Actinide chemistry in the nuclear fuel cycle begins with the extraction of uranium from minerals. The common mineral phases are oxides, carbon­ates, phosphates, silicates and vanadates. Uranium recovery is typically

accomplished by leaching extracted ore with sulfuric acid (sometimes with the addition of an oxidizing agent), nitric acid, or sodium carbonate after crushing and grinding of the ore. For uranium from basic minerals, precipi­tation of Na2U2O7 is used for purification. From acid leaching processes, solvent extraction with organophosphorus or trialkylamine extraction agents selectively isolates U(VI) from the matrix. The recovered uranium is then stripped with acidic, neutral or basic solutions (depending on the extraction process employed) to allow further purification/processing and recycle of the extractant solution. Uranium can also be recovered from phosphate minerals using a somewhat more complex solvent extraction process. [9] Among the byproducts of environmental concern are mill tailing residues from uranium mining, containing most of the radioactive decay daughter activity, but also residual uranium.

The recovered uranium is then subjected to further processing to convert it to U3O8. This uranium is oxidized and converted to the fluoride with F2, providing UF6, to allow isotope enrichment. The enriched uranium stream is then sent to fuel fabrication while the residual UF6 comprising isotopi­cally depleted uranium (>99.7% 238U) is stored for later treatment and disposal. Substantial amounts of such depleted uranium reserves are found in storage at various locations.

To prepare fuel, the enriched UF6 is hydrolyzed,

UF6 (g) + 2 H2O ^ UO2F2 + 4 HF (aq) precipitated with ammonia,

2 UO2F2 (aq) + 6 NH4(OH) (aq) ^ (HN^UO (s) + NH4F (aq) + 3 H2O

and the ammonium diuranate product reduced with H2 and converted to UO2. The “green” UO2 is pressed and sintered at 1700°C in a dry H2 atmo­sphere to give a material with a small oxygen excess (UO2+x). The UO2+x ceramic material is machined to the proper size and shape then “canned” in zirconium (or aluminum) fuel pellets which are used to prepare a fuel assembly. The enriched fuel is then used to create power through sustained fission chain reactions in a reactor, producing the mixture of fission and activation products described above.

In the single pass fuel cycle, the used fuel becomes the waste form upon its discharge from the reactor, ultimately destined for disposal in a geologic repository. As long as the used fuel remains dry and it is not altered through outside intrusion, this material can be expected to remain intact, particu­larly if the surroundings remain reducing. However, it cannot be ensured that water will never contact the waste package. Over the millennia that used fuel will remain radiotoxic, alterations in climate are expected to occur, including (with high probability) periods of wet conditions and of glaciation. When this occurs, alterations and potentially oxidation of the

used fuel should be expected to occur, which ultimately leads to the poten­tial for mobilization of the radioactive materials from the fuel and migra­tion to the biosphere.

The effects of radiation damage to the solid fuel contributes an increased friability of the predominantly UO2 matrix, resulting ultimately in the con­version of the monolithic ceramic UO2 to a more readily mobilized powder. Interfacial reactions in the thermal and radiolytic environment will ulti­mately lead to deterioration of the fuel cladding and eventually to contact between the water and the fuel matrix. At this point, leaching of the fuel components by water can result in the mobilization of radioactive materials from the waste package. The distance traveled by the components from the waste package will be governed by the chemistry of the isotopes, redox conditions, strength of the interactions between the solute components and surrounding mineral surfaces, water flow rate, temperature and radiation field strength.

As noted above, those species with the greatest potential for true solubil­ity have the highest probability for significant migration from the repository. Technetium and iodine are of primary concern, followed by Np (in oxidizing conditions, but not in reducing environments) and Cs. Over time, alteration of the mineral phase or of the fuel matrix can either enhance or retard migration potential. In the case of direct disposal of fuel, the matrix is UO2. The dissolution of spent fuel releases radioactive material to the water column. Whether waste migrates any substantial distance from the reposi­tory will be a complex function of the chemistry of the radionuclides and the nature of the surroundings.

Though such assumptions must be used with caution, the release of radio­active materials from the repository will be generally predicted based on thermodynamic models. Thermodynamic models are considered to be rep­resentative, as favorable thermodynamics are a necessary condition for there to be any migration. The validity of such an assumption will depend significantly on the completeness of the model and the ambient conditions. The complexity of the system, with many solid and fluid phase reactions to be taken into account, makes accurate predictions a formidable challenge. In addition, the constant alteration provided by radiolysis, thermal gradi­ents, changes in ground water flow rates and alteration phases ultimately complicate the development of the models and could reduce the validity of thermodynamic model predictions. Colloid transport phenomena are a par­ticular challenge to making accurate predictions of migration potential using thermodynamic modeling due to the substantial variety of colloids that can be created.

A similar range of phenomena and isotopes will be present in high level wastes from reprocessing as practiced today, except for the relative absence of uranium and plutonium isotopes. In a closed loop fuel cycle, uranium is

routed to low or intermediate level waste, plutonium is recycled to the preparation of mixed-oxide fuel (MOX). The matrix of high level waste glass from reprocessing is in most cases borosilicate glass, hence the leach­ing characteristics and mineral alteration products are expected to be dif­ferent from fuel stored in cladding. For high level reprocessing wastes, the outer container is a welded stainless steel can (as opposed to zircalloy fuel cladding in direct disposal of fuel). In any disposal scenario, the tendency for radionuclides to migrate from the point of emplacement is dependent on the ambient conditions including temperature, water flow rate and redox conditions plus the contribution of engineered backfill materials. For actinide ions in general, it is expected that they should remain largely in the repository environment if the conditions remain reducing and intru­sions are limited. The primary mechanism for long distance displacement that can be envisioned for most metallic radioactive species is probably colloid transport; ionic species of low charge (Cs+, Rb+, TcO4-, I-, Br-) would be expected to manifest significantly greater mobility and to transport as simple ions.

Mixer-settlers are classed as stage-wise or equilibrium contactors because they manifest a step concentration profile as the aqueous and solvent phases pass from stage to stage. They consist of two compartments (Fig. 3.12): [2]

Contactor Differential (D) or stage-wise (S) Reliability Flexibility Ease of critically safe design Size relative to capacity Comments Spray column D Excellent Poor Good Farge Packed column D Good Poor Good Farge Rotating disc D Poor Fair Good Medium column Disk & Donut D Excellent Poor Good Medium In use at Fa Hague, column Rotary annular D Fair Fair Good Medium France Proposal only contactor Pulsed packed D Good Fair Good Medium Packing tends to column Pulsed perforated D Excellent Good Good Medium orientate with pulses In use at Sellafield, UK plate column Reciprocating D Poor Good Good Medium plate column Raining bucket D Fair Poor Poor Farge Each phase dispersed contactor Mixer-settler S Excellent Fair Poor Farge alternately In use at Fa Hague, Pump-mix S Good Good Poor Medium France and Sellafield UK mixer-settler Centrifugal S Good Good Good Small In use at Savannah contactor Static mixer S Excellent Poor Good Small River USA Proposal only

The loaded organic stream exiting the first extraction contactor is next subjected to the first scrubbing operation with a dilute HNO3 solution (dilute relative to the feed or ~2 M HNO3) to facilitate Zr and Ru removal from the organic phase. Other fission products that can be considered “entrained” versus “extracted”, such as Cs or Sr, are also removed from the organic phase in this step. The concentration of HNO3 must be judiciously chosen to prevent back extraction of U and Pu from the loaded solvent; however, the aqueous phase from the initial scrub potentially contains some uranium and plutonium, in addition to the scrubbed impurities, and is recombined with the incoming aqueous feed and returned to the extraction operation to minimize U and Pu losses.

Second scrub

The organic solvent emanating from the first scrub operation still contains the bulk of the Tc and Np that coextracted with the U and Pu. The organic is next subjected to a “technetium scrub,” where it is contacted with two scrub solutions containing different concentrations of HNO3. The first scrub with higher concentration nitric acid solution (10 M HNO3) effectively scrubs Tc from the organic phase (Baron 1993). The second scrub with a lower 1.5 M HNO3 solution essentially back extracts acid from the organic phase and limits the acidity of the organic exiting the system (Baron 1993).

Several of the UREX+ process alternatives for the treatment of LWR SNF based on the GNEP identified repository benefits were demonstrated at Argonne National Laboratory from 2003 to 2007 (Fig. 7.1). Under the GNEP program the objective was to demonstrate that all desired spent-fuel constituents could be separated by aqueous processing and that product specifications for recycle or disposal were achievable: All of the flowsheets demonstrated proved the viability of achieving the target separations goals.

The R&D conducted in support of UREX+ process development included:

1. collection and modeling of chemical data for the Argonne Model for Universal Solvent Extraction (AMUSE)

2. process design and optimization using AMUSE

3. equipment design.

All test runs were conducted using an ANL-designed 2-cm countercur­rent centrifugal contactors and were run until steady state was achieved. The fuel-derived feed to the demonstrations was LWR SNF dissolved in nitric acid using 0.5 to 1 kg fuel batches.

The UREX+ processes were operated to produce separate U and Tc product streams, a mixed fission product stream, and a lanthanide stream. The UREX+1a process, conducted in 2005 and 2006, yielded two additional streams: a Cs/Sr stream and a TRU product containing Pu, Np, Am and Cm. The UREX+3 process was conducted in 2003 and 2007, yielding Pu/Np and Am/Cm products, as well as a Cs/Sr stream. A UREX+2 process based on co-extraction of U, Pu, and Np as a first step was conducted in 2004; this process also yielded separate Pu/Np, Am/Cm/Ln and Cs/Sr products. All five demonstrations proved the feasibility of the various UREX+ alterna­tive processes to achieve the GNEP separations goals and can be summa­rized as follows:

1. The UREX separation module was repeatedly demonstrated to be viable for the selective extraction of U and Tc. The U-Tc separations was demonstrated by selective stripping and ion exchange with the latter being a more amendable industrial application.

2. The Co-extraction of U, Pu, Np, and Tc with subsequent selective strip­ping of Pu/Np and U/Tc proved viable.

3. Both CCD-PEG and FPEX separation modules prove viable for recov­ery of Cs/Sr.

4. The NPEX separation module proves viable for recovery of Pu with Np to produce a U/Pu/Np product.

5. The TRUEX separation module was repeatedly demonstrated to be viable for the separation of actinides from lanthanides at high purities as required for fuel fabrication.

6. The TALSPEAK separation module successfully separated actinides from lanthanides at high purities as required for fuel fabrication.

Specific results for several of the UREX+ alternative process are given below.

As shown in the previous section, in the course of the UNEX process the only end products formed are a high-level strip product (a concentrate of all the recovered radionuclides) and a low-level raffinate; the spent UNEX­extractant withdrawn after its use from the process could be considered as a third product of the process.

The most important condition for evaluating the suitability of a HLW treatment technology is the effective and safe management of end (second­ary) products of such a treatment. Therefore, methods for management of the strip product, raffinate and spent extractant were tested to assess the suitability of the UNEX process.

To sample molten salt and liquid metals, remote semi-automatic devices have been developed for engineering-scale experiments carried out in several laboratories. A sampling device for molten salt and liquid cadmium was installed in the engineering-scale electrorefiner at CRIEPI, as shown in Fig. 10.14. It sucks small amounts of liquids into stainless-steel tubes submerged at a predetermined depth. To separate the liquids from solid precipitates (such as oxides and intermetallic compounds), a metal frit is attached to the head of the stainless-steel tubes. By contrast, a sampling device for actinide metal ingots has been demonstrated during metal fuel fabrication for EBR-II, which uses a high-temperature vacuum injection­casting furnace equipped with quartz moulds to produce actinide metal rods. Because of the stirring effect of induction heating, the sample has sufficient homogeneity to be accepted as a reactor fuel.

The standard approach in the development of a mathematical model for any separations scheme is to begin with the equations of mass continuity and then add additional terms (e. g., equations for equilibrium, mass transfer and reaction kinetics) as needed to accurately describe a specific process. Models developed from first principles are much more flexible than those obtained by regression or simply searching for equations that give the best ‘fit’ to empirical data. Since they are derived from fundamental principles and ensure energy and/or mass continuity, they can be used to estimate performance when system parameters are changed without the constraint of maintaining dynamic similitude. Nonetheless, the model must be vali­dated or compared to actual performance data in order to assess accuracy and/or modify terms to increase model robustness. Ideally, multiple itera­tions of this comparison are done for a range of operating parameters. This provides data for refinement and serves to increase confidence in the model and validate its utility for predictive purposes. The extent of this validation process is normally determined by several factors such as model complexity, availability of published material relating to similar models and systems, and the required accuracy of the model in terms of economic, safety and regulatory drivers. From an engineering perspective, modeling solid-phase extraction is quite similar to that of other separation processes wherein solutes are separated from a flowing fluid stream onto particles packed within a column (e. g., adsorption or ion exchange). Contacting the moving fluid with a stationary solid phase is often chosen for separating dilute solutes since the packed bed functions like a very large number of thin contactors in series. Obtaining solutions for models of these systems can, however, be difficult, since the active exchange zone is changing in both spatial and temporal dimensions during the process. Changes in concentra­tion with the radial component can usually be neglected and other simplify­ing assumptions may also be valid in order to minimize computational effort. The mass balance equation for a multi-component system to account for concentration changes in the axial direction with time is typically written as (Ruthven, 1984, Klein, 1982):

13.1

d=tF (c, q)

where:

є = bed void fraction

v = average interstitial fluid velocity

z = the distance from the bed inlet in the axial direction

D = axial dispersion coefficient for the bed

к = effective mass transfer coefficient

c, q = the fluid and solid phase concentrations, respectively

t = time

F(c, q) = a driving force to be specified With initial and boundary conditions as:

I. C. (c, q)|Z=0 = 0; starting with no sorbate on resin

B. C. c|Z=0 = C0 dC t

— = 0 13.3

dZz=L

Note: specific units are not included in this generic discussion; however, the reader should understand that choices for time, mass, length and volume units must remain consistent throughout.

A few analytical solutions have been obtained for very simple, single­component cases. Approximate solutions can also be attained in some cases by utilizing classical functions of series expansions, but solutions are best achieved by numerical integration. Numerical methods utilizing finite dif­ference, orthogonal collocation, method of characteristics or combinations thereof usually give very accurate solutions; and systems having <3 compo­nents are efficiently solved with simple finite difference algorithms (Ruthven, 1984, Tranter et al., 2009b, 2005, 2002). Due to the large increase in processing speed over the last two decades, many scientists and engineers now have adequate computational power for performing efficient numeri­cal integrations via desktop computers. Software to perform the necessary matrix operations (e. g., inversion, multiplication) are available commer­cially or can be written in user friendly languages (e. g., Visual Basic®, C++, or MATLAB®). It is evident from Eqns (13.1) and (13.2) that a driving mechanism or equation for mass transfer and equilibrium must be deter­mined along with the corresponding coefficients for mass transfer, equilib­rium and dispersion. It is best to determine the mass transfer and equilibrium parameters by separate batch experiments, since these are very significant to the accuracy of the model. Dispersion effects are often minor in com­parison and values obtained from published equations (Ruthven, 1984, Chung et al., 1968) often provide adequate correlation to experimental data. Though, the dispersion coefficient can be derived independently from tracer studies if dispersion effects are determined to be substantial for a given
system. Once the governing parameters and corresponding coefficients are obtained from independent experimentation, the values are used in the dynamic model (Eqn. 13.1 and 13.2) to predict breakthrough curves for a given resin and column configuration. The predicted breakthrough curves are then compared to data obtained from experimental column tests to assess the overall accuracy and rigor of the model.

Numerous expressions for the rate equation (Eqn. 13.2) have been pro­posed (LeVan et al., 1997, Ruthven, 1984). Although many were originally developed for ion exchange or sorption processes, the mathematics are based on the physical phenomena of diffusion to describe the resulting concentration gradients established within a porous media. They may there­fore be applied to describe solid-phase extraction processes with appropri­ate technical understanding and discretion. An evaluation of the literature shows that the assumption of a linear driving force typically provides suf­ficient model accuracy and has been used quite successfully by this author and numerous others. A linear driving force in terms of the solid phase concentration is thus used for purposes of this discussion and is written as:

where:

ce, qe = equilibrium concentration at the fluid-pore interface for the liquid and solid phases, respectively

Solution of Eqn. (13.4) requires additional equations and/or terms for calculating the mass transfer coefficient and fluid-solid pore equilibrium at each time step. The form of the equilibrium equation and corresponding equilibrium constant is specific to a given solid-phase extraction process and is selected to best represent the system and match experimental data. Equilibrium expressions from the extraction stoichiometry are often used. For example, Takeshita (1999) modeled a system for Ln extraction using a styrene-divinylbenzene copolymer impregnated with CMP (dihexyl-N-N — diethylcarbamoylmethylphosphonate) and used the following equilibrium model for calculating phase equilibrium concentrations:

where:

KLn = equilibrium coefficient for the given Ln element

Other researchers have used the equilibrium isotherm approach wherein solid and liquid phase equilibrium concentrations are obtained over a range

of interest by performing multiple, isothermal batch contacts at varying ratios of sorbent to extractable species. An appropriate isotherm equation is fit to the batch data and this equation is used in the model (Eqn. 13.1) to calculate the fluid-pore phase equilibrium concentrations for each time step in the numerical solution. The Langmuir or Freundlich isotherm models (LeVan et al., 1997) are frequently used to fit the equilibrium data for single component systems and extensions may sometimes be applicable to multi­component cases. Although the mechanism of extracting the species onto the solid phase differs from the sorption phenomena assumed for the deri­vation of these models, the isotherm models often provide a good fit to the equilibrium data and can simplify the numerical computation substantially; however, they are limited to the feed conditions under which they were generated and do not provide a straightforward way of accounting for changes of significant parameters in the liquid phase, e. g. nitrate concentra­tion or total ion activity. Ultimately the selection of a model to describe equilibrium, whether more fundamental or empirical, must be based on the complexity of the system, how well it is understood and the appropriate compromise between accuracy and computational difficulty.

The transfer of metal ion into the solid-phase extraction resin consists of several steps: 1) transport of the metal from the bulk fluid to the film inter­face between fluid and particle, 2) diffusion through the film layer, 3) dif­fusion through the particle — within the pores or gel phase — and 4) complex formation between the metal and extractant impregnated in the particle. The different regions of mass transfer are depicted in Figure 13.16.

Each of the above steps contributes to the total resistance for metal uptake by the resin; however, one or two of these processes are typically much slower than the rest and become the rate limiting steps for overall mass transfer. Transport through the bulk fluid and the complex formation reaction are usually fast in comparison to film or particle diffusion, thus coefficients for mass transfer of metal in the film and/or particle are most frequently needed for solving the rate expression of Eqn (13.5). Classical methods based on data from batch experiments (Helfferich, 1995) or column interruption tests (Tranter et al., 2009b, Kurath, 1994) may be used to determine whether film or particle resistance dominates, or if both are significant. Equations for each of these cases are written as (Ruthven, 1984):

к = kpa = 2е; particle controlled diffusion

Rp

3

к = kfa = kf ; film controlled diffusion

f f Rp

1 R R2

= — + p ; both resistances controlling

к 3kf 15De

where:

kf = mass transfer coefficient in the film layer kp = overall mass transfer coefficient in the particle Rp = average particle radius De = effective intra-particle diffusivity of the metal a = area per unit volume of a spherical particle

The above equations (Eqn. 13.6) are simplified in that they represent the overall or effective terms relating to mass transfer for a given component in each phase. It should be recognized that mass transfer in the particle takes place through multiple regions (i. e., macro, micro-pores and extract­ant), each with potentially different rates of diffusion. The solid portion of the exchanger matrix occupies a substantial portion of the medium and obstructs diffusion of the ions into and out of the matrix. Even if the aqueous phase diffusion coefficients for the ions of interest are known, predicting diffusion rates within the exchanger particle is difficult because of the varied rates within the different phases of the exchanger and the tortuous path the ions must take through the pores to reach the active exchange sites. A simplified approach is often taken by treating the exchanger as a quasi-homogeneous system and assuming an average or ‘effective’ diffusion coefficient within the particle phase. This approach is frequently used in engineering practice and usually works quite well for modeling purposes. The reader is referred to the comprehensive work by Ruthven (1984) for more detailed discussion and methods of mathematical analysis of mass transfer in sorbents for both liquid and gaseous systems.

Batch kinetic studies to determine mass transfer rates in several solid — phase extraction resins have indicated that film diffusion is the controlling resistance for only a very short time when the solute is first contacted with the sorbent phase — likely corresponding to a monolayer coverage or uptake of the of solute at the pore surface (Juang et al., 1995a, 1995b, Takeshita et al., 2000). The studies indicate that mass transfer resistance in the particle phase is the dominant controlling mechanism throughout most of the period of solute uptake. Since this is likely to be the case with many solid-phase extraction resins of interest, methods for determining the effective mass transfer coefficient in the particle phase will be the focus of this discussion. Kinetic experiments are typically performed in batch mode in order to obtain the necessary data to estimate the diffusion coefficient for a given metal in the solid-phase resin particle. One technique is to simply stir or mix a beaker of solution with known volume and concentration of metal containing a known mass and particle size of resin, and then remove small aliquots of the liquid phase to measure metal uptake as a function of time. This approach has been used successfully by many researchers, but one must to careful to ensure that attrition of the resin particles by the stirring blade does not take place since mass transfer in the particle is dependent upon particle diameter. A preferred method is to use a centrifugal contact­ing apparatus similar to that described by Helfferich (1995). A device con­sisting of a stainless steel wire cage housed within the center of a circular Teflon™ housing that is connected to a stirring motor can be easily made for this purpose (Tranter et al., 2009a). Diagrams of top and side views of this type of contactor are shown in Figs 13.17 and 13.18, respectively. The device is fashioned with a threaded top and bottom portion so that the contactor can be opened to allow access to the hollow inner portion holding the wire screen or cage. The solid-phase extraction resin is sieved to obtain a fraction of known particle diameter and a measured amount of the sized exchanger material is placed in the hollow space inside the contactor. The top portion of the apparatus is then threaded tightly back onto the body of the device and it is attached to a stirring motor via the vertical shaft, as shown in Fig. 13.18. The unit is immersed in a solution of known metal ion concentration and stirred at a fixed speed. Centrifugal action produces a rapid circulating flow of solution entering the device at the bottom and exiting the wall through the radial holes in the casing. The contactor allows for very high flow rates around the adsorbent beads, thus shrinking the film layer to a point that the diffusion resistance in the film will be very small compared to that within the particle. Uptake of the solute ion by the exchanger particle is then determined as a function of time by removing and analyzing small aliquots from the bulk solution. It is important that these aliquots are very small relative to the total volume of solution so that the bulk volume remains approximately unchanged, i. e. the total ion

concentration in the fluid phase at any given point in time is not measurably reduced by sampling.

The experimental regime provides a well-stirred finite volume system and the solution method proposed by Crank (1975) for spherical particles may be applied to the kinetic data to solve for the effective intra-particle dif — fusivity. The following assumptions are made for this analysis:

• The particles are spherical and uniform.

• The particles are initially free of solute.

• The concentration of solute in the bulk phase is always uniform and is initially Co.

• The fluid velocity is sufficient to reduce the film layer to the point that diffusion in the particle is the rate limiting step for the uptake of solute.

Normalized fractional loading or uptake of the solute (F) by the exchanger during the kinetic test changes with time and is defined as:

F _ q 13.7

q

where:

qt = metal concentration in the solid phase at time t qo = metal concentration in the solid phase at equilibrium

The fractional attainment of equilibrium is expressed by the following equation (Crank, 1975):

F _ q_ _ 1 _y 6a>(a +1)exp(-Реф2пг/Rp) 13 8

q„ П=1 9 + 9Ю + ФІЮ2

where:

t = elapsed time, min

The parameter a> is calculated from the following relationship: mq„ _ 1

vc0~ ї+й

where:

m = mass of solid-phase extraction resin V = solution volume

C0 = initial metal concentration in the solution The terms for Фп are calculated from the non-zero roots of:

tan фп = 13.10

з+юф2

Equation 13.10 is solved for n = 1 to 12 and these values are then used to obtain the series solution for F. Beyond n = 12, the additional terms usually become insignificant to the solution. Equations 13.8 and 13.9, along with the 12 solutions from Eqn 13.10, are used in to fit the fractional equi­librium data from the kinetic batch experiment. The independent variable in this approach is the elapsed time t, the dependent variable is the frac­tional attainment of equilibrium F, and the adjustable parameter is the effective intra-particle diffusivity coefficient, De, for the metal of interest. The curve fits can be obtained quite easily via the numerous commercial statistical software packages now available for desktop computers. The value for De, derived by fitting the data from the kinetic batch tests, is then used in Eqn 13.6 to calculate the mass transfer coefficient for the metal in the particle phase, kp.

In summary, the general steps for model development are:

1) Perform independent batch experiments to obtain equilibrium data for the metal(s) and solid-phase extraction resin system of interest.

2) Use the equilibrium data to elucidate the best form for the equilibrium equation and derive the corresponding equilibrium coefficients.

3) Perform independent batch experiments to obtain kinetic data for the metal(s) and solid-phase extraction resin system of interest.

4) Use the kinetic data to elucidate the best form for the mass transfer equations and derive the corresponding mass transfer coefficients.

5) Numerically solve the coupled partial differential equations (Eqns 13.1 and 13.2), using the coefficients for equilibrium and mass trans­fer derived from steps 2 and 4, to generate a predicted breakthrough curve for a specified metal feed concentration and column size of solid-phase extraction resin.

6) Perform column breakthrough experiments with test conditions specified in step 5 and compare the experimental breakthrough data to the modeled results.

7) Perform several iterations of steps 5 and 6 with varying feed concen­trations, flow rates and column dimensions to evaluate the efficacy of the model.

The thermodynamics of complexation between hard acid cation and hard ligands are often characterized by positive values of both the enthalpy and entropy changes (Choppin, 2004). The positive enthalpy values indicate a net decrease in bond strength for the system (including the solvent) going
from reactants to products. The positive reaction entropy overcomes this unfavorable enthalpic component to promote complex formation. Many lanthanide and actinide complexation reactions are considered to be “entropy-driven”, since the entropy contribution from dehydration of cation is more significant than loss of entropy associated with the combina­tion of the ion with another ligand. The observed overall changes reflect the sum of the contributions of dehydration and cation-ligand combination. It has been shown that for many of the hard-hard complexation systems, there is a linear correlation between the experimental values of enthalpy and entropy of complexation reaction, a so called “compensation effect” (Choppin, 2004).

The hydration of an actinide cation is a critical factor in the structural and chemical behavior of their complexes. During the complexation reac­tion, one or more water molecules in the hydration sphere of the metal cation are replaced with a ligand, donating electrons and electrostatic mol­ecules to the central atom. Based on Pearson hard/soft acid/base theory, they are usually characterized as hard or soft donor-ligands. Actinides are “hard” Lewis acids and exhibit a strong preference for oxygen donor ligands. The complexation in aqueous solution many times involves substitution of the solvate waters with their metal—oxygen (ion-dipole) bond by a ligand (Choppin, 1971). The water expelling ligands can form either direct bonds with the metal cation in the first (inner) coordination sphere of the cation, creating a so called “inner-sphere complex”, or, if they cannot displace the water from their inner coordination sphere, they stay directly bonded only to the primary hydration sphere of the metal cation. Such “outer sphere ligands” remain separated from direct contact with the metal ion by a mol­ecule of water; such complexes have a very subtle influence on the behavior of the metal ion.

Actinide cations are known to form both outer and inner sphere com­plexes and, for labile complexes, it is often difficult to distinguish between these two types. Choppin proposed (Choppin, Strazik, 1965); (Ensor, Choppin, 1980) and (Khalili et al., 1988) the use of thermodynamic param­eters of complexation (enthalpy and entropy) to help evaluate outer sphere vs. inner sphere complexation. Because the primary solvation sphere is minimally perturbed by the ligand in outer sphere complexes, little energy is spent on de-solvation and little disordering occurs. As a result, outer sphere complexation is often associated with usually near zero enthalpy and negative and near zero entropy. In contrast, the enthalpy for inner sphere complexation is determined by the relative balance of metal-ligand bond strength and the metal-water bonds broken; usually it is small and maybe slightly exothermic while the entropy for inner sphere complexes is usually positive because more water molecules are released than ligands com — plexed (Nash, Sullivan et al., 1986, 1991).

Predominantly outer sphere ligands include Cl-, Br-, I-, ClO3-, NO3-, sulfonate, and trichloroacetate ligands, all with acid dissociation constant pKa values <2. As the pKa increases above 2, increasing predominance of inner sphere complexation is expected for carbonate/bicarbonate, sulfate, fluoride, and most carboxylate ligands (Choppin, 1998). Comparison of the thermodynamic parameters of nitrates and chlorides also reflect the inter­mediate character of the nitrate complexes (Choppin, Strazik, 1965; Choppin, Graffeo, 1965); a near zero entropy suggests that the nitrate is probably mainly monodenate with one water molecule displaced. Water coordination may induce changes in anion coordination mode and coordi­nation number. Quantum mechanical calculations suggest that when the first coordination shell is saturated, the two types of binding modes become of similar energy, leading to different coordination numbers (CNs) and distributions of first and second shell water molecules. For instance, for La(NO3)3(H2O)6, CN ranges from 9 (3 monodentate nitrates + 6 water) to 10 (3 bidentate nitrates + 4 water) or 11 (3 bidentate nitrates + 5 water). Thus, at some point, adding water to the second or to the first shell becomes isoenergetic. As the cation becomes smaller, the preference for monoden­tate nitrate binding increases, due to avoided repulsions in the first coordi­nation sphere (Dobler et al., 2001).

Whether the U(VI)-nitrate complex is “outer sphere” or “inner sphere” is another question that is still open for debate (Rao, Tian, 2008). Earlier data on the complexation of U(VI) with nitrate at variable temperatures (10-40°C) appeared to suggest that the UO2NO3+ complex was outer sphere (Ensor, Choppin, 1980; Khalili et al., 1988). However, Rao’s calorimetric data suggest that both the inner and outer sphere complexes may exist in the U(VI) nitrate system and the UO2NO3+ complex has significant inner sphere character (Rao, Tian, 2008).

The structure of actinide complexes, when H2O is replaced by the addi­tion of the ligand, for example OH-, F-, CO32-, tends to weaken the v1 stretch of the O = An = O and increase the An = O distance. On transitioning between AnO2+ to An4+: the loss of the linear dioxo unit in the lower valent complexes results in both a higher overall charge and a smaller radius of the cation, which combines to result in a slight decrease in the An-ligand bond distance (Keogh, 2005), and with a stronger metal-ligand interaction.

Experimental data on the size and structure of the hydration sphere of a metal ion are very important for understanding of metal complexation and the behavior of complexes in separation systems. They have been probed by several direct and indirect experimental methods. Recently, two reviews devoted to critical evaluation of results obtained for solution coor­dination chemistry of actinides by both direct, including X-ray and neutron diffraction, X-ray absorption fine structure (XAFS) measurements, lumi­nescence decay, nuclear magnetic resonance (NMR) relaxation measure­ments, and indirect methods such as compressibility, NMR exchange, and optical absorption spectroscopy, have been published (Choppin, Jensen, 2006; Szabo et al., 2006) Theoretical and computational studies are also important in understanding the coordination geometry and coordination number (CN) of actinide ion hydrates (e. g., Spencer et al., 1999; Hay et al., 2000; Tsushima, Suzuki, 2000; Antonio et al., 2001).

A series of solutions containing 0.1-10 mM Pu(IV) in the Simple Feed matrix was subjected to vis-NIR measurements. The spectral overlay obtained is shown in Fig. 4.4 (left). It was observed that Pu(IV) spectral features at 500-1000 nm were not obstructed by spectroscopic features of

4.5 Vis-NIR spectra of variable Pu(IV) in TBP/dodecane extraction phase (left) and corresponding calibration plots for Pu(IV) (right). Detection limit is 0.014 mM for Pu(IV) using the 640 nm band.

UO2(NO3)2 or HNO3, and linear calibration plots were obtained using four characteristic Pu(IV) bands in this region (Fig. 4.4 right). The detection limit for Pu(IV) was determined to be 0.08 mM using the 659 nm band.

The distribution of Pu(IV) from the aqueous phase into the organic phase can be followed using vis-NIR spectroscopy of both the aqueous and organic phases. The characteristic Pu(IV) bands in the TBP/n-dodecane solution were slightly different than those in the aqueous nitrate solution, which reflects expected changes in the inner coordination environment of the Pu(IV) ion upon transport into the organic solvent.

To quantitatively determine Pu(IV) in the extraction phase, a series of solutions containing 0.2-2 mM Pu(IV) in 30% TBP/n-dodecane was mea­sured by vis-NIR spectroscopy. The resulting spectral overlay is shown in Fig. 4.5 (left). The linear standard curves of the resulting Pu(IV) data are displayed in Fig. 4.5 (right). The detection limit for Pu(IV) in 30% TBP/n- dodecane was determined to be 0.014 mM using the 640 nm band.

Neptunium is present in the dissolved spent fuel predominantly as Np(V, VI) in the NpO2+ and NpO22+ chemical forms (Madic 1984). However, its redox equilibrium Np(IV) ^ Np(V) ^ Np(VI) highly depends on the multiple factors including solution composition, temperature, etc. (Guillaume 1981). This redox chemistry determines Np distribution into 30% TBP/n — dodecane phase, and therefore, its spectroscopic monitoring is desirable. The aqueous speciation of Np(V) is complex because of its coordination with nitrate anion and formation of cation-cation complexes in accord with reactions 4.2 and 4.3 (Colston 2001):

NpO2+ + n NO3- ^ [NpO2+ ■ n NO3-] 4.2

NpO2+ + Mn+ ^ [NpO2+ ■ Mn+] 4.3

where Mn+ is transition or f-metal cation. In the dissolved spent fuel, the complex species NpO2+ ■ UO22+ formed as described by reaction 4.3 are the most prominent.

The single NpO2+ band observed in 1 M HNO3 solution splits into two bands in the presence of U(VI). A second neptunium band nm emerges in the presence of U(VI) at the concentration ranges typical to the dissolved spent fuel streams (Steele 2007). As a result, Np(V) spectroscopic proper­ties are highly mobile and dependent on solution composition. To this end, understanding and quantification of Np(V) chemistry is needed to correctly interpret its vis-NIR spectra.

To investigate the spectral nature of Np in the UREX process, a series of solutions of variable Np(V) concentration in 1.33 M UO2(NO3)2 and 0.8 M HNO3 were prepared; the vis-NIR spectra are shown in Fig. 4.6 (left).

0.08 0.07 0.06 0.05 0.04 0.03 0.02 0.01 0

0 0.2 0.4 0.6 0.8 1 1.2 1.4

U concentration, M

4.7 Spectral layout of 0.3 mM NpO2+ titrated with variable UO2(NO3)2 solution, in 2.75 M HNO3 (left), and corresponding relative concentrations of the "free" and "uranyl-bound" NpO2+ species in solution (right).

Two bands observed for the Np(V) in the UREX feed solution located at 981 and 992 nm in agreement with previous reports (Steele 2007). Figure 4.6 (right) shows the standard curves for the Np(V) vis-NIR data in the Simple Feed solution (Fig. 4.6, left). To illustrate the interaction of the [NpO2+ • UO22+] cation-cation complex, a spectrophotometric titration was carried out in which uranyl nitrate was titrated into a constant concentra­tion of Np(V). Figure 4.7 (left) shows the spectral overlay of the resulting vis-NIR spectra, revealing the gradual depletion of the “free” NpO2+ ion and the gradual increase of the “uranyl-bound” [NpO2+ • UO22+] complex. The speciation diagram for the relative concentrations of the “free” and “bound” Np species are shown in Fig. 4.7 (right).

To evaluate the feasibility of Np(V) quantification in solutions containing significant concentrations of Pu(IV), a series of feed simulant solutions containing 0.1 mM Np(V) and a variable concentration of Pu(IV) (0.1-10 mM) in 1.33 M UO2(NO3)2 and 0.8 M HNO3 matrix was measured using vis-NIR (Fig. 4.8). The spectral overlay shown in this figure illustrates that the Np(V) is detected in the presence of large excesses of Pu(IV) and U(VI); Np was 100 times less concentrated than Pu, and 13 000 times less concentrated than U in solution (Levitskaia 2008). A conservative measure of the detection limit of Np(V) can be established at < 0.1 mM under UREX flowsheet conditions. An initial distribution experiment using a UREX feed containing Np(V), 10 mM Pu(IV) and 1.3 M UO2(NO3)2 in 0.8 M HNO3 showed no detectible Np(V) in the loaded 30% TBP/n — dodecane solvent by UV-vis-NIR as would be expected for the known low extractability of Np(V).

Initial chemometric analysis of vis-NIR spectral data was undertaken using separate Simple Feed solutions containing variable Np(V), U(VI),

4.8 Absorption spectra of 0.1 mM Np(V) at variable 0.1-10 mM Pu(IV) in Simple Feed (1.3 M UO2(NO3)2 in 0.8 M HNO3).

and Pu(IV). PLS analysis of vis-NIR spectral data (containing variable UO22+/Np(V)/nitric acid concentrations) yielded linear response over 0-0.5 mM range for Np(V). A PLS model of the vis-NIR spectral region for Pu(IV) in UREX feed solution (Pu(IV) in 1.3 M UO2(NO2)2 in variable HNO3) showed a linear response over the 0-10 mM range for Pu. Figure

4.9 contains the results of the PLS analysis for Np(V) (left) and Pu(IV) (right).

The UREX process was tested in miniature centrifugal contactors during 2003 as part of a series of five different solvent extraction processes called

UREX+ (Vandegrift 2004). A fuel pin with an estimated burn-up of 29,600 MWd/MT, 4.6% initial 235U enrichment, and a cooling time of 21 years was dissolved and used as feed in this process test. After dissolution, the first solvent extraction step was the UREX process where U and Tc were separated from the other actinides and fission products. The process used AHA in the scrub section of the flowsheet to remove neptunium and plutonium from the organic phase (Fig. 6.5), and route these actinides to

the raffinate end of the cascade. In order for the AHA to complex the tetravalent actinides, the acidity of the feed solution was adjusted to a fairly low acidity of ~1 M HNO3, which also resulted in increased technetium extraction. A separate technetium strip contactor using higher acid concen­tration was included in the UREX process (Fig. 6.5). To remove excess nitric acid, an acid scrub contactor was included after the Tc strip, but before the final uranium strip. The uranium product obtained from this process test reached the limits for FP decontamination. But due to a mechanical failure during processing, the desired TRU decontamination was unsuccessful. The indications were positive and a second test was carried out one year later. Tc recovery was 95% which was in line with the requirements set on the process. Recycling of the spent solvent was not carried out during the test, but solvent degradation is fairly well established as discussed above, and would likely not be affected by the addition of AHA to the process. As previously mentioned, hydroxamic acid has low solubility in the organic solvent and a solvent clean up stage would remove any residual AHA along with any dissolved HNO3.