced in the electrical discharge, coupled with Poisson’s equation [25–27]. However, the numerical simulation of pulsed discharges of nanosecond duration is a complex task, since the set of differential equations becomes a stiff system. This is due to the formation of sharp gradients of the species densities and of the electric field during the development of pulses. Additionally, the time required to carry out the simulation can be very large, and it increases further upon adding complexity to the model through the inclusion of more chemical species. The strategy adopted in this work has been to use a combination of two solvers: COMSOL Multiphysics [28]and ZDPlaskin [29]. The DC plasma module within COMSOL Figure 3. Sample spectrum after background correction showing the presence of CO in the exhausting gas. 4 Plasma Sources Sci. Technol. 26 (2017)035009 M S Moss et al has been first used to simulate the electrical discharge in 1D for the duration of a single pulse. In this part, the continuity and Poisson’s equations have been solved in conjunction with Boltzmann equation. As a result, the electron density and reaction rate constants that involve electrons (e.g. dissociation, excitation, ionization and elastic collisions with neutral molecules)have been evaluated. These magnitudes are then averaged over radial distance and transferred to ZDPlaskin, where the 0D modeling of multi-pulses will be carried out. It must be emphasized that the reaction rate constants that are used in the 0D model are not obtained from the averaged electron energy or the averaged electric field, but by directly averaging the reaction rate constants already evaluated in 1D model. The first procedure would produce less accurate results, as would also occur if a simple estimation of the electric field were used to obtain the reaction rate constants, which is very frequent in 0D simulations [15]. Furthermore, the accuracy of the method followed in this paper has been tested by solving the 0D model in many different points along the radial direction. The species densities so obtained were then averaged over the radial coordinate and compared with those computed using the spatially averaged reaction rate constants. A satisfactory agreement was found between the two approaches. The need for splitting the modeling in two parts is imposed by the long computational time that would otherwise be required if the simulation were entirely done using the 1D model. Therefore, efforts have directed towards simplifying the calculation procedure but maintaining the precision of the modeling. The approach adopted in the present work provides more insight into the development of pulses and a more detailed picture of the temporal evolution of species during the process of CO 2 splitting. 2.2.1. The 1D fluid model. As revealed through experiments [7,30,31], the transition from corona to spark discharge is accompanied by instabilities in the electric current and it is dependent on the applied voltage, frequency, wire surface state, reactor geometry and gas mixture. For example, increasing the percentage of Argon favors the development of a spark. In our experiments, the electrical discharge was operated within the corona regime, and it appeared as a homogeneous glow that filled the entire reactor volume. Therefore, the electrical discharge will be modeled as a homogeneous discharge along the axial and azimuthal directions. With these assumptions, the problem becomes one-dimensional and the computational domain extends from the wire surface up to the surrounding cylinder along the radial coordinate. The axial dependence can be disregarded owing to the short duration of the pulse (∼1μs)as compared to the residence time of the gas inside the reactor. The electrical discharge can then be successfully described by a set of continuity equations, one for each species taking part in the discharge, coupled to Gauss’law for the electric field and to the electron energy equation. In polar coordinates, these equations can be written as: ⎡ ⎣ ⎢⎤ ⎦ ⎥ m ¶ ¶+¶ ¶-¶ ¶= N trr re eNE rD N rS 1,1 ii iii ii 0 ∣∣ () ⎡ ⎣ ⎢⎤ ⎦ ⎥ ¶ ¶-¶ ¶ ¶ ¶= N trr rD N rS 1,2 j j j j() ⎡ ⎣ ⎢⎤ ⎦ ⎥ ⎡ ⎣ ⎢⎤ ⎦ ⎥ m m ¶ ¶+¶ ¶-- ¶ ¶ +- -¶ ¶= e eee e e N trr rNE rDN r ENED N rS 1 ,3 eee e() å e = rr rE e N 1d d 1,4 i ii 0 () () f =-Er d d,5() where subscripts i,j,eand εrefer, respectively, to the ith charged species (electrons included), to the jth neutral species, to electrons (specifically), and to the electron energy per unit of charge; Ndenote density, Dis the diffusion coefficient, S represents the gain/loss term, μis the mobility, e i is the electrical charge of the ith charged species, e 0 is the elementary charge, Eis the electric field, fis the electric potential and ε 0 is the dielectric constant of the gas. The gain/loss rate of the nth species (charged or neutral) takes the form å =¼SkNN,6 n j jlm () where ¼ N N,, lm are the number densities of species that participate as reactants in the jth reaction, with reaction rate constant k j . The summation extends over all reactions involving the nth species, but the contribution of losses has negative sign. Reactions and species selected for the 1D model are highlighted in boldface in table A1 (see appendix). More details about the species will be given in the next section (0D model). Similarly, the gain/loss of electron energy density can be expressed as åe=D ¼ e SkNN,7 j jjem () where N e is the electron number density and Δε j is the energy gain/loss in the jth reaction. The relaxation of vibrational states may produce an augmentation of the gas temperature. However, as it will be shown in section 3.1, the accumulation of vibrational states in a pulsed corona discharge is relatively low. Therefore, in this model, the temperature of the gas is assumed to be constant and equal to the ambient temperature. The Scharfetter–Gummel upwind scheme of COMSOL has been adopted to integrate the set of continuity equations. This scheme has been used previously by Boeuf [27], Kulikovsky [32]and other authors, and it has demonstrated to be stable and adequate for the simulation of electrical discharges. 5 Plasma Sources Sci. Technol. 26 (2017)035009 M S Moss et al Integration of (1)and (5)require appropriate boundary conditions. At both electrodes, charged carriers (electrons and ions)are lost due to random motion within a few mean free paths from the walls, and electrons are gained at the cathode through secondary electron emission. This last process consists in the generation of electrons due to the bombardment of the cathode by positive ions, and it is essential to sustain the discharge. The boundary conditions for the electron density and the electron energy density are implemented as follows, ågGG⋅= - ⋅ = =vN rr rRnn,at and , 8 eee p pp 1 2,th 0 () åegGG⋅= - ⋅ = = ee vN rr rRnn,at and , 9 e p pp 5 6,th 0 () where nis the normal unit vector pointing towards the wall, mG=- - NDNE eeeee is the flux of electrons, mG=- -  eeee e NDNEis the flux of electron energy, mG=-NDNE pppp p is the flux of the pth positive ions, εis the mean energy of secondary electrons, γ p is the secondary emission coefficient, and v e,th is the thermal velocity of electrons, which is a function of the electron energy and, therefore, of the electric field. Secondary electron emission is assumed to take place only at the wire when it is acting as the cathode, with a coefficient value of 0.01. Otherwise it is set γ p =0. At the cylinder, owing to its large curvature radius, secondary electron emission is ignored, even when its polarity is negative with respect to the wire. Regarding positive and negative ions, their boundary conditions at the electrodes are expressed as G⋅= = =vN rr rRn,at and , 10 iii 1 2,th 0 () where mG=-ee N D NE ii iii i 0 () is the flux of the ith ion, and v i,th its thermal velocity. The electrodes may constitute a source of neutral particles due to the neutralization of ions (e.g., + C O2is converted into CO 2 on the cathode). Therefore, a balance equation between the fluxes of the ith ion and the corresponding jth neutral species must be written at the electrode in such a case, GG⋅=-⋅ = =rr rRnn,at or . 11 ji 0() Otherwise a null flux of the neutral species is set at the wall G⋅= = =rr rRn0, at or . 12 j0() Finally, for the electrical potential, boundary conditions are simply expressed as f=rVt,13 0 () () ( ) f=R0, 14() ( ) where V(t)is the impulse voltage applied to the corona wire, which is taken from the experimental measurements (see figure 2). As for the initial conditions, the number densities of the CO 2 and Ar in the gas mixture were calculated according to the ideal gas law at atmospheric pressure (760 Torr)and ambient temperature (298 K). The densities of the other heavy species depend on the past history of the electrical discharge, since they are built with the occurrence of every single past discharge. However, for the 1D modeling of the pulse, these initial densities will be taken here as zero. This approximation is used to avoid a direct coupling between the 1D and 0D models, and to reduce the computational time of the simulation. Moreover, since electrons are mainly produced by direct ionization of the background CO 2 and Ar in the gas mixture, this simplification should have a negligible influence on the computed values of the electron number density and the electron energy density. Of course, the effect of accumulation of species with each pulse will be considered in the 0D modeling. Regarding the initial electron density, a small distribution of seed of electrons (10 6 cm −3 )with a Gaussian profile is introduced near the wire electrode. This initial electron density has the purpose of triggering the electric corona discharge pulse. Figure 4shows a comparison between the current intensity predicted by the 1D modeling and that measured during the experiments. Clearly, the agreement between simulation and experiment is quite satisfactory, which confirms that the hypotheses assumed in the 1D modeling are justified. Moreover, since the current intensity is linked to the drift of electrons and ions, this agreement also supports the correctness of the electron and energy densities predicted by the numerical simulation. 2.2.2. The 0D fluid model. After the completion of the 1D modeling, the electron density is passed to the 0D model, along with an accurate estimation of the reaction rate coefficients of reactions involving electrons. All plasma parameters are assumed to be spatially homogeneous in the 0D modeling. Therefore, the plasma reactor is considered as a batch reactor, which incorporates not only the reactions Figure 4. Temporal evolution of current intensity for the duration of a pulse in pure CO 2 . 6 Plasma Sources Sci. Technol. 26 (2017)035009 M S Moss et al already used in the 1D model, but also the rest of relevant reactions, i.e., ion–ion, molecule–ion and molecul–molecule reactions. The reaction rate constants of these additional reactions have been adopted from the literature and their values are listed in the appendix (see tables A2,A3 and A4). The temporal evolution of the number densities of plasma species generated by the pulsed corona discharge is obtained from the resolution of the following set of coupled ordinary differential equations, ¶ ¶= N tS15 j j() where integration is executed from t=0 up to the residence time of the gas within the reactor. For this purpose, the ZDPlasKin code developed by Pancheshnyi et al [29]has been used. The list of species considered in the 0D model is shown in table 1, and it includes, besides electrons, 8 neutral species, 5 positive ions, 4 negative ions and 5 excited species. The choice for these species was made after numerous tests, so as to select the species deemed to be most relevant to CO 2 splitting, both with and without the presence of Ar. Following the approach of Aerts et al [19],the vibrational levels of CO 2 have been grouped in four effective levels (see table 2)in order to limit the number of species and chemical reactions. These levels are denoted as CO 2 (v1),CO 2 (v2),CO 2 (v3)and CO 2 (v4).CO 2 (v1) represents the first bending mode (010),CO 2 (v2)is the sum of the first symmetric stretch (100)and the second bending mode (020),andCO 2 (v3)is the first asymmetric stretch mode (001). Finally, the level CO 2 (v4)represents the sum of higher bending modes, like (030)and (040),with other modes of similar energies, like (110)and (120), respectively. Also, the contribution of other higher energy modesisgatheredwithinCO 2 (v4). Vibrational states of CO and O 2 were neglected in this model, since their contribution to CO 2 splitting is minimal. Regarding excited electronic states of CO 2 , they were only taken into account in the 1D modeling. As set out in Morgan’s database [33]for electron collisions with argon, the excited electronic states of argon have been also grouped in a single species, Ar * . It has been assumed that the excited states of a given species exhibit the same chemistry as its ground state, except for the energy threshold of reactions, which will be lower in the case of excited species. Since the plasma kinetics of CO 2 is complicated and the aim of this work is on CO 2 splitting, the reaction scheme for Ar has been reduced to only five major processes (elastic, excitation, ionization, penning ionization of the excited states, and quenching of the excited states back to ground state). 3. Results and discussion The energy efficiency and the conversion factor are the two most important parameters to be calculated in CO 2 splitting studies, and they are used extensively to compare different types of discharges. The absolute CO 2 conversion is defined as the change in CO 2 concentration over the initial CO 2 concentration. This can be assumed to approximately equal to the conversion to CO (or CO yield)since the production of other carbon containing products is negligible. =-´ »´ X%CO CO CO 100 CO CO 100. 16 conv 2 in 2 out 2in out 2in () [] [] [] [] [] () The effective conversion of CO 2 is defined as the product of the absolute conversion and the relative content of CO 2 in the CO 2 /Ar gas mixture, =+´ »+´ XX%CO CO Ar 100 CO CO Ar 100. 17 eff conv 2in 2in out 2in () [] [] [] [] [] [] () The absolute energy efficiency ηexpresses the ratio of the dissociation enthalpy of CO 2 , + D= = - - HCO CO 1 2O , 2.9 eV molecule 283 kJ mol 18 R22 1 1() to the actual energy cost, E CO , to produce a single CO molecule in the reactor. Therefore, it can be written as h=D´ H E % 100. 19 R CO () ( ) The value of E CO can be obtained as the ratio of the energy E injected into the reactor during the residence time of the gas to the number of CO molecules, N CO , that have left the reactor during the same interval of time, that is, E CO =E/N CO . The energy injected into the reactor can be evaluated as ò == t EftE ft VtIttd, 20 ggpulse 0 () () ( ) where fis the frequency of pulses, t g the residence time of the gas and E pulse the energy delivered by a single pulse, which is equal to the integral over the duration of the pulse, τ, of the Table 1. Species included in the 0D model. Neutrals and radicals Ar, CO 2 , CO, C 2 O, C, O 3 ,O 2 ,O Positive ions Ar + ,+ C O, 2CO + ,+ O, 2O + Negative ions - C O3,- C O, 4 - O, 2O − Excited species Ar * ,CO 2 (v1),CO 2 (v2),CO 2 (v3),CO 2 (v4) Table 2. Notation of vibrational states used in the model and their effective energy level. Species notation States Energy (eV) CO 2 (000)0 CO 2 (v1)(010)0.083 CO 2 (v2)(020)+(100)0.167 CO 2 (v3)(001)0.291 CO 2 (v4)(030)+(110), (040)+(120),K >0.25 7 Plasma Sources Sci. Technol. 26 (2017)035009 M S Moss et al applied voltage V(t)times the current intensity I(t). Taking into account (16), the number of CO molecules that have exited the reactor during t g is given by =NX QtCO , 21 gCO conv 2 in [] () where Qis the gas flow rate. Equation (19)can be found in the literature in slightly different forms, particularly in terms of the SEI, which is defined as the ratio of the discharge power, W=E/t g , to the gas flow rate Q, that is, SEI=W/Q. Using the SEI, the energy cost can be expressed as E CO =SEI/(X conv [CO 2 ] in ). As it will be discussed later, the shape of the voltage waveform will have an important influence on the chemical kinetic pathway of CO 2 dissociation. The repetition frequency of pulses was fixed at 1.7 kHz, since higher frequencies introduces instabilities in the plasma discharge, thus reducing its homogeneity and increasing the gas temperature above 300 K. Under our experimental conditions, the reactor remained at nearly room temperature, and the energy deposited in the gas by the electrical discharge was changed by modifying the residence time of the gas, which is inversely proportional to the volumetric flowrate. The energy of a single pulse (as the one shown in figure 2)was estimated to be in the range of 1–2 mJ, depending on the gas mixture. In the next section, the numerical and experimental results of pulsed corona in pure CO 2 will be first presented. Then, the effect of the addition of Ar and, particularly, its effect on the conversion factor and energy efficiency will be considered. 3.1. Results for pure CO 2 Figure 5shows the behavior of neutral species in a pure CO 2 plasma as a function of the gas residence time. Besides carbon monoxide (CO), molecular oxygen (O 2 ),ozone(O 3 )and atomic oxygen (O)are the main products resulting from the decomposition of CO 2 . The typical number densities of these last species are, respectively, one, two and three orders of magnitude lower than that of carbon monoxide. The experimental measurements of CO density at the exit of the corona reactor are also shown in this figure by means of dots. The observed agreement between simulation and experiments confirms that the proposed model is sufficiently realistic to analyze the underlying chemical pathways of CO 2 splitting in nanosecond pulsed corona discharge operating in the glow regime. Differences can be attributed to the necessary simplifications introduced during the modeling and the uncertainty surrounding the reaction rate constants used in the simulation. The temporal evolution of CO, O, O 2 and O 3 and, in general, of all species, is characterized by two distinct temporal scales: a short one, corresponding to the duration of each single pulsed discharge (∼1μs), and longer one, corresponding to the interval between two pulses (∼f −1 = 588 μs). During each pulse, the reactions initiated by electrons play a predominant role, and the number densities of species undergo sudden variations. This fact can be clearly appreciated for atomic oxygen in the inset of figure 5, but it is also present for the other species although with different amplitude. In particular, the concentrations of atomic oxygen and ozone increase with the initiation of each discharge, the first one by the effect of electron impact dissociation of CO 2 (E1), and the second one by the subsequent recombination of O with O 2 (N1). Conversely, the concentration of molecular oxygen decreases due its dissociation by electron impact (E12), and the formation of ozone (N1). During the interval between two consecutive pulses, reactions between neutral Figure 5. Number densities of the most important species generated by the nanosecond pulsed corona discharge in pure CO 2 as a function of residence time. Solid lines: numerical simulation. Dots: experimental measurements. The inset shows a magnification of O density (linear scale)around t g ≈100 s. Figure 6. Temporal evolution of the spatially averaged CO density calculated from the 1D model during a single pulse (numerical simulation). 8 Plasma Sources Sci. Technol. 26 (2017)035009 M S Moss et al Table A2. Electron–ion recombination reactions. Number Reaction Rate constant Reference (R1)e − +CO 2 + →CO+O 6.5×10 −7 [15] (R2)e − +Ar + +Ar→Ar+Ar 1.0×10 −25 Est. from [28] Table A3. Neutral–neutral reactions. Number Reaction Rate constant Reference (N1)O+O 2 +M→O 3 +M 5.85×10 −34 (M=O 2 )[9] 1.81×10 −33 (M=CO 2 ) (N2)O+O+M→O 2 +M 1.04×10 −32 (M=CO 2 )[9] (N3)O+O 3 →O 2 +O 2 8.5×10 −15 [9] (N4)O 3 +M→O 2 +O+M 4.0×10 −15 (M=O 2 )[9] (N5)O+CO+M→CO 2 +M 1.1×10 −35 (M=CO 2 )[9] (N6)C+CO+M→C 2 O+M 6.3×10 −32 (M=CO 2 )[9] (N7)O+C 2 O→CO+CO 5.0×10 −11 [9] (N8)CO 2 +CO 2 →CO+O+CO 2 3.91×10 −10 exp(−49 430/T g )[20,37] (N9)CO 2 +O→CO+O 2 2.8×10 −11 exp(−26 500/T g )[20,37] (N10)CO 2 +C→CO+CO 1.0×10 −15 [20,37] (N11)O 2 +CO→CO 2 +O 4.2×10 −12 exp(−24 000/T g )[7,20] (N12)O 3 +CO→CO 2 +O 2 4.0×10 −25 [20,37] (N13)O 2 +C→CO+O 3.0×10 −11 [20] (N14)O 3 +M→O 2 +O+M 4.12×10 −10 exp(−11 430/T g )(M=Ar)[20,37] (N15)O 2 +C 2 O→CO 2 +CO 3.3×10 −13 [20] (N16)O+C+M→CO+M 2.14×10 −29 (T g /300) −3.08 exp(−2114/T g )(M=CO 2 )[20,37] Table A1. Electron impact reactions. Number Reaction Rate constant Reference (E1)e − +CO 2 →e − +CO+Of(σ)[39] (E2)e − +CO 2 →e − +CO 2 (v1)f(σ)[36] (E3)e − +CO 2 →e − +CO 2 (v2)f(σ)[36] (E4)e − +CO 2 →e − +CO 2 (v3)f(σ)[36] (E5)e − +CO 2 →e − +CO 2 (v4)f(σ)[36] (E6)e − +CO 2 →e − +CO 2 * f(σ)[36] (E7)e − +CO 2 →2e − +CO 2 + f(σ)[36] (E8)e − +CO 2 →2e − +CO+O + f(σ)[36] (E9)e − +CO 2 →CO+O − f(σ)[33] (E10)e − +CO 2 (vx)→e+CO+Of(σ)[36] (E11)e − +CO→e − +C+O 1.0×10 −12 [37] (E12)e − +O 2 →e − +O+O 4.0×10 −9 [15] (E13)e − +O 2 →2e − +O 2 + 1.8×10 −11 [38] (E14)e − +O 3 →O+O 2 − 8.9×10 −12 [38] (E15)e − +O 3 →O 2 +O − 2.0×10 −10 [38] (E16)e − +Ar→e − +Ar * f(σ)[33] (E17)e − +Ar→2e − +Ar + f(σ)[33] (E18)e − +Ar * →2e − +Ar + f(σ)[33] (E19)e − +CO 2 →e − +CO 2 f(σ)[33] (E20)e − +Ar→e − +Ar f(σ)[33] 15 Plasma Sources Sci. Technol. 26 (2017)035009 M S Moss et al Table A5. Average reaction rate coefficients for vibrational relaxation to the ground state (V–T relaxation)and vibrational relaxation between two different energy levels (V–V relaxation). Number Reaction Rate constant Reference (V1)CO 2 (v1)+CO 2 →CO 2 +CO 2 1.07×10 −14 [19] (V2)CO 2 (v1)+CO→CO 2 +CO 7.48×10 −15 [19] (V3)CO 2 (v1)+O 2 →CO 2 +O 2 7.48×10 −15 [19] (V4)CO 2 (v2)+CO 2 →CO 2 +CO 2 9.00×10 −16 [19] (V5)CO 2 (v2)+CO→CO 2 +CO 2.79×10 −17 [19] (V6)CO 2 (v2)+O 2 →CO 2 +O 2 2.79×10 −17 [19] (V7)CO 2 (v2)+CO 2 →CO 2 (v1)+CO 2 2.90×10 −14 [19] (V8)CO 2 (v2)+CO→CO 2 (v1)+CO 2.03×10 −14 [19] (V9)CO 2 (v2)+O 2 →CO 2 (v1)+O 2 2.03×10 −14 [19] (V10)CO 2 (v3)+CO 2 →CO 2 (v2)+CO 2 7.72×10 −16 [19] (V11)CO 2 (v3)+CO→CO 2 (v2)+CO 2.32×10 −16 [19] (V12)CO 2 (v3)+O 2 →CO 2 (v2)+O 2 3.09×10 −16 [19] (V13)CO 2 (v3)+CO 2 →CO 2 (v4)+CO 2 6.05×10 −15 [19] (V14)CO 2 (v3)+CO→CO 2 (v4)+CO 1.81×10 −15 [19] (V15)CO 2 (v3)+O 2 →CO 2 (v4)+O 2 2.42×10 −15 [19] (V16)CO 2 (v3)+CO 2 →CO 2 (v1)+CO 2 (v2)2.42×10 −15 [19] (V17)CO 2 (v2)+CO→CO 2 (v1)+CO 1.70×10 −18 [19] (V18)CO 2 (v2)+O 2 →CO 2 (v1)+O 2 5.10×10 −19 [19] (V19)CO 2 (v3)+O 2 →CO 2 (v1)+O 2 6.80×10 −19 [19] (V20)CO 2 (v4)+CO 2 →CO 2 (v2)+CO 2 4.33×10 −14 [19] (V21)CO 2 (v4)+CO→CO 2 (v2)+CO 3.03×10 −14 [19] (V22)CO 2 (v4)+O 2 →CO 2 (v2)+O 2 3.03×10 −14 [19] (V23)CO 2 (v4)+CO 2 →CO 2 (v1)+CO 2 9.08×10 −18 [19] (V24)CO 2 (v4)+CO→CO 2 (v1)+CO 6.18×10 −15 [19] (V25)CO 2 (v4)+O 2 →CO 2 (v1)+O 2 6.18×10 −15 [19] Table A4. Ion–ion and ion–molecule reactions. Number Reaction Rate constant Reference (I1)O − +CO 2 +M→CO 3 − +M9×10 −29 (M=CO 2 )[9] (I2)O 2 − +CO 2 +M→CO 4 − +M 1.0×10 −29 (M=CO 2 )[9,20,37] (I3)O 2 − +CO 2 + →CO+O 2 +O 6.5×10 −7 [20] (I4)O + +CO 2 →O 2 + +CO 9.4×10 −10 [20] (I5)O + +CO 2 →CO 2 + +O 4.5×10 −10 [20,37] (I6)CO 2 + +O→O + +CO 2 9.62×10 −11 [20] (I7)CO 2 + +O 2 →O 2 + +CO 2 5.3×10 −11 [20] (I8)CO 3 − +CO 2 + →CO 2 +CO 2 +O 5.0×10 −7 [20] (I9)O 2 + +CO 3 − →CO 2 +O 2 +O 3.0×10 −7 [20,37] (I10)O 2 + +CO 4 − →CO 2 +O 2 +O 2 3.0×10 −7 [20,37] (I11)CO 3 − +O→O 2 − +CO 2 8.0×10 −11 [20] (I12)CO 4 − +O→CO 3 − +O 2 1.1×10 −10 [20] (I13)CO 4 − +O→O − +CO 2 +O 2 1.4×10 −11 [20] (I14)O + +O 2 →O 2 + +O 1.9×10 −11 (T g /300) −0.5 [20,37] (I15)O 2 − +O + +M→O 3 +M 2.0×10 −25 (M=CO 2 )[20] (I16)O 2 − +O + →O+O 2 2.7×10 −7 [20] (I17)O 2 − +O 2 + →O 2 +O 2 2.0×10 −7 [20] (I18)O 2 − +O 2 + →O+O+O 2 4.2×10 −7 [20] (I19)O 2 − +O 2 + +M→O 2 +O 2 +M 2.0×10 −25 (M=O 2 )[20] (I20)O − +O + →O+O 4.0×10 −8 [20] (I21)O − +O + +M→O 2 +M 2.0×10 −25 (M=O 2 )[20] (I22)O − +O 2 + →O 2 +O 1.0×10 −7 [20] (I23)O − +O 2 + →O+O+O 2.6×10 −8 [20] (I24)O − +O 2 + +M→O 3 +M 2.0×10 −25 (M=O 2 )[20] 16 Plasma Sources Sci. 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