Surface Segregation on Manganese Doped Ceria Nanoparticles and

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Surface Segregation on Manganese doped Ceria Nanoparticles and Relationship with Nanostability Longjia Wu, Sanchita Dey, Mingming Gong, Feng Liu, and Ricardo H. R. Castro J. Phys. Chem. C, Just Accepted Manuscript • Publication Date (Web): 24 Nov 2014 Downloaded from http://pubs.acs.org on November 25, 2014

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The Journal of Physical Chemistry

Surface Segregation on Manganese Doped Ceria Nanoparticles and Relationship with Nanostability ，

Longjia Wu1, Sanchita Dey1, Mingming Gong1 2, Feng Liu2, Ricardo H.R. Castro1,* 1

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

California, Davis, CA 95616, USA; 2State Key Laboratory of Solidification Processing, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, P.R. China.

ABSTRACT: Highly stable ceria nanoparticles (< 11 nm) with different manganese contents were prepared by a co-precipitation method. The powders were studied by x-ray diffraction, transmission electron microscopy, electron energy loss spectroscopy, and water adsorption microcalorimetry. The data show that only a small fraction of the manganese ions dissolved into ceria fluorite structure as solid solution, and most segregated on the particles’ surface, causing decrease of the average surface energy of the particles with increasing dopant concentration. This was confirmed by direct surface energy measurements using water adsorption microcalorimetry, and has consequences on particle coarsening behavior. That is, the results explain why manganese doped ceria nanoparticles show stronger resistance to coarsening as compared to undoped ceria. The enthalpy of surface segregation of manganese was calculated and discussed as an important parameter to design highly metastable ceria nanoparticles on a thermodynamic basis. 1 / 38

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Keywords: Surface enrichment; Mn doped ceria; Surface energy; thermodynamic stability.

Introduction Cerium oxide is a fluorite structured ceramic finding applications in many oxidative catalysts 1 and gas sensors 2. In those scenarios, particles with elevated surface areas are of particular interest as they increase exposure of active surfaces. However, while ceria nanoparticles are suitable candidates due to their high surface to volume atomic ratios, this is also responsible for an increase in the driving force (total surface energy) for coarsening phenomena, causing nanoparticles to be highly unstable at moderate to elevated temperatures. One of the most effective ways to improve stability of nanoparticles is the usage of ionic additives. When an additive is introduced into a particulate system, it may create a second phase 3

, dissolve into the crystal structure of the host material to form a solid solution 4 or segregate to

the surface (as a surface excess) or at the grain boundaries (as grain boundary excess) of the host particles 5. If surface segregation happens, it will greatly modify nanoparticle’s surface chemistry, and hence possibly lead to an increase in nanostability. That is, surface segregation of a dopant is intrinsically connected to a reduction of the surface energy of the host materials, as described by Gibbs adsorption isotherm equation for two-components 6: dγ = −Γ1dµ1 − Γ 2 dµ2

(1)

Where γ is the surface energy, subscripts “1” and “2” denote components 1 for solvent and 2 for solute, Γ is the excess at the surface (also called relative excess surface quantities or the relative adsorption of component 2 with respect to component 1), expressed by n/A with n the amount of

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component at the surface and A the surface area, and µ is the chemical potential of each components 1 and 2. Under the dilute solution, µ can be described by

µ = µ 0 + RT ln x

(2)

with µ0 being the chemical potential of the pure component and x the molar fraction of the component in bulk phase. If only these two components integrate the system (x1+x2=1), equations (2) and (1) can be changed into: dγ = −

RT A

 x2   n2 − n1  dlnx2 = − RT Γ 2,1dlnx2 1 − x2  

(3)

where Γ2,1 is the Gibbs excess. From Eq. (3), we can draw the conclusion that the surface energy of a system decreases with an increase of the surface excess of dopant. Consistently with coarsening models 7, where the particle size is directly proportional to the surface energy, one can then expect that a decrease in surface energy will promote smaller particle sizes at a given temperature. Or in other words, the surface excess will be directly related to the thermodynamic stability of the nanoparticles, and can be used as a designing tool. The effects of surface segregation on the thermodynamic stability of nanoparticles have been shown for many different systems by using simulation methods. For example, Deng et al. have studied the surface segregation and atomic-scale structural features of Au-Ag nanoparticles using Monte Carlo simulations8. The results showed Ag segregates on the surface of Au nanoparticles. Besides, due to the competition between surface segregation and alloy formation, larger Au nanoparticles had more alloying features but smaller Au nanoparticles had more obvious segregation features, indicating the positive effect of Ag surface segregation on improving

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nanostablity of Au nanoparticles. Additionally, this segregation phenomenon has been experimentally observed for many alloys systems in the past decades. By measuring the contractile forces in thin foils, the surface energy of dilute alloy of iron with phosphorus has been obtained9 and the results revealed that the surface energy of the iron alloy system decreased due to the phosphorus segregation on the interfaces. Therefore, the iron alloy is thermodynamically more stable than the corresponding pure iron nanosystem. Many doped oxides have also shown indirectly this effect of segregation on nanostability. For instance, by using a nitric acid washing method, the amount of the surface excess of Mg ion when doping tin dioxide was quantitatively determined and a relationship between this amount, the surface energy and the particle size was established by Gouvea et al.

10

. As predicted by

equation (3), because Mg is very prone for segregation in SnO2, by increasing dopant concentration, surface excess of Mg ion will also increase, causing a systematic decrease in the surface energy and smaller equilibrium particle sizes. Similar phenomenon was found in Gd doped CeO2 particles

11-12

, where the grain size of the nanoparticles was remarkably decreased

with increasing Gd content, suggesting the decrease of the surface energy. The studies of Zr dopedγ–Al2O313, Mg doped ZrO214 and Sb doped TiO215 also showed the similar effects. However, direct evidence of this decrease in the surface energy associated with the surface excess is rarely found in the literature. This is because the surface energies are extremely small quantities, and though many methods have been proposed in the literature

16-17

, only recently

practical experimental techniques have been reported to assess the surface energies of oxides with high accuracy

16, 18-19

. Amongst the methods, water adsorption microcalorimetry has

recently demonstrated the potential to assess surface energies of doped system using a single sample for testing 20. Per principle, the method is based on the measurement of the heat of water 4 / 38


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molecules adsorption on the particle’s surface as a function of the water surface coverage. The surface energy of the anhydrous state can then be calculated based on the equation: = + ∙ Δ

(4)

Where θ is the surface coverage, ∆ is the heat of water adsorption, is the surface energy of the anhydrous surface and is the surface energy at the θ coverage. The adsorption experiment is performed till the point where the surface is fully covered by water, such that the surface behaves water-like. At this point the heat of adsorption converges to -44 kJ.mol-1 (heat of liquefaction of water), and the surface energy of the particle converges to that of water itself (0.072 J.m-2), enabling the calculations of the anhydrous state energy according to equation (4). Note that, besides the advantage of this method that it only requires a single sample, the measurement is carried out at the room temperature, avoiding problems associated with high temperatures, such as changes in stoichiometry 21-22. In this work, with the goal of achieving thermodynamically designed highly stable CeO2 nanoparticles, we have studied Mn as a dopant that was likely prone to segregate to the surface of the particles, and correlated segregation profile, surface energetics and particle sizes. The dopant was selected because of the ionic radii, given the premise that dopant cations with ionic radii greatly different from the host structure cations are likely to segregate to the surface 23, and based on previous indirect evidences of segregation reported in the literature

24

. Segregation

studied were carried out by using Electron Energy Loss Spectroscopy (EELS) in Scanning Transmission Electron Microscopy 25-26.

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Experimental Procedures Synthesis: Mn doped ceria nanoparticles were synthesized by a co-precipitation method. Cerium nitrate hexahydrate [Ce(NO3)3•6H2O, 99.99%, Alfa Aesar] and Manganese carbonate [MnCO3, 99.9%, Alfa Aesar] were used as the cationic precursors, and ammonia solution was used as the precipitating agent. In a typical synthesis procedure, 100 mL of a solution containing cerium ([100 – x] mol%) and manganese ([x = 2, 5, or 10] mol%) ions (0.15M for total cations) were added drop wise into a 100 mL of ammonia solution (1.5M), which was kept under constant stirring at room temperature. After homogenizing for 2 h, the resultant suspension (hydroxide) was centrifuged and washed repeatedly with distilled water and ethanol. The precipitate was dried at 90°C for 24 h and calcined at 600°C for 8 h under oxygen flow to obtain the Mn doped cerium oxide nanoparticles. Characterization: X-ray powder diffraction (XRD) data was collected using a Bruker D8 Advance diffractometer using CuKα1 radiation (λ=1.5406Å) and a spinning sample holder. The operating parameters were 40 kV and 40 mA, with a 0.017°step size and 0.7s dwell time. LaB6 (NIST SRM 660a) was mixed with the sample as a standard for the lattice parameter calculations. To determine the crystallite size, WPF (Whole Pattern Fitting) refinement was performed in the JADE software (version 6.11, 2002, Materials Data Inc., Livermore, CA). In order to examine the morphology and aggregation state of the samples, transmission electron microscope (TEM) images were acquired with JEOL JEM 2500 transmission electron microscope (TEM) operated at 200 kV. The TEM samples were prepared by dispersing the powders into ethanol, ultra-sonicating the solution and depositing the dispersed nanoparticles on a copper grid.

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By using a Micromeritics ASAP 2020 instrument, the surface areas of the Mn doped CeO2 samples were measured based on the Brunauer-Emmett-Teller (BET) method. For these measurements, all samples were degassed under vacuum at 400℃ for 12 h and then reoxidized under oxygen (P=700 mmHg) at 400 °C for another 12 h. During the analysis, the sample tube was dipped into liquid nitrogen and then five-point adsorption isotherms of nitrogen were acquired at the relative pressure range from 0.05 to 0.30. Each sample was examined three times to get an average value of the surface area. In order to measure the water content of the samples as well as to design a proper degassing temperature (needed for the water adsorption experiment), thermogravimetric analysis and differential scanning calorimetry (TGA/DSC) was performed simultaneously by using a SETSYS 1600 system (Setaram Inc., France). The Mn doped CeO2 samples were heated from room temperature up to 1300 °C at 10°C/min under air at a flow rate at 20 mL/min. The final data were collected after subtracting the baseline correction: a TGA/DSC run with empty platinum crucibles under the same conditions. The surface segregation of Mn on Ceria nanoparticles was determined by STEM-EELS analysis using a JEOL JEM 2100F/Cs scanning transmission electron microscope (STEM) operated at 200 kV. STEM probe size was ~1.5 Å. Spectrum imaging was recorded using a Gatan Tridiem parallel electron energy loss spectrometer. Beam damage of the sample was avoided by using a cryo-holder stage which keeps the sample at about -176 °C. The EELS spectra were acquired with a pixel dwell time of 0.75 s and dispersion of 0.2 eV/channel. Water Adsorption Microcalorimetry: The aim of this experiment is to measure the surface energy of the pure CeO2 and Mn doped CeO2 samples. In order to achieve this goal, a Micromeritics ASAP 2020 instrument and a Setaram Sensys Calvet microcalorimeter were 7 / 38



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combined to measure the enthalpy of water molecules adsorption on the surface of particles as a function of coverage. In this combination, the ASAP 2020 instrument, equipped with turbo pumps and a furnace for sample degassing, was used to record the relative pressure of water vapor (defined as the absolute water vapor pressure inside the tube divide by the saturated water vapor pressure at operating temperature).and adsorbed water quantities. Meanwhile, the microcalorimeter was used to acquire the heat of water adsorption, which after proper calibration (with gallium melting) and combination with the adsorbed water quantities was used to calculate the enthalpy of adsorption per mol (details of this experimental setup can be found elsewhere 1819,27

). The uncertainties in the calculated heats of adsorption are estimated below 2%, considering

errors from microstructural characterizations and calorimetric measurements themselves. For a typical experiment, the sample with a total surface area around 2 m2 was put into one leg of a fork tube and the other leg was left empty as a reference in the heat measurement. Prior to analysis, the sample was degassed under vacuum for 12 h at 400℃ to get an anhydrous surface condition (as determined by DSC/TG run as the condition where no mass change is observed) and then oxidized under oxygen at the same temperature for another 12 h to allow oxidation of the surface reduced by the vacuum. After that, the fork tube was kept at 25℃ for the rest of the experiment, and about 2 µmol water per dose was kept pumping into the fork tube by the ASAP 2020 automatically until the relative pressure reached the value of ~0.72. The equilibrium delay time between two doses was 2 h at the beginning of the experiment (initial doses), and then it was changed to 1 h and finally reduced to 0.5 h at the higher relative pressure. The change in time is consistent with the time required for the adsorption process to take place (as monitored by length of calorimetric peaks). In order to subtract the amount of water adsorbed to the fork tube and manifold, an empty tube run was performed. 8 / 38


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Results and Discussion Mn segregation on the surface of CeO2 nanoparticles: Figure 1 shows the X-ray diffraction patterns for pure CeO2 and Mn doped CeO2 samples containing 2, 5, and 10 mol% Mn. Only the CeO2 cubic fluorite structure was detected in all samples, with the absence of second phases. Due to the ionic radii difference, direct solid solution of Mn in CeO2 would lead to pronounced peak position shifting towards higher 2θ angles; this was not observed, indicating limited solid solution up to 10mol% Mn. To further evaluate this, lattice parameter measurements were performed for pure CeO2 and Mn doped CeO2 samples using LaB6 as a standard and the results are shown in Figure 2 and Table 1.

4.0

10%Mn

3.5 3.0

Intensity (a.u.)

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


5%Mn 2.5 2.0

2%Mn

1.5 1.0

0%Mn

0.5 0.0 20

30

40

50

60

70

80

90

Two Theta (degrees)

Figure 1. The X-ray diffraction pattern for Mn doped CeO2 samples with different dopant concentration (0, 2, 5, 10 mol% Mn). 9 / 38



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The lattice constant for undoped nanocrystalline CeO2 was determined as 5.4129(5)Å, which is slightly larger than previously reported bulk CeO2 parameter, 5.411Å. Variations in the lattice parameter in nanocrystalline ceria have been attributed to a larger lattice strain induced by the presence of Ce3+ and associated oxygen vacancies, as described by Deshpande et al. 28. That is, small sizes lead to increase in Ce3+ concentration. However, the observed ∆a in the present work is not consistent with the correlation between grain size and lattice distortion prediction by Deshpande et al. This difference can be explained based on the oxidation procedure adopted in the synthesis of nanoparticles here, which is designed to minimize the amount of reduced cerium. That is, the content of reduced cerium is not only dependent on the grain size, but also on the processing history. On the other hand, by using Deshapande et al. data, one can also establish a relationship between lattice distortion and Ce3+ content in the sample. By doing that, one may calculate that the Ce3+ content in the pure CeO2 nanocrystalline samples in our work is below 1 mol% of the total cerium atoms.

Table 1. Lattice parameters from XRD patterns for Mn doped CeO2 samples with different dopant concentration (0, 2, 5, 10 mol% Mn) and crystallite sizes calculated from WPF refinement and surface area measured by BET method.

Sample

Lattice Parameter, Å

Crystallite size, nm (XRD)

Surface area, m2/g (BET)

CeO2

5.41295±0.00030

10.8±0.4

70.77

2%Mn CeO2

5.41021±0.00037

9.6±0.3

72.67

5%Mn CeO2

5.40695±0.00045

8.5±0.3

76.35

10%Mn CeO2

5.40505±0.00049

7.3±0.3

78.95

10 / 38


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Figure 2 also shows that after doping with Mn, the lattice parameter of the doped CeO2 sample slightly decreases, suggesting the formation of limited solid solution. Given that Mn is expected to be found in the 3+ valence state, oxygen vacancies are generated during solubility, causing lattice distortion 29. However, based on Vegard’s law 30, a linear dependence of lattice parameter on dopant concentration is expected whenever all dopant content is dissolved in solid solution. The deviation from linearity then suggests the occurrence of Mn surface segregation, especially when Mn concentration is higher than 5 mol% 24.

5.414

Lattice Parameter (angstrom)

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


5.412

5.410

5.408

5.406

5.404 0

2

4

6

8

10

Dopant Concentration (mol%)

Figure 2. The lattice parameter for Mn doped CeO2 samples with different dopant concentration (0, 2, 5, 10 mol% Mn). The evidence of segregation is also supported by the clear broadening of the reflection peaks in the XRD patterns (Figure 1) with increasing Mn concentration. This indicates a systematic decrease of the crystallite size. Table 1 summarizes the crystallite sizes calculated from WPF refinement and specific surface areas measured by BET method. The simultaneous increase of surface area and decrease in crystallite sizes suggest an increase in the nanostability of CeO2 11 / 38



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nanoparticles by the addition of Mn dopant since all samples were calcined at the same temperature. As suggested by equation (3), this is likely to be dependent on a decrease of surface energy associated with surface segregation. The particle sizes were directly measured for pure ceria and 10 mol% Mn doped CeO2 samples also from TEM images and the results are 11.7±4.5nm and 7.9±2.4nm, respectively, and are very consistent with XRD data. The errors here are particle size distribution, not uncertainties. Furthermore, assuming all of the nanoparticles are spherical and there is no agglomeration in the samples, we can estimate the average nanoparticle grain sizes based on the surface area results using equation D = 6000/ (ρ*SA), where D is the average particle grain size, ρ is density and SA is the surface area. The results are D (pure ceria) = 11.8nm and D (10%Mn-CeO2) = 10.5nm. This average grain size of pure ceria is corresponding very well with the grain size from TEM images as well as the crystallite size estimated from XRD. However, for 10 mol% Mn doped CeO2 sample, the average grain size estimated from the surface area is larger than the crystallite size calculated from XRD, resulting from the agglomeration in Mn doped CeO2 nanoparticles.

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Figure 3. EELS Spectrum Imaging. (a) The HAADF STEM micrograph of a CeO2 containing 10 mol% Mn (inset: the full particle). (b) The spatial distribution map of the integrated Mn EELS intensities. High intensities are presented by gray/white colors while low intensities are black/light gray. During spectrum image acquisition spatial drift of the TEM sample could not be avoided and hence caused a rigid shift of the spectral intensities with respect to (a). (c) and (d) are the profiles of Mn EELS intensities extracted along the arrows in (b). To directly test the surface segregation hypothesis, electron energy loss spectroscopy (EELS) was performed on the samples. For convenience, we focus on 10 mol % Mn doped CeO2, as the higher concentration allows better visualization of the manganese distribution profile. Figure 3(a) shows a high-angle annular dark-field (HAADF) STEM micrograph of the nanoparticle that served as a survey image for subsequent EELS acquisition. The EELS spectrum imaging of the 13 / 38



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Mn L3 ionization edges (at 640 eV) was carried out from the area marked in Figure 3(a). Spectral intensities for the Mn L3 edges were background subtracted using an inverse power-law approximation of energy intervals above and below the ionization edges. Figure 3(b) shows a spatial distribution map of the integrated Mn EELS intensities confirming preferential segregation of Mn on the surface. During acquisition, the signals were corrected for unintentional drift of the TEM sample, but still small spatial drift of the TEM sample caused the rigid shift of the spectral intensities for Mn. Hence, we can see some intensity in the lower-farmost pixels on right side of the spectrum image although that region is outside the particle geometry depicted in Figure 3(a). Two intensity line profiles across portion of the CeO2 particle to edge of the particle, extracted along the arrows marked in Figure 3(b), are plotted in Figures 3(c) and 3(d). Both EELS profiles reveal larger Mn concentrations at the surface of the particles when compared to the volume, confirming the indirect evidences of segregation from XRD and BET analyses. Surface enrichment in doped metal oxide materials has been explained based on two basic phenomena. One is the formation of a space charge layer31. Surfaces and grain boundaries in ionic crystals can assume a net charge due to the allocation of defects at the interface and the difference between activation energies for the formation of charged defects. This causes a net charge at either surface or grain boundary that must be compensated by the formation of a charged layer of opposite sign. For metal oxide doped with aliovalent cations, this space charge layer also influences dopant distribution profile, leading to segregation 3. On the other hand, the elastic strain energy caused by the ionic size mismatch between dopant and host cations32 and the associated energy for vacancy generation for charge compensation (when dealing with aliovalent dopants) will also provide additional driving force for segregation 5. Assuming that manganese is 14 / 38


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in the 3+ valence state in ceria, as studied previously

29

, the strain energy theory could be the

main reason for Mn segregation on the surface of CeO2 nanoparticles due to the difference between the ionic radius of Mn3+ (0.58Å) and Ce4+ (1.01Å) 33 and the associated energy for enthalpy of formation of vacancies for charge compensation34-35. Moreover, the different crystal structure between CeO2 and Mn2O3 (fluorite and bixbyite/spinel respectively) may also be a reason to preferentially form the Mn surface segregation, rather than solid solution.

Effects of Mn segregation on the surface energy: The fact that the crystallite size decreases and the surface area increases as a function of Mn concentration can be studied considering coarsening models governing particle size evolution31, 36. It has been suggested that ceria particle growth follows Ostwald ripening model 31:

− =

(5)

Where t is time, at is the particle size after time t, a0 is the initial particle size, D is the diffusion coefficient, γ is the surface energy, C∞ is the equilibrium solubility of the particles, Vm is the molar volume, R is the gas constant and T is the temperature. In this equation, aside from molar volume, the main two variables that can be potentially affected by doping are the diffusion coefficient and the surface energy. Note that, even if this particular coarsening model is not justifiable, D and γ are common variables in general coarsening models since from a physical point of view, final particle sizes tend to be larger with increasing diffusion in a coarsening process, while smaller surface energies tend to promote smaller particle sizes at a given temperature and time.

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In our particular case, because manganese is expected to be in the 3+ valence state, oxygen vacancies are expected for charge compensation. That is, Mn3+ substitutes Ce4+, leaving a negative net charge that is compensated by the formation of oxygen vacancies. With increasing vacancy concentration, net diffusion in ceria is increased with manganese doping. Based on this, larger particle sizes should be expected with increasing dopant concentration, which is not observed. On the other hand, because manganese is segregating to the surfaces, it also acts as an obstacle for atom diffusion, potentially decreasing the diffusion coefficient. A more likely explanation for the smaller particle sizes comes from the effect of the segregated Mn on the surface energy, as predicted in equation (3). In order to quantify the influence of Mn segregation on the surface energy, water adsorption microcalorimetry was performed for pure CeO2 and Mn doped CeO2 samples and the results are shown in Figure 4 and 5. Figure 4 shows the water coverage and the differential heats of water adsorption as a function of relative pressure for pure CeO2. According to previous studies 20, the adsorption behavior can be separated into three distinct regions based on the derivative of the adsorption isotherm curve. At very small relative pressures ( {100}, and the surface energy of the whole sample should be closer to the surface energy of {111} and {110} surfaces, in good agreement with this theoretical results. Additionally, Hayun et al. used a non-aqueous sol-gel method to synthesize nanoceria particles and determined the surface energy of nanoceria by high temperature oxide melt solution calorimetry

22

as

1.16±0.02J/m2. This is very close to what we report here, and the difference could be attributed to the different frequency of surface planes on the particles, caused by the different synthesis method. The results in Table 3 also reveal the surface energy dependence on the dopant concentration. With increasing Mn content, the surface energy decreases down to 0.95 J/m2 for 10 mol% Mn doped CeO2 sample. While the surface energy values for pure ceria and 2 mol% Mn doped CeO2 are very close to each other considering the error in the surface energy results (±0.03 J/m2), there is a significant decrease of surface energy from pure ceria to 5 or 10 mol% Mn doped CeO2 23 / 38



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samples, which will greatly increase the nanoparticle stability. That is, observing the surface area of the powders prepared at the same temperature of calcination but with different Mn contents in Table 2, one observes an increase in the surface area as the surface energy is decreasing. Figure 7 shows a plot of these two quantities evidencing the inverse proportionality. The data suggests an increase in the overall stability of nanoparticles with decreasing surface energy, consistently with coarsening model. The net change in surface energy (-0.13 J.m-2) with doping may initially sound too small to cause any representative microstructural reflection. However, when considering that the surface area of the powder is about 78.95m2/g, an energy difference of 10 J/g (comparing the doped and undoped surface energies) is observed in the total free energy of the nanoparticles and this energy decrease would potentially decrease coarsening. Note that heats of coarsening have been determined as ~30-40 J/g for MgO and ZnO nanoparticles39, suggesting that this decrease is a 30% decrease in driving force.

Table 3. The surface energy of CeO2 and Mn doped CeO2 samples. Literature data for surface energies of CeO2 are reported for comparison. Numbers in braces are surface planes. Surface energy (J/m2) 0%Mn CeO2 1.08

2%Mn CeO2

5%Mn CeO2

10%Mn CeO2

1.05

0.97

0.95

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1.16 32; 1.44 {100}; 1.06 {110}; 0.71 {111) 29

-

-

Figure 7. Surface energy and surface area of Mn doped CeO2 samples as a function of dopant concentration. Circle represents surface energy and Square represents surface area.

Enthalpy of surface segregation and the amount of surface excess: The surface energy data determined for the different dopant concentration enable the calculation of the enthalpy of Mn surface segregation on CeO2 nanoparticles, a quantity of prime importance to enable prediction of surface energy changes

40

. Krill et al.

41

derived a useful expression to show the relationship

between the enthalpy of surface segregation, ∆ H seg , s , and the surface energy change, γ s − γ s 0 , due to solute segregation: 25 / 38



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γ s = γ s 0 + Γs ∆ H seg , s

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(6)

Where Γs is the excess Mn at the surface. In order to determine the enthalpy of surface segregation, the surface excess Γs has to be known. According to the definition of surface excess, Γs can be written as

s nMn s , where nMn denotes the number of moles of Mn segregated to A

s the surface and A is the total surface area. But nMn is equal to the total mole numbers of s molecules at the surface, ns , multiplied by the mole fractions of Mn at the surface, xMn ,

therefore Γs can also be written as

s xMn . Here the physical meaning for A ns is the molar area A ns

of the molecules at surface, which is approximately equal to Ω 2 3 N avg ms , where Ω is the average volume per molecule, N avg is Avogadro’s number and ms is the number of layers for surface. Combining all these experessions, the surface excess of Mn can be written as:

Γs ≈

s ms xMn Ω 2 3 N avg

(7)

(

)

Because each unit cell of a fluorite crystal structure contains four molecules, Ω = a0 3 4 where a0 is the lattice constant. Assuming ms=1, which means the surface is a monolayer around the

particle (which is enough volume to accommodate all dopants), Eq. (7) directly relates surface excess to the mole fractions of solute at the surface. On the other hand, from Langmuir isotherm, the enthalpy of surface segregation ∆ H seg , s (ignoring the entropy of segregation) can also be expressed in terms of the mole fractions of Mn b s in the bulk (b) and the surface (s)19 xMn and xMn , as: 26 / 38


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s b  ∆H seg , s  xMn xMn  = exp − s b RT  1 − xMn 1 − xMn 

(8)

b s From molar conservation, the following relation between xMn and xMn must hold true:

s b (1 − f s ) = xMn xMn f s + xMn

(9)

Where xMn is the total dopant (Mn) concentration, and f s is the surface site fraction, approximately equal to the surface volume Vs divided by the total volume of the particles V. Assuming all the particles are spherical, f s can be expressed as: 4π (G 2 ) δ s 6δ s fs = = 3 G 4π (G 2 ) 3 2

(10)

Here G is the average diameter of the particles and δ s is the thickness of the surface, which can be expressed by m s Ω 1 3 . Here we use least squares method to find the optimum value of ∆H seg , s for all dopant b s concentration and then the value of xMn as well as xMn by combining Eq. (6) to (10). Note that,

although the enthalpy of surface segregation should change for different dopant concentrations, i.e. the value at lower dopant concentrations is expected to be higher than that at higher dopant concentration due to a steric hindrance effect, as proposed by Sayle et al.

42

, the optimum

enthalpy of surface segregation calculated here represents the average value for all compositions. This is a limitation of the proposed method to calculate this quantity. On the other hand, the value can still be considered a strong experimental criterion to judge the tendency of the dopant surface segregation. The calculation yields ∆ H seg , s = -29.7 kJ/mol. This value corresponds well

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Page 28 of 38

to the surface segregation enthalpies of other dopants in CeO2 materials, such as 20 mol% Gd doped CeO2 (-47.7 kJ/mol)43, 10 mol% La doped CeO2 (-34.2 kJ/mol)44 and 10 mol% Cu doped CeO2 (-38.6 kJ/mol)45. Because of this very negative enthalpy of surface segregation, we may expect that Mn has a strong thermodynamic driving force to segregate on the surface of CeO2, as we have observed by EELS analysis in this paper.

Figure 8. The mole fractions of Mn in the bulk and on the surface of CeO2 materials as a function of Mn dopant concentrations. Circle represents the mole fraction of Mn segregated on the surface and Square represents the mole fraction of Mn dissolved in the bulk phase.

The enthalpy of segregation enables the calculation of mole fractions of Mn in the bulk and on the surface of CeO2 using the above mentioned equations, which gives a quantitative analysis of the segregation profile. Figure 8 shows the surface segregation of Mn and reveal that by adding Mn, both the amount of Mn in the bulk phase and on the surface will increase simultaneously,

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but the increase in the amount of Mn on the surface will be much faster than that in the bulk phase, suggesting most of the Mn dopant will be segregated on the surface and only a small part of Mn will dissolve in the bulk phase to form limited solid solution, which is in a good agreement with the results of lattice parameter. On the other hand, the very pronounced segregation observed in Figure 8 may raise questions about the moderate segregation profile observed in Figure 3. The discrepancy is however due to a limitation of the spectroscopic analysis. That is, one cannot get only information about the bulk phase of particles without getting also information from the surface since the electron beam has to be transmitted though the sample. Therefore, when collecting the Mn EELS signals from the “bulk”, signals from the top and the bottom of surface of the particle will also be summed to the intensity. This makes the measured Mn EELS intensity to be higher than the actual bulk intensity (without any surface contribution), leading to a smaller Xs/Xb ratio.

Conclusion

Mn doped CeO2 nanoparticles were synthesized using the co-precipitation method and Mn ion was confirmed to form surface excess by X-ray diffraction, electron energy loss spectroscopy and other characterization methods. The results showed that most of the Mn ion was segregated on particles surface and only a limited amount dissolved into CeO2 crystal structure to form solid solution. In order to find out the influence of Mn segregation on surface chemistry, we quantified

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Page 30 of 38

for the first time the surface energies of Mn doped CeO2 samples for different dopant concentration (2, 5, 10 mol%) by water adsorption microcalorimetry and the measured surface energies were found to be 1.05 J/m2 for 2 mol% Mn doped CeO2 sample, 0.97 J/m2 for 5 mol% Mn doped CeO2 sample and 0.95 J/m2 for 10 mol% Mn doped CeO2 sample. Comparing to the surface energy of pure CeO2 (1.08 J/m2), it is clear to see that the Mn segregation could cause the decrease in surface energy. With the surface energy data for different dopant concentration, the enthalpy of surface segregation was calculated, which is -29.7kJ/mol, and the mole fractions of Mn in the bulk phase and on the surface were also calculated. The strong dependence of the thermodynamic metastability of ceria nanoparticles on Mn surface segregation was confirmed by showing the close relationship between Mn concentration, surface area, and surface energy.

AUTHOR INFORMATION

Corresponding Author * Ricardo H. R. Castro. Address: One Shield Ave, Davis, CA, 95616. Phone: (530)754-2132. Email: [email protected]

Author Contributions The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.

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ACKNOWLEDGMENT

UC Lab Fees Research Program 12-LF- 239032 is acknowledged for funding. F. Liu and Mingming Gong are grateful to the Natural Science Foundation of China (Nos.51134011 and 51431008), and China National Funds for Distinguished Young Scientists (No. 51125002). DMR Ceramics 1055504 supported in part this work (R.H.R.C.)

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Table of Contents graphic

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Surface Segregation on Manganese Doped Ceria Nanoparticles and

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