TiO2 Surface Engineering to Improve Nanostability: The Role of

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C: Surfaces, Interfaces, Porous Materials, and Catalysis

TiO2 Surface Engineering to Improve Nanostability: the Role of Interface Segregation Andre Luiz da Silva, Dereck N. F. Muche, Lorena Batista Caliman, Jefferson Bettini, Ricardo H. R. Castro, Alexandra Navrotsky, and Douglas Gouvêa J. Phys. Chem. C, Just Accepted Manuscript • Publication Date (Web): 05 Feb 2019 Downloaded from http://pubs.acs.org on February 5, 2019

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The Journal of Physical Chemistry

TiO2 Surface Engineering to Improve Nanostability: the Role of Interface Segregation Andre L. da Silvaa,* Dereck N. F. Mucheb, Lorena B. Calimana, Jefferson Bettinic, Ricardo H. R. Castrob, Alexandra Navrotskyd and Douglas Gouvêaa a

Department of Metallurgical and Materials Engineering, Polytechnic School -

University of São Paulo, São Paulo 05508-030, Brazil; b

Department of Materials Science and Engineering and NEAT ORU, University of

California, Davis, One Shields Avenue, Davis, CA 95616, United States; c

Brazilian Nanotechnology National Laboratory (LNNano), Rua Giuseppe Maximo

Scolfa ro 10000, BR-13083100 Campinas, SP, Brazil; d

Peter A. Rock Thermochemistry Laboratory and NEAT ORU, University of California,

Davis, One Shields Avenue, Davis, CA 95616, United States

* Corresponding Author. Tel. +55 (11) 97414-5238. E-mail address: [email protected] (Andre L. Silva) ABSTRACT Nanoparticle stability against coarsening is one of the keys to allow better exploitation of the properties of nanoscale materials. The intrinsically high interfacial energies of nanoparticles constitute the driving force for coarsening and therefore can serve as targets to design materials with improved thermal stability. In this study, we discuss the surface engineering of TiO2 nanocatalyst for artificial photosynthesis by exploiting the spontaneous segregation of Ba2+ ions to the interfaces of TiO2 nanocrystals. Ba2+ is a strong candidate for photoelectrocatalytic reduction of CO2, and its effects on interfacial energies lead to remarkable increase in thermal stability. By using a systematic lixiviation method, we quantified Ba2+ content located at both the surface and at grain boundary (GB) interfaces and combined with direct calorimetric measurements of surface energies and microstructural studies to demonstrate Ba2+ excess quantities directly impact

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coarsening of TiO2 nanocatalysts by creating meta-equilibrium configurations defined by the Ba2+ content and segregation potentials at each individual interface. The results establish fundamental framework for the design of ultra-stable nanocatalysts. INTRODUCTION Nanomaterials have attracted worldwide attention since the end of the last century due to their remarkable properties as compared to their bulk counterparts.1 The large surface to volume ratio allows the use of nanocrystals in advanced surface-dependent applications, including photocatalysis,2-4 solar cells,5 gas sensing,6 energy storage7 and artificial photosynthesis (AP).8 Besides the large specific surface area (SSA), some applications, such as AP, require special attention in the physico-chemistry of interfaces (surfaces and grain boundaries (GB)) to improve performance. In this case, a semiconductor with the ability to promote water splitting, such as TiO2, is usually the material of choice.9 However, the production of organic molecules, such as formic acid and methanol, using AP also requires the photoelectrocatalytic reduction of CO2.10 In an ideal scenario, the H2O and CO2 molecules should be captured from the air and a continuous production of organic molecules using solar energy would be performed. A possible strategy to achieve this is to partially modify the surface of the semiconductor using a nano-oxide that tends to adsorb CO2, while the uncoated surface could adsorb H2O and promote the water splitting coupled with CO2 reduction.8 In this context, the use of selected ionic dopants prone to surface segregation on nanocrystals can likely provide such conditions, because segregation occurs anisotropically on the different available surface crystallographic planes. BaO is a possible candidate for doping TiO2 with since it has the potential for CO2 adsorption at basic surface sites to form anionic surface carbonate species.11 While segregation of ions can be used to control the physical chemistry of surfaces, the phenomenon is also intrinsically connected to the thermodynamic stability of the nanoparticles by the surface energy term. Surface segregation has been used as an effective tool to improve the stability of nanoparticles, e.g. ZnO doped TiO2,12 ZnO doped SnO2,13 Y3+, Gd3+ and La3+ doped MgAl2O414 and Mn doped CeO215 have shown an increase in nanostability promoted by surface (and GB) segregation. The spontaneous segregation of ions in those systems occurs due to energetically favorable conditions rather than a kinetically trapped ion distribution state. In crystalline systems, four types of driving forces have been recognized as the reasons for surface segregation (or excess):


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difference in surface energy between the doping oxide and the host (∆𝐻𝜎), an elastic solute strain energy due to size difference between the doping and host ions (∆𝐻𝜀), solutesolvent interaction (∆𝐻𝜔), and electrostatic potential/charge compensation (∆𝐻𝜙). Hence, the enthalpy of segregation (∆𝐻𝑠𝑒𝑔) can be written by Eq. 1.16,17 ∆𝐻𝑠𝑒𝑔 = ∆𝐻𝜎 + ∆𝐻𝜀 + ∆𝐻𝜔 + ∆𝐻𝜙

(1)

The difference between the surface energies, (𝜎2 ― 𝜎1), of the solute and the solvent, phases provides a contribution to the enthalpy of segregation, which can be represented by Eq. 2.16,17 ∆𝐻𝜎 = (𝜎2 ― 𝜎1)Α

(2)

where Α symbolizes the surface area. The elastic strain energy in the system is directly influenced by the difference in the ionic radius between the two components and is denoted by Eq. 3.16,17

∆𝐻𝜀 =

24πKGr1r2(r1r2)2

(3)

4Gr1 + 3Kr2

where, 𝑟1 and 𝑟2 are the ionic radius of the solute and the solvent ions, respectively, G is the stiffness modulus and K is the compression modulus. The solute-solvent interaction gives its contribution to the heat of segregation according to Eq. 4.16,17

∆𝐻𝜔 =

Δ𝐻𝑚 Z

∗

(4)

Xb1Xb2

where Δ𝐻𝑚 is the heat of mixing, Z ∗ is the solute fraction on the surface of the solvent, and Xb1 and Xb2 are the molar fractions of the solvent and the solute in the bulk, respectively. Finally, the electrostatic potential and charge compensation are represented by Eq. 5. ∆𝐻𝜙 = ―𝑞𝑒ϕ∞


(5)


where q is the product of the ion charges e is the electron charge and

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ϕ∞ is the electrical

potential in the depletion layer.16,17 Although all driving forces contribute simultaneously to the enthalpy of segregation, in ionic solids the elastic strain energy and electrostatic components are usually predominant.16 Based on this, and on the required physical chemical conditions of the surface discussed above, in this study, we selected BaO to work as a surface dopant on TiO2 interfaces. The large difference in ionic radius between Ba2+ (149 pm) and Ti4+ (74.5 pm) and their charge difference would hypothetically lead to spontaneous segregation of BaO on TiO2. Thus, two benefits are expected from this segregation: (1) changes in the electrochemical potentials and adsorption sites at the surface, which can provide an increase in the adsorption of CO2; and (2) increase in the nanoparticle stability, which can provide a higher SSA with more sites available for reaction using this material in AP. The surface segregation of a dopant is intrinsically connected to a reduction of the interface energies (𝜎𝑖) as described in Eq. 6 which is based on an extension of the Gibbs adsorption isotherm.15,18-20 𝜎𝑖 = 𝜎0 ― Γ𝑖Δ𝐻𝑠𝑒𝑔

(6)

where 𝜎0 is the interface energy of the undoped material, Δ𝐻𝑠𝑒𝑔 is the enthalpy of segregation, and Γ𝑖 is the solute excess at the interface, expressed by 𝑛 𝐴 with 𝑛 being the amount of component at the surface and 𝐴 the surface area. Eq. 6 works for systems with a single phase only (with low dopant concentration) and can be used for both surface and GB interfaces. From Eq. 6, we can draw the conclusion that the surface energy of a system decreases with an increase of the surface segregation (excess) of dopant.15 Based on the fact that surface energies are the main driving forces for coarsening, it can be expected that a decrease in surface energy will promote smaller particle sizes at a given temperature. According to traditional coarsening models, during the isothermal growth of nanoparticles, the average particle size 𝑑𝑡 is modified with time, 𝑡, and the change follows a general growth empirical equation (Eq. 7). 𝑑𝑛𝑡 ― 𝑑𝑛0 = 𝑘𝐷𝜎𝑖(𝑡 ― 𝑡0)


(7)

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Here, 𝑑0 is the average particle size at 𝑡0; 𝐷 is the diffusion coefficient; 𝜎𝑖 is the interface energy; 𝑘 is a constant that depends on the approach to develop the kinetic equation; 𝑛 is equal to 2, 3, or more and generally represents the mechanism of growth.13 Fundamentally, thermodynamic segregation is a strong candidate for composition design of nanocrystals for AP. However, it has been recently reported that segregation occurs not only on the surface but also in the GB of nanocrystals. GBs are commonly found in nanocrystals given the spontaneous aggregation and agglomeration occurring during synthesis to lower excess surface energies. These boundaries typically have lower energies as compared to surfaces, but thermodynamic data on such interfaces are still limited. While from a coarsening perspective, understanding the split segregation of dopants to surfaces and GBs is relevant to predicting the microstructural stability, from a physical-chemical perspective one should also recall that GBs can affect charge transfer (electrons and holes) between particles, affecting lifetime for species recombination, and implying the control of GB chemistry is equally important of that of the surface. Therefore, the aim of the present work is to understand Ba2+ segregation behavior in TiO2, quantifying dopant excesses on surfaces and GBs, while discussing the relationship with the observed microstructural evolution. Direct calorimetric measurements show that BaO reduces the surface energy of TiO2, which is attributed to the segregation of ions as quantified by a lixiviation method. The system shows pronounced segregation to GBs as well, which combined with the surface energy decrease allows for smaller crystallite sizes for TiO2. We show for the first time that the observed segregation is unquestionably thermodynamically controlled, demonstrating that the behavior (and consequent microstructural evolution) is persistent and only dependent on temperature and composition of the system. Photocatalysis analyses are not reported due to the already high complexity of the microstructural studies and will be addressed in a separate paper. EXPERIMENTAL METHODS Synthesis of Undoped and Doped TiO2 Nanoparticles. TiO2-based powders containing BaO were synthesized by the polymeric precursor method. The titanium-oxide polymeric precursor was prepared by mixing titanium isopropoxide (19.4 wt %) with ethylene glycol (45.4 wt %) at 40 °C, followed by heating to 70 °C and addition of citric acid (35.2 wt %). Thus, the solution was heated to 120 °C for polyesterification. The addition of BaO was made using an acid barium solution (0.2



mol/L). This solution was obtained by solubilizing the appropriate amount of Ba(NO3)2 in an aqueous nitric acid solution (0.1 M), followed by chemical analysis. The samples were prepared by mixing calculated amounts of the solution and the precursor, with the target molar concentrations of 0.0, 0.1, 0.5, 1.0 and 5.0 %. The corresponding samples used in this study were labeled as Ti000Ba, Ti001Ba, Ti005Ba, Ti010Ba, and Ti050Ba. The calcination was carried out in two steps, the first one with the objective of decomposing the organic trace. Each sample was held at 350 °C for 4 h. Thus, the powder was manually ground with a mortar and pestle and treated in air at 350 °C for 15 hours to complete the oxidation and particle stabilization. Sample Characterization. The chemical compositions were analyzed by inductively coupled plasma atomic emission optical spectroscopy (ICP OES) using a Spectro Across spectrometer. The samples were prepared by melting the powders with sodium borate, followed by acid digestion. The powder X-ray diffraction patterns were obtained using a Philips X´Pert PRO PW 3040/00 diffractometer with Cu K radiation at 0.02° steps per second over the 2 range of 5-90 °. The diffractograms were analyzed using X´Pert Highscore software. The lattice parameters and crystallite sizes were calculated using whole profile fitting using Materials Studio 6.0 software with CaF2 and anatase structures as standards. The powder density was obtained using a Micrometrics AccuPyc II 1340 gas pycnometer after 200 purges for degassing. Surface area measurements were carried out using the Brunauer, Emmett, and Teller (BET) method with nitrogen gas adsorption (77 K) (Micromeritics Gemini VII).21 The samples were degassed at 300 °C for ~16 hours using a Micromeritics VacPrep 061. Surface Segregation. The surface excess of BaO in TiO2 nanoparticles was determined by superficial lixiviation, electron energy loss spectroscopy (EELS) in scanning electron transmission microscopy mode (STEM) and X-ray photoelectron spectroscopy (XPS). The superficial lixiviation was performed by ultrasonicating ~100 mg of powder with 2 g of 0.1 M HNO3 solution (pH = 1) for 1 h. Hence, the samples were centrifuged at 13,000 RPM (10,390 G) for 20 min. Approximately 1 g of the supernatant solution was collected, diluted in ~10 g of H2O, and analyzed by inductively coupled plasma atomic emission optical spectroscopy (ICP OES) using a Spectro Across spectrometer.12,13 For the EELS measurements the Ti050Ba sample was chosen. To allow better spatial resolution of Ba distribution across the sample, the sample was coarsened at 700 °C for 4 h to allow growth ACS Paragon Plus Environment

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and particles to be significantly larger than the probe size. EELS measurements were conducted in a JEM-2100F (JEOL) equipped with an 863 GIF Tridiem spectrometer (Gatan). All measurements were carried out in STEM mode. The probe size used was 0.7 nm, the pixel size for EELS image spectrum was 0.5 nm and the pixel time acquisition was 2 s for the line profile measurement. The probe size used was 1 nm, the pixel size for EELS image spectrum was 0.62 nm and the pixel time acquisition was 0.2 s for the round TiO2 nanoparticle measurements. The X-ray photoelectron spectroscopy (XPS) measurements were carried out using a ScientaOmicron ESCA+ spectrometer equipped with a monochromatic X-ray source (K 1486.6 eV) and a hemispherical type electron analyzer. During the measurements, the pressure in the analysis camera was 2 × 10-9 mbar. The survey and high-resolution spectra were registered at 0.1 and 0.5 eV energy steps, respectively. The composition was determined by the relative peak areas corrected by Scofield atomic sensitivity factors with ~5 % accuracy. The spectra were deconvoluted using Voigt profiles with combinations of Gaussian (70 %) and Lorentzian (30 %) terms. The width at half height varied between 1.2 and 2.0 eV, and the peak positions were determined with ~0.1 eV accuracy. Surface Energy. Water adsorption microcalorimetry was used to measure the surface energy of the undoped and doped TiO2. It is important to consider that surface energy is a very small thermodynamic quantity, thus, highly sensitive instrumentation is required for reliable assessment. The use of the microcalorimetry of water adsorption to probe the surface energy has been proven effective for nano-oxides.14,15,18,22-25 The method is based on a thermodynamic correlation between the heat of water adsorption on the surface and the surface energy itself. The instrument and methodology are described in detail elsewhere.22,24 In a typical experiment powder with a surface area of ~2 m² was placed into a glass tube. This glass tube was then placed into the left side chamber of a Setaram SetSYS Evolution Calvet microcalorimeter calibrated against the enthalpy of fusion of gallium and connected to a 3Flex sorption analyzer (Micromeritics). An empty glass tube was put into the right side chamber of the apparatus which was also connected to the same port of the sorption system, so that the calorimeter could record the differential heat. The instruments measure the enthalpy of water adsorption of the sample and the water coverage simultaneously. Two sets of samples were used in these experiments: the asprepared powders (0.0 - 5.0 mol % BaO-doped TiO2), which were degassed at 200 °C for 12 h under vacuum to remove the residual surface water; and the lixiviated powders



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degassed at 250 °C for 4 h under vacuum and then at 350 °C for 15 h under oxygen atmosphere. The degassing condition was established by using thermogravimetry. The lixiviated samples were labeled as Ti000BaLixRet, Ti001BaLixRet, Ti005BaLixRet, Ti010BaLixRet and Ti050BaLixRet, which correspond to the initial BaO doping composition of 0.00, 0.01, 0.05, 0.10 and 0.50%, respectively. The same batches of lixiviated powders were treated in a similar degassing system at the same conditions and characterized by X-ray diffraction, BET surface area, chemical composition by ICP, Xray

photoelectron

spectroscopy

and

new

lixiviation

procedure.

After

the

degassing/retreatment procedures, the chamber was kept at 25 °C, and the dosing routine was programmed to be ~2 µmol H2O per dose and equilibration time ~1.75 h for the first four doses, ~1 h for the fifth dose, ~0.75 h for sixth and seventh and ~0.5 h from eighth dose on. The equilibrium time was designed to be enough for the measured heat signal in the calorimeter to return to the baseline. The surface energies of the anhydrous synthesized specimens were calculated using the water adsorption data using a custom written program (MATLAB Release 2010a, MathWorks, Natick, MA), reported elsewhere.24 The water adsorption curve was fit using a modified Langmuir-BET adsorption curve (Eq. 8).

𝜃 = 𝜃𝑐

𝑏 𝑥

𝑐𝑥 + 𝜃𝑝 (1 ― 𝑥)(1 + (𝑐 ― 1)𝑥) 1+𝑏 𝑥

(8)

Here, θc is the monolayer coverage of the dissociative water; θp is the physisorption monolayer coverage; b and c are unit-less fitting parameters; and x is the relative pressure (p/p0). The differential heat of adsorption curve was fitted using Eq. 9.24

d𝐻𝑅 dHcon = 𝐷𝑒 −𝜃 ⁄𝑑 + 𝐸(𝑓𝜃 − 𝜃 2 )𝑒 −𝜃 ⁄𝑒 + � dθ dθ T o ,p o

(9)

Eq. 9 is an empirical relationship for the differential heat of water adsorption as a function of the water coverage, where HR is the heat of adsorption, and Hcon is the enthalpy of liquefaction of water. The equation requires five parameters: d and e are decay parameters that relate how strongly the specimen’s surface affects the adsorbed water; and D, E, and f are fit parameters with units of kJ/mol, kJ/mol³, and mol, respectively.


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After fitting the water adsorption curve and the differential heat of adsorption data using Eqs. (8) and (9), the surfaces energies of the samples were numerically computed by substituting the mentioned equations into Eq. (10).

{

( ) )}

d2SAd𝜃 dσ SA d𝜃 d2𝐻rd𝜃 d𝜇gas dSA d2𝜃 d𝑥 SA 2 = + ― 𝜎 + ― 2 + SA d𝑥 d𝜃2 d𝑥 d𝑥 d𝜃 d𝑥 d𝜃2 d𝑥 d𝑥 𝜃 d𝑥2 d𝜃 d2𝜎

(

2

(10)

Eq. (10) correlates the surface energy and water adsorption. The adsorbed water is a function of the pressure, x; and the differential heat of water adsorption is a function of the adsorbed water, θ. In this Equation, SA is the surface area of the sample; 𝜎 is the surface energy at a given state; and µgas is the vapor chemical potential. RESULTS AND DISCUSSION Characterization of the nanoparticles and surface segregation The XRD patterns for pure TiO2 and BaO-doped TiO2 samples are shown in Figure 1. The non-lixiviated (as prepared) powders and the powders lixiviated/retreated are shown in Figure 1(a) and (b), respectively. Anatase (JCPDS card n.71-1167) was the predominant phase for all compositions, and its Miller indices are identified in Figure 1(a) and (b). Broad peaks can be observed, which is typical of nanosized crystallites. The broadening increased systematically as the BaO concentration increased, which is associated with the change in crystallite sizes, as shown in Table 2. Figure 1(b) suggests that after the lixiviation and additional thermal treatment, the crystallite of the nanopowders increased, which is evidenced by narrower peaks. This small increase can be attributed to the reduction in dopant content, suggesting the lixiviation process was successful.



Figure 1. X-ray diffraction patterns of TiO2 and BaO-doped TiO2. a) As prepared nano-oxides. b) Powders lixiviated and retreated at 350 °C for 15 h under oxygen.


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The chemical compositions and density of the samples are shown in Table 1. The amount of BaO-doped TiO2 analyzed by ICP was similar to the target composition. After the first lixiviation process, the barium content for all samples was reduced by ~30 %. The measured density of pure TiO2 (3.62 g/cm³) was slightly smaller than the theoretical TiO2 anatase (3.79 g/cm³). Moreover, the density decreased as the percentage of BaO increased. In fact, one should expect an increase in density by incorporating BaO since the theoretical density of BaO (5.72 g/cm³) is higher than TiO2. However, BaO is expected to be on the surface of the particles and in this location, Ba2+ can interact with CO2 and decrease in overall density of the nanoparticles. The evidence for the existence of CO2 on the surface of the nanoparticles by DRIFT spectra analyses of pure TiO2 and 5 mol % BaO-doped TiO2 is presented in Figure S1. The bands positioned at 2330 cm-1 and 1380 cm-1, associated with CO2, were clearly more intense in the Ba containing samples. This reinforces the hypothesis of a CO2 containing superficial layer coating with lower density on the nanoparticles and also suggests that BaO can cause increase of surface reactivity to CO2. Table 1. Chemical analysis, chemical composition after first lixiviation and density of BaO-doped TiO2 as prepared nano-powders. Sample Target composition Chemical Chemical Density (x mol% BaO-doped

analysis

composition after first

TiO2)

(BaO mol%)

lixiviation (BaO

(g/cm³)

mol%) Ti000Ba

0.00

0.00

0.00

3.62 ± 0.01

Ti001Ba

0.10

0.11

0.08

3.47 ± 0.01

Ti005Ba

0.50

0.48

0.35

3.52 ± 0.01

Ti010Ba

1.00

1.01

0.74

3.32 ± 0.01

Ti050Ba

5.00

5.11

3.48

3.25 ± 0.01

Spatially resolved EELS was used to verify the barium surface enrichment with doped TiO2 nanoparticles before lixiviation. Only one composition was studied due to the complexity of the experiment. To allow better spatial resolution of Ba distribution across the sample, the sample was coarsened at 700 °C for 4 h to allow growth and particles to be significantly larger than the probe size. Figure 2 shows the result for measurement of EELS line profile for 5 mol % BaO-doped TiO2.



Figure 2. EELS measurement for line profile crossing some TiO2 nanoparticles. a) Dark Field image of a nanoparticles aggregation, b) area measured with 3x zoom, and c) the ratio between the peaks areas of Ba and Ti.

Figure 2a shows an aggregation of nanoparticles with different morphologies (spherical, cubic and irregular) and an average size around 15 nm. The line profile shown in Figure 2a at the bottom of the TiO2 aggregates crosses at least three nanoparticles. Figure 2c shows the ratio of the areas of Ba and Ti peaks (solid curve). This result was obtained from the integrated area of Ba L2 and L3 peaks divided by the integrated area of Ti L2 and L3 peaks. Figure 2c also shows the intensity variation obtained by the dark field images (dashed curve). Combined, the results definitely indicate Ba surface enrichment. At the center of nanoparticles, the Ba/Ti ratio is close to 0.04. It shows a sevenfold increase on the left surface (edge) and sixfold increase on the right surface of the nanoparticles. The results are consistent with the dark-field intensity save for a small shift that can be explained by the probe size used (0.7 nm) and the delocalization of the EELS measurement. However, after the measurement, some physical sputtering (mass loss) occurred as can be observed in Figure 2b by the dark contrast in the position where the measurement was made. To assure the sputtering did not affect the compositional gradient, the acquisition time for each spectrum point was reduced from 2 s to 0.2 s to mitigate sputtering, and the probe size was increased from 0.7 nm to 1 nm. Consequently, the EELS signal/noise ratios in the new measurements were five times lower than in the initial conditions. Moreover, Ba L2 and L3 peaks were mostly undetectable in each individual pixel in the spectrum image. To overcome this limitation, the results were


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analyzed by integrating linear or circular areas in the EELS spectrum image in order to increase the signal/noise ratio. Figure 3 shows the EELS measurement for a circular projection of a TiO2 nanoparticle (spectrum image box, Figure 3a). Figure 3a is the same figure shown in Figure 2a while Figure 3b shows an image with 4 × zoom of the measured area. In Figure 3i one observes a reduction of Ti L2 and L3 peaks intensities while the Ba L2 and L3 peaks intensities remain almost constant (inset graph in Figure 3i) from measurements taken from the center to the surface of the TiO2 nanoparticle. This result indicates a threefold Ba surface enrichment, as observed in Figure 3h through the ratio peaks areas between Ba and Ti. It is important to point out that the last ring does not correspond to the surface of the TiO2 nanoparticle, moreover, this ring also gets some information from the nanoparticle touching the upper left corner of the TiO2 nanoparticle under consideration. So the Ba surface enrichment could be even higher than the reported value.



Figure 3. EELS measurement for a circular projection of a TiO2 nanoparticle. a) Dark Field image of a BaO-doped TiO2 aggregated nanoparticles, b) the area measured with 4x zoom, c) EELS spectrum image with the circular rings where the EELS signal was integrated to analyze the Ba content, d), e), f) and g) areas used for EELS signal integration, h) color composite image identifying each EELS area integrated individually, i) EELS spectra integrated from each area with the Ti background removed; the inset shows a zoom correspondent to the Ba L2 and L3 peaks, and j) the ratio area peaks between Ba and Ti for the rings area integrated.

This evidence of Ba surface segregation is also consistent with the observed microstructural evolution of the samples. The crystallite sizes (a = b and c), lattice parameters (a = b and c) and the unit cell volume of the as-prepared (non-lixiviated) and lixiviated/retreated samples are shown in Table 2. Lattice contraction and a decrease in the unit cell volume were observed in both non-lixiviated and lixiviated/retreated samples as the amount of dopant increased. This behavior can be associated with the decrease in particle size and/or with the change in the particle surface environments.26 Size-dependent changes in the anatase structure have been reported for both lattice expansion27,28 and lattice contraction12,29,30 at small crystallite sizes. This divergence is mostly associated with the nanoparticle synthesis and with the type of precursor used, which can lead to the surface-associated impurities due to adsorption of organic molecules and/or ions from the solution.26 For example, Mi, et al.28 reported lattice contractions in nano-anatase (~3-12 nm) prepared with HCl, while lattice expansion was observed in nano-anatase prepared with H2SO4.28 The difference could be explained by the different binding strengths of Cland SO42- on the titania surface. Stronger binding in the latter could result in a negative surface stress and hence a lattice expansion at small sizes.26


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Table 2. Crystallite sizes, lattice parameters, and unit cell volume of BaO-doped TiO2 (0-5 mol%). As prepared nano-oxides (non-lixiviated) Sample

Powders lixiviated and retreated at 350 °C for 15 h under oxygen

Crystallit

Crystallit

Lattice

Lattice

Unit cell volume (Å³)

Sample

Crystallite

Crystallite

Lattice

Lattice

Unit cell

sizes a=b

sizes c

parameters

parameters c

volume (Å³)

(nm)

(nm)

a=b (Å)

(Å)

e sizes

e sizes c

parameters

parameters c

a=b (nm)

(nm)

a=b (Å)

(Å)

Ti000Ba

19.9±1.3

22.0±3.4

3.7898±0.0001

9.5137±0.0013

136.64±0.02

Ti000BaLixRet

20.5±1.4

24.0±4.2

3.7773±0.0001

9.4818±0.0014

135.28±0.02

Ti001Ba

7.4±0.1

7.1±0.2

3.7893±0.0024

9.4958±0.0063

136.35±0.26

Ti001BaLixRet

11.1±0.4

11.7±1.1

3.7770±0.0001

9.4654±0.0020

135.03±0.03

Ti005Ba

5.9±0.1

5.8±0.2

3.7804±0.0008

9.4756±0.0004

135.42±0.06

Ti005BaLixRet

7.8±0.2

8.0±0.4

3.7739±0.0008

9.4546±0.0004

134.65±0.06

Ti010Ba

5.3±0.2

5.0±0.1

3.7790±0.0001

9.4618±0.0001

135.12±0.01

Ti010BaLixRet

7.0±0.2

7.1±0.3

3.7648±0.0009

9.4225±0.0005

133.55±0.07

Ti050Ba

5.3±0.2

4.2±0.5

3.7824±0.0049

9.4357±0.0131

134.99±0.54

Ti050BaLixRet

5.0±0.2

4.8±0.4

3.7622±0.0016

9.3873±0.0008

132.87±0.13



Zhang et al.30 showed an interdependence between particle size and unit cell parameter change, demonstrating that a reduction in crystallite sizes from ~25 to ~5 nm resulted in ~0.5 % reduction in the unit cell volume. In our work, the unit cell volume reduced ~1.2 % from Ti000Ba to Ti050Ba samples and ~1.8 % from Ti000BaLixRet and Ti050BaLixRet, while the crystallite sizes reduced from ~21 to ~5 nm. In this sense, the major contribution to lattice parameters contraction in the present study can be attributed to the change in surface stress caused by BaO interface enrichment and consequent reaction with CO2. A systematic decrease in the crystallite sizes as the doping content increases was also observed, which suggests an increase in the stability of TiO2 nanoparticles against coarsening. According to coarsening models,31 the particle size is directly proportional to the surface energy, which is related to the surface segregation (Eq. 7). Thus, by increasing the surface excess of a dopant, a smaller particle size can be promoted at a given temperature. This relationship between surface excess and crystallite size has been observed for many systems.12,13,15,18 In the present study, even a small amount of dopant caused a major impact in the crystallite size. The addition of 0.1 mol % BaO decreased the crystallite size by about a factor of three. However, after 0.5 mol % of dopant, the crystallite sizes did not change significantly. The XRD data also indicate the crystallite shape becomes more symmetric in the doped samples. This is evidenced by the decrease in the difference between the crystallite sizes from “a = b” and from “c”. It is reported in the literature that different TiO2 planes have different surface energies32-35 (see Table 5). Thus, in order to minimize the overall energy of the system, the additive BaO is expected to segregate preferably on the planes with higher energy, leading to a more symmetric particle after doping. Comparing the non-lixiviated samples to the lixiviated/retreated ones, it is perceived that the crystallite sizes increased after the lixiviation and new thermal treatment. The difference is more pronounced in the doped samples, especially for 0.11.0 mol % BaO-doped TiO2. While the pure TiO2 increased ~5 % on average, the doped samples increased their crystallite sizes by about 30 %. Two phenomena could contribute for this increase: (a) the removal of adsorbed substances, such as carbonates (and other anions) and CO2 from the surface of the nanoparticles due to the lixiviation, and (b) the reduction of the amount of BaO on the surface of the particles. While the first is likely responsible for the behavior observed in the undoped TiO2, the main contribution for the BaO doped sample is attributed to the decrease in the amount of dopant. That is, barium


Page 16 of 34

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is removed from the surface of the sample and while this does not itself cause a significant change in crystallite size, after heat (re)treatment, the samples grow to the size consistent with the new barium concentration in the sample. This would suggest that Ba ions are quite mobile in the system and redistribute after heat treatment to minimize the total particle energy. The elemental analysis at the surface region (< 5 nm) of nanoparticles at the different states: as-synthesized, after lixiviation, and with subsequent heat treatment, was performed by high-resolution XPS (Table 3) to assess this hypothesis. The samples with the higher concentration of barium (~5 mol%) were chosen for this experiment. Four main elements were identified: oxygen, titanium, barium, and carbon. The Ti050Ba and Ti050BaLix samples showed similar amounts of oxygen, titanium and carbon, while the Ti050BaLixRet showed a higher concentration of oxygen and titanium and lower amount of carbon. This compositional change can be mainly attributed to the new calcination in a controlled oxygen atmosphere which favored the burning of carbon and consequently increased the concentration of oxygen and titanium. The concentration of barium (Ba 3d5/2) decreased from 1.0 to 0.3 at % after lixiviation (before recalcination). The remaining barium can be associated with the dopant concentrated in the GB or bulk of the crystal (solid solution) which is not accessible to the acid lixiviation. Surprisingly, after the new thermal treatment, the amount of barium almost returned to the initial concentration. The 0.7 at % represents ~70 % of the initial Ba composition (1.0 at %), which is consistent (considering mass conservation) when compared to the chemical composition after the first lixiviation listed in Table 1. From Table 1 it is observed that the amount of BaO left in the TiO2 particles indeed represents ~70 % of the initial concentration of BaO. Thus, the data imply the new surface enrichment is a consequence of a redistribution of the Ba ions trapped within the nanoparticles in solid solution or GBs (see Figure 4 - schematics). Considering the solubility of BaO in TiO2 is very small, one may assume barium to be mostly located at the GB region. The complete X-ray photoelectron spectra and discussion are shown in Figure S2 in Supporting Information.



Page 18 of 34

Table 3. Atomic concentration (at%) of the nanoparticles elements on the surface of 5 mol% BaO-doped TiO2 samples obtained from high-resolution X-ray photoelectron spectra (precision ±5%). Sample / Element

Ti050Ba (% at.)

Ti050BaLix (% at.)

Ti050BaLixRet (% at.)

Oxygen (O 1s)

43.3

42.5

47.4

Ti (Ti 2p3/2)

13.9

13.9

16.9

Barium (Ba 3d5/2)

1.0

0.3

0.7

Carbon (C1s)

41.8

43.3

35.1

Figure 4. Schematic representation of the selective lixiviation method to determine the surface excess and new distribution of the additive after a new thermal treatment.

The accumulated evidence suggests that although Ba is segregated to the surface, a significant fraction is likely located at the GBs. This has significant implications to microstructure as interface segregation is intimately connected to its stability. The specific surface area (SSA), total specific area (TSA), specific grain boundary (SGB) interface and GB/SSA ratio of the as-prepared BaO-doped TiO2 and the powders lixiviated and retreated at 350 °C for 15 h under oxygen atmosphere are shown in Table 4.


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Table 4. SSA, TSA, SGB and GB/SSA ratio of the as-prepared BaO-doped TiO2 (0-5 mol%) and the powders lixiviated and retreated at 350 °C for 15 h under an oxygen atmosphere. As prepared nano-oxides (non-lixiviated)

Powders lixiviated and retreated at 350 °C for 15 h under oxygen

Specific grain

GB/SSA

boundary area

ratio

Specific surface

Total specific

area (m²/g)

area (m²/g)

Ti000Ba

60.6±0.4

80.7±23.6

10.0±3.0

0.17

Ti001Ba

88.5±0.7

237.5±16.6

74.5±5.8

Ti005Ba

105.1±0.8

291.2±19.1

Ti010Ba

127.7±1.0

Ti050Ba

133.8±0.5

Sample

Specific grain

GB/SSA

boundary area

ratio

Specific surface

Total specific

area (m²/g)

area (m²/g)

Ti000BaLixRet

49.7±0.4

77.0±24.1

13.7±4.4

0.28

0.84

Ti001BaLixRet

62.8±0.5

153.2±26.0

45.2±8.0

0.72

93.0±6.8

0.88

Ti005BaLixRet

101.5±0.6

216.3±21.9

57.4±6.1

0.57

348.8±31.3

110.6±10.7

0.87

Ti010BaLixRet

103.1±0.7

257.3±22.6

77.1±7.3

0.75

381.2±79.1

123.7±26.2

0.92

Ti050BaLixRet

81.4±0.5

374.9±55.2

146.8±22.5

1.80

Sample

(m²/g)


(m²/g)


Page 20 of 34

The evolution of the specific surface area (SSA) of the as-prepared powders followed the expected opposite trend from that observed in the crystallite sizes (Table 2). It increased systematically up to 1.0 mol % BaO and then remained relatively constant between Ti010Ba and Ti050Ba samples. Modifications of the SSA and crystallite size associated with a single phase have been reported for doped TiO2 and are related to surface segregation12 and decrease in surface energy.18 The total specific surface area (TSA) was calculated from the crystallite size by assuming an ellipsoidal shape, using Eq. 11. 𝑇𝑆𝐴 = 𝐴𝑔/(𝜌 × 𝑉𝑔)

(11)

where 𝑉𝑔 is the ellipsoid crystallite volume, 𝐴𝑔 is the ellipsoid crystallite area, and 𝜌 is the powder density (Table 1). An ellipsoidal shape was chosen based on the symmetry of the TiO2 lattice parameters, where a = b < c. The SGB interface was calculated as half of the difference between the TSA and SSA (Eq. 12). 𝑆𝐺𝐵 = (𝑇𝑆𝐴 ― 𝑆𝑆𝐴)/2

(12)

The TSA and SGB are much higher in doped samples than in undoped ones, which follows the crystallite size trend (Table 2). The GB/SSA ratio follows the same trend and tends to be higher for doped samples. This increase in TSA, SGB and GB/SSA ratio demonstrates a change in the relative stability of interfaces probably because of the change in the balance of the interface energy due to BaO segregation on both surface and GB. Higher values of GB/SSA ratio for doped samples suggest that the major part of the BaO additive segregates in the GB interface and stabilizes it. Comparing the non-lixiviated powders with the lixiviated/retreated ones, it is observed that in general the SSA and TSA decreased. These differences are due to the increase in crystallite sizes (Table 2), which was already discussed. In particular, the sample Ti050BaLixRet presented lower SSA and higher SGB compared to Ti010BaLixRet and Ti005BaLixRet, a possible indication of GB stabilization. Surface energies Thermodynamically induced surface segregation must be connected to surface energy reduction, which can be directly measured using microcalorimetric techniques. Here we present the surface energy measurements for the as-synthesized and


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lixiviated/retreated samples. It is unfortunately unfeasible to test the lixiviated samples without retreatment given the degassing step required in the microcalorimetry protocol is equivalent to a retreatment. Figures 5 (a) and (b) show the water adsorption isotherm on the surface of the powders, before and after lixiviation/retreatment, and Figures 5 (c) and (d) present the respective enthalpy of adsorption versus water coverage. Based on the derivative of the adsorption isotherm curve, two stages are observed in the adsorption process. At very small relative pressures (

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