Computational Investigation of Reactive to Nonreactive Capture of

Oct 13, 2010 - Department of Chemistry, Cornell College, Mount Vernon, Iowa 52314, ... Chemistry, UniVersity of Tennessee, KnoxVille, Tennessee 37966,...
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J. Phys. Chem. A 2010, 114, 11761–11767

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Computational Investigation of Reactive to Nonreactive Capture of Carbon Dioxide by Oxygen-Containing Lewis Bases Craig M. Teague,*,†,‡ Sheng Dai,‡,§ and De-en Jiang*,‡ Department of Chemistry, Cornell College, Mount Vernon, Iowa 52314, United States, Chemical Sciences DiVision, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States, and Department of Chemistry, UniVersity of Tennessee, KnoxVille, Tennessee 37966, United States ReceiVed: June 17, 2010; ReVised Manuscript ReceiVed: September 24, 2010

Recent work has shown that room temperature ionic liquid systems reactively absorb CO2 and offer distinct advantages over current CO2 capture technologies. Here we computationally evaluated CO2 interaction energies with a series of oxygen-containing Lewis base anions (including cyclohexanolate and phenolate and their respective derivatives). Our results show that the interaction energy can be tuned across a range from reactive to nonreactive (or physical) interactions. We evaluated different levels of theory as well as possible corrections to the interaction energy, and we explained our calculated trends on the basis of properties of the individual anions. We found that the interaction energy between CO2 and the Lewis bases examined here correlates most strongly with the atomic charge on the oxygen atom. This insight provides a useful handle to tune the anion-CO2 interaction energy for future experimental and computational studies of novel CO2 capture systems. 1. Introduction Postcombustion CO2 capture and sequestration (CCS) is a critical part of a suite of energy and environmental technologies aimed at stabilizing and eventually decreasing global CO2 emissions. CCS will continue to be important for the foreseeable future, even as other scientific and technological advances spur the widespread use of alternative energy sources.1-7 The CO2 separation technologies in widespread industrial use today (e.g., in natural gas sweetening) are aqueous amine systems, especially 2-aminoethanol (also known as monoethanolamine, MEA).3-10 These systems have several desirable properties3,7-9 and can be used to remove CO2 from flue gases as well.2,4,10 However, aqueous MEA systems suffer from significant drawbacks such as oxidative degradation of the amine and evaporative losses due to the volatility of both the amine and water.3-6,10 Furthermore, due to the thermodynamics of aqueous amine systems, their use on a large scale is highly energy intensive (i.e., there is a large energy requirement for solvent regeneration), which is a major economic hurdle for the use of aqueous MEA systems.2-4,6,10 Although engineering considerations can improve aqueous MEA systems,3,8,10 investigating the chemistry of alternative CO2 capture systems is an important area of study which may lead to more energy-efficient CO2 capture. Efforts to investigate alternative CO2 separation and capture systems have shown promise. In particular, systems employing room temperature ionic liquids (RTILs) avoid many of the issues surrounding aqueous amine systems.4-7,11-16 A number of researchers have examined the physical absorption of CO2 in RTIL systems.4,11-13 However, due to the relatively weak ion-CO2 interactions, CO2 solubilities achieved13 in these RTILs are up to about 0.03 mol fraction at 1 atm and 298 K. Alternatively, other RTIL systems feature stronger ion-CO2 binding, where chemical absorption (i.e., CO2 capture via a * To whom correspondence should be addressed, cteague@ cornellcollege.edu and [email protected]. † Department of Chemistry, Cornell College. ‡ Chemical Sciences Division, Oak Ridge National Laboratory. § Department of Chemistry, University of Tennessee.

chemical reaction) is the dominant mechanism. Davis and coworkers were the first to report this kind of system;5 they designed an amine-functionalized cation in an IL system that reversibly bound nearly 0.5 mol of CO2 per mole of IL. This amount of CO2 absorption is comparable to traditional aqueous MEA systems (and substantially higher than in RTIL systems involving only physical absorption); in both cases the CO2 reacts with the amino functionality to form a carbamate. It was noted that amine-functionalized RTIL systems often showed an increase in viscosity upon CO2 absorption, which has been explained by the formation of extensive hydrogen bonding networks.7 In a different approach to the chemical absorption of CO2 in RTIL systems, Noble and co-workers4 used RTIL/ alkanolamine (e.g., RTIL/MEA) mixtures to chemically bind CO2. In certain RTILs, MEA-carbamate precipitated, a behavior not observed in aqueous MEA systems.4,8 RTILs with aminefunctionalized anions have also been explored for CO2 capture.6,14 Beyond amine functionalization or RTIL/alkanolamine mixtures, Jessop and co-workers17 reported a novel system wherein a molecular (nonionic) liquid mixture of a superbase and an alcohol is converted to an ionic liquid upon reactive absorption of CO2. The chemistry here is that the superbase extracts the proton from the alcohol to generate the Lewis base anion ROwhich then reacts with CO2 to form a carbonate. This system can be switched back to the molecular liquid mixture by bubbling N2 or Ar through the formed carbonate, releasing CO2. More recently, our group showed that 1:1 mixtures of an alcohol-functionalized RTIL and a superbase quickly and reversibly captured CO2 via both chemical and physical mechanisms.15 This type of system avoids the issues caused by volatile components present in MEA systems, in some composite RTIL/amine systems, and in mixtures of a neutral superbase and an alcohol. Finally, our group just reported a new system16 wherein a superbase deprotonates a weak proton donor (e.g., an alcohol) to form a protic IL system before capturing CO2; the resulting Lewis base anion then reacts with CO2 in a 1:1 manner (e.g., see Scheme 1). Such superbase-derived protic IL

10.1021/jp1056072  2010 American Chemical Society Published on Web 10/13/2010

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SCHEME 1: Reaction between a Lewis Base Anion and CO2

systems are insensitive to water and are capable of reversibly absorbing high molar and gravimetric amounts of CO2. In the nucleophilic attack of CO2 by a Lewis base (Scheme 1) to form a carbonate or carbamate, too strong an interaction energy between CO2 and the base may hinder the release of CO2. Since a complete CO2 separation cycle involves both capture and then release of CO2, an optimized interaction energy would balance the capture and release processes. Hence we ask: How can one tune the interaction between the anion of ionic liquid systems and CO2? Can one continuously vary the interaction across the entire range from chemical to physical interaction? What are the important parameters that cause the interaction energy to vary? We use quantum mechanical computations to address these questions systematically. Specifically, we focused on cyclohexanolate and phenolate ring moieties with a variable number of fluorine substituents (see Figure 1) as typical oxygen-containing Lewis base anions. The rest of the paper is organized as follows. In section 2, we describe the quantum mechanical methods used, including different levels of theory and thermal as well as basis set superposition error (BSSE) corrections to the anion-CO2 interaction energy. In section 3.1, we present a general trend of structures and energetics for CO2 interactions from a pure density functional theory (DFT) method. In section 3.2, we examine different levels of theory including DFT with a hybrid functional and post-Hartree-Fock perturbation theory. In section 3.3, we examine BSSE and finite-temperature corrections to the interaction energy and compute entropy and free-energy changes upon CO2-anion binding. In section 3.4, we investigate the dependence of the interaction energy on two parameters of the individual anions: proton affinity and partial atomic charge on the oxygen atom. In section 3.5, we discuss implications of the present work on experimental discovery of RTIL-based systems for CO2 capture. We summarize and conclude in section 4. 2. Methods We used Turbomole V5.10 to perform three sets of calculations.18,19 In all calculations we used triple-ζ valence basis

Teague et al. sets with polarization, specifically the def2-TZVP orbital basis sets,20 for all atoms. When we employed the resolution-of-theidentity (RI) approximation, we used def2-TZVP auxiliary basis sets21,22 for all atoms as well. For each set of calculations, we calculated full geometry optimizations for each free anion shown in Figure 1, the free CO2 molecule, and each anion-CO2 complex. The force convergence criterion was set at 10-3 a.u., and geometry optimized structures were confirmed to be (local) minima by the absence of imaginary vibrational frequencies. Mulliken population analyses23 were performed in the basis of Cartesian atomic orbitals, while natural population analyses using the Natural Bond Orbital (NBO) method24,25 were performed in the basis of atomic orbitals. We used Molden26 to help build input structures and to visualize and record output geometries. We also used VMD27 to help visualize structures and record geometries. First, we performed parallel RI-DFT calculations28,29 using the Becke88-Perdew86 (BP) form30-32 of the generalized gradient approximation (GGA) for the exchange and correlation functionals. We also calculated full geometry optimizations for the protonated (i.e., neutral acid) form of each chemical species shown in Figure 1 at this level of theory using these functionals. Second, we performed parallel DFT calculations using the Becke88-Lee-Yang-Parr (B3LYP) form30,33-35 of a three parameter hybrid GGA for the exchange and correlation functionals. Third, for selected complexes we performed ab initio post-Hartree-Fock calculations in the form of RI secondorder Møller-Plesset perturbation theory (RI-MP2) calculations36 with the frozen core approximation.37 After obtaining converged geometry optimizations for each species with a given level of theory, we calculated the anion-CO2 interaction energy

anion-(g) + CO2(g) f [anion-CO2complex]-(g) ∆E ) Ecplx - [Eion + ECO2]

(1)

where each E on the right-hand side of eq 1 is the energy from the geometry optimization of the particular chemical entity denoted by the subscript. We calculated the interaction energy ∆E for all complexes formed from anions shown in Figure 1 using BP and B3LYP and for select complexes at the RI-MP2 level. At the RI-DFT level with the BP functional, we also calculated the proton affinity ∆EPA for each anion. Following the usual convention,38 we defined proton affinity from a gas phase deprotonation reaction

Figure 1. Anions investigated in this study with number labels used in this paper.

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acid(g) f ion-(g) + H+(g) ∆EPA ) Eion - Eacid

(2)

where each E on the right-hand side of eq 2 is again a full geometry optimization. With this convention, proton affinities are positive quantities with a large positive value corresponding to a high proton affinity of the anion. We evaluated corrections to the anion-CO2 interaction energy for selected complexes at the DFT-BP level with def2-TZVP basis sets for all atoms. First, we calculated BSSE and fragment relaxation energy corrections to the interaction energy.37,39,40 One way to account for both potential corrections is to perform both counterpoise calculations and single point calculations in the geometry of the complex for each monomer present in the complex. See the Supporting Information for details. Then we calculated corrections to the interaction energy due to zero point vibrational energy and finite-temperature translationalrotational-vibrational contributions; we also calculated the entropy and free-energy changes for anion-CO2 binding. Again, see the Supporting Information for details. 3. Results and Discussion 3.1. Energies and Structures at the DFT Level with the BP Functional. From organic chemistry, one knows that cyclohexanolate is a strong base while phenolate is a weak base; therefore, one expects that the former will react with CO2 more strongly than the latter. One can further tune the interaction between either of these two prototypical bases and CO2 by substituents across the series shown in Figure 1. We computed the interaction energies for this series at the DFT level with the BP functional and show them in Table 1 together with structural parameters of optimized complexes. One can see that we can tune the interaction energy from a chemical interaction (i.e., one that has a large covalent bonding character) to a much weaker noncovalent interaction. Below we analyze the energetics and structures in detail. The interaction energies vary as the ring structure and the number of fluorine substituents change; so do structural parameters within the anion-CO2 complexes. We examined two structural features within the complex: the OCO bond angle within CO2 and the distance between the O atom in the anion and the C atom in CO2. We show structures of two anion-CO2 complexes in Figure 2. One can see the strong covalent O-C bond (150.6 pm) and the smaller OCO angle in the complex 1-CO2 but the long O-C distance (242.9 pm) and the larger OCO angle in the complex 9-CO2. The two complexes serve as two extrema in the interaction range, 1-CO2 being covalent and 9-CO2 being physical or van der Waals. In Table 1, one can also see that from 1-CO2 to 9-CO2 both the O-C distance and the OCO angle increase as the interaction energy changes from covalent to noncovalent. The phenolate-CO2 (6-CO2) complex is in the middle of the series in terms of the interaction energy. Moreover, fluorination always leads to a weaker interaction (i.e., a less negative interaction energy), for either phenolate or cyclohexanolate derivatives, by strongly withdrawing electrons from the oxygen atom. 3.2. Interaction Energy at Different Levels of Theory. To evaluate the effect of method choice, we also computed the interaction energy using B3LYP and MP2 methods with the same basis sets (Table 2). Most important, we found that the three levels of theory yield the same trend. On comparison of DFT calculations with two different functionals, BP and

TABLE 1: Anion-CO2 Interaction Energy (∆E, As Defined in Equation 1), O-C-O Angle of CO2 (∠OCO), and Distance between O of Anion and C of CO2 (rO-C), Calculated the DFT-BP Level anion

∆E (kJ mol-1)

∠OCO (deg)

rO-C (pm)

1 2 3 4 5 6 7 8 9

-140.4 -120.8 -98.0 -72.7 -64.9 -45.1 -30.4 -28.5 -23.1

134.0 135.0 136.6 138.9 139.0 141.5 148.7 159.0 167.8

150.6 153.1 156.5 161.9 161.9 169.8 189.8 216.3 242.9

B3LYP give remarkably similar interaction energies, structural parameters, and behaviors of energy versus structural parameters (see the Supporting Information for B3LYP structure parameters). One of the important features of our study is the variation of the anion-CO2 interaction energy across all nine anions. We sought to test this broad trend using a more robust methodology, MP2 calculations, and our strategy was to calculate four of the nine to see if the broad trend held at the higher level of theory. As shown in Table 2, for a given complex the interaction energy calculated at the MP2 level is always more negative (i.e., the interaction is stronger) than either of the interaction energies calculated at DFT levels. The relative difference between MP2 and either BP or B3LYP becomes more pronounced for weakly bound complexes such as 9-CO2. Because MP2 includes longrange dynamic electron correlation effects, calculations at this level are able to include van der Waals type interactions.40 Such interactions, which are energetically favorable, are not typically handled well by DFT methods with these functionals.41 However, when considering the above discussion as well as computational cost, it appears that calculations at the DFT level with the BP functional are sufficient for the purposes of this study, since the three levels of method give the same trend. 3.3. Corrections to the Interaction Energy and the Entropic Effect. In this work, we sought to evaluate and account for broad trends in anion-CO2 interaction energies. In addition, a goal of this study was to identify one or more key molecular parameters that could be calculated quickly and easily. For these reasons, we calculated gas phase interaction energies uncorrected for zero point energy and thermal effects as in Tables 1

Figure 2. Calculated geometries of anion-CO2 complexes at the DFTBP level: (a, b) two views of the 1-CO2 complex; (c, d) two views of the 9-CO2 complex. Carbon is gray, hydrogen is white, oxygen is red, and fluorine is green.

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TABLE 2: Calculated Anion-CO2 Interaction Energies (∆E in kJ mol-1) Using DFT Calculations with the B3LYP Functional or at the MP2 Levela anion

DFT-B3LYP

MP2

1 2 3 4 5 6 7 8 9

-145.5 -124.1 -98.6 -70.9 -62.4 -42.1 -28.2 -29.9 -26.1

-156.9 -111.9 -49.1 -34.6

a See the Supporting Information for structural data of these complexes.

TABLE 3: Uncorrected Anion-CO2 Interaction Energy (∆E), ∆EBSSE (Including Both BSSE and Fragment Relaxation Corrections), BSSE-Corrected Energy (∆E1), Entropic Contribution to the Free-Energy Change at 298 K and 1 bar (T∆S), and Free-Energy of Binding at 298 K and 1 bar (∆G), Calculated at the DFT Level with the BP Functionala anion

∆E

∆EBSSE

∆E1b

Τ∆S

∆Gc

1 3 6 9

-140.4 -98.0 -45.1 -23.1

10.8 8.4 6.2 3.7

-129.6 -89.6 -38.9 -19.4

-39.8 -41.0 -33.9 -24.4

-75.7 -41.6 -1.5 12.7

a All values are in kJ mol-1. b ∆E1 ) (∆E + ∆EBSSE). c ∆G ) ∆E1 + ∆(ZPE) + ∆ET/R/V - RT - T∆S (see the Supporting Information for more details).

and 2. Several factors may be investigated to refine these calculated energies. First, BSSE and fragment relaxation may influence interaction energies. Second, to fully account for anion-CO2 interaction energies within RTIL systems, one would need to include zero point energies, thermal effects, and solvation effects. In a combined experimental and computational study,14 Schneider, Brenneke, and co-workers found that experimentally determined anion-CO2 reaction enthalpies in an RTIL system were in remarkably good agreement with computationally determined anion-CO2 reaction enthalpies in the gas phase. The authors suggested this was because the reactant and product anions had similar solvation energies. We expect the same behavior for the anions considered in our study. Below we first examine the BSSE corrections and then the thermal and entropic effects. 3.3.1. BSSE-Related Effects. The calculation of interaction energies between two chemical species can be hampered by two possible effects, BSSE and fragment relaxation energy. These effects are present even for gas phase reactions, and we evaluated these potential corrections first. To evaluate how BSSE and fragment relaxation effects modify our interaction energies, we calculated these corrections to the anion-CO2 interaction energy for selected complexes and collected the results in Table 3. We see that the trend remains the same despite the corrections. Certain trends are observed within the BSSE correction calculations. BSSE arises because one monomer can “borrow” orbitals from the other monomer in the complex, thereby artificially lowering the individual monomer energies and creating an overbinding in the calculation of ∆E from eq 1.37,39,40 Our corrected interaction energies ∆E1 are always less negative than their respective uncorrected counterparts ∆E, as expected. Furthermore, we note that the correction becomes more important (on a relative basis) as the interaction energy gets

less negative (e.g., 9 versus 1 in Table 3). Therefore, BSSE correction effects are more important for complexes containing only weaker physical interactions, as noted before.39,42 It should be noted that BSSE is usually discussed in terms of nonbonded complexes.39,40,42 In the case of a strongly bonded system, the basis set superposition “error” reflects a substantial amount of real chemical behavior (i.e., covalent bond formation as in some of our complexes) in addition to the mathematical and computational artifacts inherent in using noninfinite basis sets.40 Intramolecular BSSE exists,37,39 but it is not clear how to define intramolecular BSSE as a general case.37 However, within the framework of our study, the calculation of the BSSE corrections can be done in the same way across the entire series of complexes examined in this study. The trends within the BSSE corrections, while not solely due to a true “error” within the calculations, can be understood in the context of the variation across our set of complexes as discussed above. 3.3.2. Thermal and Entropic Effects. We included zero point energies and translational/rotational/vibrational contributions to the energy, and we then computed the entropy and free-energy changes for anion-CO2 binding for selected complexes at 298 K and 1 bar and collected the results also in Table 3. Due to the loss of entropy during CO2-anion binding, the negative ∆E (or ∆E1) is offset by the entropy contribution; in other words, the complex is destabilized by the entropic effect. However, in the case of strong interaction, the free-energy change is still highly favorable (such as for 1-CO2) because it is dominated by ∆E (or the enthalpic contribution). In the case of weak interaction such as for 9-CO2, now the free-energy change is positive and the gas phase reaction is unfavorable at 298 K and 1 bar. Here one may need to increase the pressure and/or lower the temperature to drive the CO2-anion binding. In the case of intermediate interaction such as for 6-CO2, the negative ∆E is roughly balanced by the entropy loss. So from the entropy loss, one may estimate that the interaction energy should be roughly -30 kJ mol-1 or more negative to overcome the entropic destabilization. While BSSE corrections and thermal effects can be important in many applications, in the context of our study the uncorrected values for the anion-CO2 interaction energy seem to be sufficient. In other words, as we seek to understand the results of our calculations, the broad trends present in the uncorrected interaction energies are our focus. We now turn to explaining our results on the basis of molecular energetics, charges, and structures. 3.4. Understanding the Trends and Predicting the Behavior. The range of interaction energies seen in Table 1 prompted us to ask two important questions. What are the fundamental molecular properties that govern the anion-CO2 interaction energies? Furthermore, how can we predict interaction energies for other species not present in this study? One idea is to relate the basicity of the anion to the interaction energy. Two ways to characterize the basicity of the anion are (a) the proton affinity of the anion and (b) the partial charge on the O atom in the anion. Below we analyze the data for potential correlation in these two ways. 3.4.1. Proton Affinity. Our hypothesis is that the anion-CO2 interaction energy ∆E has a direct relationship with the proton affinity of the anion ∆EPA. In Figure 3, we investigate this possibility. Across our entire set of anions, there is a rough correspondence between these two calculated values. In other words, as a general rule in the gas phase, the stronger a given anion reacts with a proton, the stronger it interacts with a CO2 molecule. This very general behavior should have some predic-

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Figure 3. Variation of anion-CO2 interaction energy ∆E with anion proton affinity ∆EPA at the DFT-BP level. Due to the definition of proton affinity, stronger proton binding is on the left. See Table 1 and the Supporting Information for calculated data values. Linear fits for subgroups are shown; R2 values are 0.978 (cyclohexanolates) and 0.936 (phenolates); a linear fit including all data here (not shown) gives R2 ) 0.911. Space filling models (van der Waals radii) of 5-CO2 and 6-CO2 are shown near the data points corresponding to their respective complexes.

tive value in future studies of systems like these, especially because proton affinities are experimentally accessible quantities. Perhaps more striking than the general trend in Figure 3 is the fact that molecular structure leads to two distinct groups within the data: the cyclohexanolates form one subgroup while the phenolates form a second subgroup. Within either subgroup, the data are more linear than across the entire set of anions. Within a subgroup, proton affinity should be a strong predictor of an anion’s ability to bind CO2. However, as a stand-alone predictor of anion-CO2 interaction energy, proton affinity is only a rough gauge of an anion’s ability to bind CO2. We note one other interesting implication of the data as shown in Figure 3. In comparing the end of the cyclohexanolate trend and the beginning of the phenolate trend, note that 6, phenolate, has a more positive proton affinity than 5, a decafluorocyclohexanolate. Therefore, recalling the definition of proton affinity in eq 2, the gas phase addition of H+ to 6 is more energetically favorable than a similar addition to 5. However, the CO2 interaction energy is reversed, so adding CO2 to 6 is less energetically favorable than a similar addition to 5. It appears that electronic effects play a dominant role in these interactions, as steric effects would seem to favor a stronger CO2 interaction with 6 than with 5. The rough correlation between proton affinity and CO2-anion interaction energy in Figure 3 indicates that the charge-charge (proton-anion) interaction correlates with the quadrupole-charge (CO2-anion) interactions. The reason is that the CO2-anion interaction is also dominated by the charge-charge interaction; as shown in Figure 2, when CO2 interacts with the anion, it is mainly through its positively charged C atom (as shown by the geometry of the complex in Figure 2). 3.4.2. Charge on Oxygen in the Anions. In another effort to understand our calculated data, which includes focusing on electronic effects, we examined the influence of the O partial charge on the interaction energy in Figure 4. We used two methods of population analysis to arrive at partial charges: Mulliken and NBO. In either case, one sees a nice correspondence between the interaction energy and O charge in

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Figure 4. Variation of anion-CO2 interaction energy ∆E with the calculated Mulliken or NBO charge on the O atom in the free anion at the DFT level with the BP functional. See Table 1 and the Supporting Information for calculated data. Linear fits for each trend are shown; R2 values are 0.961 (Mulliken) and 0.976 (NBO). See the Supporting Information for similar plots involving Mulliken charges using B3LYP and MP2.

the anion. As the interaction energy changes from -140 kJ mol-1 to -23 kJ mol-1, the Mulliken charge on O changes from -0.62 e to -0.47 e while the NBO charge on O changes from -0.87 e to -0.67 e. It is not surprising that the two methods of population analysis give different magnitudes of O partial charge;37,40 what is important here is that the two methods give similar trends as seen in Figure 4. Mulliken charge alone is certainly useful in examining trends within a study like ours.40 On the other hand, certain characteristics of Mulliken charges can be problematic (e.g., individual Mulliken charges do not converge to a stable value as the basis set size is increased) and NBO charges alleviate some of these problematic aspects.37,40 When taken as an entire group across the series of anions in this study, the O charge is a very good indicator of the anion-CO2 interaction energy. The fact that we see this trend for either Mulliken or NBO charges lends credence to this statement. For chemical interactions, the O partial charge indicates the driving force for the nucleophilic attack on CO2, while for physical interactions the O partial charge can polarize the CO2 molecule and attract the partial positive C atom of the CO2 molecule. Therefore, it seems reasonable that the O partial charge offers a strong correlation with the interaction energy across the chemical to physical interaction range. As an alternative to partial atomic charges, one may consider the electrostatic potential at the nucleus (EPN) of the oxygen atom in our series of anions. Other researchers have found excellent correlation between EPN and either hydrogen bonding43,44 or experimental reactivity constants.45 We therefore also calculated the EPN of the anion oxygen, and we found that it correlates with the anion-CO2 interaction energy slightly better than does the proton affinity but not as well as the partial charges (see Figure S4 in the Supporting Information). This is not surprising because Mulliken and NBO charges were found not to correlate as well with hydrogen bonding44 or experimental reactivity constants45 as EPN. Either Mulliken or NBO partial atomic charge on the anion base should be of use in the design of other studies on systems related to ours. In particular, these charges are easily and quickly obtained from quantum chemical calculations,37,40 and future computational studies of anion-CO2 interactions can make use

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of the correspondence between partial atomic charge and interaction energy. Moreover, this correspondence is not limited to O-containing anion bases and may be applied to other bases such as imidazolate.16 3.5. Implications for Experimental Discovery of Ionic Liquid Systems for CO2 Capture. Our results show that a single molecular parameter, the partial charge on the O atom in the anion, is a very good indicator of the anion-CO2 interaction energy across a range of interactions encompassing both chemical and physical absorption. This should provide a useful handle to tune RTIL systems for a particular desired interaction energy. Calculations like these can be used to prescreen candidate RTIL systems for their CO2 interaction energy. The computational demands are not intensive: a single calculation (geometry optimization of the isolated free anion), a fast calculation with a widely available functional (a DFT calculation with the BP functional), and either of two rapid and widely used methods for calculating charges (Mulliken and NBO population analyses). In addition, for direct comparison to experimentally determined quantities, one could use the proton affinity of the anion as a rough guide to the expected anion-CO2 interaction energy in RTIL systems, especially within particular structural groups of anions (e.g., cyclohexanolates or phenolates). Either way, we expect this work to be of use to those designing new RTIL-based CO2 capture systems. Our calculations here focused on oxygen-containing Lewis base anions. As noted in the Introduction, several studies5,6,14-16 have used nitrogen-containing Lewis bases for CO2 capture. We anticipate that our findings and conclusions here will also apply to such systems in terms of tuning the interaction energy and correlating it to partial atomic charge. Naturally, RTIL systems need a cation as well; recent work from our group16 has focused on superbase-derived protic cations, and these systems have shown promise for efficient and reversible CO2 capture. 4. Conclusions We calculated anion-CO2 interaction energies for a series of cyclohexanolate and phenolate anions. Importantly, our results showed that the interaction energy can be tuned over an energy range encompassing both chemical and physical types of interactions. After considering various levels of theory and corrections to the interaction energy, we concluded that uncorrected DFT calculations with the BP functional were sufficient to give a useful trend. In an effort to understand the calculated interaction energies, we examined three characteristics of the anions employed in this study: proton affinity, oxygen partial charge, and the electrostatic potential at the nucleus of the oxygen atom. We found that the interaction energy correlates very well with the oxygen partial charge when all anions are considered. Our results show that one can tune the interaction energy between CO2 and a Lewis base anion all the way across chemical and physical ranges. This knowledge should be of use in designing future CO2 capture systems that balance efficient capture and easy release. Acknowledgment. This work was supported by the Division of Chemical Sciences, Geosciences, and Biosciences, Office of Basic Energy Sciences, U.S. Department of Energy. C.M.T. gratefully acknowledges a Campbell R. McConnell Sabbatical Fellowship from Cornell College and the assistance of both the Oak Ridge Science Semester administered by Denison University and the U.S. Department of Energy Higher Education Research Experiences for Faculty at Oak Ridge National Laboratory administered by the Oak Ridge Institute for Science and Education. We thank Ms. Fengyu Li for assistance with one of the figures.

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