Time-Dependent Oxidative Capacities of La_𝟐O_𝟑, Lu_𝟐O_𝟑, CeO_𝟐, and Bi_𝟐O_𝟑 Materials Interacting with Air-CO or Air-CH_𝟒 Flows

Abstract

Using Fourier transform infrared (FTIR) spectroscopy analyses, we have studied the oxidation processes of methane or carbon monoxide in air-CH₄ or air-CO flows interacting with polycrystalline catalytic oxides, as a function of temperature (T) and time (t). The gas flows crossed through La₂O₃, Lu₂O₃, CeO₂, or Bi₂O₃ porous walls with constant composition and rate. The oxidation capacities of materials were determined from the intensities 𝐼(𝑡,𝑇) of CO₂ vibrational bands resulting from the total oxidation of CH₄ or CO into CO₂. To interpret the time-dependent variations of these intensities, we have applied a model derived from Johnson-Mehl-Avrami approaches. This simple approach delivers pertinent parameters describing time-dependent oxidation rates.

1. Introduction

In the general framework of catalytic gas sensing or depolluting microsystems development, we study the time-dependent oxidation capacities of polycrystalline materials interacting with air-CO or air-CH₄ gas flows. The main objective is to convert toxic CO or undesired CH₄ gases into CO₂ gas. To follow the reaction processes, we make use of Fourier transform infrared spectroscopy and determine the time- (𝑡) and temperature- (𝑇) dependent intensities 𝐼(𝑡,𝑇) of CO₂ vibrational bands resulting from the oxidation processes of CH₄ or CO in air-CH₄ or air-CO gas flows. In this study, we determine the catalytic efficiencies of La₂O₃, Lu₂O₃, CeO₂, and Bi₂O₃ polycrystalline oxides as a function of reaction time, at various temperatures: the air-CH₄ or air-CO flows cross through porous polycrystalline walls of these rare earth-based oxides and a system based on the Bi₂O₃ phase [1].

Rare earth oxides are well known for the similarity of their chemical and physical properties, in relation with the electronic structures (4f-5d-6s) of rare earth cations. Despite this similarity, these oxides generally present diversified physical and chemical properties allowing their use in many applications. The cerium oxide (ceria) has been extensively studied as a catalyst [2–5] or semiconducting material [6–8]. The catalytic properties of ceria have been ascribed to the capacity of cerium to change its valence from Ce⁴⁺ to Ce³⁺ and thus to oxidize or reduce gases. In the case of lanthanum oxide (lantana), catalytic behaviours have been studied in the past [9]. This oxide is used in the conversion of CH₄ into syngas (H₂ + CO) [10]. However, very few studies on the reactivity of lutetium oxide (lutetia) in presence of gases are available in the literature: this oxide is mainly involved in optical, luminescence applications [11–14]. In 1976, the catalytic oxidation of butane was studied over a series of lanthanide oxides in order to investigate the effect of the electronic configuration on the catalytic activity [15]. The authors showed that lanthanum oxide was one of the least active catalysts; cerium oxide was the most active one, and the activity decreased with an increase in the atomic number from cerium to gadolinium. They also observed that the activity of terbium oxide was the second highest, and again the activity decreased from terbium to lutetium. In other terms, for the authors, lutetia should have the weakest activity in the case of oxidation of butane.

In the case of our previous studies on the system Bi₂O₃-CeO₂ [1], we clearly observed a high catalytic activity of the bismuth oxide interacting with air-CO gas flows and a poor activity of this oxide in presence of air-CH₄ gas flows.

In these experimental studies [1], the evolution versus time of oxidation capacities 𝐼(𝑡,𝑇) (CH₄ or CO being converted into CO₂) presents a common behavior, characterized by at least three periods: initiating, intermediate, and stabilization periods. Some samples present abnormal maxima of 𝐼(𝑡,𝑇) in the intermediate period of reaction. Such behaviors might be conditioned by the nature of grain surfaces in the materials.

In the present study, we try to interpret the time-dependent evolutions of the FTIR intensities 𝐼(𝑡,𝑇) using elemental Avrami models [16–18]. The modeling approach is applied to La₂O₃, CeO₂, Lu₂O₃, and Bi₂O₃ phases.

2. Experimental Section

2.1. Samples

The various samples were synthesized via specific routes previously described by us [1, 19–22] and based on wet chemistry processes involving nitrate-based solutions. The ceria phase was elaborated in nanocrystalline form at 200°C. The La₂O₃ and Lu₂O₃ were obtained after final thermal treatment at 750°C. The Bi₂O₃ phase was obtained after thermal treatment at 600°C during 4 hours. Each polycrystalline phase was clearly identified using classical X-ray diffraction from D5000 Bruker equipment in θ–2θ configuration. Brunauer-Emmett-Teller (BET) [23] analyses were carried out to determine the sample-specific surface areas noted as 𝐴_BET in m²/g. This method delivers the effective surface exposed to gas adsorption. In the case of absence of agglomerations, the 𝐴_BET values can be related to individual grain dimensions. The 𝐴_BET values were found to be 11.5 m²/g for La₂O₃, 82.0 m²/g for CeO₂, 5.0 m²/g for Lu₂O₃, and 2.0 m²/g for Bi₂O₃.

2.2. FTIR Spectroscopy and Reactivity Analyses

The rare earth or bismuth-based materials were exposed to air-CH₄ and air-CO gas flows in a homemade cylindrical reaction cell (see Figure 1). The transformation of CH₄ or CO into CO₂ was analyzed by Fourier transform infrared (FTIR) spectroscopy, using a FTIR Unicam-Mattson-Bruker spectrometer. The gases pass through a polycrystalline porous walls constituted of the various phases. The polycrystalline walls are fixed between two porous separators. A constant mass of 𝑚₀=0.1g was used in each experiment.

Figure 1 

Catalytic reactor.

All experimental details have been extensively described in previous works. The conversion reactions are analyzed from the infrared absorption band intensities of CO₂ (doublet at 2340–2360 cm⁻¹), resulting from one of the overall reactions: CH₄+2O₂→CO₂+2H₂O(1)CO+12O₂→CO₂(1)^′ The conversion intensity 𝐼(𝑡,𝑇) was determined from the measurements of CO₂ absorption bands, at a certain time t of the gas/solid interaction. Each vibrational spectrum was recorded over a period of Δ𝑡=10swith intervals of 30 s between two spectra. The total exposure time was two hours. For a given total time 𝑡 of reaction and a given temperature 𝑇_react, the intensity 𝐼(𝑡,𝑇) was assumed to be proportional to the amount of CO₂ molecules formed during the time Δ𝑡 of FTIR record. All experiments were characterized by a first initiating regime in which the CO₂ intensities increase upto a maximal value after a time of about 10–15 minutes.

Figures 2(a) and 2(b) represent typical FTIR spectra associated with conversions of CH₄ and CO after solid gas interactions. The CO₂ FTIR band intensity increases as the CH₄ or CO band intensities decrease.

(a)

(b)

Figure 2 

FTIR spectroscopy of emitted gases. Transmittances without any catalytic sample and in presence of a catalyst Lu2O3: (a) CH4 converted into CO2 and H2O and (b) CO converted into CO2.

To compare the various reactivities, we have normalized the curves 𝐼(𝑡,𝑇) using the specific surfaces 𝐴_BET by calculating the values 𝐼^∗(𝑡,𝑇)=𝐼(𝑡,𝑇)/𝐴_BET. It should be noted that, in our experiments, the temperature ranges were limited to 275°C for air-CO flows and 525°C for air-CH₄ flows in order to avoid direct oxidation of CO or CH₄ by oxygen (this direct oxidation was tested in our experimental device in the absence of active sample).

3. Modeling Approaches

In our previous work [24], we proposed a semiempirical model based on typical catalytic steps summarized as follows:(i)surface adsorption of gas and O₂ (air) on the surface of the solid; (ii)surface reaction CH₄ + 2O₂→ CO₂ + 2H₂O or CO + O₂→ CO₂, with reduction of catalyst surface, followed by CO₂ desorption; (iii)regeneration of the solid (with oxidation of surfaces) due to adsorbed oxygen from the air; (iv)desorption of gases.

It should be important to note that, in the present experiments, the gas flows cross through polycrystalline porous walls of materials, with a fixed speed and a fixed gas composition: in these circumstances, the gas-solid interactions result from a complex equilibrium involving four distinct kinetics of adsorption, desorption, degradation, and regeneration of active sites. In our model, we have assumed that the desorption steps of final gases (CO₂) might be described by surface reaction laws.

The intermediate surface reactions between adsorbed molecules and active sites might be described as follows.(i)Oxidation step of adsorbed molecules from mobile surface oxygen O^∗ of one active site 𝑆_red-O^∗, delivering one reduced site “𝑆_red”: CH_4ads+4𝑆_red-O^∗→CH_4ads+4𝑆_red+4O^∗→CO₂+4𝑆_red+2H₂O(2)or (CO)_ads+𝑆_red-O^∗→(CO)_ads+𝑆_red+O^∗→CO₂+𝑆_red(3)(i)Formation of mobile oxygen species O^∗ from adsorbed dioxygen from air∶(O₂)_ads→2O^∗.(ii)Regeneration (oxidation) of reduced sites “𝑆_red”: 4𝑆_red+4O^∗→4𝑆_red-O^∗(4)or 𝑆_red+O^∗→𝑆_red-O^∗(5)

The general expression delivering the CO₂ vibrational band intensity is assumed to result from sites delivering oxygen 𝑆_red-O^∗ and sites regenerated from oxygen from air 𝑆_red: 𝑑CO₂()(𝐷()(.𝑑𝑡=𝐼𝑡,𝑇=𝐴𝑡,𝑇)[𝑡,𝑇+𝑅𝑡,𝑇)](6) In this expression, the symbol [CO₂] designates the total amount of CO₂ molecules formed after a reaction time 0074. The derivative 𝑑[CO₂]/𝑑𝑡=Δ[CO₂]/Δ𝑡 is proportional to the instantaneous amount Δ[CO₂] recorded at time 𝑡, during the period Δ𝑡. The term 𝐴(𝑡,𝑇) describes the adsorption of gases on the solid surfaces, 𝐷(𝑡,𝑇) describes the reaction between oxidative active sites and reducing gas molecules, and 𝑅(𝑡,𝑇) describes the site regeneration due to oxygen from air adsorbed at the solid surface. Each 𝐴,𝐷,𝑅 term was previously expressed using three distinct Avrami’s approaches. The final general expression adapted to the normalized data 𝐼^∗=𝐼/𝐴_BET was as follows: 𝐼^∗(𝑡,𝑇)=𝑋₀⋅1−exp−𝐾₀𝑡⋅𝑆₁⋅exp−𝐾₁𝑡^𝑝+𝑆₂1−exp−𝐾₂𝑡^𝑞.(7) In this expression, the parameter 𝑋₀ is proportional to the composition of the air-gas flow. This composition (2500 ppm in air) was fixed for all experiments. As the normalized 𝐼^∗ values characterize the instantaneous amounts of CO₂ molecules formed per surface unit of material, the 𝑋₀ parameter can act as a scaling factor. The 𝐾₀ kinetics factors result from first-order classical adsorption law. The parameters 𝑆₁ and 𝑆₂ are linked to the initial active sites (oxygen donors) and to the final re-activated sites, respectively, due to oxygen (air) action. The 𝐾₁ and 𝐾₂ parameters and 𝑝, 𝑞 exponents result from specific Avrami models and are conditioned by the chemical processes of degradation or reconstructive growth. Surface degradation is conditioned by the presence of initial O^∗ species reacting with adsorbed “gas” molecules in increasing number (because of the constant gas flow). The degradation mechanism requires interaction between one adsorbed molecule “gas” and one active site delivering a free O^∗ species. This interaction is complex and could be divided into three main steps: (i)reduction step with formation of one oxygen vacancy and one O^∗ free oxygen species, (ii)O^∗ migration out of the solid,(iii)reaction between gas (CH₄ or CO) and O^∗ giving rise to CO₂.

In our calculations, we tried some adjustments of this parameter. Finally, the value 𝑝=2 was found to be satisfactory.

Surface regeneration is associated with a first-order reaction between surface molecules [O^∗]^air_surf (or oxygen O₂ from air) and the solid. To regenerate active sites, a lot of O^∗ surface species (from air) are available on the solid surface: no substantial O^∗ migration is required to interact with one active site. This is the reason why an exponent 𝑞=1 might be expected for such a mechanism. We have fixed this value in our calculations.

As 𝑋₀  is a scale factor, five pertinent parameters result from our hypotheses. The 𝐾₀  constant is the adsorption parameter, the 𝐾₁  constant is the kinetics parameter associated with adsorption and reaction with one active site, and the 𝐾₂  constant is the corresponding kinetics parameter of oxygen regenerating one deactivated site. The 𝑆₁  and 𝑆₂  constants are proportional to the initial surface area of active sites and final surface area of reactivated sites, respectively.

Regarding the surface reactions, the active sites subjected to degradation (oxygen loss) can be considered as being regenerated by oxygen from air (oxidation), so the numbers of active and regenerated sites are assumed to be equal. Thus, as a first simplified hypothesis, we could assume that 𝑆₁ and 𝑆₂ should be equal. Therefore, the conversion rate can be expressed as follows: 𝐼^∗(𝑡,𝑇)=𝑋₀⋅𝑆₂⋅1−exp−𝐾₀𝑡⋅exp−𝐾₁𝑡²+1−exp−𝐾₂𝑡.(7)^′ Apart from the 𝑋₀ parameter (scaling factor), each parameter could be dependent on the temperature. The parameters 𝑆₁=𝑆₂ depend on the nature of the surface and on the active site densities at a fixed temperature.

For a short experimental time, the expression can be reduced to 𝐼^∗(𝑡,𝑇)=𝑋₀⋅𝐾₀⋅𝑆₂⋅𝑡.(8) For long experimental time, the expression can be reduced to: 𝐼^∗_max(𝑡,𝑇)=𝑋₀⋅𝑆₂.(9) The maximal values of 𝐼^∗ observed for long reaction times can directly deliver the 𝑆₂ term, with 𝑋₀ being fixed to an arbitrary value.

4. Results

The first step of calculation consists in assimilating the 𝐼^∗_max values (constant values reached after a long time of reaction) to 𝑋₀⋅𝑆₂. Then, the various parameters have been adapted to obtain a good fit to the various experimental curves.

In Tables 1 and 2, we have reported the optimized parameters in the cases of air-CO and air-CH₄ gas flows interacting with La₂O₃, CeO₂, Lu₂O₃, and Bi₂O₃.

Table 1 

Simulation parameters for solids interacting with air-CO gas flows at various temperatures.

Table 2 

Simulation parameters for solids interacting with air-CH₄ gas flows at various temperatures.

Figures 3 and 4 give the experimental data and the simulated values of the catalytic efficiencies 𝐼(CO₂) of the (1−𝑥)CeO₂-𝑥/2Bi₂O₃(0≤𝑥≤1) phases, respectively, interacting with air-CO and air-CH₄ flows (2500 ppm CO or CH₄ in air).

(a)

(b)

(c)

(d)

Figure 3 

Simulation of CO oxidation efficiencies in the case of air-CO flows (2500 ppm CO) interacting with: (a) CeO2; (b) La2O3; (c) Lu2O3; (d) Bi2O3 as a function of time and for various temperatures. Experimental data: dotted line; model data: continuous line.

(a)

(b)

(c)

(d)

Figure 4 

Simulation of CH4 oxidation efficiencies in the case of air-CH4 flows (2500 ppm CH4) interacting with: (a) CeO2; (b) La2O3; (c) Lu2O3; (d) Bi2O3 as a function of time and for various temperatures. Experimental data: dotted line; model data: continuous line.

Figures 5(a) and 5(b) compare the 𝑆₂=𝑆₁ parameters as a function of temperatures in the case of air-CO and air-CH₄ gases. It should be noted that the calculated curves (Figures 3 and 4) 𝐼^∗(𝑡,𝑇) fit well the experimental 𝐼^∗_exp(𝑡,𝑇) data in the initiating periods of catalytic process.

(a)

(b)

Figure 5 

(a) Evolution of 𝑆1=𝑆2 parameter as a function of temperature in the case of air-CO flows interacting with La2O3, CeO2, Lu2O3, and Bi2O3. (b) Evolution of 𝑆1=𝑆2 parameter as a function of temperature in the case of air-CH4 flows interacting with La2O3, CeO2, Lu2O3, and Bi2O3.

The three 𝐾₀, 𝐾₁, and 𝐾₂ parameters vary with temperature (Tables 1 and 2): they are associated with the adsorption, degradation, and regeneration mechanisms. The 𝑆₂ parameter (𝑆₁=𝑆₂) increases with temperature: it is characteristic of the surface of each solid, at specific temperatures and under partial pressures of oxygen from air.

In the case of abnormal behaviors observed during the initiating period, it has been possible to simulate such undulations or maxima. The 𝐾₁ parameter is strongly coupled to the 𝐾₀ one. It plays a very important role in the short time reactions.

5. Discussion

In the case of air-CO flow interacting with the present oxides, the 𝑆₂ (and 𝑆₁=𝑆₂) parameters are characteristic of long time behaviors (after initiating period) for all samples and each temperature. Their values directly depend on the choice of unique scale factor 𝑋₀, identical in each experiment. They systematically increase with temperature, and their activation energies can be representative of thermal equilibrium at the solid surfaces. The highest values of 𝑆₂ regeneration parameters (Tables 1 and 2) are observed for Bi₂O₃ and Lu₂O₃.

The 𝐾₀ parameters (Tables 1 and 2) characterize the progressive adsorption of gases and behave diversely as temperature increases. In the case of ceria interacting with air-CO gas, we observe small increasing values; in the case of La₂O₃, they strongly decrease; in the case of Lu₂O₃, they slowly decrease. Finally, in the case of Bi₂O₃, the 𝐾₀ values irregularly vary.

The 𝐾₁ parameters are correlated with the 𝐾₀ parameters, and they play an important role in the initiating and intermediate periods, before the 𝐼_max values have been reached. They allow good fitting of undulations observed on several curves (for intermediate time) even if this observation is not systematic. These 𝐾₁ parameters are relatively weak in the case of CeO₂ and Bi₂O₃. They have large values in the case of La₂O₃ and Lu₂O₃. This suggests different degradation processes associated with reduction of the solid surfaces. The 𝐾₂ parameters characterize the oxidation capacity of the solid surfaces due to oxygen from air. They present two types of similar values, firstly in the case of CeO₂ and Bi₂O₃, and secondly in the case of Lu₂O₃ and Bi₂O₃.

In the case of air-CH₄ flow interacting with the present oxides, all calculated 𝐼^∗ curves fit well the experimental 𝐼^∗ data. The 𝐾₀ and 𝐾₁ parameters increase with temperature. The 𝑆₂=𝑆₁ parameters all increase with temperature. The highest values are observed for Lu₂O₃ sample. These evolutions of parameters are probably conditioned by the specific high stability of methane in presence of oxygen and by a complex decomposition of CH₄ giving rise to two molecules CO₂ and H₂O.

To better interpret the abnormal evolutions observed in the case of Bi₂O₃ oxide (Figure 3(d)), with a maximum of 𝐼(𝑡,𝑇) during the intermediate period, at 200 and 225°C, it is possible to invoke the presence of oxygen, carbonate, or hydroxide species, initially adsorbed on grain surfaces of solids, and favor additional oxidation of CO. Such adsorbed species are generally eliminated between 150 and 250°C. After thermal elimination of these surface species (presently for 𝑇>175^∘C), the oxidation process is governed firstly by the oxygen molecules present in gas flows and then by oxygen species delivered by the solids. In the case of methane, as oxidation occurs above 400°C and desorption of species occurs below 400°C, the elimination of such surface species cannot be observed.

6. Conclusions

The Johnson- Avrami Mehl models allowed us to determine pertinent parameters characteristic of the porous media and of the two kinds of gas-solid interactions involving methane or carbon monoxide gases. The different time-dependent oxidation processes characterized by at least three steps have been well described from these parameters: (i) the initiating period is governed by the 𝐾₀ parameter, (ii) the intermediate period is governed by both 𝐾₀ and 𝐾₁ parameters, and (iii) the stabilization period is governed by the 𝑆₂ parameter. This last parameter represents the number of active sites at the internal solid surfaces and conditions the catalytic efficiencies for long reaction time: it is directly related to regeneration of solid surfaces via oxygen from air. The 𝐾₀ and 𝐾₁ parameters represent successively the adsorption kinetics of CH₄ or CO molecules and the reduction kinetics of active sites at the solid surfaces. They condition the initiating period of oxidation reaction (ranging between 10 and 20 minutes in the present experiments). It should be interesting to note that the 𝐾₁ parameter can be used to interpret the experimental undulations of the intensity 𝐼^∗, just before this intensity reaches a constant value. Both 𝐾₀ and 𝐾₁ parameters might be directly linked to the presence or not of adsorbed species on the surfaces of polycrystalline solids. The 𝐾₂ parameter plays a moderate role in fitting calculated curves to experimental data.

Acknowledgments

The authors gratefully acknowledge the Provence-Alpes-Côte d’Azur Regional Council, the General Council of Var, and the agglomeration community of Toulon Provence Mediterranean for their helpful financial supports. This work was developed in the general framework of ARCUS CERES project (2008–2011).