An M05-2X DFT Study - ACS Publications - American Chemical Society

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Can the Gibbs Free Energy of Adsorption Be Predicted Efficiently and Accurately: An M05-2X DFT Study A. Michalkova,† L. Gorb,‡ F. Hill,§ and J. Leszczynski*,†,§ †

Interdisciplinary Nanotoxicity Center, Department of Chemistry and Biochemistry, Jackson State University, 1400 Lynch Street, P.O. Box 17910, Jackson, Mississippi 39217, United States ‡ Badger Technical Services, LLC, Vicksburg, Mississippi, United States § U.S. Army Engineer Research and Development Center (ERDC), Vicksburg, Mississippi, United States ABSTRACT: This study presents new insight into the prediction of partitioning of organic compounds between a carbon surface (soot) and water, and it also sheds light on the sluggish desorption of interacting molecules from activated and nonactivated carbon surfaces. This paper provides details about the structure and interactions of benzene, polycyclic aromatic hydrocarbons, and aromatic nitrocompounds with a carbon surface modeled by coronene using a density functional theory approach along with the M05-2X functional. The adsorption was studied in vacuum and from water solution. The molecules studied are physisorbed on the carbon surface. While the intermolecular interactions of benzene and hydrocarbons are governed by dispersion forces, nitrocompounds are adsorbed also due to quite strong electrostatic interactions with all types of carbon surfaces. On the basis of these results, we conclude that the method of prediction presented in this study allows one to approach the experimental level of accuracy in predicting thermodynamic parameters of adsorption on a carbon surface from the gas phase. The empirical modification of the polarized continuum model leads also to a quantitative agreement with the experimental data for the Gibbs free energy values of the adsorption from water solution.

1. INTRODUCTION The transport and fate of any chemical in the environment depend partially on the degree to which they partition between different natural phases (air, water, and soil (sediments)).1-4 Ideally, this dependence could be characterized by an adsorption isotherm or, in the most simplified case, by the partitioning coefficient (KD) of a chemical distribution between the corresponding phases. The usual definition of KD is   Cphase 1 ΔG ð1Þ KD ¼ exp ¼ RT Cphase 2 where ΔG is the difference in Gibbs free energy that governs the phase transition; Cphase 1 and Cphase 2 are the equilibrium concentrations of the chemical after the distribution between the phases, R is the universal gas constant, and T is temperature. Therefore, one of the ways to predict the value of KD is to obtain the ΔG value, which, for example, can be evaluated actually by using computational methods. In recent publications, most of the computational predictions of KD tend to avoid direct evaluation of the ΔG values (to our best knowledge, there are only a few papers trying to estimate the ΔG values computationally).5-7 Instead of a direct calculation of the ΔG values, different versions of the quantitative r 2011 American Chemical Society

structure-activity relationship (QSAR)8-11 are used. Very often, the QSAR studies analyze the correlations between KD and the quantum chemically calculated values of the adsorption energies.12 The explanation for such approach is quite simple; the computational technique to estimate the ΔG values should be able to treat accurately both electrostatic and dispersion adsorbateadsorbent interactions. At the same time, the approach needs to be computationally inexpensive if one is to consider a relatively large fragment of adsorbent. Until recently, it was quite difficult to find such a quantum chemical method that would satisfy these requirements for routine calculations. However, the development of new density functional theory (DFT) approaches has made this study possible.13 Particularly, in this paper, we applied one of the recently developed DFT functionals (M05-2X, a new hybrid meta functional developed by the Truhlar group13) to computationally estimate the ΔG values for the adsorption of benzene, several polyaromatic hydrocarbons (PAHs), and aromatic nitrocompounds (NACs) on the soil surface. Received: December 23, 2010 Revised: January 31, 2011 Published: March 01, 2011 2423

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The Journal of Physical Chemistry A Among a variety of possible adsorbent structures, we have considered only very simplified models of the carbon surface. Such models can be attributed to different types of activated or nonactivated carbon particles and soot, as shown theoretically12,14,15 and experimentally.16-18 The adsorbent model will be denoted in the text as the soot surface. Two types of adsorption (from vacuum and water solution) were calculated. Another problem encountered in the study of the adsorption on different adsorbents (which one should always keep in mind) is the heterogeneity of the natural sorbents. This heterogeneity results in an existence of mutual adsorption sites of different nature.19-27 However, in the case of carbon particles, the nature of the adsorption sites is relatively well established.5,9,17,18,28-30 Moreover, the values of log KD for the PAHs' adsorption on the carbon surfaces considered in this paper are known. They were obtained from experimental measurements17,18,28-30 or by the QSAR estimations.9 An understanding of adsorption and solvation properties of organic contaminants at the atomistic level is vital for the development of methods and technologies for decontamination. Despite the existence of a number of experimental studies to measure KD values and the application of various strategies to estimate KD of contaminants at the water/soil interface, this parameter has not yet been clearly characterized. This study can help to solve these problems and bring important innovation into the cleanup techniques of contaminants. A long-term goal of this study is to develop a computational protocol which will aid in the prediction of KD values of organic contaminants in the environment, where there is a paucity of experimental data.

2. COMPUTATIONAL DETAILS The adsorption of benzene, polycyclic aromatic hydrocarbons (PAHs), and nitroaromatic compounds (NACs) on the surface of soot was investigated through application of density functional theory in conjunction with the M05-2X functional13 and the ccpVDZ basis set31 as implemented in the Gaussian09 program package, E.01 version.32 The M05-2X functional was chosen because it shows acceptable performance for the main group thermochemistry and noncovalent interactions (especially weak interactions, hydrogen bonding, and π 3 3 3 π stacking).13 The authors performed the calculations without the counterpoise corrections (CP) for the basis set superposition error (BSSE) and showed very good agreement with the experimental data. We would also like to clarify that to obtain the best performance in the prediction of thermochemical properties for noncovalent interacting systems, the developers of the hybrid meta GGA density functionals suggest not to apply the BSSE correction when such functionals are used.33 Thus, the interaction energies in our study have not been corrected for the BSSE. The studied systems were allowed to fully relax. After the optimization of studied systems, the final geometry was used to calculate the vibrational frequencies. The minimum-energy geometries were determined to be the true minima by absence of the imaginary frequencies in the calculated vibrational spectra. The soot surface was modeled by a single coronene (C24H12) molecule, which was generated using both experimental and theoretical data.15,22 This simplification is justifiable because the soot-PAH adsorption occurs mainly through the π-π interactions. Coronene was substituted as a truncated representation of the soot surface with the assumption that the π 3 3 3 π van der Waals forces dominate the PAH-soot attraction. Benzene, PAH,

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and nitrocompound molecules were placed in various positions near the energy-minimized soot model. The initial positions of the adsorbate were chosen to reflect the London dispersion, dipole-dipole, H-bonding, and van der Waals terms of the intermolecular interactions with the soot surface. Thus, the adsorbate in the initial configuration was located in stable positions for a variety of bonding arrangements rather than preselecting only one type of bonding. For table and figure captions, the following conventions have been followed for the soot model: the single coronene model will be denoted c, and a coronene model with two layers will be denoted as c_c. Functionalized groups attached to the coronene model will be added at the end of the notation. The effect of the solvent water was simulated at the same level of theory as that listed above using the dielectric polarized continuum model (PCM).34 In this method, the solvent is taken as a continuum of uniform dielectric constant (ɛ = 78.4), and the reaction field is described so that the solute is placed in a molecular cavity within the solvent field. Model adsorbate-coronene systems were used to calculate the adsorption enthalpy (ΔH) and Gibbs free energy (ΔG) at room temperature (298.15 K) during the partition of the contaminant between soot and air or soot and water. The entropy S(T) values were calculated using the rigid rotorharmonic oscillator-ideal gas approximation based on the vibrational frequencies at 298.15 K and 1 atm of pressure. In contrast to the numerical computational studies, which use a negative value of adsorption enthalpy (or even adsorption energy) as the criterion of an effective adsorption, we have chosen eq 1 as the criterion. On the basis of this equation, the case of effective adsorption is described by the negative values of Gibbs free energy, which for the distribution of a contaminant between soot and air is calculated as ΔGads ¼ ΔHads - TΔSads

ð2Þ

Formally, the same equation is valid for the case of adsorption of a contaminant in the bulk water w - TΔSwads ΔGwads ¼ ΔHads

ð3Þ

where superscript w means the adsorption from the bulk water. However, if ΔHwads is calculated in the framework of the continuum approximation, direct application of eq 3 is not appropriate because a significant part of the adsorbent is not surrounded by water molecules. This fact could be overcome by using the following formula w w ¼ ΔHAB - ðΔHAw þ ΔHBw Þ ΔHads

ΔHwAB,

ΔHwA,

ð4Þ

ΔHwB

where and are the enthalpies of the hydrated adsorbed complex, hydrated adsorbent, and hydrated surface, respectively. Each component of eq 4 can be expressed as a sum of two contributions that originate from the gas phase (superscript g) and water solution (superscript hyd) ΔH w ¼ ΔH g þ ΔH hyd

ð5Þ

Therefore, eq 4 can be rewritten as follows g

hyd

g

hyd

w ΔHads ¼ ðΔHAB þ ΔHAB Þ - ðΔHA þ ΔHA þ ΔHBw Þ ð6Þ

As one can see, eq 6 is accurate for the case of interactions in water. In the case of adsorption from the water solution, two hyd components (namely, ΔHhyd AB and ΔHA ) will be different as 2424

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Figure 1. The difference between the bulk water hydration in a water solution (A) and during the adsorption of a substance from a water solution (B).

compared to the values estimated from the continuum model approach. Therefore, to take this fact into account, we have introduced the empirical correction of eq 6 as follows g

hyd

g

hyd

w ¼ ðΔHAB þ aΔHAB Þ - ðΔHA þ bΔHA þ ΔHBw Þ ΔHads

ð7Þ To better explain the logic behind the empirical correction of eq 6 to eq 7, a simple illustration is presented in Figure 1. Figure 1A represents the classical continuum hydration (described by eq 6). Figure 1B shows hydration of the adsorbed complex as described by eq 7, and it demonstrates the modification of the continuum model. This picture also helps to clarify the difference between the enthalpy from the bulk water (ΔHw) and the enthalpy from water solution (ΔHhyd). The main difference in these terms is that the first one (ΔHw) considers full interactions of the adsorbent with water, while the second term (ΔHhyd) takes into account the fact that the adsorbent interacts only partially with the water molecules (it is a part of ΔHw). Thus, ΔHw can be described as a combination of ΔHg and ΔHhyd (see eq 5). We found that application of eq 7 using a = b = 0.7 gives reasonable agreement with the experimental values, as will be shown below. Formally, the same technique should be applied also to the entropy values (ΔSwads). However, it was revealed that the entropy term (TΔSwads) was impacted by less than 0.5 kcal/ mol, as compared to the TΔSads values. Therefore, we used the gas-phase calculated values for the TΔSwads term.

3. RESULTS AND DISCUSSION 3.1. Adsorption from the Gas Phase. The adsorption ability of such nonpolar contaminants as benzene (Ben), naphthalene (Nap), anthracene (Ant), and phenantrene (Phen) on a regular carbon surface will be discussed. The optimized structure of all of these contaminants on the bare soot surface is presented in Figure 2A-D. Structural relaxation leads to optimal placement of all of the adsorbates in a parallel position slightly shifted from the middle of the soot model. The optimized distances are 3.35 (Ben_c), 3.42 (Nap_c), 3.32 (Ant_c), and 3.4 Å (Phen_c). The

van der Waals forces between the π-electrons within the aromatic rings of both PAH and soot surfaces govern the adsorption. This finding is in agreement with the results of experimental studies of interactions of PAHs with different types of soot.16-18 We have revealed that the larger, more planar, and more aromatic the adsorbate, the stronger the adsorption. This result is consistent with the conclusion of a theoretical study12 of benzene and PAH interactions with soot and with an experimental study18 of the sorption of PAHs on soot and soot-like materials. Table 1 contains the thermodynamic parameters of the adsorption process. Despite that the ΔHads values for all systems are negative, the entropy effect causes the ΔGads values to become positive. This is not surprising and reflects the fact that during intermolecular interactions, the values of relative Gibbs free energy differ significantly as compared to the corresponding relative enthalpy data. This is caused by the replacement of three translational degrees of freedom from a total of six by the rotational and vibrational degrees of freedom.6 Therefore, we concluded that such a type of adsorption is energetically unfavorable at room temperature. The calculation of nitrobenzene (NB), dinitrobenzene (DNB), and trinitrotoluene (TNT) adsorption on the bare soot surface (see Figure 2E-G, which presents the optimized structures of NB, DNB, and TNT adsorbed on the coronene model) shows that the presence of polar nitro group does not affect the orientation and location of the adsorbate. This means that the target molecules are placed in a parallel way toward the surface where the optimized distances amount to 3.44 Å for NB_c, 3.42 Å for DNB_c, and 3.4 Å for TNT_c. On the other hand, it attributes to greater binding affinity of the adsorbate toward soot. Nitrocompounds adsorb on soot due to stronger intermolecular interactions, which are governed by not only dispersion forces (as in the case of PAH_c) but also electrostatics. Therefore, more negative values of adsorption enthalpies (see Table 1 for the thermodynamic parameters (ΔHads, ΔGads) of the adsorption of NACs on bare soot) result in the negative values of adsorption Gibbs free energies. In other words, we predict that this type of adsorption is effective for DNB and TNT binding with the bare soot surface model from vacuum at room temperature. Obviously, the results presented above could be attributed only to the case of an ideal homogeneous surface of carbon particles. In reality, such a surface is quite heterogeneous due to the presence of micropores and noncarbon containing sites. Movement of PAHs into micropores could enhance log(KD) because both sides of PAHs could be involved in the π-π interactions with the micropore walls. Thus, the next simulations were devised to increase the level of complexity of the system by simulating the interaction of PAHs with the walls of the micropores. As follows from Figure 2H-J, the PAH molecules have been intercalated between two coronene models (the optimized distances between the molecule and the surface are 3.34 Å for Ben_c_c and Nap_c_c, and 3.46 Å for Ant_c_c). Benzene and all of the PAHs in the study were intercalated parallel in the middle between two coronene layers. As expected, the values of adsorption enthalpies for such a type of adsorption are now negative enough to secure effective adsorption for all considered PAHs. A similar conclusion was made in the molecular dynamics study of pyrene interacting with the soot model.35 Removing the pyrene molecule not only requires its diffusion through the micropores, but the energy lost due to formation of a large “vacancy” in the carbon structure must also be regained. 2425

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Figure 2. The optimized structure of benzene (Ben_c (A) and Ben_c_c (H)), naphthalene (Nap_c (B) and Nap_c_c (I)), anthracene (Ant_c (C) and Ant_c_c (J)), phenantrene (Phen_c (D)), nitrobenzene (NB_c (E)), dinitrobenzene (DNB_c (F)), and trinitrotoluene (TNT_c (G)) adsorbed and intercalated on the bare soot surface model obtained at the M05-2X/cc-pVDZ level.

In addition to pores, the surface of carbon particles consists of numerous oxygen- and nitrogen-containing sites.5,19-25 In particular, oxygen was found to have an important effect on the adsorption capacity of carbon surfaces for water, polar gases, and vapors and on their storage.19 To study this type of carbon adsorption sites, the ideal soot surface was modified by addition of hydroxyl, carboxyl, and amino groups in the way as presented in Figure 3 (the optimized structure of NB, DNB, and TNT adsorbed on modified soot surface by added —OH, —COOH, and —NH2 groups). Because it is intuitively clear that this type of adsorption will be important only for polar compounds, we did not study the adsorption of PAHs on those sites. As follows from the results given in Table 1 (the ΔHads and ΔGads values in the first and second columns for the soot_NAC systems) and Figure 3, the presence of the functional groups on the soot surface has a significant influence on the sorption ability of the substrate. Indeed, the data presented in Table 1 suggest a very clear trend predicting the NH2-containing adsorption sites to be the most efficient in the adsorption of considered nitrocompounds. According to our best knowledge, there are only a few experimental data available with which we can compare our theoretical results for the adsorption from the gas phase. Some of them relate to the adsorption of benzene on different surfaces of

activated or nonactivated carbon and nanotubes. The only parameter available for comparison is the experimentally measured adsorption energy, which (according to the definition) could be compared with the calculated enthalpy of adsorption. The experimentally measured values of adsorption energy are changed in the range from -2.436 to -4.3 kcal/mol.37 These values are very close to our results regarding the adsorption enthalpy of benzene adsorbed on the regular carbon surface (-5.2 kcal/mol; see Table 1 for more details). This good agreement can be partially caused by use of the new M05-2X DFT functional, which has been specially parametrized to accurately reproduce thermodynamics of the intermolecular interactions of organic compounds. The verification of usage of this functional can be found in recently published work of Truhlar and co-workers.38 Finally, we would like to mention that recently, we suggested a slightly more complicated computational protocol which provides experimental accuracy for the calculated intermolecular ΔG values of small (mostly hydrogen-bonded) complexes.6,7 Thus, we suggest the theoretical data presented in this work follow a trend of moving toward the level of experimental accuracy. Moreover, the analysis and comparison in the last few paragraphs show that our adsorption models are efficient and can be used for prediction of the thermodynamics of interaction of PAHs and NACs with soot from the gas phase. 2426

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Table 1. Adsorption Enthalpy and Gibbs Free Energy [kcal/mol] from the Gas Phase (ΔHads, ΔGads) and from a Water Solution (ΔHwads, ΔGwads) Calculated at the M05-2X/cc-pVDZ Level ΔHads

ΔGads

ΔHwads

ΔGwads

Ben_c

-5.2

6.7

-5.3

6.7

Naph_c Ant_c

-7.5 -9.6

3.5 2.6

-7.0 -8.1

3.9 4.1

Phen_c

-9.2

4.1

-8.6

4.7

NB_c

-9.6

3.1

-9.3

3.3

-12.9

-0.2

-11.6

1.1

-14.0

-0.5

-10.1

-1.0

-11.4

1.5

-2.7,16 -2.039

-11.3

0.6

-3.7,16,18 -4.141

-10.6

1.1

-3.4,17,18 -2.8,39 -3.7,41 -2.7, -2.942

System

DNB_c TNT_c

-15.8

-2.2

Ben_c_c

-10.9

-0.5

Nap_c_c

-15.0

-2.8

Ant_c_c Ben_cO-

-19.2

-6.8

-

Nap_cO

-

Ant_cO

-

Phen_cO

ΔGwads(exp)d

-1.316

-9.2

2.2

-11.4

-0.7

-3 to -6,39 -0.943

DNB_cOH

-12.8

-0.2

-15.6

-3.0

-3 to -6,39 -2.344

TNT_cOH

-16.3

-2.6

-28.7

-12.6

NB_cCOOH DNB_cCOOH

-9.2 -12.6

2.7 0.1

-12.4b -15.8b

-1.3b -3.5b

TNT_cCOOH

-17.0

-3.4

-30.0b

-14.2b

NB_cNH2

-13.0

-0.8

-15.0

-3.0c

DNB_cNH2

-15.8

-3.2

-16.9

-2.7c

TNT_cNH2

-18.3

-4.7

-31.8

NB_cOH

a

a

a

a

a

a

c c c

-17.3c

The R—CO dissociated adsorbed site has been considered. The R—COO dissociated adsorbed site has been considered. c The R—NH3þ polarized adsorbed site has been considered. d ΔGwads(exp) were obtained directly from the experimental study44 or they were calculated using the experimental log KD values16-18,39,41-43 by applying eq 1 at room temperature a

-

b

-

Figure 3. The optimized structure of nitrobenzene (NB_cOH (A), NB_cCOOH (D), and NB_cNH2 (G)), dinitrobenzene (DNB_cOH (B), DNB_cCOOH (E), and DNB_cNH2 (H)), and trinitrotoluene (TNT_cOH (C), TNT_cCOOH (F), and TNT_cNH2 (I)) adsorbed on the modified soot surface model obtained at the M05-2X/cc-pVDZ level. 2427

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The Journal of Physical Chemistry A 3.2. Adsorption from the Water Solution. As expected, the adsorption on the regular carbon surface from the water solution (see the ΔHwads and ΔGwads values presented in the third and fourth columns of Table 1) is revealed to be less thermodynamically favorable because of the interactions of dissolved species with the bulk water. A similar conclusion was made in a study of the mechanism of adsorption of aromatic compounds on activated carbon, where water presence leads to reducing sorption capacity.30 The influence of water (solvent) increases with the addition of aromatic rings and nitro groups to the adsorbate.

Figure 4. The optimized structure of benzene (Ben_cO- (A)), naphthalene (Nap_cO- (B)), anthracene (Ant_cO- (C)), and phenantrene (Phen_cO- (D)) adsorbed on the modified soot surface model obtained at the M05-2X/cc-pVDZ level.

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Due to the limitation of our model, we did not consider the adsorption of PAHs and NACs onto micropores from a water solution. However, modification of the soot model by the addition of different functional groups (as described in section 3.1) allows one to consider the changes in the adsorption behavior (which one could expect when the carbon surface is activated by oxygen- and nitrogen-containing groups). Due to the fact that all oxygen-containing functional groups on soot are very acidic in nature, we considered modification of the soot model only by the dissociated fragments such as R—CO- and R—COO-. On the other hand, the absence of the oxygencontaining groups at the edges causes carbon basicity.22 This can be induced also by the presence of the NH2 group classified as an electron donor easily capable of accepting the hydrogen proton and so forming the R—NH3þ functional group of the carbon surface. Therefore, this type of soot fragment (cNH3þ) was also considered in the case of the adsorption from water solution. We have found that the presence of water solvent changes the geometry of the adsorbates only slightly. They interact with the solvated soot model (see Figures 4 and 5, which display the optimized structure of benzene, PAHs, and NACs adsorbed on the altered soot surface by the above-mentioned functional groups) in almost the same way as with the regular soot model from the gas phase. This means only a small change of the position of the target molecule position in the complexes containing the bare soot models. The interaction of benzene and PAHs with the modified soot surface model causes a slight tilting of the adsorbate and its positioning closer to the adsorption site with the added groups (the distance between the adsorbate and surface is decreased by about 0.1 Å as compared with the binding encountered with the bare soot model). NB, DNB, and TNT still remain in a parallel orientation toward these altered cNH3þ, cCOO-, and cOsurfaces. The NO2 group of the nitrocompounds remains a little bit closer to the functional group. In the case of the sootNH3þ

Figure 5. The optimized structure of nitrobenzene (NB_cO- (A), NB_cCOO- (D), and NB_ cNH3þ (G)), dinitrobenzene (DNB_cO- (B), DNB_cCOO- (E), and DNB_ cNH3þ (H)), and trinitrotoluene (TNT_cO- (C), TNT_cCOO- (F), and TNT_ cNH3þ (I)) adsorbed on the modified soot surface model obtained at the M05-2X/cc-pVDZ level. 2428

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The Journal of Physical Chemistry A model, the adsorption occurs also due to the formation of a quite strong hydrogen bond between the N—H group of the surface (proton donor) and an oxygen atom (proton acceptor) of the molecular NO2 group with a 1.8-1.85 Å H 3 3 3 O (2.69-2.75 Å O 3 3 3 O) distance. The ΔHwads and ΔGwads values presented in Table 1 suggest quite effective adsorption of NACs by all tested adsorption sites (phenolic, carboxyl, and ammonia-like) of the altered soot surface. A clear trend can be indicated showing the strongest adsorption in the case of the R—NH3þ carbon surface model. Obviously, due to the rather empirical modification of the continuum model (the method of calculation of the Gibbs free energy values for the adsorption from the water solution as shown in Computational Details), we do not expect to obtain the same accuracy for ΔGwads as that for the ΔGads values (adsorption from the gas phase). Nevertheless, we have found in the literature a number of experimental data39-44 which suggest that our model is quantitatively correct (see Table 1). Among the advantages of the model is that nearly experimental accuracy is obtained in the prediction of the ΔGwads values for NACs and adsorption of benzene on the carbon surface. However, more detailed analysis shows that this is caused by the cancellation of errors because neither ΔHwads nor ΔSwads have been predicted as accurately as ΔGwads. In addition, our model predicts a trend for the adsorbate to be more strongly sorbed to the surface with increasing number of nitro groups in the target molecule.44 TNT was revealed to interact the most strongly with the soot surface (the ΔGwads values are from -12.6 to -17.3 kcal/mol depending on the type of added functional group). However, as follows from comparison of the experimental and calculated data for the adsorption of naphthalene, anthracene, and phenantrene, we are just approaching the experimental values for ΔGwads.

4. CONCLUSION The adsorption of benzene, polycyclic aromatic hydrocarbons (PAHs), and nitrocompounds (NACs) on the carbon surface modeled by the single coronene molecule at 298 K was investigated at the M05-2X/cc-pVDZ level of theory. The stabilization of the adsorbate was strongly increased on the activated carbon particles with the oxygen- and nitrogen-containing functional groups, where these groups act as strong active sites. On such carbon surfaces, the adsorbate remains confined in the vicinity of the functional group site, in contrast with the bare soot surface, where the target molecule is more flexible and is placed above the middle of the carbon model. The binding of studied molecules on carbon consists of interplay between the dispersion and electrostatic interactions. The adsorption strength of the adsorbate on soot is largely affected by the presence of water, which partially controls the thermodynamics of the target molecule. The relative importance of all effects depends on the chemical nature, the size, and the shape of the adsorbate. The Gibbs free energies of benzene-, PAH-, and nitrocompound-bare soot complexes show that such adsorption is thermodynamically feasible only in the case of DNB (gas phase) and TNT (gas phase and water solution). Placing the contaminant between two coronene layers stabilizes the target molecule about two times more as compared to the adsorption on the bare carbon surface. From comparison of the calculated and available experimental thermodynamic parameters, the method and models used in this

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study have been shown to be efficient in the prediction of these parameters for adsorption of different organic contaminants on a variety of carbon particles. The accuracy was revealed to be stronger in the case of the adsorption from the gas phase than that in the water solution. However, on the basis of good agreement between the experimental and theoretical Gibbs free energy values of the intermolecular interactions in both types of environments, we conclude that the method of modeling presented here is quantitatively correct and describes adequately the partitioning of studied organic contaminants.

’ AUTHOR INFORMATION Corresponding Author

*E-mail: [email protected]. Phone: 001-601-979-3482. Fax: 001-601-979-7823.

’ ACKNOWLEDGMENT This work was facilitated by support from the High Performance Computing Major Shared Resource Center at the ERDC (Vicksburg, MS) and the Office of Naval Research Grant No. N00034-03-1-0116. The use of trade, product, or firm names in this report is for descriptive purposes only and does not imply endorsement by the U.S. Government. Results in this study were funded and obtained from research conducted under the Environmental Quality Technology Program of the United States Army Corps of Engineers by the U.S. Army ERDC. Permission was granted by the Chief of Engineers to publish this information. The findings of this report are not to be construed as an official Department of the Army position unless so designated by other authorized documents. ’ REFERENCES (1) Baily, G. W.; White, J. L. Residue Rev. 1970, 32, 29. (2) Pionke, H. B.; Chesters, G. J. Environ. Qual. 1973, 2, 29. (3) Karickhoff, S. W. J. Hydraul. Eng. 1984, 110, 707. (4) Larson, R. A.; Weber, E. J. Reaction Mechanisms in Environmental Organic Chemistry; Lewis Publishers: Boca Raton, FL, 1994; pp 124135. (5) Efremenko, I.; Sheintuch, M. Langmuir 2006, 22 (8), 3614. (6) Isayev, O.; Gorb, L.; Leszczynski, J. J. Comput. Chem. 2007, 28, 1598 and references therein.. (7) Isayev, O.; Furmanchuk, A.; Gorb, L.; Leszczynski, J. Chem. Phys. Lett. 2008, 451, 147. (8) Worrall, F.; Thomsen, M. Chemosphere 2004, 54, 585. (9) Fara, D.; Kahn, I.; Maran, U.; Karelson, M.; Andersson, P. J. Chem. Inf. Model. 2005, 45, 94. (10) Lu, Ch.; Wang, Y.; Yin, Ch.; Guo, W.; Hu, X. Chemosphere 2006, 63, 1384. (11) Brasquet, C.; Le Cloirec, P. Langmuir 1999, 15, 5906. (12) Kubicki, J. D. Environ. Sci. Technol. 2006, 40, 2298. (13) Zhao, Y.; Schultz, N. E.; Truhlar, D. G. J. Chem. Theory Comput. 2006, 2, 364. (14) Kubicki, J. D. Abstr. Pap. Am. Chem. Soc. 2000, 220, ENVR 24, Part 1. (15) Kubicki, J. D. Geomchem. Trans. 2000, 1, 41. (16) Bucheli, T. D.; Gustafsson, O. Environ. Sci. Technol. 2000, 34 (24), 5144. (17) Kleineidam, S.; Sch€uth, Ch.; Grathwohl, P. Environ. Sci. Technol. 2002, 36, 4689. (18) Jonker, M. T. O.; Koelmans, A. A. Environ. Sci. Technol. 2002, 36 (17), 3725. 2429

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