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The influence of surface desorption on tritium recovery and inventory in fusion solid breeders
Journal of Nuclear Materials 141-143 (1986) 316-320 North-Holland, Amsterdam
316
THE INFLUENCE OF SURFACE DESORPTION ON TRITIUM RECOVERY AND INVENTORY IN FUSION SOLID BREEDERS * M.C. B I L L O N E Fusion Power Program, Argomle National Laboratory, Argonne, IL 60439, USA
In previous work, models were developed to describe the roles of bulk diffusion and solubility in tritium recovery and inventory in tritium-breeding ceramics (e.g., LizO and LiA102) for fusion reactor blankets. These models were tested against the data from closed-capsule (e.g., FUBR-1A) and purge-flow (e.g., TRIO) tests with varying degrees of success, depending on the breeder microstructure and the chemistry of the gas phase in and around the ceramic breeding material. In this paper, the role of surface adsorption/desorption is explored to better understand the conditions under which this mechanism is rate-limiting for tritium release and makes a significant contribution to the tritium inventory. The surface adsorption data for several oxides (e.g., A1203, F%O3, TiO2, ZnO, and SIO2) are reviewed. A model for chemisorption and physisorption (Type II) of water vapor onto solid surfaces is developed, with the constants in the model chosen to match the AI203 data. Model predictions are then compared to data from closed- and open-capsule tests.
1. Introduction A number of lithium ceramics (e.g., Li20, "y-LiAIO2, Li4S~O4, Li2ZrO3) have been considered as candidates for the solid breeder component of fusion reactor blankets. Of these materials, Li20 and T-LiAIO2 have received the most attention with regard to measurement of fundamental material properties and in-reactor performance [1]. In assessing the potential performance of candidate solid breeder materials, tritium release rate and retention (i.e., inventory) are important considerations. Tritium is generated in the breeder primarily by the 6Li (n,a) 3H reaction. It migrates (probably in cationic form) to grain boundaries by bulk diffusion and along grain boundaries to interconnected porosity by grain boundary diffusion. At pore-solid interfaces, tritium desorbs in molecular form as "1"2, HT, "1"20, a n d / o r HTO depending on the chemistry of the solid and of the gas phase in the pores. Some tritium beyond that needed for concentration-driven diffusion will remain in and on the solid due to chemical solubility, precipitation of tritium compounds, adsorption, and radiation-induced trapping. Once the tritium molecules desorb, they percolate through the interconnected porosity to a purge stream which convects the tritium out of the breeder. Depending on the specific design of the blanket with regard to coolant and purge streams, some tritium may be lost to the coolant stream through permeation. Which of the above processes are rate-limiting for tritium release and contribute the most to tritium inventory within the solid depends on the range of operating temperatures, the chemistry of the gas phase, and microstructural parameters such as grain size and porosity distribution. Bulk diffusion is reasonably well understood and modeled for both Li20 [1.] and LiA102 [1,2]. * Work supported by the US Department of Energy, Office of Fusion Energy.
While grain boundary diffusion has not been characterized, generally it is much faster than bulk diffusion and is not considered to be rate limiting. The solubility of tritoxide (OT) and the conditions under which LiOT precipitates out as a separate phase are understood reasonably well for Li20. It is generally believed that the solubility of tritium in ternary ceramics such as LiA102 should be less than it is for Li 20. However, this remains to be determined experimentally along with the solubility of tritium species when the gas phase consists primarily of T2(HT). Finally, models and material properties are available to describe tritium percolation, permeation, and convection [3]. In the present work, the chemical and physical adsorption of T20 (HTO) is addressed to determine the conditions under which surface adsorption may be an important contribution to tritium inventory. The behavior of several other oxide materials is considered, and a semi-empirical model is proposed. Model predictions are then compared to the results from open-capsule, purge-flow tests such as TRIO [4,5] and closed-capsule tests such as FUBR-1A [6].
2. Review of tritium transport modeling The tritium inventory ( I ) within the solid breeder is assumed to be the sum of three components: diffusive inventory (Id), sohibility inventory (Is), and surface adsorption inventory (Ia). The diffusive inventory depends o n the diffusion coefficient for tritium in the ceramic of interest, the grain radius, and the temperature distribution. The diffusivity of tritium in singlecrystal Li20 has been measured [7] to be quite high (e.g., an extrapolated value of 8.0 × 10 -9 cm2/s at 500°C a n d 6.1 x 10 -7 cm2/s at 900°C). For LiAIO 2, the diffusivity determined from an analysis [2] of TRIO data for fine-grained, porous, annular pellets indicates much lower values (e.g., 8.4 × 10 -17 cm2/s at 500°C and an extrapolated value of 2.4 × 10 -13 cm2/s at 900 o C).
0 0 2 2 - 3 1 1 5 / 8 6 / $ 0 3 . 5 0 © Elsevier Science Publishers B.V. ( N o r t h - H o l l a n d Physics P u b l i s h i n g Division)
M.C. Billone / Influence of surface desorption on tritium recovery and inventory
Thermodynamic solubility measurements for the Li20 system have been performed and reported [8,9]. In order to avoid precipitation of LiOH(T) as a separate phase in Li20, the moisture partial pressure must be kept below a temperature-dependent limit. For example, at 410°C the H 2 0 (1"20) partial pressure limit is 48 Pa, and at 900°C the limit is 3.4 × 10 a Pa to avoid LiOH(T) precipitation. Equations describing the solubility of hydroxide (tritoxide) in Li20 are available as functions of moisture partial pressure and temperature [9]. The solubility limit of tritium as tritoxide in Li20 is 1.31 × 10 -2 wppm at 410°C and 48 Pa and 1.37 × 103 wppm at 900°C and 3.4 x 104 Pa. No comparable data are available for the solubility of hydroxide in LiAIO2. In the absence of data, Is is assumed to be zero for model predictions of retention in LiA102. Also, while some data [10] exist on the solubility of deuterium in Li20 as a function of temperature and partial pressure, experimental verification is required before such results can be explained and used with confidence. Thus, hydrogen isotopes are treated as insoluble in Li20 and LiAlO2"for the purposes of this study. Characterizing the surface adsorption/desorption of lithium-based ceramics is very difficult to do without some basic data because of the complex nature of the mechanisms involved. In the next section, past work with other oxides is reviewed, and a semi-empirical model is proposed to estimate the order of magnitude of the adsorption inventory.
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Fig. 1. Moisture retention of several oxides. Samples were heated for 4 h in vacuum (1.33×10 -3 Pa) at the indicated temperature. The data are taken from Morimoto et al. [14,15]. chemisorbed OH was observed to be from 1 : 2 to 1 : 1 for the samples studied by Morimoto et al. [14,15]. A semi-empirical model was used to fit the Al203 data of Morimoto et al. A reasonably good fit to the A1203-chemisorbed OH at - 10 -3 Pa system pressure (fig. 1) was obtained by the correlation:
3. D a t a and models for surface adsorption
Nov = 7.1 × 101s(1064/T - 1)
Literature [11-15] pertaining to surface adsorption of gases on solids was reviewed. Of particular interest were the papers [14,15] on the chemisorption and physisorption of water vapor on the surfaces of several oxides (Al203, Fe203, TiO2, ZnO and SiO2). The data for these oxides along with the models presented in the literature [11-13] are used in the following to estimate the order of magnitude of surface effects on tritium inventory. Fig. 1 summarizes the data for the amounts of chemisorbed water (residual after degassing at - 10-3 Pa) on the surfaces of A1203, F%O3, TiO2, ZnO and SiO 2. The data can be used in two ways. First, the results are directly applicable to fabrication because they indicate the range of temperatures which must be used to "dry out" such materials after fabrication. Second, they indicate the potential for surfaces to trap OH groups when the O and H are generated within the shmple as well as from the gas. If the samples are heated in the presence of an H 2 0 partial pressure, additional chemisorption occurs. As the temperature is reduced in the presence of the H 2 0 partial pressure, then physisorption also occurs. For example, the ratio of physisorbed H 2 0 to
where T is in K. Eq. (1) gives the water content of the A1203 samples after degassing for four hours at a system pressure of - 10-3 Pa. In addition to this set of tests, Morimoto et al. [14] conducted water-adsorption-isotherm experiments by pre-treating samples at - 10 -3 Pa and temperatures of 100 to 600°C for four hours before subjecting the samples to a moisture environment at 20°C. The pressure-dependence of these results were fit with a Type-II isotherm relationship of 21(P/P0)(1 - P / P o ) - 1 (1 + 2 0 P / P o ) -1, where P is the H 2 0 partial pressure and P0 is the saturation pressure. The total chemisorbed OH groups (residual OH content from pretreatment plus additional chemisorbed OH at 20°C) is -1019 O H / m 2 at P / P o = 0.1792 (corresponds to monolayer coverage) regardless of the pretreatment temperature. To fit these data, let Nca be the additional chemisorbed OH groups after pretreatment. Then No at 20°C can be represented by:
(H atoms/m2),
(1)
21(v/p0) Noa = (1 - P / t ' o ) ( 1 + 2 0 ~ ' / ~ o )
X [1019 - 7.1 X 101s(1064/T - 1)]
(2)
M.C. Billone / Influence of surface desorption on tritium recovery bnd inventory
318 (H atoms/m2),
number (6.023 x 10 ~ atoms/g-atom) to give
where T is the preheat temperature in K. N o water-adsorption isotherm data are presented by Morimoto et al. for T > 293K and P/Po > 0. Thus, the temperature in eq. (2) is to be interpreted only as the preheat temperature, and Po is to be interpreted as the saturation temperature at 293 K (20 ° C). To extrapolate eq. (2) to higher adsorption temperatures, increased values of P0 are to be used at the adsorption temperature. The number of H atoms associated with physisorption can also be determined from the data of Morimoto et al. to be:
I a = 3 S . 3 ( 1 0 6 4 / T - 1)A s
21(P/Po)
Np = (1 -
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(H atoms/m2), •
(2Nmp) (3)
where Nmp is the surface density of liquid H20 molecules. For H20, Nmp varies from 6 × 10 is molecules/m 2 at robm temperature to 2.8 × 10 is molecules/m 2 at 374°C (the triple point for water). In terms of standard models for physisorption, eq. (3) is in the form of a Type II adsorption isotherm [12]. Eq. (1) agrees with the data of Morimoto et al. to within 11% for Nov in the preheat temperature range of 100-700°C.,At 791°C (1064 K), eq. (1) gives Nov=0 whereas the data indicated - 0 . 4 x 1018 H / m 2. Thus, Nov should be set to 0 in eq. (1) for T > 1064 K. For N¢,, the agreement between eq. (2) and the data is reasonable for preheat temperatures greater than 300 ° C. With regard to pressure-dependence, the agreement between eq. (2) and the data is excellent in the reduced pressure range of 0.1 < P/Po < 0.3. The correlation between eq. (3) and the results of Morimoto et al. is one-to-one because they essentially calculate Np from a similar equation. In summary, eq. (1) is applicable to the experimental and design ranges of temperatures for solid breeders. However, it lacks a moisture-pressure dependence. Eqs. (2) and (3) were developed based on a saturation pressure (2.34 × 10 3 Pa) of moisture at 20°C. They can be extrapolated to the triple point of moisture (374 ° C) by varying P0 from 2.34 × 103 Pa to the upper limit of 2.21 x 107 Pa at 374°C and Nmp from 6 X 10 ts molec u l e s / m 2 at 20°C to 2.8 x 10 ts molecules/m 2 at 374°C. However, the T in eq. (2) needs to be interpreted as the preheat temperature, not the adsorption temperature. In order to apply eqs. (1)-(3) to the fusion breeder problem, assume that the hydrogen isotope of interest is tritium. Let A s be the specific pore-solid surface area in m2/g for the breeder material. To convert to wppm of tritium in the breeder, the number bf H a t o m s / m 2 is simply multiplied by A s times the atomic weight of tritium (3 g / g - a t o m ) times 10 6 divided by Avagodro's
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(4)
In the next section, eq. (4) is tested against the TRIO data (LiA102) and the FUBR-1A data (LiA102 and Li20). Eq. (4) should be viewed as an upper bound on tritium retention in the sense that it assumes that no protium is available to occupy any of the surface trapping sites. Also, eq. (4) has the limitation that the temperature (T) is to be interpreted as the operating temperature and the saturation pressure (P0) is to be interpreted as the value at the temperature at which the inventory is measured for comparison between predictions and experimental data. 4. Comparison of model predictions to data Sample calculations are preformed for the TRIO-1 and FUBR-1A "y-LiA102 materials and the FUBR-1A Li20 material. A crude estimate was made from photo micrographs to determine A s for the TRIO-1 material. The specific pore-solid surface area associated with the large particles ( - 50 g m in diameter) was only - 0.02 m2/g while the fine pore-solid surface area associated with the grains ( - 0.2 g m in diameter) was 0.45 m2/g. Thus, to the first order, As - 0.5 m2/g for the y-LiA102 used in TRIO. Fig. 2 shows a comparison between the model predictions (dashed lines) for la and the values determined from the TRIO data (solid lines) for Ia. The experimental values were determined by subtracting the calculated diffusive inventory from the reported total inventory. The model predictions were calculated from eq. (4) assuming P/Po <<< 1 (i.e., using only the first term). This is because of the high temperatures involved (high saturation pressure) and the low moisture content of the purge flow. The agreement between the model calculations and the TRIO data for I , is remarkably good. 'In general, the predictions are within the error bars (based on uncertainties in generation rate and retained tritium) for the data. F o r the case of Run 20 when 02 was added to the purge, the model underpredicts the data (open circles indicate that equilibrium was not achieved). If any oxygen atoms are adsorbed to the LiA102 surface during this run, then the chemisorbed tritium in the form of OT would be greater. A limitation in the current model is that the influence of H2 a n d / o r 02 partial pressure is not included. The specific surface areas for the FUBR-1A pellets
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Fig. 2. Estimation of the "surface adsorption" inventory for TRIO-1 Runs 9-27 as a function of purge chemistry and average LiA102 temperature. Solid lines are from data. Dashed lines are based on model calculations (eq. (4)). Open circles indicate that the runs did not achieve equilibrium conditions. are 0.5 m2/g for 85% dense y-LiA102, 0.04 m2/g for 95% dense y-LiA102, and 0.085 m2/g for 85% dense Li20 [16]. Table i lists the model predicted values for diffusive, solubility, and adsorption inventories for the F U B R samples along with the total inventory measured. Because the FUBR samples were cooled before the measurements were taken, a temperature of 30°C was assumed for the calculation of P0 in eq. (4). At this temperature, the partial pressure of T20 is a critical variable. As this pressure is not known, the pressure is back calculated such that the calculated tritium retention (Id + Is + Ia) agrees with the measured inventory. Therefore, the test of the models lies in the evaluation
319
of how reasonable the back-calculated T20 partial pressures axe. The inventories axe forced to match. The calculation is straightforward for the "y-LiA102 cases because solubility is ignored. The calculated diffusive inventory is negligible for the two higher, temperatures and only 4% of the measured inventory at the lowest temperature. The amount of chemisorbed tritium (in the form of OT) is calculated to be small at the operating temperatures ( - 0 at 863°C, 1.34 wppm at 716°C, and 6.96 wppm at 490°C). As the temperature is reduced to the assumed 30°C after operation, the partial pressures needed at this temperature to bring the total physisorbed and chemisorbed retentions into agreement with the data are 88 Pa for the first case, 350 Pa for the second case and 3 100 Pa for the third case. These moisture pressures appear high and are plausible only if the cerium getter tabs incorporated into the capsules axe not effective in reducing the moisture level in the capsule. For the Li20 cases, the calculation is more complicated because of the effect of solubility inventory. The calculated diffusive inventory is negligible for all three cases even allowing for grain growth. The high temperature case is easily rationalized by assuming 10 Pa of T20 at the operating temperature. Solubility is the dominant retention mechanism under these conditions. The adsorption inventory is negligible at the operating temperature and only 0.7 wppm at 30°C and 10 Pa. The middle temperature case requires a T20 partial pressure of 420 Pa at the operating temperature to yield 13.7 wppm for Is. The adsorption inventory is only 0.29 wppm at the operating temperature and 11.3 wppm at 30°C and 420 Pa T20 pressure. For the low temperature case, the formation and precipitation of LiOT at 490°C and 270 Pa is the dominant retention mechanism. 5. Discussion The model proposed for chemisorption and physisorption of tritium is intended for scoplng calculations to determine the range of temperatures, T20 partial
Table 1 Comparison between measured tritium retention (I) and calculated values for the diffusive (Id), solubility (Is), and surface adsorption (la) inventories for the y-LiAIO2 and Li20 materials used in FUBR-1A Material
Average temp. ( oC)
Measured I (wppm)
y-LiA102
863 716 490
17 40 190
Li 20
867 697 490
t
8.2 25 82
Calculated retention (wppm)
[d < 0.00 0.04 7.90 < 0.00 < 0.00 < 0.00
is 7.5 13.7 72.5
la
Assumed PT20 at 30 oC (Pa)
17 40 180
88 350 3100
0.7 11.3 9.5
10 420 270
320
M. C Billone / Influence of surface desorption on tritium recovery and inventory
pressures, and specific surface areas for which surface adsorption may be important in determining tritium inventory. The model needs to be generalized to include the steady-state effect.~ of T2, HT, H2, H 2 0 , and HTO partial pressures in the gas phase and the transient kinetics of adsorption/desorption. Also, model parameters need to be made specific to LiA102 and Li20 materials. Recall that data for A1203 were used to determine model parameters for the current work. Future efforts should be directed toward determining the solubility and surface adsorption of tritium in and on LiA102 as a function of pore-solid surface area, temperature, and partial pressures of T2, HT, H 2, T20, H20, and HTO. While the solubility of H 2 0 in Li20 is understood reasonably well, more experiments are needed to determine the solubility of H2 ( a n d / o r D 2 and T2) in Li20 and flae surface adsorption characteristics for Li20. The ongoing efforts in this direction are discussed in a separate paper [17]. With regard to the F U B R closed-capsule experiments, additional data will become available for higher-density, lower-specific-surface-area samples and higher burnup samples. Some of this additional data is prgsented in another paper [18]. It will be interesting to see if the higher density LiA102 samples have lower tritium inventory as would be expected from the surface adsorption model (eq. (4)). It would also be interesting to see if the tritium inventories increase with bumup for the various ~LiA102 and Li20 samples. With the current models presented in this paper, it is difficult to rationalize the high tritium inventories observed in closed-capsule tests for LiA102. However, the modeling has been .hampdred somewhat by the uncertainty in T20 partial -pressure'witldn the capsule. Also, the effects of irradiation (e.g., defects, helium bubbles, etc.) on the effective bulk diffusion coefficient and the effects of isolated, closed porosity have not beeen included in the calculations. 6. Conclusions
The calculations performed in this study, while prehminary in nature, suggest that surface adsorption could be a significant contributor to tritium inventory in LiAIO2 blanket designs with purge streams containing low protium levels ( - 3 Pa) a n d / o r high oxygen levels ( - 6 8 0 Pa). The high inventories observed in closedcapsule LiAIO2 tests remain somewhat of a mystery unless some combination of solubility, surface adsorp-
tion, and high TzO partial pressures is included. For Li20 which has an extremely high bulk diffusion coefficient, it appears that solubility, LiOT precipitation, and surface adsorption are the dominant factors in rationalizing the high tritium inventories observed in dosed capsule tests. Further testing should include thermodynamic tests to determine solubility and adsorption of moisture in LiAIO2 and surface adsorption for Li20. Future in-reactor tests should include closed and open capsules with controlled (or at least measured) moisture, oxygen, and protium levels in the gas phase. References
[1] Y.Y. Liu, M.C. Billone, A.K. Fischer, S.W. Tam and R.G. Clemmer, J. Fusion Technol., 8 (1985) 1970. [2] M.C. Billone and R.G. Clemmer, J. Fusion Technol. 8 (1985) 875. [3] M.C. Billone and Y.Y. Liu, J. Fusion Technol. 8 (1985) 881. [4] R.G. Clemmer et al., ANL-84-55, Argonne National Laboratory (1984). [5] R.G. Clemmer et at., J. Nucl. Mater. 133 & 134 (1985) 171. [6] G.W. Hollenberg, J. Nucl. Mater. 133 & 134 (1985) 242. [7] D. Guggi et at., J. Nucl. Mater. 18 (1983) 100. [8] M. Tetenbaum and C.E. Johnson, J. Nucl. Mater. 126 (1984) 25. [9] M. Tetenbaum, A.K. Fischer and C.E. Johnson, Fusion Technol. 7 (1985) 53. [10] H.R. Ihle and C.H. Wu, J. Nucl. Mater. 123 (1984) 901. [11] A. Clark, The Theory of Adsorption and Catalysis. (Academic Press, New York, 1970). [12] S.J. Gregg and K.S.W. Sing, Adsorption, Surface Area and Porosity, 2nd Ed. (Academic Press, New York, 1982). [13] E.A. Flood, The Solid-Gas Interface, (Marcel Dekker, Inc., New York, 1967). [14] T. Morimoto, M. Nagao and J. Imai, Bull. Chem. Soc. of Japan 44 (1971) 1282. [15] T. Morimoto, M. Nagao and F. Tokunda, Bull. Chem. Soc. of Japan 41 (1967) 1533. [16] G.N. Wilson and G.W. Hollenberg, Fabrication of lithium ceramics by hot pressing, in: DOE/ER-0113/2, US Department of Energy (1983). [17] A.K. Fischer, J.A. McDaniel and C.E. Johnson, Studies on surface adsorption properties of LiAIO2, to be published in J. Nucl. Mater. [18] D.L. Baldwin and G.W. Hollenberg, Measurements of tritium and helium in fast neutron irradiated lithium ceramics using high temperature vacuum extraction, to be published in J. Nucl. Mater.
316
THE INFLUENCE OF SURFACE DESORPTION ON TRITIUM RECOVERY AND INVENTORY IN FUSION SOLID BREEDERS * M.C. B I L L O N E Fusion Power Program, Argomle National Laboratory, Argonne, IL 60439, USA
In previous work, models were developed to describe the roles of bulk diffusion and solubility in tritium recovery and inventory in tritium-breeding ceramics (e.g., LizO and LiA102) for fusion reactor blankets. These models were tested against the data from closed-capsule (e.g., FUBR-1A) and purge-flow (e.g., TRIO) tests with varying degrees of success, depending on the breeder microstructure and the chemistry of the gas phase in and around the ceramic breeding material. In this paper, the role of surface adsorption/desorption is explored to better understand the conditions under which this mechanism is rate-limiting for tritium release and makes a significant contribution to the tritium inventory. The surface adsorption data for several oxides (e.g., A1203, F%O3, TiO2, ZnO, and SIO2) are reviewed. A model for chemisorption and physisorption (Type II) of water vapor onto solid surfaces is developed, with the constants in the model chosen to match the AI203 data. Model predictions are then compared to data from closed- and open-capsule tests.
1. Introduction A number of lithium ceramics (e.g., Li20, "y-LiAIO2, Li4S~O4, Li2ZrO3) have been considered as candidates for the solid breeder component of fusion reactor blankets. Of these materials, Li20 and T-LiAIO2 have received the most attention with regard to measurement of fundamental material properties and in-reactor performance [1]. In assessing the potential performance of candidate solid breeder materials, tritium release rate and retention (i.e., inventory) are important considerations. Tritium is generated in the breeder primarily by the 6Li (n,a) 3H reaction. It migrates (probably in cationic form) to grain boundaries by bulk diffusion and along grain boundaries to interconnected porosity by grain boundary diffusion. At pore-solid interfaces, tritium desorbs in molecular form as "1"2, HT, "1"20, a n d / o r HTO depending on the chemistry of the solid and of the gas phase in the pores. Some tritium beyond that needed for concentration-driven diffusion will remain in and on the solid due to chemical solubility, precipitation of tritium compounds, adsorption, and radiation-induced trapping. Once the tritium molecules desorb, they percolate through the interconnected porosity to a purge stream which convects the tritium out of the breeder. Depending on the specific design of the blanket with regard to coolant and purge streams, some tritium may be lost to the coolant stream through permeation. Which of the above processes are rate-limiting for tritium release and contribute the most to tritium inventory within the solid depends on the range of operating temperatures, the chemistry of the gas phase, and microstructural parameters such as grain size and porosity distribution. Bulk diffusion is reasonably well understood and modeled for both Li20 [1.] and LiA102 [1,2]. * Work supported by the US Department of Energy, Office of Fusion Energy.
While grain boundary diffusion has not been characterized, generally it is much faster than bulk diffusion and is not considered to be rate limiting. The solubility of tritoxide (OT) and the conditions under which LiOT precipitates out as a separate phase are understood reasonably well for Li20. It is generally believed that the solubility of tritium in ternary ceramics such as LiA102 should be less than it is for Li 20. However, this remains to be determined experimentally along with the solubility of tritium species when the gas phase consists primarily of T2(HT). Finally, models and material properties are available to describe tritium percolation, permeation, and convection [3]. In the present work, the chemical and physical adsorption of T20 (HTO) is addressed to determine the conditions under which surface adsorption may be an important contribution to tritium inventory. The behavior of several other oxide materials is considered, and a semi-empirical model is proposed. Model predictions are then compared to the results from open-capsule, purge-flow tests such as TRIO [4,5] and closed-capsule tests such as FUBR-1A [6].
2. Review of tritium transport modeling The tritium inventory ( I ) within the solid breeder is assumed to be the sum of three components: diffusive inventory (Id), sohibility inventory (Is), and surface adsorption inventory (Ia). The diffusive inventory depends o n the diffusion coefficient for tritium in the ceramic of interest, the grain radius, and the temperature distribution. The diffusivity of tritium in singlecrystal Li20 has been measured [7] to be quite high (e.g., an extrapolated value of 8.0 × 10 -9 cm2/s at 500°C a n d 6.1 x 10 -7 cm2/s at 900°C). For LiAIO 2, the diffusivity determined from an analysis [2] of TRIO data for fine-grained, porous, annular pellets indicates much lower values (e.g., 8.4 × 10 -17 cm2/s at 500°C and an extrapolated value of 2.4 × 10 -13 cm2/s at 900 o C).
0 0 2 2 - 3 1 1 5 / 8 6 / $ 0 3 . 5 0 © Elsevier Science Publishers B.V. ( N o r t h - H o l l a n d Physics P u b l i s h i n g Division)
M.C. Billone / Influence of surface desorption on tritium recovery and inventory
Thermodynamic solubility measurements for the Li20 system have been performed and reported [8,9]. In order to avoid precipitation of LiOH(T) as a separate phase in Li20, the moisture partial pressure must be kept below a temperature-dependent limit. For example, at 410°C the H 2 0 (1"20) partial pressure limit is 48 Pa, and at 900°C the limit is 3.4 × 10 a Pa to avoid LiOH(T) precipitation. Equations describing the solubility of hydroxide (tritoxide) in Li20 are available as functions of moisture partial pressure and temperature [9]. The solubility limit of tritium as tritoxide in Li20 is 1.31 × 10 -2 wppm at 410°C and 48 Pa and 1.37 × 103 wppm at 900°C and 3.4 x 104 Pa. No comparable data are available for the solubility of hydroxide in LiAIO2. In the absence of data, Is is assumed to be zero for model predictions of retention in LiA102. Also, while some data [10] exist on the solubility of deuterium in Li20 as a function of temperature and partial pressure, experimental verification is required before such results can be explained and used with confidence. Thus, hydrogen isotopes are treated as insoluble in Li20 and LiAlO2"for the purposes of this study. Characterizing the surface adsorption/desorption of lithium-based ceramics is very difficult to do without some basic data because of the complex nature of the mechanisms involved. In the next section, past work with other oxides is reviewed, and a semi-empirical model is proposed to estimate the order of magnitude of the adsorption inventory.
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Fig. 1. Moisture retention of several oxides. Samples were heated for 4 h in vacuum (1.33×10 -3 Pa) at the indicated temperature. The data are taken from Morimoto et al. [14,15]. chemisorbed OH was observed to be from 1 : 2 to 1 : 1 for the samples studied by Morimoto et al. [14,15]. A semi-empirical model was used to fit the Al203 data of Morimoto et al. A reasonably good fit to the A1203-chemisorbed OH at - 10 -3 Pa system pressure (fig. 1) was obtained by the correlation:
3. D a t a and models for surface adsorption
Nov = 7.1 × 101s(1064/T - 1)
Literature [11-15] pertaining to surface adsorption of gases on solids was reviewed. Of particular interest were the papers [14,15] on the chemisorption and physisorption of water vapor on the surfaces of several oxides (Al203, Fe203, TiO2, ZnO and SiO2). The data for these oxides along with the models presented in the literature [11-13] are used in the following to estimate the order of magnitude of surface effects on tritium inventory. Fig. 1 summarizes the data for the amounts of chemisorbed water (residual after degassing at - 10-3 Pa) on the surfaces of A1203, F%O3, TiO2, ZnO and SiO 2. The data can be used in two ways. First, the results are directly applicable to fabrication because they indicate the range of temperatures which must be used to "dry out" such materials after fabrication. Second, they indicate the potential for surfaces to trap OH groups when the O and H are generated within the shmple as well as from the gas. If the samples are heated in the presence of an H 2 0 partial pressure, additional chemisorption occurs. As the temperature is reduced in the presence of the H 2 0 partial pressure, then physisorption also occurs. For example, the ratio of physisorbed H 2 0 to
where T is in K. Eq. (1) gives the water content of the A1203 samples after degassing for four hours at a system pressure of - 10-3 Pa. In addition to this set of tests, Morimoto et al. [14] conducted water-adsorption-isotherm experiments by pre-treating samples at - 10 -3 Pa and temperatures of 100 to 600°C for four hours before subjecting the samples to a moisture environment at 20°C. The pressure-dependence of these results were fit with a Type-II isotherm relationship of 21(P/P0)(1 - P / P o ) - 1 (1 + 2 0 P / P o ) -1, where P is the H 2 0 partial pressure and P0 is the saturation pressure. The total chemisorbed OH groups (residual OH content from pretreatment plus additional chemisorbed OH at 20°C) is -1019 O H / m 2 at P / P o = 0.1792 (corresponds to monolayer coverage) regardless of the pretreatment temperature. To fit these data, let Nca be the additional chemisorbed OH groups after pretreatment. Then No at 20°C can be represented by:
(H atoms/m2),
(1)
21(v/p0) Noa = (1 - P / t ' o ) ( 1 + 2 0 ~ ' / ~ o )
X [1019 - 7.1 X 101s(1064/T - 1)]
(2)
M.C. Billone / Influence of surface desorption on tritium recovery bnd inventory
318 (H atoms/m2),
number (6.023 x 10 ~ atoms/g-atom) to give
where T is the preheat temperature in K. N o water-adsorption isotherm data are presented by Morimoto et al. for T > 293K and P/Po > 0. Thus, the temperature in eq. (2) is to be interpreted only as the preheat temperature, and Po is to be interpreted as the saturation temperature at 293 K (20 ° C). To extrapolate eq. (2) to higher adsorption temperatures, increased values of P0 are to be used at the adsorption temperature. The number of H atoms associated with physisorption can also be determined from the data of Morimoto et al. to be:
I a = 3 S . 3 ( 1 0 6 4 / T - 1)A s
21(P/Po)
Np = (1 -
P/Po)(1 +'20P/Po)
(H atoms/m2), •
(2Nmp) (3)
where Nmp is the surface density of liquid H20 molecules. For H20, Nmp varies from 6 × 10 is molecules/m 2 at robm temperature to 2.8 × 10 is molecules/m 2 at 374°C (the triple point for water). In terms of standard models for physisorption, eq. (3) is in the form of a Type II adsorption isotherm [12]. Eq. (1) agrees with the data of Morimoto et al. to within 11% for Nov in the preheat temperature range of 100-700°C.,At 791°C (1064 K), eq. (1) gives Nov=0 whereas the data indicated - 0 . 4 x 1018 H / m 2. Thus, Nov should be set to 0 in eq. (1) for T > 1064 K. For N¢,, the agreement between eq. (2) and the data is reasonable for preheat temperatures greater than 300 ° C. With regard to pressure-dependence, the agreement between eq. (2) and the data is excellent in the reduced pressure range of 0.1 < P/Po < 0.3. The correlation between eq. (3) and the results of Morimoto et al. is one-to-one because they essentially calculate Np from a similar equation. In summary, eq. (1) is applicable to the experimental and design ranges of temperatures for solid breeders. However, it lacks a moisture-pressure dependence. Eqs. (2) and (3) were developed based on a saturation pressure (2.34 × 10 3 Pa) of moisture at 20°C. They can be extrapolated to the triple point of moisture (374 ° C) by varying P0 from 2.34 × 103 Pa to the upper limit of 2.21 x 107 Pa at 374°C and Nmp from 6 X 10 ts molec u l e s / m 2 at 20°C to 2.8 x 10 ts molecules/m 2 at 374°C. However, the T in eq. (2) needs to be interpreted as the preheat temperature, not the adsorption temperature. In order to apply eqs. (1)-(3) to the fusion breeder problem, assume that the hydrogen isotope of interest is tritium. Let A s be the specific pore-solid surface area in m2/g for the breeder material. To convert to wppm of tritium in the breeder, the number bf H a t o m s / m 2 is simply multiplied by A s times the atomic weight of tritium (3 g / g - a t o m ) times 10 6 divided by Avagodro's
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(4)
In the next section, eq. (4) is tested against the TRIO data (LiA102) and the FUBR-1A data (LiA102 and Li20). Eq. (4) should be viewed as an upper bound on tritium retention in the sense that it assumes that no protium is available to occupy any of the surface trapping sites. Also, eq. (4) has the limitation that the temperature (T) is to be interpreted as the operating temperature and the saturation pressure (P0) is to be interpreted as the value at the temperature at which the inventory is measured for comparison between predictions and experimental data. 4. Comparison of model predictions to data Sample calculations are preformed for the TRIO-1 and FUBR-1A "y-LiA102 materials and the FUBR-1A Li20 material. A crude estimate was made from photo micrographs to determine A s for the TRIO-1 material. The specific pore-solid surface area associated with the large particles ( - 50 g m in diameter) was only - 0.02 m2/g while the fine pore-solid surface area associated with the grains ( - 0.2 g m in diameter) was 0.45 m2/g. Thus, to the first order, As - 0.5 m2/g for the y-LiA102 used in TRIO. Fig. 2 shows a comparison between the model predictions (dashed lines) for la and the values determined from the TRIO data (solid lines) for Ia. The experimental values were determined by subtracting the calculated diffusive inventory from the reported total inventory. The model predictions were calculated from eq. (4) assuming P/Po <<< 1 (i.e., using only the first term). This is because of the high temperatures involved (high saturation pressure) and the low moisture content of the purge flow. The agreement between the model calculations and the TRIO data for I , is remarkably good. 'In general, the predictions are within the error bars (based on uncertainties in generation rate and retained tritium) for the data. F o r the case of Run 20 when 02 was added to the purge, the model underpredicts the data (open circles indicate that equilibrium was not achieved). If any oxygen atoms are adsorbed to the LiA102 surface during this run, then the chemisorbed tritium in the form of OT would be greater. A limitation in the current model is that the influence of H2 a n d / o r 02 partial pressure is not included. The specific surface areas for the FUBR-1A pellets
M.C. Billone / Influence of surface desorption on tritium recovery and inventory T E M P E R A T U R E , *C l
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Fig. 2. Estimation of the "surface adsorption" inventory for TRIO-1 Runs 9-27 as a function of purge chemistry and average LiA102 temperature. Solid lines are from data. Dashed lines are based on model calculations (eq. (4)). Open circles indicate that the runs did not achieve equilibrium conditions. are 0.5 m2/g for 85% dense y-LiA102, 0.04 m2/g for 95% dense y-LiA102, and 0.085 m2/g for 85% dense Li20 [16]. Table i lists the model predicted values for diffusive, solubility, and adsorption inventories for the F U B R samples along with the total inventory measured. Because the FUBR samples were cooled before the measurements were taken, a temperature of 30°C was assumed for the calculation of P0 in eq. (4). At this temperature, the partial pressure of T20 is a critical variable. As this pressure is not known, the pressure is back calculated such that the calculated tritium retention (Id + Is + Ia) agrees with the measured inventory. Therefore, the test of the models lies in the evaluation
319
of how reasonable the back-calculated T20 partial pressures axe. The inventories axe forced to match. The calculation is straightforward for the "y-LiA102 cases because solubility is ignored. The calculated diffusive inventory is negligible for the two higher, temperatures and only 4% of the measured inventory at the lowest temperature. The amount of chemisorbed tritium (in the form of OT) is calculated to be small at the operating temperatures ( - 0 at 863°C, 1.34 wppm at 716°C, and 6.96 wppm at 490°C). As the temperature is reduced to the assumed 30°C after operation, the partial pressures needed at this temperature to bring the total physisorbed and chemisorbed retentions into agreement with the data are 88 Pa for the first case, 350 Pa for the second case and 3 100 Pa for the third case. These moisture pressures appear high and are plausible only if the cerium getter tabs incorporated into the capsules axe not effective in reducing the moisture level in the capsule. For the Li20 cases, the calculation is more complicated because of the effect of solubility inventory. The calculated diffusive inventory is negligible for all three cases even allowing for grain growth. The high temperature case is easily rationalized by assuming 10 Pa of T20 at the operating temperature. Solubility is the dominant retention mechanism under these conditions. The adsorption inventory is negligible at the operating temperature and only 0.7 wppm at 30°C and 10 Pa. The middle temperature case requires a T20 partial pressure of 420 Pa at the operating temperature to yield 13.7 wppm for Is. The adsorption inventory is only 0.29 wppm at the operating temperature and 11.3 wppm at 30°C and 420 Pa T20 pressure. For the low temperature case, the formation and precipitation of LiOT at 490°C and 270 Pa is the dominant retention mechanism. 5. Discussion The model proposed for chemisorption and physisorption of tritium is intended for scoplng calculations to determine the range of temperatures, T20 partial
Table 1 Comparison between measured tritium retention (I) and calculated values for the diffusive (Id), solubility (Is), and surface adsorption (la) inventories for the y-LiAIO2 and Li20 materials used in FUBR-1A Material
Average temp. ( oC)
Measured I (wppm)
y-LiA102
863 716 490
17 40 190
Li 20
867 697 490
t
8.2 25 82
Calculated retention (wppm)
[d < 0.00 0.04 7.90 < 0.00 < 0.00 < 0.00
is 7.5 13.7 72.5
la
Assumed PT20 at 30 oC (Pa)
17 40 180
88 350 3100
0.7 11.3 9.5
10 420 270
320
M. C Billone / Influence of surface desorption on tritium recovery and inventory
pressures, and specific surface areas for which surface adsorption may be important in determining tritium inventory. The model needs to be generalized to include the steady-state effect.~ of T2, HT, H2, H 2 0 , and HTO partial pressures in the gas phase and the transient kinetics of adsorption/desorption. Also, model parameters need to be made specific to LiA102 and Li20 materials. Recall that data for A1203 were used to determine model parameters for the current work. Future efforts should be directed toward determining the solubility and surface adsorption of tritium in and on LiA102 as a function of pore-solid surface area, temperature, and partial pressures of T2, HT, H 2, T20, H20, and HTO. While the solubility of H 2 0 in Li20 is understood reasonably well, more experiments are needed to determine the solubility of H2 ( a n d / o r D 2 and T2) in Li20 and flae surface adsorption characteristics for Li20. The ongoing efforts in this direction are discussed in a separate paper [17]. With regard to the F U B R closed-capsule experiments, additional data will become available for higher-density, lower-specific-surface-area samples and higher burnup samples. Some of this additional data is prgsented in another paper [18]. It will be interesting to see if the higher density LiA102 samples have lower tritium inventory as would be expected from the surface adsorption model (eq. (4)). It would also be interesting to see if the tritium inventories increase with bumup for the various ~LiA102 and Li20 samples. With the current models presented in this paper, it is difficult to rationalize the high tritium inventories observed in closed-capsule tests for LiA102. However, the modeling has been .hampdred somewhat by the uncertainty in T20 partial -pressure'witldn the capsule. Also, the effects of irradiation (e.g., defects, helium bubbles, etc.) on the effective bulk diffusion coefficient and the effects of isolated, closed porosity have not beeen included in the calculations. 6. Conclusions
The calculations performed in this study, while prehminary in nature, suggest that surface adsorption could be a significant contributor to tritium inventory in LiAIO2 blanket designs with purge streams containing low protium levels ( - 3 Pa) a n d / o r high oxygen levels ( - 6 8 0 Pa). The high inventories observed in closedcapsule LiAIO2 tests remain somewhat of a mystery unless some combination of solubility, surface adsorp-
tion, and high TzO partial pressures is included. For Li20 which has an extremely high bulk diffusion coefficient, it appears that solubility, LiOT precipitation, and surface adsorption are the dominant factors in rationalizing the high tritium inventories observed in dosed capsule tests. Further testing should include thermodynamic tests to determine solubility and adsorption of moisture in LiAIO2 and surface adsorption for Li20. Future in-reactor tests should include closed and open capsules with controlled (or at least measured) moisture, oxygen, and protium levels in the gas phase. References
[1] Y.Y. Liu, M.C. Billone, A.K. Fischer, S.W. Tam and R.G. Clemmer, J. Fusion Technol., 8 (1985) 1970. [2] M.C. Billone and R.G. Clemmer, J. Fusion Technol. 8 (1985) 875. [3] M.C. Billone and Y.Y. Liu, J. Fusion Technol. 8 (1985) 881. [4] R.G. Clemmer et al., ANL-84-55, Argonne National Laboratory (1984). [5] R.G. Clemmer et at., J. Nucl. Mater. 133 & 134 (1985) 171. [6] G.W. Hollenberg, J. Nucl. Mater. 133 & 134 (1985) 242. [7] D. Guggi et at., J. Nucl. Mater. 18 (1983) 100. [8] M. Tetenbaum and C.E. Johnson, J. Nucl. Mater. 126 (1984) 25. [9] M. Tetenbaum, A.K. Fischer and C.E. Johnson, Fusion Technol. 7 (1985) 53. [10] H.R. Ihle and C.H. Wu, J. Nucl. Mater. 123 (1984) 901. [11] A. Clark, The Theory of Adsorption and Catalysis. (Academic Press, New York, 1970). [12] S.J. Gregg and K.S.W. Sing, Adsorption, Surface Area and Porosity, 2nd Ed. (Academic Press, New York, 1982). [13] E.A. Flood, The Solid-Gas Interface, (Marcel Dekker, Inc., New York, 1967). [14] T. Morimoto, M. Nagao and J. Imai, Bull. Chem. Soc. of Japan 44 (1971) 1282. [15] T. Morimoto, M. Nagao and F. Tokunda, Bull. Chem. Soc. of Japan 41 (1967) 1533. [16] G.N. Wilson and G.W. Hollenberg, Fabrication of lithium ceramics by hot pressing, in: DOE/ER-0113/2, US Department of Energy (1983). [17] A.K. Fischer, J.A. McDaniel and C.E. Johnson, Studies on surface adsorption properties of LiAIO2, to be published in J. Nucl. Mater. [18] D.L. Baldwin and G.W. Hollenberg, Measurements of tritium and helium in fast neutron irradiated lithium ceramics using high temperature vacuum extraction, to be published in J. Nucl. Mater.