Influence of Adsorbed Water on the Activation Energy of Model

Jan 5, 2017 - Two commercial (Merck and Sigma-Aldrich) and two home prepared (HP05 and HP05C) powdered TiO2 photocatalysts were investigated by fast f...
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Influence of Adsorbed Water on the Activation Energy of Model Photocatalytic Reactions Francesco Parrino, Pellegrino Conte, Claudio De Pasquale, Vito Armando Laudicina, Vittorio Loddo, and Leonardo Palmisano J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.6b11945 • Publication Date (Web): 05 Jan 2017 Downloaded from http://pubs.acs.org on January 12, 2017

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Influence of Adsorbed Water on the Activation Energy of Model Photocatalytic Reactions F. Parrino*1, P. Conte2, C. De Pasquale2, V. A. Laudicina2, V. Loddo1, L. Palmisano1

1

Dipartimento di Ingegneria Elettrica, Dipartimento di Energia, Ingegneria dell’Informazione, e

Modelli Matematici (DEIM), v.le delle Scienze, Edificio 6, 90128 – Palermo, Italy. E-mails: [email protected]; [email protected]; [email protected]. 2

Dipartimento di Scienze Agrarie e Forestali, Università degli Studi di Palermo, v.le delle Scienze,

Edificio 4, 90128 – Palermo, Italy. E-mails: [email protected]; [email protected]; [email protected]. *Corresponding author: [email protected], tel. 0039 091 238 63748.

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Abstract Two commercial (Merck and Sigma-Aldrich) and two home prepared (HP05 and HP05C) powdered TiO2 photocatalysts were investigated by fast field cycling nuclear magnetic resonance experiments in order to explore the nature of the interactions between water and the solid surfaces. The results were related to the activation energies determined at temperatures ranging from 303 to 353 K for the photocatalytic oxidation in water of three model molecules presenting different interactions with the solid surface (catechol, phenol and metylbenzoate). The photoactivity results at different temperatures were comparable to each other because the runs were carried out while keeping constant the concentration of O2 in the suspensions. The study highlights the influence of the adsorbed water on the activation energy of a photocatalytic reaction. In particular, we showed that competition between water and substrate adsorption is a determining factor in the activation energy of a photocatalytic oxidation reaction.

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1. Introduction Since the discovery of photocatalytic water splitting on a TiO2 electrode in 1972,1 TiO2 is the most widely used semiconductor in photocatalysis. Being an abundant, low-cost, and environmentally benign material, TiO2 has obtained commercial success and it has been widely used as a white pigment in sunscreens, paints, ointments and toothpastes.2 The possibility of solar light exploitation along with the non-toxicity of TiO2, makes photocatalysis in aqueous media a promising tool for environmental remediation3 and for green chemistry applications. Therefore, understanding the interaction between the photocatalyst and water appears to be of paramount importance. In fact, water interactions with TiO2 surfaces play a key role in addressing many photocatalytic processes, such as water splitting, organic syntheses and waste remediation.4-6 Generally, in the presence of irradiated TiO2, adsorbed water molecules may undergo oxidation through photogenerated holes producing reactive oxygen species which, in turn, enable photocatalytic oxidation.7 The role of water in gas-solid systems has been deeply investigated as it influences the activity of the catalytic powder. In fact, low water amounts contribute to maintain the activity of the catalyst by replacing the hydroxyl groups consumed during the reaction. Conversely, higher H2O amounts compete for the adsorption sites with target organic compounds as observed in several studies.8,9 Competition between water and organic substrates has been also hypothesized in liquid phase depending on their affinity with the catalyst surface.10 Such competition has been often invoked in order to explain rare cases of highly selective photocatalytic reactions.11 Water as co-solvent in the presence of other organic solvents is reported to enhance the mineralizing ability of the photocatalytic system.12 In other cases, water showed also poisoning effects on reactions such as in the photocatalytic sulfoxidation of alkanes.13 Despite the countless cases testifying the central importance of the interaction between water and catalyst surface in aqueous systems, only few results have been experimentally obtained on this topic. The anatase phase was in this sense only theoretically investigated.14 This task was recently approached by Conte et al.15 which, for the first time,

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experimentally proved the different behavior of adsorbed water in two commercial TiO2 samples by a physicochemical point of view. The aim of the present study is to relate the information obtained from FFC NMR relaxometry to the activation energy of a photocatalytic reaction. Plenty of hypotheses have been advanced in order to individuate the parameters influencing the activation energy in heterogeneous photocatalysis.16-18 It has been reported that temperatures between 293 and 353 K weakly influenced the oxidation rates of photocatalytic reactions.19 At lower temperatures (between 233 and 273 K) the apparent activation energy increased, whilst at temperatures higher than 353 K it became negative.16 However, at the aforementioned intermediate temperature values the activation energy reported for photocatalytic reactions are lower (few kJ·mol-1) than the ones measured for thermal reactions. In particular, Matthews20 and Okamoto et al.21 reported activation energies equal to ca. 10 kJ·mol-1 for the photocatalytic degradation of salicylic acid and phenol, respectively. Since the activation energy of OH radicals reactions with ferrocyanide ions is reported to be 13 kJ·mol-1 it was suggested that hydroxyl radical reactions may predominantly contribute to the activation energy of photocatalytic reactions.17 On the other hand, Herrmann16 suggested that the rate limiting step may be the desorption of the oxidation products. In fact, the activation energy of reactions, involving hydrogen formation on Pt modified TiO2, was found22 similar to the opposite of the hydrogen adsorption enthalpy on Pt. Kiwi18 also reported that the increase of temperature results in small changes in the quasi-Fermi level of the semiconducting powders (∆V = ca. 0.04 V) corresponding to improved interfacial electron transfer. Based on these results, it was often reported that minor changes in temperature does not influence the photocatalytic activity.19 In this paper it is proposed, on the basis of experimental evidences, that the activation energy, considered as an indirect measure of the temperature dependence of a photocatalytic reaction, is related to the dynamics of water adsorbed on the photocatalyst surface, being the morphological features of the powder and the interactions with the adsorbed molecules determining factors. 4 ACS Paragon Plus Environment

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2. Materials and Methods 2.1 Materials Commercial TiO2 samples from Merck (anatase phase) and from Sigma-Aldrich (rutile phase), and two home prepared TiO2 powders (labeled as HP05 and HP05C) were used for the present investigation. The preparation details of HP05 sample are reported elsewhere.23 Only some essential information is presented here. Briefly, the precursor solution for HP05 and HP05C was obtained by slowly adding 5 mL of TiCl4 into 50 mL of distilled water under magnetic stirring. The solution was then sealed, mixed for 12 h at room temperature and subsequently boiled at 373 K for 0.5 h. The white suspension obtained was dried at 323 K under vacuum. The powder was finally washed with distilled water and centrifuged several times until the chloride ions concentration in the washing water reached a negligible value. The sample, indicated as HP05, consisted mainly of amorphous TiO2 (ca. 92%) and crystals of anatase and rutile24 with a specific surface area (SSA) of 234 m2·g-1. The HP05C sample (ca. 44% anatase, 16% rutile and 40% amorphous, SSA: 51 m2·g-1) was obtained by calcining HP05 sample at 773 K for 4 h. All the chemicals were analytical grade and used as received without further purification. 2.2 Specific surface area measurements Specific surface area, porosity and particle size were measured by a Micromeritics Accelerated Surface Area and Porosity (ASAP 2020) apparatus with N2 as the adsorbate. 2.3 X-ray diffraction analysis X-ray diffraction (XRD) patterns of the TiO2 powders were recorded at room temperature by an Ital Structures APD 2000 powder diffractometer, using the Cu Kα radiation and a 2θ scan rate of 2°·min-1. The percentage of crystalline phases was determined with respect to a CaF2 reference according to a method described in literature.25

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2.4 Fast field cycling (FFC) NMR relaxometry 1 g of each sample (Merck, Sigma-Aldrich, HP05 and HP05C) was suspended in 3 mL of MilliQ grade water (resistivity of 18.2 MΩ⋅cm at 298 K). The suspensions were allowed to sediment overnight prior to the relaxometry investigations. The samples were put in the probe of a Stelar Smartracer fast-field-cycling relaxometer (Stelar s.r.l., Mede, PV−Italy) and analyzed at 298, 313, 333 and 343 K. The basic theory about FFC NMR relaxometry and the sequence applied for the experiments reported in this study have been already summarized in Conte and Alonzo.26 In brief, by quickly changing the intensity of an applied magnetic field, it is possible to observe the fluctuation in longitudinal relaxation time values (T1) of the observed nuclei (in this case 1H). The dispersion of the T1 values occurs when each frequency in the distribution of magnetic fields (DMF) generated by the motional fluctuations matches the Larmor frequencies (ωL) of the observed nuclei. The 1H Larmor frequency in a dynamic system as, for instance, the two dimensional random motion of water across a solid surface, is related to the frequency of the water motion. Therefore, it is possible to investigate the water dynamics in porous media by modulating the intensity of the applied magnetic field. The experimental design of FFC NMR experiments is based on both a prepolarized (PP) and a non-polarized (NP) sequence so that three steps can be recognized: polarization, relaxation and acquisition. In the PP sequence, a polarization field (BPOL) set at the ωL of 10 MHz was applied for a period of time (referred to as polarization time or TPOL) corresponding to five times the T1 estimated at this frequency. Thereafter, in the NP sequence, a relaxation field (BRLX) was applied at 1H Larmor frequency (ωL) values ranging from 0.01 to 10 MHz. Each BRLX was applied for a period τ (during which the magnetization intensity relaxes to reach a new equilibrium condition) arrayed with 16 logarithmic spaced time sets, each of them adjusted at every relaxation field in order to optimize the sampling of the decay/recovery curves. At the end of each BRLX field, a 1H 90° pulse was applied into an acquisition magnetic field (BACQ) held for a fixed time at the ωL value of 7.2 MHz. The 1H 90° pulse was needed to make magnetization observable 6 ACS Paragon Plus Environment

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and the free induction decay (FID) acquirable. A time domain of 100 µs sampled with 1000 points was applied. Field-switching time was 3 ms, while spectrometer dead time was 15 µs. For all of the experiments a recycle delay of 20 s was used. The crossover field between NP and PP sequences was approximately retrieved when the relaxation field intensity was half that of the polarization field.27

2.5 Elaboration and meaning of FFC NMR relaxometry data The longitudinal relaxation time (T1) values of the observed nuclei were obtained for each BRLX by changing the τ values as reported above. The relationship between signal intensity and τ is modeled by Equation 1: (1)

I (τ) = I 0 exp [ -(τ/T1)k ]

Here, I(τ) is the 1H signal intensity at each fixed BRLX, I0 is the 1H signal intensity at the thermal equilibrium, T1 is the average proton spin-lattice relaxation time and k is a heterogeneity parameter related to the stretching of the decay process. This function, which accounts for the large sample heterogeneity resulting in a multi-exponential behavior of the decay/recovery curves,28 can be considered as a superposition of exponential contributions, thereby describing the likely physical picture of some distribution in T1. Equation 1 has the advantage that it is able to handle a wide range of behaviors within a single model. For this reason, assumptions about the number of exponentials to be used in modeling NMRD data are not necessary. The NMRD profiles reporting the calculated longitudinal relaxation rate (R1 = 1/T1) values vs ωL were exported to OriginPro 7.5 SR6 and fitted with a Lorentzian function of the type:29,30 n

R1 = ∑ cn 1=1

τn 2 1 + (2ω Lτ n )

(2)

The number n of Lorentzians that can be included in Equation 2 without unreasonably increasing the number of parameters was determined by means of the merit function analysis.29 For the present study, n=3 was used for the mathematical fit of the NMRD profiles. The obtained six fit parameters 7 ACS Paragon Plus Environment

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(c1, c2, c3, τ1, τ2, τ3) were used to obtain an average exchange correlation time according to Equation 3:15

τ =

∑ cτ ∑c

n n

n

n

(3)

n

Notably, the six fit parameters individually taken does not possess any physical meaning, so that their single values are not reported. Conversely, their average value , as expressed by Equation 3, represents the exchange correlation time.29 This parameter is the time taken for a molecule to rotate one radian or to move a distance of the order of its own dimension.31 Longer exchange correlation times indicate slower molecular motions thereby revealing restrictions in the motional freedom degrees of the molecules. Conversely, smaller exchange correlation times express faster molecular motions.

2.6 Photocatalytic experiments Photocatalytic experiments were carried out in aqueous suspensions of the different TiO2 materials. The photoreactor had a cylindrical shape (internal diameter: 32 mm; height: 188 mm) and contained 150 mL of the aqueous suspensions. A water cooled, 1000 W medium pressure mercury lamp, positioned outside the reactor at a distance of 3 cm from the outer wall of the reactor was used as the light source. The radiation intensity impinging on the suspension was measured by a radiometer Delta Ohm DO9721 with an UVA probe; the radiation power absorbed per unit volume of the suspension was about 19 mW·mL-1. The amount of each catalyst used during the photocatalytic runs was 0.8 g·L-1 and the initial substrate (catechol, phenol or methyl benzoate) concentration was 0.5 mM. Catechol and methyl benzoate were chosen as they have a different interaction with the catalytic surface with respect to phenol (i.e. stronger and weaker adsorption, respectively). The amount of catalyst used was chosen in order to obtain the same amount of photons absorbed during each run affording comparable results. This was achieved by measuring the photon flux impinging

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the reacting mixture at different catalyst concentrations until the transmitted photon flux was virtually negligible. The temperature of the suspension was set at 303, 328 or 353 K by controlling the temperature of water circulating through the Pyrex thimble surrounding the reactor. A water condenser was placed on the top of the reactor to avoid losses of matter through evaporation. O2 and N2 were mixed through a mass-flow controller and the gaseous mixtures were continuously bubbled during the experiments. The N2 mass flow was fixed (200 mL·min−1), whereas the O2 mass-flows were 32, 44 and 50 mL·min−1 for runs carried out at 303, 328 and 353 K, respectively. Being the O2 concentration in the suspension strongly depending on the temperature, the different O2 concentrations in the gaseous flow entering the reacting mixtures at the three considered temperatures were calculated by means of the Henry law in order to ensure the same O2 concentration in the aqueous phase (5.34 mg·L−1). In this way, the temperature dependence results obtained were comparable. The lamp was switched on at time t = 0, after a dark period of 0.5 h. The substrates concentration was measured before the addition of catalyst and after the dark period in order to determine the extent of their adsorption on the catalyst surface. Samples were withdrawn at fixed times during the photoactivity runs and were immediately filtered through 0.2 µm membranes (HA, Millipore) before analysis. The quantitative determination of the substrates was performed by means of a Beckman Coulter HPLC (System Gold 126 Solvent Module and 168 Diode Array Detector), equipped with a Phenomenex Synergi 4 µm Hydro-RP 80A column at 298 K. The eluent consisted of a mixture of acetonitrile and 13 mM trifluoroacetic acid aqueous solution (20:80 volumetric ratio) and the flow rate was 0.8 mL·min−1.

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3. Results and Discussion 3.1 Conceptual background Before analyzing the results it is useful, for the sake of clarity, to briefly describe the conceptual background of this work. Two different and independent analytical procedures (FFC NMR relaxometry and analysis of the temperature dependence of the photocatalytic degradation of model substrates) have been applied in order to investigate the role of water adsorbed on the surface of a photocatalyst during a photocatalytic reaction carried out in water. The FFC NMR analysis allows to obtain information on the water dynamics on the surface of a photocatalyst. In particular, by performing the analysis at different temperatures, it is possible to determine activation energy values associated to the mobility of water on the solid surface. In other words, it is possible to quantitatively estimate how strong is the affinity of the water molecules with the surface. Higher activation energy values correspond to systems where water is moving slowly, as it strongly interacts with the solid surface. The photocatalytic degradation of three different model substrates was performed at different temperatures keeping constant the other relevant experimental conditions. Activation energy values could be obtained according to the Arrhenius model applied to the photocatalytic degradation runs. These values are not directly related to the photocatalytic activity (PA) but they express only PA temperature dependence which is mainly related to adsorption-desorption equilibria on the surface of the photocatalyst. High values of activation energy describe systems where a high energetic barrier must be overcome to allow the occurrence of the photocatalytic reaction. By comparing the values of the two different activation energies obtained through the two independent analysis it is possible to understand to which extent the water dynamics influences the activation energy of a photocatalytic reaction.

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3.2 Morphological and structural characterization Table 1 reports the specific surface areas (SSA, Brunauer-Emmett-Teller), adsorption average pore widths by using the Barrett-Joyner-Halenda (BJH) method and the particle sizes of the photocatalysts.

Table 1: Polymorphic phase, average micropores and mesopores width, specific surface area and particle size for HP05, HP05C, Sigma-Aldrich, and Merck TiO2 samples. A: anatase phase; R: rutile phase. Sample

HP05

Polymorphic

Average

Average

Specific surface

Particle size

phase

micropores

mesopores

area (SSA, BET)

[nm]

width (BJH)

width (BJH)

[m2/g]

[nm]

[nm]

1.7

6.5

234

26

2.0

20.0

51

116

A-7% R-1%

HP05C

A-44% R-16%

Sigma-Aldrich

R-100%

1.8

12.4

2.4

2500

Merck

A-100%

1.9

4.0

9.9

610

From the results in Table 1, it can be noticed that the average micropores width does not change significantly for all of the samples (standard deviation: ca. 0.2). On the other hand, the mesopores width is higher for HP05C (20.0 nm) and Sigma-Aldrich (12.4 nm) samples and lower for HP05 (6.5 nm) and Merck (4.0 nm) samples. It is worth to note that samples with higher specific surface area present lower nanoparticle size.

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3.3 Fast Field Cycling analysis Water molecules are subjected to two-dimensional random motions across solid surfaces as solid porous media are placed in the liquid.32 In particular, a water molecule remains close to the surface for a short time after which it moves away and it is replaced by another molecule coming from the bulk liquid. The distribution of the water motional frequencies is affected by the surface homogeneity of the porous medium. In fact, water confined in small sized pores is more tightly constrained than when mesopores with higher width are present. This implies that water molecules on solids with big pores stay on the surface for a shorter time before moving away into the bulk with respect to solids with small sized pores where water is more constrained. This scenario is shown in Figure 1.

τ1 τ1

τ1

τ1

τ1 ˂˂ τ2 τ2

τ2 τ2

τ2 τ2 τ2

Figure 1. Water dynamics on the surface of big sized (top) and small sized (bottom) pores. The exchange correlation time, τ, is higher in the presence of small sized pores than in the presence of big sized pores.

Figure 2 shows the nuclear magnetic resonance dispersion (NMRD) profiles retrieved at 298, 313, 333 and 343 K for HP05 (A), Merck (B) and Sigma-Aldrich (C) samples suspended in water. 12 ACS Paragon Plus Environment

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298 K 313 K 333 K 343 K

Relaxation rate (s-1)

A 100 B 10

C

1

0.01

0.1

1

10

Magnetic field (MHz)

Figure 2. NMRD profiles at 298 K, 313 K, 333 K and 343 K of HP05 (A), Merck (B) and Sigma-Aldrich (C) TiO2 powders suspended in water.

Figure 3 compares the NMRD profiles retrieved at 298, 313, 333 and 343 K for the HP05 (A) and HP05C (B) samples suspended in water.

A Relaxation rate (s-1)

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298 K 313 K 333 K 343 K

100

B 10

1 0.01

0.1

1

10

Magnetic field (MHz)

Figure 3. NMRD profiles at different temperatures of (A) HP05 and (B) HP05C TiO2 powders.

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All profiles (Figure 2 and 3) show the classical stretched Lorentzian shapes.26 In particular, the profiles retrieved for the HP05 sample at the considered temperatures were at faster R1 values than those acquired for Merck and Sigma-Aldrich (Figure 2). Furthermore, the profiles retrieved for the HP05 sample show faster R1 values than for the HP05C one (Figure 3). All of the samples revealed similar temperature dependence (longitudinal relaxation decreasing with temperature enhancement), with the exception of Merck whose profiles did not depend on temperature changes. Exchange correlation time values (τ), calculated by applying Equations (2) and (3) to all of the NMRD profiles in Figures 2 and 3, show different behavior. The τ values retrieved from the Lorentzian shape of Merck and Sigma-Aldrich samples (Figure 2) ranged from 329 to 505 and from 42 to 45 ns, respectively. On the other hand, HP05 and HP05C samples (Figure 3) show τ values in the range between 3666 - 1326 and 884 - 346 ns, respectively. Moreover, the τ values show a trend similar to that of the specific surface area (SSA) values of the samples (see Table 1). In fact, as above mentioned, water dynamics on the surface of porous media is strongly related to SSA values. In particular, calcination of a porous solid affords sintering of the particles which increases their average size causing densification of the material but also formation of voids among the bigger particles.33 In particular HP05 sample with respect to HP05C presents higher SSA and smaller particles size, but the average adsorption width of its mesopores is smaller (see Table 1). The τ values of HP05 and HP05C samples reveal different interactions with water molecules (Figure 3). The mobility of water results higher in the HP05C sample compared to the HP05 one, thus in the first case water can freely move in larger interparticles voids thereby resulting less bound with respect to the non-calcined sample. Furthermore, water molecules showed a different behavior corresponding to the degree of crystallinity. Decrease of SSA and increase in the crystallinity giving rise to bigger particles with formation of interparticles voids, occur after calcination of the HP05 sample, which becomes HP05C. The agglomerates of particles have an intrinsic porosity (see Table 1) and an interparticle 14 ACS Paragon Plus Environment

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volume, which depends on the particle size. By hypothesizing spherical particles, the higher is the particle size, the higher the volume of the interparticle voids. Then, from the figures of particle size (Table 1), the interparticle volume increases in the following order: HP05 < HP05C < Merck < Sigma-Aldrich. Moreover, also macropores with an average pores width equal to ca. 80 nm (result not reported in Table 1) were measured for Sigma-Aldrich sample. As water molecules flow through large sized pores or the interparticles voids, their motion occurs at a frequency that is broader than the frequency of water molecules constrained in small sized pores. As a consequence, intermolecular dipolar interactions are weakened. This has been observed in the case of Merck and Sigma-Aldrich TiO2 consisting of bigger particles and consequently forming greater interparticles voids. A reduction of the proton longitudinal relaxation rate (shorter R1 values) can be observed compared with the R1 values for slowly moving or immobilized water systems.31 The comparison between the HP05 and HP05C TiO2 samples indicates that the lowest water mobility (Figure 3) corresponds to the highest SSA and activation energy (Ea) related to the mobility of water determined by τ values (see in the following, Fig. 4). In both cases of study, HP05C and HP05 TiO2 samples, water is not chemically retained on the surface of the porous medium because of the inverse relationship between the exchange correlation time and the temperature enhancement.26,31 Merck and Sigma-Aldrich samples show faster relaxation rates so that their water fast motion regimes appear prevalent according to their low SSA values. Figure 4 shows the temperature dependence of τ through the Arrhenius equation graphs in terms of ln(τ) vs 1/T for HP05 and HP05C samples. The activation energy (Ea) values determined by the linear fitting of FFC experimental values (τ) are lower for HP05C (16 kJ/mol) than for HP05 sample (21 kJ/mol). The higher the water mobility, the lower the activation energy is. Conversely, the behavior of Merck and Sigma-Aldrich samples could not be satisfactorily described through the Arrhenius model, probably due to their low SSA. For this reason experimental values

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are not shown in Figure 4, but are reported in the S.I. section. In particular, the τ values were constant for Sigma-Aldrich and increased with temperature in the case of Merck sample. 9

A 8

Ln (τ)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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B

7

6

5 0.0029

0.0030

0.0031

1/T

0.0032

0.0033

0.0034

(K-1)

Figure 4. Arrhenius graphs reporting the temperature variation of the exchange correlation time (τ) for HP05 (A) and HP05C (B) samples.

3.4 Photocatalytic activity and temperature dependence In order to investigate the photocatalytic activity and its temperature dependence we considered the influence of the TiO2 sample and of the model substrate at three different temperatures (303, 328 and 353 K), under the same experimental conditions. In the first case phenol was chosen as the model substrate in the presence of different TiO2 samples (HP05, HP05C, Merck, and SigmaAldrich). In the second case HP05C sample was chosen as the model photocatalyst and the photocatalytic degradation of three different substrates (catechol, phenol and methyl benzoate) was evaluated.

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3.4.1 Influence of the photocatalyst Figure 5 shows the degradation of phenol during the irradiation time in the presence of HP05, HP05C, Merck and Sigma-Aldrich samples carried out at 328 K. The same trend was obtained at 303 and 353 K so that the results are not shown. 1.2 A 1.0 0.8 0.6

C/C

C/C 0

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0.4 0.2 0.0 0

50

100

150

200

Time (min)

Figure 5. Photocatalytic degradation of phenol at 328 K in the presence of Merck (■ - red line), HP05C (♦ - orange line), Sigma-Aldrich (● – green line) and HP05 (▲ – blue line).

TiO2 Merck sample resulted the most active among the considered photocatalysts allowing almost total phenol degradation after 120 minutes. Sigma-Aldrich and HP05 samples showed similar activity as almost 60% of the initial phenol concentration disappeared after 180 minutes. HP05C sample presented intermediate activity affording almost 90% degradation after 180 minutes. The temperature dependence of the photocatalytic degradation of phenol for the HP05C sample is shown in Figure 6. The degradation trend for the other photocatalysts was similar so that the curves are not shown for the sake of brevity.

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Figure 6. Photocatalytic degradation of phenol in the presence of HP05C sample at 303 (▲ – blue line), 328 (● – green line), and 353 K (♦ - red line).

It is evident that an increase of temperature resulted in higher photocatalytic activity. Notably, the results are comparable as the concentration of O2 dissolved in the reacting mixtures is the same for each run. On the basis of these results it is possible to plot the rate of phenol degradation versus the inverse of temperature as shown in Figure 7.

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30

32

34

1/T · 10 4 (K-1)

Figure 7. Arrhenius plot reporting the temperature dependence of the phenol degradation rate constant (k) in the presence of Merck (♦), HP05C (■), Sigma-Aldrich (●) and HP05 (▲). 18 ACS Paragon Plus Environment

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It can be noted that the influence of the temperature on the phenol photodegradation rate was the highest in the presence of Merck, whilst it was the lowest in the presence of Sigma Aldrich and HP05, which showed similar dependence.

3.4.2 Influence of the model substrate The three substrates have been chosen by considering their interaction with the surface of TiO2. It is well known34 that catechol strongly interacts by means of vicinal oxygen bridges with the surface of TiO2. The chemical adsorption allows formation of a charge transfer complex whereby an electron can be injected from the catechol moiety into the conduction band of TiO2 under visible light excitation. This is experimentally evident as a yellow color immediately is formed when TiO2 comes into contact with a catechol solution. Although similar charge transfer mechanism has been invoked also in the case of phenol adsorbed on TiO2 surface,35 the adsorption of phenol is less effective compared to that of catechol. The adsorption of methyl benzoate results even weaker, by taking into account its chemical structure. Figure 8 shows the photocatalytic degradation of catechol (A) and of methyl benzoate (B) in the presence of HP05C sample at different temperatures. The degradation rate of catechol was not influenced by temperature changes in the considered range. On the other hand, increasing the reaction temperature resulted in higher degradation rate of methyl benzoate.

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Figure 8. Photocatalytic degradation of catechol (A) and methyl benzoate (B) in the presence of HP05C sample at 303 (▲), 328 (●), and 353 K (♦).

By comparing results shown in Figure 6 and 8 one can observe that the temperature dependence of the degradation rate of the three model molecules was the highest in the case of methyl benzoate, lower in the case of phenol and virtually negligible in the case of catechol. These results are more evident by considering the Arrhenius plot shown in Figure 9. 5 4

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30

32

34

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Figure 9. Arrhenius plot reporting the temperature dependence of the degradation rate of catechol (◊), phenol ( ), and methyl benzoate (□), in the presence of HP05C sample. 20 ACS Paragon Plus Environment

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The results indicate that the temperature dependence of the degradation rate decreased when the strength of the substrate-surface interaction increased. This finding highlights that the temperature dependence of a photocatalytic reaction, which has been often considered “low”,19 can be strongly related with the interactions molecule-photocatalyst, depending on the chosen experimental conditions.

3.5 Correlation between FFC NMR analysis and photocatalytic activity Table 2 presents the activation energy and the exchange correlation time obtained from the relaxometric analysis along with the activation energy associated with the phenol photodegradation for all of the TiO2 samples.

Table 2. Exchange correlation time values and activation energies obtained from photocatalytic oxidation of phenol and from FFC NMR analysis for HP05, HP05C, Merck and Sigma-Aldrich TiO2 samples. A: anatase phase, R: rutile phase TiO2

Exchange Correlation

Activation Energy

Activation Energy

sample

Time

(phenol photodegradation)

(from FFC NMR)

(τ, ns)

(Ea, kJ·mol-1)

(Ea, kJ·mol-1)

HP05 (A)

3666-1326

17.8

21.0

HP05C (A+R)

884-346

14.8

16.0

Merck (A)

329-505

20.5

not measurable

Sigma-Aldrich (R)

42-45

8.7

not measurable

The activation energies obtained from the photocatalytic degradation of phenol, listed in Table 2, range between ca. 9 and 20 kJ·mol-1. The corresponding Ea values obtained from FFC NMR relaxometry have the same order of magnitude and follow the same trend indicating a strong correlation between them. Notably, τ values of Merck and Sigma-Aldrich samples did not show any

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evident temperature dependence, probably due to their low SSAs. For this reason the corresponding activation energy values could not be provided by the Arrhenius model. By considering the two commercial samples, the highest activation energy for the photocatalytic reaction was obtained in the case of Merck, which presented stronger interactions with water. In this case a chemically bound shell of water surrounding the surface caused lower mobility of water hindering phenol adsorption which thus became the rate limiting step. On the other hand SigmaAldrich sample showed lower τ values indicating that the mobility of water on the surface is higher than in the case of TiO2 Merck. Sigma-Aldrich TiO2 sample presented the highest water mobility so that interactions between phenol and the surface was easier and, as a consequence, the lowest activation energy for phenol degradation was obtained. Notably, Merck presented the highest phenol photodegradation rate with respect to the other photocatalysts (see Figure 5). This seems to be in contrast with its high activation energy listed in Table 2, but it should be considered that the activation energy value obtained in this way cannot be straightforwardly related to the photocatalytic activity. In fact, the activation energy represents the dependence of the photocatalytic degradation rate on the temperature and it takes into account only surface adsorption-desorption phenomena which are one of the parameters that may affect the photocatalytic activity. Similar mechanism may be invoked for HP05 and HP05C samples. These powders present higher SSA values (correspondingly higher τ values were obtained) and a high amount of amorphous phase with respect to the commercial samples, so that the temperature dependence of the τ values was evident. In these cases the crystalline phase consisted mainly of anatase as evidenced by XRD results. The higher hydroxylation degree of the HP05 sample, reported by Parrino et al.,36 led to stronger interactions with water. As previously mentioned, HP05C was obtained by calcination of the HP05 sample. This treatment lowered its SSA value (size of particles increased) with respect to HP05, and consequently lower τ values were recorded. Moreover, mesopores with a higher average width along with a significant amount of interparticles voids were formed. Another piece of information derived from the XRD 22 ACS Paragon Plus Environment

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analysis, indicates that HP05C sample presents higher crystallinity degree and higher rutile content with respect to HP05. The higher crystallinity can be related to lower surface hydroxylation degree, thus causing the presence of a lower amount of water on the surface. On the other hand, the presence of rutile enhances the motion of water molecules as reported by Conte et al.15 Correspondingly, the activation energies obtained both from photocatalytic results of all of the three model substrates and from NMRD profiles are lower than the ones obtained for the HP05 sample. To sum up, Ea values obtained by the photocatalytic experiments indicate the energetic barrier to be overcome in order to degrade phenol molecules. On the other hand, the activation energy obtained by the τ values retrieved from the Lorentzian shape of NMRD profiles are related to the mobility of water on the surface. Therefore, it is evident that the mobility of water on the surface of TiO2 represents a determining parameter for the activation energy of a photocatalytic reaction, although a correlation between water mobility and photocatalytic activity is not straightforward. In fact, this latter is influenced by many parameters each differently contributing to the whole process (e.g. type of substrate, oxygen concentration, temperature, irradiation intensity, amount of catalyst, crystallinity, presence of defects, specific surface area, density of active sites, electronic and optical properties of the catalyst). Conversely, the correlation between water mobility and activation energy of a photocatalytic reaction is a parameter which can be compared because it does not represent the activity per se but only its dependence on the temperature. Therefore, the similar values obtained for the activation energy related to water dynamics and to photocatalytic activity on the surface of different photocatalysts demonstrate that the water interactions with the surface greatly contribute to the energetic barrier to be overcome for a photocatalytic reaction to occur. Although this sounds quite reasonable, the correlation between water mobility and activation energy of a photocatalytic reaction is hereby for the first time reported on the basis of experimental results. Furthermore, in this work a quantitative evaluation of the contribution of the water competition in a photocatalytic reaction is provided by means of FFC NMR analysis. This information could be helpful particularly when photocatalysis is applied to synthesize valuable organic compounds. Indeed, in these cases the 23 ACS Paragon Plus Environment

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knowledge of the water dynamics on the surface and its influence on the adsorption-desorption equilibria is a key factor determining the selectivity of the process. It is worth to note that photocatalysis, as the first part of the name suggests, is a photochemical process, thereby accessing high energy excited states (electrons and holes) in short times and overcoming large activation barriers typical of thermal processes. However, because of the intrinsically catalytic nature of the process, surface adsorption-desorption equilibria are often limiting steps and must be taken into account. In this sense the activation energy may be seen as key descriptor of these latter phenomena and their temperature dependence. Table 3 reports the activation energy values obtained from the relaxometric analysis along with those obtained for the photocatalytic degradation of the three different substrates in the presence of the HP05C and HP05 TiO2 samples. The values of the activation energies obtained for catechol photodegradation in the presence of both HP05C and HP05 samples are the lowest with respect to the other ones. On the other hand, values referred to phenol or methylbenzoate photodegradation are almost one order of magnitude higher and both of them are similar to those determined by means of the FFC NMR analysis. In particular, the activation energy values obtained for the photocatalytic degradation of methylbenzoate result slightly higher than the ones obtained for phenol photodegradation.

Table 3. Activation energy (Ea) values obtained from the photocatalytic oxidation of catechol, phenol and methylbenzoate and from FFC NMR analysis of the HP05C and HP05 TiO2 samples.

Ea, kJ·mol-1

Ea, kJ·mol-1

Ea, kJ·mol-1

Ea, kJ·mol-1

(Catechol)

(Phenol)

(Methyl benzoate)

(FFC NMR)

HP05C

1.7

14.8

17.0

16

HP05

2.8

17.8

24.6

21

TiO2 sample

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The hereby reported results indicate that the activation energy of a photocatalytic reaction depends on the relationship between the interaction strengths of the substrate and water with the photocatalyst surface. Physical adsorption-desorption equilibria on the catalyst surface appear to be a predominant factor influencing Ea of a photocatalytic reaction, and this is particularly evident by observing the behavior of molecules which show different adsorptive properties on TiO2. The photocatalytic degradation of molecules strongly adsorbed as catechol was virtually not influenced by temperature changes. In fact, in this case water molecules cannot compete with the substrate for adsorption on the active sites even at the highest temperature considered. On the other hand, molecules showing weaker adsorption on the surface of TiO2, as phenol or methyl benzoate show significant temperature dependence according to the Arrhenius low. The activation energy in these cases is one order of magnitude higher compared with the degradation of catechol and similar to the activation energy values related to water dynamics, determined by means of FFC NMR analysis. In particular, the activation energy values associated with the degradation of methyl benzoate are slightly higher than those related to phenol. This is in accordance with the minor interactions with the TiO2 surface of methyl benzoate with respect to phenol. Indeed, water molecules may compete for adsorption with methyl benzoate molecules much easily than with phenol molecules, so that the activation energy (and the temperature dependence) of the photocatalytic degradation resulted higher in the first case. The similarity between the Ea values obtained by the aforementioned independent experiments, FFC NMR relaxometry and photocatalytic degradation of phenol and methyl benzoate, supports the hypothesis that photocatalytic oxidation reactions are affected by competition phenomena between water and the model organic pollutant, if the latter is not very strongly adsorbed on the TiO2 surface. The oxidation mechanism is related to the H-bond formation on the porous media surface. This interpretation fully agrees with that provided by Hermann16 including all the physico-chemical equilibria of the polar molecules present on the catalysts surface.

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Notably, in some case photocatalytic reactions can efficiently proceed also for species which do not adsorb on the surface of the photocatalyst. This scenario mainly occurs (i) when the photogenerated active radicals can attack the substrate (for instance cyanide ions) in the bulk of the reacting mixture but close to the surface of the photocatalyst

37

or (ii) when not adsorbed molecules react by means

of energy transfer from the photocatalyst through shutter species present on its surface.38

3

Conclusions

Although water mobility and photocatalytic activity are not straightforwardly correspondent, the relationship of water dynamics with the activation energy of a photocatalytic reaction results more evident. In fact, the activation energy does not represent the activity per se but only its dependence on the temperature. The present study shows the correlation between the dynamics of water molecules on the surface of TiO2 and the activation energy of the oxidation of three model substrates as a probe photocatalytic reactions. It has been found that the activation energies obtained from FFC NMR relaxometry have the same order of magnitude of the activation energies of the photocatalytic oxidation of molecules (as phenol or methyl benzoate) weakly adsorbed on the surface of TiO2, indicating that they are strictly related. On the other hand, the photodegradation rate of molecules strongly adsorbed on the TiO2 surface did not present any temperature dependence in the considered experimental conditions. Therefore, the competition on the surface between water molecules and substrate, often hypothesized in literature as a determining parameter, results experimentally proven. This finding is general as it was observed by considering TiO2 samples with different physico-chemical properties and different model substrates. The results confirm the possible use of NMRD analysis as a valuable characterization tool for a catalytic system allowing to investigate the influence of adsorption-desorption phenomena on the activation energy of the considered reaction.

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Author contributions PC, CDP and VAL performed the FFC NMR investigations; FP, VL and LP synthesized the catalysts and performed the BET, the X-ray diffraction and the photocatalytic experiments; all the authors equally contributed to the paper writing.

Supporting Information



X-ray diffraction patterns of Sigma-Aldrich, Merck, HP05C, and HP05 TiO2 samples.



Arrhenius graphs reporting temperature variation of the exchange correlation time (τ) for Merck and Sigma-Aldrich TiO2 samples.

Acknowledgement University of Palermo is acknowledged for economical support. Dr. Giulia Cimò and Dr. Valentina Marsala from University of Palermo are kindly acknowledged for their technical support.

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