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An ab initio study of oxygen adsorption on tin dioxide
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Surface Science 602 (2008) 1072–1079 www.elsevier.com/locate/susc
An ab initio study of oxygen adsorption on tin dioxide Matthew Habgood a,*, Nicholas Harrison b a
QIP IRC Group, University of Oxford, Department of Materials, Parks Road, Oxford OX1 3PH, United Kingdom b Department of Chemistry, Imperial College London, Exhibition Road, SW7 2AZ, United Kingdom Received 24 October 2007; accepted for publication 7 January 2008 Available online 24 January 2008
Abstract In spite of detailed experimental and theoretical studies, a definitive model of oxygen adsorption on the surface of SnO2 has yet to emerge. In this study, density functional theory (DFT) calculations were performed to simulate various potential scenarios for oxygen placement on the planar reduced SnO2 (1 1 0) surface. Models for four adsorbate species that have been experimentally observed are hence proposed. Most importantly, these include the species labelled as ‘O 2 ’ and ‘O ’ in classical gas sensor theory, which are directly concerned with the gas sensing action of SnO2. Ó 2008 Elsevier B.V. All rights reserved. Keywords: Ab initio quantum chemical methods and calculations; Density functional calculations; Adsorption; Surface electrical transport; Oxygen; Tin oxides; Semiconducting surfaces
1. Introduction Tin dioxide is a wide band gap (3.6 eV) n-type semiconductor with rutile bulk structure [1]. Self-doping occurs via oxygen vacancies. It has numerous applications in the sensing of reducing gases and in the catalysis of hydrocarbon combustion [2]. Used in the earliest reducing – gas sensor research [3,4], SnO2 continues to be the basis for much contemporary sensor development [5–14]. The first stage of the reducing-gas sensing action is the preadsorption of oxygen onto a reduced SnO2 surface [2]. The forms in which oxygen adsorbs, and the effect that this has on the electronic structure and geometry of the reducing surface, are only understood in the most general terms. It is apparent that a deeper understanding of the adsorption, preferably at an atomistic and quantum mechanical level, would provide a basis for a more detailed characterisation of sensing action [9]. This study aims to develop such an understanding. The basis of gas sensing behaviour in SnO2 is the fall in surface conductivity observed upon adsorption of oxygen *
Corresponding author. Tel.: +44 7769867122. E-mail addresses: [email protected] (M. Habgood), [email protected] (N. Harrison). 0039-6028/$ - see front matter Ó 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.susc.2008.01.017
[2]. Within the classic theory of gas sensing, this results from the extraction of conduction electrons by the adsorbate species. Localised trap states are formed high in the band gap, extracting electrons from the conduction band in the surface region [2]. The most widely used model of this process was developed in the 1960s, based on the kinetic studies of Chon et al. [15] and others [16]. Oxygen ionosorbs onto the surface, extracting conduction electrons. Localised trap states form in the band gap, ‘bending’ the bands in the surface region and forming a barrier to conduction. Two ionosorbate species are assumed to form. One is a superoxo species, O 2 , which does not react with reducing gasses. The other is an atomic ion, O, that reacts rapidly with reducing gasses and hence is responsible for the sensing action of these gasses. The sequence of reactions that forms the adsorbates is thought to be: O2gas ! O2physisorbed O2phys þ e ! O 2 O 2 þ e ! 2O
As has been pointed out in one recent review [17], however, experimental data (to be discussed below) suggest that these species cannot simply be treated as gas-phase
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superoxo and atomic ions that adsorb onto SnO2 and move around freely. Nevertheless this model may be viewed as a useful but limited guide to the surface processes of oxygen on SnO2 which makes no reference to, for example, the placement or geometry of the oxygen species. Motivated by the importance of oxygen adsorption processes to the function of any SnO2 based sensing device, the current work therefore aims to use DFT calculations to generate more accurate models of the oxygen adsorbate species that form on SnO2, as judged by correspondence with the available experimental evidence. 2. Experimental and computational background A number of structurally different SnO2 surfaces may be prepared, which may be expected to display differing adsorption behaviours. Nevertheless, most experimental studies and sensing devices have been carried out using polycrystalline surfaces, such as those prepared by sputtering. These are the surfaces of interest in this study. Of the crystal faces of SnO2, (1 1 0) is the most stable [1], and is expected to be a major component of such polycrystalline surfaces. Beyond this, they have been characterised electronically by X-ray photoelectron spectroscopy (XPS), ultraviolet photoelectron spectroscopy (UPS) and conductivity measurements [18–23], compositionally by auger electron spectroscopy (AES) and ion scattering spectroscopy (ISS), and structurally by low energy electron diffraction (LEED) [21–23]. Scanning tunnelling microscopy (STM) studies have also been performed [24–26]. Although these studies have not defined an unambiguous structure for the polycrystalline SnO2 surface, a number of conclusions can be drawn. Annealing at >800 K reliably produces a 1 1 reconstruction with significant surface conductivity. The conductivity will fall following oxygen adsorption. There are two types of oxygen vacancy, which are thought to result from in-planar and superplanar (‘bridging’) oxygen atoms, and seem to be irregularly distributed. Here, ‘planar’ refers to the plane of the SnO2 surface. The bridging oxygen vacancy is associated with a localisation of excess charge at neighbouring tin atoms [27]. Various computational studies have attempted to model such surfaces [28–37]. Most significantly, the studies of Oviedo and Gillan [34], Bouzoubaa et al. [36], and Batzill et al. [37] have confirmed the likelihood of mixed bridging and in-planar vacancy formation at high levels of oxygen extraction. These studies have largely focused on the 1 1 0 surface, motivated by its high stability. A recent review of tin oxide surfaces is found in Ref. [38]. It is necessary at this point to define the terminology encountered in discussions of the SnO2 (1 1 0) surface and its planar reduced reconstruction. In the 1 1 0 direction SnO2 can be seen as a series of three-atom-deep layers. Each unit cell of such a layer takes the form O–Sn2O2–O. The 1 1 0 surface is outermost of these layers. At this surface, the atoms with two-coordination in the outermost layer of oxygen are referred to as ‘bridging’ oxygen atoms;
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removal of one creates a ‘bridging vacancy’. Removal of oxygen atoms in the last Sn2O2 plane creates an ‘in-plane vacancy’, while removal of an atom from the next plane of oxygen creates a ‘sub-bridging’ vacancy. The bridging oxygen atoms coordinate to six-coordinated tin atoms, denoted Sn6c. The second tin atom in each layer is five coordinate, denoted Sn5c. This (stochiometric) surface is sometimes also referred to as the ‘oxidised’ surface. Fig. 1 shows this surface. The so-called ‘planar reduced’ surface is generated by removing all the bridging oxygen atoms from the stochiometric surface. This gives one bridging vacancy per unit cell, and reduces the coordination of six-coordinated tin atoms to four; these centres are then denoted Sn4c. Fig. 2 shows this surface. The challenge of interest, though, is to model oxygen adsorbate species on SnO2. Numerous experimental studies have addressed this subject. Although they have not provided a definitive picture of oxygen adsorption, they have provided a number of facts about the adsorbate species. Any attempt to provide a model of oxygen adsorption must be in agreement with these facts. The relevant studies include the electron spin resonance (ESR) and reactive gas experiments of van Hoof [39]; the low temperature ESR work by Meriaudeau et al. [40]; the study of ESR data by Lunsford [41] and the later review by Che and Tench [42]; the combined ESR, conductivity, and temperature programmed desorption (TPD) measurements of Mizokawa et al., Iwamoto et al., and Yamazoe et al. [43–46]; the temperature dependent conductivity and ESR study of Chang [47]; the TPD investigation of Joly et al. [48]; the TPD work of Shen et al. [49]; the XPS and UPS study of
Fig. 1. The SnO2 (1 1 0) stochiometric surface, ‘top’ and ‘side’ views. The black box represents a unit cell. Diagram is not to scale.
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Fig. 2. The SnO2 (1 1 0) planar reduced surface, side view. Diagram is not to scale.
Nagasawa et al. [50]; and the more recent TPD and conductivity measurements of Saukko et al. [51]. Although they were carried out on ZnO, the experiments of Chon and Prater [15] should also be taken into account. Species adsorbed on ZnO are expected to qualitatively resemble those adsorbed on SnO2. Combining data from conductivity and Hall effect measurements, they determined that two species adsorbed on ZnO in the temperature range 473–573 K. One predominated at lower temperatures, and withdrew many fewer ‘free’ (i.e. conduction band) electrons from the surface than the other, which predominated at higher temperatures. Importantly, kinetic studies suggested that the higher temperature species was monatomic. These conclusions should apply qualitatively to adsorption on SnO2. A note is important about the treatment of the conclusions of Nagasawa et al. [50] in the current work. On the basis of their UPS and XPS data, Nagasawa et al. concluded that two species of oxygen adsorbate are found following adsorption at lower temperatures, 298–473 K, and that these are both localised at Sn4c centres. It was further concluded that a different adsorbate species formed following adsorption at 573–673 K, and that this was localised at the Sn5c centre. Re-examination of the data they present indicates an alternative explanation. Nagasawa et al. are correct to state that their data indicates the presence of two species at low adsorption temperatures, and a different species following adsorption at higher temperatures. However, it was also concluded in the current work that their data demonstrate the lower temperature species are localised at the Sn5c centre and the higher temperature species is localised at the Sn4c centre, rather than the reverse conclusion reached by the original authors. This study follows Nagasawa et al. in discussing their results in terms of the planar reduced surface. From examination of the experimental works listed above, it was concluded that four different oxygen adsor-
bate species can form on the reduced SnO2 surface during adsorption at different temperatures. If the adsorbed species can be expected to undergo first-order desorption (that is, if it is molecular), an adsorption energy can be estimated from the temperature of the corresponding TPD peak using the Redhead formula [52]. Little adsorption is possible on the stochiometric surface [1]. The first species is formed following very low temperature adsorption (<200 K). It is molecular, symmetric, and has a Redhead adsorption energy of 0.52 eV [48]. This species will be labelled adsorbate 1. Close agreement in ESR signals suggests that this will resemble the second species in electronic structure. The second species is formed following adsorption at around room temperature (298 K). It is localised at Sn5c, and close agreement in ESR signals suggest that it will resemble adsorbate 1 in electronic structure although it will not necessarily be symmetric. Its presence or absence is not associated with large changes in conductivity, and analogy with the results of Chon et al. [15] suggests that it will be molecular. Redhead adsorption energies are around 1.05 eV [43–48]. This species will be labelled adsorbate 2. The third species is formed following adsorption at 423 K. It is associated with an ESR signal, but unlike the first two species, it can be shown that the electron spin is localised away from the oxygen adsorbate in this case [41]. It is localised at Sn5c, and analogy with the kinetic results of Chon et al. [15] suggests that it will be atomic. Given this, the use of a Redhead adsorption energy is not justified. The species is associated with a fall in conductivity relative to the unadsorbed surface. This species will be labelled adsorbate 3. The fourth species is formed following adsorption at around 673 K, depending on the exact SnO2 surface prepared. It is associated with lowered conductivity relative to the unadsorbed surface, but is ESR inactive. It is localised at Sn4c, and has a Redhead adsorption energy of between 1.7 and 2.3 eV [46,48] in different studies. This species will be labelled adsorbate 4. It has also been noted that heating a reduced SnO2 surface at 773 K under sufficient pressure of oxygen (130 Pa) [22] will heal all vacancies, oxidising it. It is also apparent that the adsorbate species that form on the SnO2 surface are heavily dependent on adsorption temperature, and that more stable species form at higher adsorption temperatures. It must be concluded that there is a significant kinetic factor in the formation of these adsorbate species, and that the more stable species also have higher kinetic barriers to their formation. Hence the highly stable oxidised surface requires high temperatures to be observed; and the (more stable) adsorbate 4 only forms in preference to (for example) adsorbate 1 if the temperature is high enough to overcome the kinetic barrier to its formation. There have been a number of previous theoretical studies of the adsorbed oxygen species on SnO2 [53–61]. In many studies the planar reduced 1 1 0 surface is used as the model for the reduced surface. The planar reduced sur-
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face has bridging oxygen vacancies and is a 1 1 reconstruction (in common with the experimentally observed species), but can be modelled using a small unit cell, making it desirable for computational modelling. However, Oviedo and Gillan’s assertion [35] that the experimentally observed 1 1 reconstruction is ‘usually interpreted’ as the planar reduced surface is not supported in the literature. Nonetheless, the planar reduced surface is a sensible choice for computational modelling, and was adopted for this study. The planar reduced surface does not include the in-plane oxygen vacancies that have been theoretically predicted [34,36,37] and experimentally observed [18–26] on reduced SnO2 1 1 0 surfaces, and is therefore not an exact model of real-life SnO2 surfaces. Two considerations inform its use in this study as a model surface. Firstly, it is clear that modelling of oxygen adsorption at SnO2 surfaces must include vacancies of some sort. A combination of conduction studies, UPS and XPS [18–23,50] has established that adsorbed oxygen atoms interact with a combination of bridging and in-plane oxygen vacancies, and that it is this interaction that leads to changes in conductivity which form the basis of gas detecting action. It is also known that full oxidisation of SnO2 1 1 0 surfaces to a stochiometric form requires relatively high temperatures and pressures (as discussed above, and [22]). The SnO2 surfaces that carry out gas sensing action, it must be concluded, are not prepared under such conditions, are partially reduced, and contain oxygen vacancies. As established, it is these that lead to oxygen adsorption and gas sensing action. Conversely, it has been established that fully stochiometric SnO2 1 1 0 surfaces do not interact with oxygen [1]. This is supported by some modelling [58], although Slater et al. [57] predict oxygen adsorption at a SnO2 1 1 0 surface, and Levy and Pagnier [61] consider this situation (without comparison to alternatives, however). The latter two studies were carried out at a lower level of theory (the LDA DFT functional) than the former (a GGA functional), and their divergence from experiment seems to indicate that they are mistaken. Overall, the literature indicates that oxygen vacancies are responsible for oxygen adsorption at the SnO2 1 1 0 surface. Secondly, inclusion of in-plane oxygen vacancies requires a large unit cell for computational calculations, since the inclusion of an in-plane vacancy in every 1 1 unit cell would produce a surface layer of tin metal for which there is no experimental evidence. The use of the planar reduced surface therefore provides a computationally cheap model for the partially reduced surface, which still includes the oxygen vacancies that are essential to understanding the adsorption of oxygen. The presence of oxygen vacancies is not fundamental in the adsorption of non-oxygen species, and the stochiometric surface may therefore be used as a model surface when considering such adsorbates [62,63]. Oviedo and Gillan [58] presented a comprehensive assignment of the observed species to calculated adsorption scenarios. As with other studies, though, these did not fully
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match the experimental facts listed above, and it has been noted [17] that there is a gulf between computational and experimental results in this area. Ref. [57] assigns adsorbate 1 to an oxygen molecule placed at Sn5c with the molecular axis tilted at 70o to the vertical in the 1 1 0 direction, and adsorbates 2 and 3 as an oxygen molecule symmetrically bonded to two adjacent Sn4c centres, with and without the presence of adsorbate 1 respectively. However, as previously noted, adsorbate 1 is in fact symmetric, and adsorbates 2 and 3 are localised at Sn5c, rather than Sn4c. Additionally, adsorbate 3 is atomic, rather than molecular. Sensato et al. [59] have shown that DFT [64] calculations with the B3LYP exchange-correlation functional [65] reproduce accurate electronic structure calculations for SnO2 (for example, giving a band gap of 3.3 eV as compared to an experimental value of 3.6 eV [1]). This finding is in line with previous findings of the authors which demonstrated that the hybrid exchange approach reproduces the electronic structure of a variety of materials far better than local or gradient corrected functionals [66]. 3. Methodology All calculations were performed using the CRYSTAL03 software [67]. The crystalline orbitals are expanded in an atom centred basis set of Gaussian type primitives. A basis set employing different numbers of Gaussians for different core shells in the sequence [9/7/6/3] and a two non-fixed Gaussians with a polarisation function for the valence shell for Sn, and a more straightforward 8–411* set for O, was adopted [68]. Electronic exchange and correlation were approximated using the hybrid exchange formalism as implemented in the B3LYP [65] functional which is generally more reliable than the local or gradient corrected functionals for describing the ground state energetics and electronic structure of insulating solids [66,69]. The convergence criterion on energy integrals was set to 106 Hartrees, with 9 k-points (3 3 1) in the irreducible Brillouin zone. Preliminary calculations of the electronic structure of the bulk crystal at the lattice constants ˚ with u = 0.3058, produced a a = 4.815 and c = 3.272 A band gap of 3.3 eV in agreement with that observed and the previous findings of Sensato et al. [59]. The surface was modelled as a symmetric slab periodic in two-dimensions and adsorbate atoms were introduced symmetrically on both surfaces. The size of the surface unit ˚) cell was fixed at bulk values (a = 4.815 and c = 3.272 A and the internal coordinates of the atoms were fully relaxed. The computed surface energy was converged with re˚ (from spect to the thickness of the slab, ultimately 12.8 A the uppermost bridging oxygen atom to the lowest bridging oxygen atom, after relaxation) for a system with four O– Sn2O2–O layers. The surface energy changed only negligibly on the addition of further O–Sn2O2–O layers. Slab calculations in CRYSTAL03 are fully two-dimensional, so a vacuum gap is not required. The planar reduced surface was modelled by removing all bridging oxygen ions from
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the stochiometric surface; this surface is used as the reference for all adsorption energies. Starting charges were set to 1 for O and +2 for Sn. The isolated oxygen molecule was described using the same basis set as that used for the surface. Preliminary calculations correctly reproduced the triplet ground state with ˚ and binding energy of 5.13 eV a bond length of 1.22 A which are in excellent agreement with the observed values ˚ and 5.14 eV [70]. An isolated O molecule was of 1.21 A 2 also modelled for comparison with adsorbed molecular ˚ , in species, and predicted to have a bond length of 1.36 A reasonable agreement with the experimental value of ˚ [70]. 1.34 A A series of adsorption ‘scenarios’ were then generated by placing adsorbate oxygen atoms (as molecules or individually) symmetrically with respect to the double-sided slab, and relaxing the whole structure. The term ‘scenario’ is adopted to distinguish these hypothetical placements of oxygen atoms from real-life adsorbates that are observed in experiments. The latter are referred to strictly as ‘species’ in this study. A very wide variety of possible scenarios can be imagined, with atomic or molecular adsorption, and with adsorbed molecules placed side-on or end-on to the surface. However, these are not useful if they do not take into account the constraints provided by experimental data (as discussed in Section 2). Scenarios were therefore selected which conformed to these constraints (taking into account calculated relaxations in the SnO2 surface). Only these scenarios are reported in this study. As discussed previously, the planar reduced surface is used in this study as a model for the partially reduced surfaces at which oxygen adsorption takes place. Similarly, the scenarios reported in this study are models of the real-life adsorbed species. Their accuracy is limited by the differences between the planar reduced surface and the reduced surfaces used in experiments and applications. In this spirit, the scenarios are also considered at maximum surface coverage. Usually this implies full surface coverage of oxygen, although in some cases the accompanying surface reconstructions were only predicted at half coverage. This represents another approximation, but it is hoped that these model scenarios still capture much of the essential features of the observed adsorbate species, though in a simplified physical picture. All calculations were run in spin-polarised mode, and spin distributions were hence also evaluated. Spin was not constrained in the self-consistent solution process. Mulliken population analysis [71] was performed. BSSE was estimated using the counterpoise method. Adsorption energy per oxygen molecule for a given scenario is calculated from the reference of an unadsorbed surface and a free oxygen molecule using the formula [72]: Eads ¼ ðnEO2 þ Eslab E½nO2 =slabÞ=n: Four adsorption scenarios were considered as models of the adsorbate species 1–4; these are correspondingly labelled scenarios 1–4. They are, respectively, an oxygen molecule coordinated symmetrically to Sn5c (with full
coverage); an oxygen molecule coordinated, asymmetrically, to every other Sn5c centre in a 1 2 unit cell; an oxygen atom coordinated to Sn5c with full coverage; and a molecule with a ‘twisted’ geometry, coordinated to two adjacent Sn4c centres (inspired by the similar scenario proposed by Oviedo and Gillan [58]). Schematic representations of these scenarios are shown in Fig. 3a–d. These do not reflect the relaxations of the scenarios from ideal geometry. These are depicted at unrelaxed geometries, for example scenario 2 is not in fact simply a half coverage version of scenario 1, the difference lying in the detail of the relaxations. The basic planar reduced 1 1 unit cell with four layers contains 22 atoms. There are 26 atoms per unit cell in scenario (a), 48 in (b), 24 in (c), and 48 in (d). 4. Results and discussion The computed data for each of the adsorption scenarios are presented in Table 1 (local geometries and adsorption energies) and Table 2 (population analysis). Where appropriate, data for the stochiometric surface and the unadsorbed planar reduced surface are included for comparison. It should also be noted that scenarios 1 and 2 both display excess spin density at the oxygen adsorbate. The adsorbate is symmetrically placed in scenario 1 but not in scenario 2, and similarly the spin distribution is symmetric in 1 but not in 2. In scenario 3, there is spin polarisation of the underlying substrate, but not on the adsorbate species. Scenario 4 displays no spin density whatsoever. These adsorption scenarios can be compared directly to the observed adsorbate species (1–4) discussed above. Scenario 1 has an adsorption energy of 0.58 eV, in close agreement with the species 1 adsorption energy of 0.52 eV. It is also symmetric (a symmetrically distributed spin density) which is consistent with the ESR data for species 1. Also, the adsorbate is localised at Sn5c. Species 1 is considered from the resemblance in ESR data ([40], and see discussion in Section 2) to be similar in structure to species 2, which is known from XPS and UPS data [50] to be localised at Sn5c. Scenario 2 has an adsorption energy of 1.09 eV in close agreement with the species 2 adsorption energy of 1.05 eV. In agreement with observations of species 2 it is localised at Sn5c and resembles the model scenario for species 1 in structure (although the adsorbate is not symmetric in this case). It has unpaired spin density, and is hence capable of giving an ESR signal. As suggested by the results of Chon and Prater [15], it is a molecular adsorbate. As species 2 seems to be the species that has been labelled as ‘O 2 ’ in research on sensor theory over many years, it is worth examining to what extent this label is justified for the scenario 2 model presented here. The charge population is indeed 0.99 |e| but the O–O separation of ˚ is much larger than the calculated vacuum O bond 1.57 A 2 ˚ . A description of this species as a somelength of 1.36 A what modified version of the gas phase O 2 ion is strongly supported by the data presented here.
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Fig. 3. Schematic representations of adsorption scenarios 1–4, represented by (a)–(d), respectively. Unit cells are represented by black boxes. (a) Oxygen molecule coordinated symmetrically at Sn5c, molecular axis aligned in the 1 1 0 direction. (b) Oxygen molecule coordinated asymmetrically to alternate Sn5c in the 1 1 0 direction, 1 1 0 direction. Relaxations from ideal geometry not shown. (c) Oxygen atom coordinated to Sn5c, full surface coverage. (d) Oxygen molecule in a ‘twisted’ geometry, coordinated to two adjacent Sn4c centres.
Table 1 Inter-ionic distances and adsorption energies (per gas phase oxygen molecule) for the various scenarios ˚) ˚) Scenario O–O (A Sn5c–O (A
˚) Sn4c–O (A
Adsorption energy (eV)
Stochiometric surface (healing bridging vacancies) Scenario 1 – molecule at Sn5c Scenario 2 – molecule at alternate Sn5c, 1 2 Scenario 3 – atom at Sn5c Scenario 4 – ‘twisted’ molecular coadsorption to adjacent Sn4c
– – – – 2.33
9.4 0.58 1.09 1.61 1.91
– 1.46 1.57 – 1.92
– 2.17 2.15 2.01 –
The separations of molecular species from Sn centres are taken from the centre of the O–O bond.
Table 2 Mulliken population-derived charges Scenario
Charge on adsorbate species (|e|)
Charge at Sn5c (|e|)
Charge at Sn4c (|e|)
Stochiometric surface Planar reduced surface Scenario 1 – molecule at Sn5c Scenario 2 – molecule at alternate Sn5c, 1 2 Scenario 3 – atom at Sn5c Scenario 4 – ‘twisted’ molecular coadsorption to adjacent Sn4c
0.975 (bridging O) – 0.63 0.99 0.59 1.54
+2.37 +2.33 +2.39 +2.39/+2.29 +2.37 +2.32
+2.42 (Sn6c) +1.84 +2.33 +1.98 +2.18 +2.19
Where two numbers are separated by a slash, the first is the centre in the cell adjacent to the adsorbate, and the second is the centre directly coordinated to the adsorbate.
Scenario 3 has an adsorption energy of 1.61 eV. This is a monatomic and the desorption process will be of secondorder so a direct comparison with the Redhead adsorption
energy deduced from the TPD data is not valid. Nevertheless, scenario 3 is more stable than scenarios 2 and 1, which is qualitatively consistent with the order of desorption ob-
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served in the TPD experiment. The monatomic nature of scenario 3 is consistent with the kinetic studies of Chon and Prater. A small spin polarisation of the surfaces occurs but none of the spin density is localised on the adsorbate ion, consistent with the ESR data [41]. Scenario 3 is therefore assigned as the model for species 3. The question again arises as to whether scenario 3 justifies the ‘O’ label that has been previously attached to species 3. Since it has a charge of 0.6|e| and no spin density (which would be expected at an isolated O species), the answer is, once again, that the label is partially justified. Scenario 4 has an adsorption energy of 1.91 eV, which is within the range (1.7–2.3 eV) of values reported for the adsorption energy of species 4. No unpaired spin density appears, and the adsorbate is coordinated to Sn4c centres. This scenario is hence assigned as the model for species 4. These four model scenarios lead to some general conclusions about oxygen adsorption on SnO2 (and perhaps adsorption of other oxidising gases). In line with experiment (especially the STM data [24–26]), the planar reduced surface has generally higher electron population than the stochiometric surface, and in particular electron population is localised at the Sn4c centre. The oxygen molecule coordinated to the Sn centres of low coordination (Sn4c) (scenario 4) is more strongly bonded to the surface and is associated with greater charge transfer from the surface than molecules coordinated to the Sn5c centres (scenarios 1 and 2). This species also has a longer O–O bond length, and hence a weaker intramolecular bond. The same combination of charge transfer, strong bonding and a weakened intramolecular bond is evident in adsorption scenarios with lower surface coverages. For example, scenario 2 is more strongly adsorbed and extracts more charge than scenario 1, but has a weaker intra-molecular bond. Finally, adsorption at either centre appears to deplete charge density from Sn4c, although unsurprisingly this effect is larger for adsorbates directly coordinated to Sn4c. The general picture that emerges from this data is that the binding energy of a given species is determined by the degree to which it is able to accept transfer of weakly bound electron density from the reduced surface. This picture is in agreement with the lack of adsorption at the stochiometric surface [1]. In the case of oxygen molecules, the charge is transferred into antibonding orbitals and stronger binding to the surface is accompanied by a weakening of the molecular bond. The weakly bound charge of the surface is mostly, but not strongly, localised at the Sn4c centre. Thus, adsorption at the Sn5c centre can occur and involves charge transfer from the neighbouring Sn4c centre. The governing role of charge transfer from the surface is revealed by the stability of each species. Adsorption is strongest to Sn4c (in scenario 4), weaker to alternate Sn5c centres (scenario 2), and even weaker when all Sn5c centres are coordinated (scenario 1). Finally, the fact that the more strongly bonded scenarios (including the stochiometric surface, with the bridging atom as the ‘adsorbate’) model those species which require the highest temperatures to
form suggests that the kinetic barrier preventing the most stable adsorbates from forming is also correlated to the strength of adsorption. 5. Summary We have used DFT to calculate four scenarios for the placement of oxygen on the planar reduced SnO2 (1 1 0) surface. By comparing our own results with various experimental results, these scenarios have been assigned as models for the four adsorbate species which form at various different adsorption temperatures on the reduced SnO2 surface. We have hence proposed geometries and some electron distributions for those species. The consistency between the scenarios suggested in this study and experimental data is a significant improvement on that achieved in previous studies that were reviewed recently review by Gurlo [17]. However, the role of the planar reduced 1 1 0 surface as an approximate model for experimentally encountered reduced surfaces, and hence of these scenarios as approximate models for the species, is emphasized. Acknowledgements MH is grateful to the Nuffield Trust for funding the earlier part of this work via an Undergraduate Research Bursary. The authors are thankful to Barbara Montanari, Adrian Wander and Jennifer Chan for useful discussions, to Barry Searle for making the computational calculations possible, and to Jason Smith for helpful comments on the manuscript of the paper. References [1] V.E. Henrich, P.A. Cox, The Surface Science of Metal Oxides, Cambridge University Press, Cambridge UK, 1994. [2] M.J. Madou, S.R. Morrison, Chemical Sensing with Solid State Devices, Academic Press, Boston MA, 1989, Chapters 1–3, p. 5. [3] T. Seiyama, A. Kato, K. Fujiishi, M. Nagatani, Anal. Chem. 34 (1962) 1502. [4] K. Ihogura, J. Watson, Stannic Oxide Gas Sensors, CRC Press, Tokyo, 1993. [5] O.V. Safonova, G. Delabouglise, B. Chenevier, A.M. Gaskov, M. Labeau, Mater. Sci. Eng. C 21 (2002) 105. [6] P. Ivanov, E. Llobet, X. Vilanova, J. Brezmes, J. Hubalek, X. Corrieg, Sensor Actuat. B 99 (2004) 201. [7] W.J. Moon, J.H. Yu, G.M. Choi, Sensor Actuat. B 87 (2002) 464. [8] A. Heilig, N. Barsan, U. Weimar, W. Gopel, Sensor Actuat. B 58 (1999) 302. [9] A. Cabot, A. Vila, J.R. Morante, Sensor Actuat. B 84 (2002) 12. [10] M. Sauvan, C. Pijolat, Sensor Actuat. B 58 (1999) 295. [11] N. Yamazoe, Y. Kurokawa, T. Seiyama, Sensor Actuator 4 (1983) 283. [12] K.R. Han, C.S. Kim, H.J. Koo, D.I. Kang, J. He, J. Electroceram. 10 (2003) 69. [13] B.P.J. de Lacy-Costello, R.J. Ewen, N.M. Ratcliffe, P.S. Sivanand, Sensor Actuat. B 92 (2003) 159. [14] J.H. Yu, G.M. Choi, Sensor Actuat. B 61 (1999) 59. [15] H. Chon, C.D. Prater, Discuss. Faraday Soc. 41 (1966) 381. [16] K.M. Saunier, J. Catal. 9 (1967) 331. [17] A. Gurlo, Chem. Phys. Chem. 7 (2006) 2041.
M. Habgood, N. Harrison / Surface Science 602 (2008) 1072–1079 [18] E. de Fresart, J. Darville, G.M. Gilles, Surf. Sci. 126 (1983) 518. [19] E. de Fresart, J. Darville, G.M. Gilles, Appl. Surf. Sci. 11/12 (1982) 637. [20] E. de Fresart, J. Darville, G.M. Gilles, Solid State Commun. 37 (1981) 13. [21] J.W. Erickson, S. Semancik, Surf. Sci. 187 (1987) L658. [22] D.F. Cox, T.B. Fryberger, S. Semancik, Phys. Rev. B 38 (1988) 3072. [23] D.F. Cox, T.B. Fryberger, S. Semancik, Surf. Sci. 224 (1989) 121. [24] F.H. Jones, R. Dixon, J.S. Foord, R.G. Egdell, J.B. Pethica, Surf. Sci. 376 (1997) 367. [25] C.L. Pang, S.A. Haycock, H. Raza, P.J. Moller, G. Thornton, Phys. Rev. B 62 (2000) R7775. [26] M. Sinner-Hettenbach, M. Gothelid, J. Weissenrieder, H. von Schenck, T. Weiss, N. Barsan, U. Weimar, Surf. Sci. 477 (2001) 50. [27] P.A. Cox, R.C. Egdell, C. Harding, W.R. Patterson, P.J. Tavener, Surf. Sci. 123 (1982) 179. [28] I. Manassisdis, J. Goniakowski, L.N. Kantorovich, M.J. Gillan, Surf. Sci. 339 (1995) 258. [29] J. Goniakowski, M.J. Gillan, Surf. Sci. 350 (1996) 145. [30] J. Goniakowski, J.M. Holender, L.N. Kantorovich, M.J. Gillan, J.A. White, Phys. Rev. B 53 (1996) 957. [31] T.T. Rantala, T.S. Rantala, V. Lantto, Surf. Sci. 420 (1999) 103. [32] T.T. Rantala, T.S. Rantala, V. Lantto, Mater. Sci. Semicond. Process 3 (2000) 103. [33] J. Oviedo, M.J. Gillan, Surf. Sci. 463 (2000) 93. [34] J. Oviedo, M.J. Gillan, Surf. Sci. 467 (2000) 35. [35] J. Oviedo, M.J. Gillan, Surf. Sci. 513 (2002) 26. [36] A. Bouzoubaa, A. Markovits, M. Calatayud, C. Minot, Surf. Sci 583 (2005) 107. [37] M. Batzill, K. Katsiev, J.M. Burst, U. Diebold, A. Chaka, B. Delley, Phys. Rev. B 72 (2005) 165414. [38] M. Batzill, U. Diebold, Prog. Surf. Sci. 75 (2005) 47. [39] J.H.C. van Hoof, J. Catal. 11 (1968) 277. [40] P. Meriaudeau, C. Naccache, A.J. Tench, J. Catal. 21 (1971) 208. [41] J.H. Lunsford, Catal. Rev. 8 (1973) 135. [42] M. Che, A.J. Tench, Adv. Catal. 32 (1983) 1. [43] Y. Mizokawa, S. Nakamura, Jpn. J. Appl. Phys. 14 (1975) 779. [44] Y. Mizokawa, S. Nakamura, Jpn. J. Appl. Phys. 46 (1977) 580. [45] M. Iwamoto, Y. Yoda, N. Yamazoe, T. Seiyama, J. Phys. Chem. 82 (1978) 2564. [46] N. Yamazoe, J. Fuchigami, M. Kishikawa, T. Seiyama, Surf. Sci. 86 (1979) 335. [47] S.C. Chang, J. Vac. Sci. Technol. 17 (1980) 366. [48] J.P. Joly, L. Gonzalez-Cruz, Y. Arnaud, Bull. Soc. Chim. Fr. 1 (1986) 11.
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Surface Science 602 (2008) 1072–1079 www.elsevier.com/locate/susc
An ab initio study of oxygen adsorption on tin dioxide Matthew Habgood a,*, Nicholas Harrison b a
QIP IRC Group, University of Oxford, Department of Materials, Parks Road, Oxford OX1 3PH, United Kingdom b Department of Chemistry, Imperial College London, Exhibition Road, SW7 2AZ, United Kingdom Received 24 October 2007; accepted for publication 7 January 2008 Available online 24 January 2008
Abstract In spite of detailed experimental and theoretical studies, a definitive model of oxygen adsorption on the surface of SnO2 has yet to emerge. In this study, density functional theory (DFT) calculations were performed to simulate various potential scenarios for oxygen placement on the planar reduced SnO2 (1 1 0) surface. Models for four adsorbate species that have been experimentally observed are hence proposed. Most importantly, these include the species labelled as ‘O 2 ’ and ‘O ’ in classical gas sensor theory, which are directly concerned with the gas sensing action of SnO2. Ó 2008 Elsevier B.V. All rights reserved. Keywords: Ab initio quantum chemical methods and calculations; Density functional calculations; Adsorption; Surface electrical transport; Oxygen; Tin oxides; Semiconducting surfaces
1. Introduction Tin dioxide is a wide band gap (3.6 eV) n-type semiconductor with rutile bulk structure [1]. Self-doping occurs via oxygen vacancies. It has numerous applications in the sensing of reducing gases and in the catalysis of hydrocarbon combustion [2]. Used in the earliest reducing – gas sensor research [3,4], SnO2 continues to be the basis for much contemporary sensor development [5–14]. The first stage of the reducing-gas sensing action is the preadsorption of oxygen onto a reduced SnO2 surface [2]. The forms in which oxygen adsorbs, and the effect that this has on the electronic structure and geometry of the reducing surface, are only understood in the most general terms. It is apparent that a deeper understanding of the adsorption, preferably at an atomistic and quantum mechanical level, would provide a basis for a more detailed characterisation of sensing action [9]. This study aims to develop such an understanding. The basis of gas sensing behaviour in SnO2 is the fall in surface conductivity observed upon adsorption of oxygen *
Corresponding author. Tel.: +44 7769867122. E-mail addresses: [email protected] (M. Habgood), [email protected] (N. Harrison). 0039-6028/$ - see front matter Ó 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.susc.2008.01.017
[2]. Within the classic theory of gas sensing, this results from the extraction of conduction electrons by the adsorbate species. Localised trap states are formed high in the band gap, extracting electrons from the conduction band in the surface region [2]. The most widely used model of this process was developed in the 1960s, based on the kinetic studies of Chon et al. [15] and others [16]. Oxygen ionosorbs onto the surface, extracting conduction electrons. Localised trap states form in the band gap, ‘bending’ the bands in the surface region and forming a barrier to conduction. Two ionosorbate species are assumed to form. One is a superoxo species, O 2 , which does not react with reducing gasses. The other is an atomic ion, O, that reacts rapidly with reducing gasses and hence is responsible for the sensing action of these gasses. The sequence of reactions that forms the adsorbates is thought to be: O2gas ! O2physisorbed O2phys þ e ! O 2 O 2 þ e ! 2O
As has been pointed out in one recent review [17], however, experimental data (to be discussed below) suggest that these species cannot simply be treated as gas-phase
M. Habgood, N. Harrison / Surface Science 602 (2008) 1072–1079
superoxo and atomic ions that adsorb onto SnO2 and move around freely. Nevertheless this model may be viewed as a useful but limited guide to the surface processes of oxygen on SnO2 which makes no reference to, for example, the placement or geometry of the oxygen species. Motivated by the importance of oxygen adsorption processes to the function of any SnO2 based sensing device, the current work therefore aims to use DFT calculations to generate more accurate models of the oxygen adsorbate species that form on SnO2, as judged by correspondence with the available experimental evidence. 2. Experimental and computational background A number of structurally different SnO2 surfaces may be prepared, which may be expected to display differing adsorption behaviours. Nevertheless, most experimental studies and sensing devices have been carried out using polycrystalline surfaces, such as those prepared by sputtering. These are the surfaces of interest in this study. Of the crystal faces of SnO2, (1 1 0) is the most stable [1], and is expected to be a major component of such polycrystalline surfaces. Beyond this, they have been characterised electronically by X-ray photoelectron spectroscopy (XPS), ultraviolet photoelectron spectroscopy (UPS) and conductivity measurements [18–23], compositionally by auger electron spectroscopy (AES) and ion scattering spectroscopy (ISS), and structurally by low energy electron diffraction (LEED) [21–23]. Scanning tunnelling microscopy (STM) studies have also been performed [24–26]. Although these studies have not defined an unambiguous structure for the polycrystalline SnO2 surface, a number of conclusions can be drawn. Annealing at >800 K reliably produces a 1 1 reconstruction with significant surface conductivity. The conductivity will fall following oxygen adsorption. There are two types of oxygen vacancy, which are thought to result from in-planar and superplanar (‘bridging’) oxygen atoms, and seem to be irregularly distributed. Here, ‘planar’ refers to the plane of the SnO2 surface. The bridging oxygen vacancy is associated with a localisation of excess charge at neighbouring tin atoms [27]. Various computational studies have attempted to model such surfaces [28–37]. Most significantly, the studies of Oviedo and Gillan [34], Bouzoubaa et al. [36], and Batzill et al. [37] have confirmed the likelihood of mixed bridging and in-planar vacancy formation at high levels of oxygen extraction. These studies have largely focused on the 1 1 0 surface, motivated by its high stability. A recent review of tin oxide surfaces is found in Ref. [38]. It is necessary at this point to define the terminology encountered in discussions of the SnO2 (1 1 0) surface and its planar reduced reconstruction. In the 1 1 0 direction SnO2 can be seen as a series of three-atom-deep layers. Each unit cell of such a layer takes the form O–Sn2O2–O. The 1 1 0 surface is outermost of these layers. At this surface, the atoms with two-coordination in the outermost layer of oxygen are referred to as ‘bridging’ oxygen atoms;
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removal of one creates a ‘bridging vacancy’. Removal of oxygen atoms in the last Sn2O2 plane creates an ‘in-plane vacancy’, while removal of an atom from the next plane of oxygen creates a ‘sub-bridging’ vacancy. The bridging oxygen atoms coordinate to six-coordinated tin atoms, denoted Sn6c. The second tin atom in each layer is five coordinate, denoted Sn5c. This (stochiometric) surface is sometimes also referred to as the ‘oxidised’ surface. Fig. 1 shows this surface. The so-called ‘planar reduced’ surface is generated by removing all the bridging oxygen atoms from the stochiometric surface. This gives one bridging vacancy per unit cell, and reduces the coordination of six-coordinated tin atoms to four; these centres are then denoted Sn4c. Fig. 2 shows this surface. The challenge of interest, though, is to model oxygen adsorbate species on SnO2. Numerous experimental studies have addressed this subject. Although they have not provided a definitive picture of oxygen adsorption, they have provided a number of facts about the adsorbate species. Any attempt to provide a model of oxygen adsorption must be in agreement with these facts. The relevant studies include the electron spin resonance (ESR) and reactive gas experiments of van Hoof [39]; the low temperature ESR work by Meriaudeau et al. [40]; the study of ESR data by Lunsford [41] and the later review by Che and Tench [42]; the combined ESR, conductivity, and temperature programmed desorption (TPD) measurements of Mizokawa et al., Iwamoto et al., and Yamazoe et al. [43–46]; the temperature dependent conductivity and ESR study of Chang [47]; the TPD investigation of Joly et al. [48]; the TPD work of Shen et al. [49]; the XPS and UPS study of
Fig. 1. The SnO2 (1 1 0) stochiometric surface, ‘top’ and ‘side’ views. The black box represents a unit cell. Diagram is not to scale.
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Fig. 2. The SnO2 (1 1 0) planar reduced surface, side view. Diagram is not to scale.
Nagasawa et al. [50]; and the more recent TPD and conductivity measurements of Saukko et al. [51]. Although they were carried out on ZnO, the experiments of Chon and Prater [15] should also be taken into account. Species adsorbed on ZnO are expected to qualitatively resemble those adsorbed on SnO2. Combining data from conductivity and Hall effect measurements, they determined that two species adsorbed on ZnO in the temperature range 473–573 K. One predominated at lower temperatures, and withdrew many fewer ‘free’ (i.e. conduction band) electrons from the surface than the other, which predominated at higher temperatures. Importantly, kinetic studies suggested that the higher temperature species was monatomic. These conclusions should apply qualitatively to adsorption on SnO2. A note is important about the treatment of the conclusions of Nagasawa et al. [50] in the current work. On the basis of their UPS and XPS data, Nagasawa et al. concluded that two species of oxygen adsorbate are found following adsorption at lower temperatures, 298–473 K, and that these are both localised at Sn4c centres. It was further concluded that a different adsorbate species formed following adsorption at 573–673 K, and that this was localised at the Sn5c centre. Re-examination of the data they present indicates an alternative explanation. Nagasawa et al. are correct to state that their data indicates the presence of two species at low adsorption temperatures, and a different species following adsorption at higher temperatures. However, it was also concluded in the current work that their data demonstrate the lower temperature species are localised at the Sn5c centre and the higher temperature species is localised at the Sn4c centre, rather than the reverse conclusion reached by the original authors. This study follows Nagasawa et al. in discussing their results in terms of the planar reduced surface. From examination of the experimental works listed above, it was concluded that four different oxygen adsor-
bate species can form on the reduced SnO2 surface during adsorption at different temperatures. If the adsorbed species can be expected to undergo first-order desorption (that is, if it is molecular), an adsorption energy can be estimated from the temperature of the corresponding TPD peak using the Redhead formula [52]. Little adsorption is possible on the stochiometric surface [1]. The first species is formed following very low temperature adsorption (<200 K). It is molecular, symmetric, and has a Redhead adsorption energy of 0.52 eV [48]. This species will be labelled adsorbate 1. Close agreement in ESR signals suggests that this will resemble the second species in electronic structure. The second species is formed following adsorption at around room temperature (298 K). It is localised at Sn5c, and close agreement in ESR signals suggest that it will resemble adsorbate 1 in electronic structure although it will not necessarily be symmetric. Its presence or absence is not associated with large changes in conductivity, and analogy with the results of Chon et al. [15] suggests that it will be molecular. Redhead adsorption energies are around 1.05 eV [43–48]. This species will be labelled adsorbate 2. The third species is formed following adsorption at 423 K. It is associated with an ESR signal, but unlike the first two species, it can be shown that the electron spin is localised away from the oxygen adsorbate in this case [41]. It is localised at Sn5c, and analogy with the kinetic results of Chon et al. [15] suggests that it will be atomic. Given this, the use of a Redhead adsorption energy is not justified. The species is associated with a fall in conductivity relative to the unadsorbed surface. This species will be labelled adsorbate 3. The fourth species is formed following adsorption at around 673 K, depending on the exact SnO2 surface prepared. It is associated with lowered conductivity relative to the unadsorbed surface, but is ESR inactive. It is localised at Sn4c, and has a Redhead adsorption energy of between 1.7 and 2.3 eV [46,48] in different studies. This species will be labelled adsorbate 4. It has also been noted that heating a reduced SnO2 surface at 773 K under sufficient pressure of oxygen (130 Pa) [22] will heal all vacancies, oxidising it. It is also apparent that the adsorbate species that form on the SnO2 surface are heavily dependent on adsorption temperature, and that more stable species form at higher adsorption temperatures. It must be concluded that there is a significant kinetic factor in the formation of these adsorbate species, and that the more stable species also have higher kinetic barriers to their formation. Hence the highly stable oxidised surface requires high temperatures to be observed; and the (more stable) adsorbate 4 only forms in preference to (for example) adsorbate 1 if the temperature is high enough to overcome the kinetic barrier to its formation. There have been a number of previous theoretical studies of the adsorbed oxygen species on SnO2 [53–61]. In many studies the planar reduced 1 1 0 surface is used as the model for the reduced surface. The planar reduced sur-
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face has bridging oxygen vacancies and is a 1 1 reconstruction (in common with the experimentally observed species), but can be modelled using a small unit cell, making it desirable for computational modelling. However, Oviedo and Gillan’s assertion [35] that the experimentally observed 1 1 reconstruction is ‘usually interpreted’ as the planar reduced surface is not supported in the literature. Nonetheless, the planar reduced surface is a sensible choice for computational modelling, and was adopted for this study. The planar reduced surface does not include the in-plane oxygen vacancies that have been theoretically predicted [34,36,37] and experimentally observed [18–26] on reduced SnO2 1 1 0 surfaces, and is therefore not an exact model of real-life SnO2 surfaces. Two considerations inform its use in this study as a model surface. Firstly, it is clear that modelling of oxygen adsorption at SnO2 surfaces must include vacancies of some sort. A combination of conduction studies, UPS and XPS [18–23,50] has established that adsorbed oxygen atoms interact with a combination of bridging and in-plane oxygen vacancies, and that it is this interaction that leads to changes in conductivity which form the basis of gas detecting action. It is also known that full oxidisation of SnO2 1 1 0 surfaces to a stochiometric form requires relatively high temperatures and pressures (as discussed above, and [22]). The SnO2 surfaces that carry out gas sensing action, it must be concluded, are not prepared under such conditions, are partially reduced, and contain oxygen vacancies. As established, it is these that lead to oxygen adsorption and gas sensing action. Conversely, it has been established that fully stochiometric SnO2 1 1 0 surfaces do not interact with oxygen [1]. This is supported by some modelling [58], although Slater et al. [57] predict oxygen adsorption at a SnO2 1 1 0 surface, and Levy and Pagnier [61] consider this situation (without comparison to alternatives, however). The latter two studies were carried out at a lower level of theory (the LDA DFT functional) than the former (a GGA functional), and their divergence from experiment seems to indicate that they are mistaken. Overall, the literature indicates that oxygen vacancies are responsible for oxygen adsorption at the SnO2 1 1 0 surface. Secondly, inclusion of in-plane oxygen vacancies requires a large unit cell for computational calculations, since the inclusion of an in-plane vacancy in every 1 1 unit cell would produce a surface layer of tin metal for which there is no experimental evidence. The use of the planar reduced surface therefore provides a computationally cheap model for the partially reduced surface, which still includes the oxygen vacancies that are essential to understanding the adsorption of oxygen. The presence of oxygen vacancies is not fundamental in the adsorption of non-oxygen species, and the stochiometric surface may therefore be used as a model surface when considering such adsorbates [62,63]. Oviedo and Gillan [58] presented a comprehensive assignment of the observed species to calculated adsorption scenarios. As with other studies, though, these did not fully
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match the experimental facts listed above, and it has been noted [17] that there is a gulf between computational and experimental results in this area. Ref. [57] assigns adsorbate 1 to an oxygen molecule placed at Sn5c with the molecular axis tilted at 70o to the vertical in the 1 1 0 direction, and adsorbates 2 and 3 as an oxygen molecule symmetrically bonded to two adjacent Sn4c centres, with and without the presence of adsorbate 1 respectively. However, as previously noted, adsorbate 1 is in fact symmetric, and adsorbates 2 and 3 are localised at Sn5c, rather than Sn4c. Additionally, adsorbate 3 is atomic, rather than molecular. Sensato et al. [59] have shown that DFT [64] calculations with the B3LYP exchange-correlation functional [65] reproduce accurate electronic structure calculations for SnO2 (for example, giving a band gap of 3.3 eV as compared to an experimental value of 3.6 eV [1]). This finding is in line with previous findings of the authors which demonstrated that the hybrid exchange approach reproduces the electronic structure of a variety of materials far better than local or gradient corrected functionals [66]. 3. Methodology All calculations were performed using the CRYSTAL03 software [67]. The crystalline orbitals are expanded in an atom centred basis set of Gaussian type primitives. A basis set employing different numbers of Gaussians for different core shells in the sequence [9/7/6/3] and a two non-fixed Gaussians with a polarisation function for the valence shell for Sn, and a more straightforward 8–411* set for O, was adopted [68]. Electronic exchange and correlation were approximated using the hybrid exchange formalism as implemented in the B3LYP [65] functional which is generally more reliable than the local or gradient corrected functionals for describing the ground state energetics and electronic structure of insulating solids [66,69]. The convergence criterion on energy integrals was set to 106 Hartrees, with 9 k-points (3 3 1) in the irreducible Brillouin zone. Preliminary calculations of the electronic structure of the bulk crystal at the lattice constants ˚ with u = 0.3058, produced a a = 4.815 and c = 3.272 A band gap of 3.3 eV in agreement with that observed and the previous findings of Sensato et al. [59]. The surface was modelled as a symmetric slab periodic in two-dimensions and adsorbate atoms were introduced symmetrically on both surfaces. The size of the surface unit ˚) cell was fixed at bulk values (a = 4.815 and c = 3.272 A and the internal coordinates of the atoms were fully relaxed. The computed surface energy was converged with re˚ (from spect to the thickness of the slab, ultimately 12.8 A the uppermost bridging oxygen atom to the lowest bridging oxygen atom, after relaxation) for a system with four O– Sn2O2–O layers. The surface energy changed only negligibly on the addition of further O–Sn2O2–O layers. Slab calculations in CRYSTAL03 are fully two-dimensional, so a vacuum gap is not required. The planar reduced surface was modelled by removing all bridging oxygen ions from
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the stochiometric surface; this surface is used as the reference for all adsorption energies. Starting charges were set to 1 for O and +2 for Sn. The isolated oxygen molecule was described using the same basis set as that used for the surface. Preliminary calculations correctly reproduced the triplet ground state with ˚ and binding energy of 5.13 eV a bond length of 1.22 A which are in excellent agreement with the observed values ˚ and 5.14 eV [70]. An isolated O molecule was of 1.21 A 2 also modelled for comparison with adsorbed molecular ˚ , in species, and predicted to have a bond length of 1.36 A reasonable agreement with the experimental value of ˚ [70]. 1.34 A A series of adsorption ‘scenarios’ were then generated by placing adsorbate oxygen atoms (as molecules or individually) symmetrically with respect to the double-sided slab, and relaxing the whole structure. The term ‘scenario’ is adopted to distinguish these hypothetical placements of oxygen atoms from real-life adsorbates that are observed in experiments. The latter are referred to strictly as ‘species’ in this study. A very wide variety of possible scenarios can be imagined, with atomic or molecular adsorption, and with adsorbed molecules placed side-on or end-on to the surface. However, these are not useful if they do not take into account the constraints provided by experimental data (as discussed in Section 2). Scenarios were therefore selected which conformed to these constraints (taking into account calculated relaxations in the SnO2 surface). Only these scenarios are reported in this study. As discussed previously, the planar reduced surface is used in this study as a model for the partially reduced surfaces at which oxygen adsorption takes place. Similarly, the scenarios reported in this study are models of the real-life adsorbed species. Their accuracy is limited by the differences between the planar reduced surface and the reduced surfaces used in experiments and applications. In this spirit, the scenarios are also considered at maximum surface coverage. Usually this implies full surface coverage of oxygen, although in some cases the accompanying surface reconstructions were only predicted at half coverage. This represents another approximation, but it is hoped that these model scenarios still capture much of the essential features of the observed adsorbate species, though in a simplified physical picture. All calculations were run in spin-polarised mode, and spin distributions were hence also evaluated. Spin was not constrained in the self-consistent solution process. Mulliken population analysis [71] was performed. BSSE was estimated using the counterpoise method. Adsorption energy per oxygen molecule for a given scenario is calculated from the reference of an unadsorbed surface and a free oxygen molecule using the formula [72]: Eads ¼ ðnEO2 þ Eslab E½nO2 =slabÞ=n: Four adsorption scenarios were considered as models of the adsorbate species 1–4; these are correspondingly labelled scenarios 1–4. They are, respectively, an oxygen molecule coordinated symmetrically to Sn5c (with full
coverage); an oxygen molecule coordinated, asymmetrically, to every other Sn5c centre in a 1 2 unit cell; an oxygen atom coordinated to Sn5c with full coverage; and a molecule with a ‘twisted’ geometry, coordinated to two adjacent Sn4c centres (inspired by the similar scenario proposed by Oviedo and Gillan [58]). Schematic representations of these scenarios are shown in Fig. 3a–d. These do not reflect the relaxations of the scenarios from ideal geometry. These are depicted at unrelaxed geometries, for example scenario 2 is not in fact simply a half coverage version of scenario 1, the difference lying in the detail of the relaxations. The basic planar reduced 1 1 unit cell with four layers contains 22 atoms. There are 26 atoms per unit cell in scenario (a), 48 in (b), 24 in (c), and 48 in (d). 4. Results and discussion The computed data for each of the adsorption scenarios are presented in Table 1 (local geometries and adsorption energies) and Table 2 (population analysis). Where appropriate, data for the stochiometric surface and the unadsorbed planar reduced surface are included for comparison. It should also be noted that scenarios 1 and 2 both display excess spin density at the oxygen adsorbate. The adsorbate is symmetrically placed in scenario 1 but not in scenario 2, and similarly the spin distribution is symmetric in 1 but not in 2. In scenario 3, there is spin polarisation of the underlying substrate, but not on the adsorbate species. Scenario 4 displays no spin density whatsoever. These adsorption scenarios can be compared directly to the observed adsorbate species (1–4) discussed above. Scenario 1 has an adsorption energy of 0.58 eV, in close agreement with the species 1 adsorption energy of 0.52 eV. It is also symmetric (a symmetrically distributed spin density) which is consistent with the ESR data for species 1. Also, the adsorbate is localised at Sn5c. Species 1 is considered from the resemblance in ESR data ([40], and see discussion in Section 2) to be similar in structure to species 2, which is known from XPS and UPS data [50] to be localised at Sn5c. Scenario 2 has an adsorption energy of 1.09 eV in close agreement with the species 2 adsorption energy of 1.05 eV. In agreement with observations of species 2 it is localised at Sn5c and resembles the model scenario for species 1 in structure (although the adsorbate is not symmetric in this case). It has unpaired spin density, and is hence capable of giving an ESR signal. As suggested by the results of Chon and Prater [15], it is a molecular adsorbate. As species 2 seems to be the species that has been labelled as ‘O 2 ’ in research on sensor theory over many years, it is worth examining to what extent this label is justified for the scenario 2 model presented here. The charge population is indeed 0.99 |e| but the O–O separation of ˚ is much larger than the calculated vacuum O bond 1.57 A 2 ˚ . A description of this species as a somelength of 1.36 A what modified version of the gas phase O 2 ion is strongly supported by the data presented here.
M. Habgood, N. Harrison / Surface Science 602 (2008) 1072–1079
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Fig. 3. Schematic representations of adsorption scenarios 1–4, represented by (a)–(d), respectively. Unit cells are represented by black boxes. (a) Oxygen molecule coordinated symmetrically at Sn5c, molecular axis aligned in the 1 1 0 direction. (b) Oxygen molecule coordinated asymmetrically to alternate Sn5c in the 1 1 0 direction, 1 1 0 direction. Relaxations from ideal geometry not shown. (c) Oxygen atom coordinated to Sn5c, full surface coverage. (d) Oxygen molecule in a ‘twisted’ geometry, coordinated to two adjacent Sn4c centres.
Table 1 Inter-ionic distances and adsorption energies (per gas phase oxygen molecule) for the various scenarios ˚) ˚) Scenario O–O (A Sn5c–O (A
˚) Sn4c–O (A
Adsorption energy (eV)
Stochiometric surface (healing bridging vacancies) Scenario 1 – molecule at Sn5c Scenario 2 – molecule at alternate Sn5c, 1 2 Scenario 3 – atom at Sn5c Scenario 4 – ‘twisted’ molecular coadsorption to adjacent Sn4c
– – – – 2.33
9.4 0.58 1.09 1.61 1.91
– 1.46 1.57 – 1.92
– 2.17 2.15 2.01 –
The separations of molecular species from Sn centres are taken from the centre of the O–O bond.
Table 2 Mulliken population-derived charges Scenario
Charge on adsorbate species (|e|)
Charge at Sn5c (|e|)
Charge at Sn4c (|e|)
Stochiometric surface Planar reduced surface Scenario 1 – molecule at Sn5c Scenario 2 – molecule at alternate Sn5c, 1 2 Scenario 3 – atom at Sn5c Scenario 4 – ‘twisted’ molecular coadsorption to adjacent Sn4c
0.975 (bridging O) – 0.63 0.99 0.59 1.54
+2.37 +2.33 +2.39 +2.39/+2.29 +2.37 +2.32
+2.42 (Sn6c) +1.84 +2.33 +1.98 +2.18 +2.19
Where two numbers are separated by a slash, the first is the centre in the cell adjacent to the adsorbate, and the second is the centre directly coordinated to the adsorbate.
Scenario 3 has an adsorption energy of 1.61 eV. This is a monatomic and the desorption process will be of secondorder so a direct comparison with the Redhead adsorption
energy deduced from the TPD data is not valid. Nevertheless, scenario 3 is more stable than scenarios 2 and 1, which is qualitatively consistent with the order of desorption ob-
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served in the TPD experiment. The monatomic nature of scenario 3 is consistent with the kinetic studies of Chon and Prater. A small spin polarisation of the surfaces occurs but none of the spin density is localised on the adsorbate ion, consistent with the ESR data [41]. Scenario 3 is therefore assigned as the model for species 3. The question again arises as to whether scenario 3 justifies the ‘O’ label that has been previously attached to species 3. Since it has a charge of 0.6|e| and no spin density (which would be expected at an isolated O species), the answer is, once again, that the label is partially justified. Scenario 4 has an adsorption energy of 1.91 eV, which is within the range (1.7–2.3 eV) of values reported for the adsorption energy of species 4. No unpaired spin density appears, and the adsorbate is coordinated to Sn4c centres. This scenario is hence assigned as the model for species 4. These four model scenarios lead to some general conclusions about oxygen adsorption on SnO2 (and perhaps adsorption of other oxidising gases). In line with experiment (especially the STM data [24–26]), the planar reduced surface has generally higher electron population than the stochiometric surface, and in particular electron population is localised at the Sn4c centre. The oxygen molecule coordinated to the Sn centres of low coordination (Sn4c) (scenario 4) is more strongly bonded to the surface and is associated with greater charge transfer from the surface than molecules coordinated to the Sn5c centres (scenarios 1 and 2). This species also has a longer O–O bond length, and hence a weaker intramolecular bond. The same combination of charge transfer, strong bonding and a weakened intramolecular bond is evident in adsorption scenarios with lower surface coverages. For example, scenario 2 is more strongly adsorbed and extracts more charge than scenario 1, but has a weaker intra-molecular bond. Finally, adsorption at either centre appears to deplete charge density from Sn4c, although unsurprisingly this effect is larger for adsorbates directly coordinated to Sn4c. The general picture that emerges from this data is that the binding energy of a given species is determined by the degree to which it is able to accept transfer of weakly bound electron density from the reduced surface. This picture is in agreement with the lack of adsorption at the stochiometric surface [1]. In the case of oxygen molecules, the charge is transferred into antibonding orbitals and stronger binding to the surface is accompanied by a weakening of the molecular bond. The weakly bound charge of the surface is mostly, but not strongly, localised at the Sn4c centre. Thus, adsorption at the Sn5c centre can occur and involves charge transfer from the neighbouring Sn4c centre. The governing role of charge transfer from the surface is revealed by the stability of each species. Adsorption is strongest to Sn4c (in scenario 4), weaker to alternate Sn5c centres (scenario 2), and even weaker when all Sn5c centres are coordinated (scenario 1). Finally, the fact that the more strongly bonded scenarios (including the stochiometric surface, with the bridging atom as the ‘adsorbate’) model those species which require the highest temperatures to
form suggests that the kinetic barrier preventing the most stable adsorbates from forming is also correlated to the strength of adsorption. 5. Summary We have used DFT to calculate four scenarios for the placement of oxygen on the planar reduced SnO2 (1 1 0) surface. By comparing our own results with various experimental results, these scenarios have been assigned as models for the four adsorbate species which form at various different adsorption temperatures on the reduced SnO2 surface. We have hence proposed geometries and some electron distributions for those species. The consistency between the scenarios suggested in this study and experimental data is a significant improvement on that achieved in previous studies that were reviewed recently review by Gurlo [17]. However, the role of the planar reduced 1 1 0 surface as an approximate model for experimentally encountered reduced surfaces, and hence of these scenarios as approximate models for the species, is emphasized. Acknowledgements MH is grateful to the Nuffield Trust for funding the earlier part of this work via an Undergraduate Research Bursary. The authors are thankful to Barbara Montanari, Adrian Wander and Jennifer Chan for useful discussions, to Barry Searle for making the computational calculations possible, and to Jason Smith for helpful comments on the manuscript of the paper. References [1] V.E. Henrich, P.A. Cox, The Surface Science of Metal Oxides, Cambridge University Press, Cambridge UK, 1994. [2] M.J. Madou, S.R. Morrison, Chemical Sensing with Solid State Devices, Academic Press, Boston MA, 1989, Chapters 1–3, p. 5. [3] T. Seiyama, A. Kato, K. Fujiishi, M. Nagatani, Anal. Chem. 34 (1962) 1502. [4] K. Ihogura, J. Watson, Stannic Oxide Gas Sensors, CRC Press, Tokyo, 1993. [5] O.V. Safonova, G. Delabouglise, B. Chenevier, A.M. Gaskov, M. Labeau, Mater. Sci. Eng. C 21 (2002) 105. [6] P. Ivanov, E. Llobet, X. Vilanova, J. Brezmes, J. Hubalek, X. Corrieg, Sensor Actuat. B 99 (2004) 201. [7] W.J. Moon, J.H. Yu, G.M. Choi, Sensor Actuat. B 87 (2002) 464. [8] A. Heilig, N. Barsan, U. Weimar, W. Gopel, Sensor Actuat. B 58 (1999) 302. [9] A. Cabot, A. Vila, J.R. Morante, Sensor Actuat. B 84 (2002) 12. [10] M. Sauvan, C. Pijolat, Sensor Actuat. B 58 (1999) 295. [11] N. Yamazoe, Y. Kurokawa, T. Seiyama, Sensor Actuator 4 (1983) 283. [12] K.R. Han, C.S. Kim, H.J. Koo, D.I. Kang, J. He, J. Electroceram. 10 (2003) 69. [13] B.P.J. de Lacy-Costello, R.J. Ewen, N.M. Ratcliffe, P.S. Sivanand, Sensor Actuat. B 92 (2003) 159. [14] J.H. Yu, G.M. Choi, Sensor Actuat. B 61 (1999) 59. [15] H. Chon, C.D. Prater, Discuss. Faraday Soc. 41 (1966) 381. [16] K.M. Saunier, J. Catal. 9 (1967) 331. [17] A. Gurlo, Chem. Phys. Chem. 7 (2006) 2041.
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