Stabilizing Capacity of Water Bridges in Nanopore Segments of Humic

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Stabilizing Capacity of Water Bridges in Nanopore Segments of Humic Substances: A Theoretical Investigation Ade´lia J. A. Aquino,*,†,‡ Daniel Tunega,*,†,‡ Gabriele E. Schaumann,§ Georg Haberhauer,| Martin H. Gerzabek,‡ and Hans Lischka*,†,⊥ Institute for Theoretical Chemistry, UniVersity of Vienna, Wa¨hringer Strasse 17, A-1090 Vienna, Austria, Institute of Soil Research, UniVersity of Natural Resources and Applied Life Sciences Vienna, Peter-Jordan-Strasse 82, A-1190 Vienna, Austria, Institute of EnVironmental Sciences, EnVironmental and Soil Chemistry, UniVersita¨t Koblenz-Landau, Fortstr. 7, 76829 Landau, Germany, ARC Seibersdorf Research, A-2444 Seibersdorf, Austria, and Institute of Organic Chemistry and Biochemistry, Academy of Sciences of the Czech Republic and Center for Biomolecules and Complex Molecular Systems, FlemingoVo nam. 2, 166 10 Prague 6, Czech Republic ReceiVed: June 11, 2009; ReVised Manuscript ReceiVed: August 2, 2009

Molecular simulations using density functional theory (DFT/PBE and DFT/tight-binding (DFTB)) have been performed to study wetting processes of model nanopore segments in humic substances (HS). A complex of two poly(acrylic acid) trimers (trimer complex, TC) arranged in parallel alignment was used to provide the structural example for supramolecular contact of two HS chains by means of hydrogen bonds. Their interaction with a local network of water molecules represented the influence of wet spots. Displaced TC structures were constructed by horizontal motion of the chains relative to each other in order to study the capacity of the water cluster to hold the two chains together even though their distance is too far for direct hydrogen bonding between the carboxyl groups. Geometry optimizations and molecular dynamics simulations were used to investigate the hydrogen-bonded structures formed and to compute their energetic stabilities. At shorter distances between the two oligomer chains an outer solvation was most stable. However, with increasing distance of the two polyacrylic trimers the water molecules penetrated into the inside of the created free space, keeping the two chains together by means of a hydrogen-bonded network. Significant stabilization effects of 10-20 kcal/mol were observed by this intrusion of water molecules at trimer distances of ∼13 Å. The present model, therefore, strongly supports the hypothesized bridging function of water molecules in humic substances provided a local distribution of appropriate functional groups is available in the HS matrix. I. Introduction Humic substances (HSs) are one of the main constituents of soil organic matter (SOM), being natural compounds produced by break down of plant and animal residues through microbial activity. They contain large macromolecules of variable size characterized by their high compositional and structural variability with its reactivity depending on the functional groups and the microstructure of the local environment. A key fraction (approximately 50%) of the earth’s carbon occurs in the form of humic materials (fulvic and humic acids). HSs are, therefore, crucial components of the biogeochemical carbon cycle and other life processes.1-3 It is well known that HSs participate actively in sorption processes in soils.4 They act as traps for pollutants mainly via surface functional groups or binding in cavity-like sorption sites.5 Even though numerous investigations have dealt with the structural composition of SOM, its complexity is so variable that current models can neither predict nor fully explain the role SOM plays in the sorption processes. Numerous models * To whom correspondence should be addressed. E-mail: adelia.aquino@ univie.ac.at, [email protected], and [email protected]. † University of Vienna. ‡ University of Natural Resources and Applied Life Sciences Vienna. § Universita¨t Koblenz-Landau. | ARC Seibersdorf Research. ⊥ Academy of Sciences of the Czech Republic and Center for Biomolecules and Complex Molecular Systems.

have been developed to describe and explain the sorption behavior of SOM, including general partitioning models (e.g., refs 6-8), polymer and polymer partitioning models (e.g., refs 9-12), and the simplified link solvation model (refs 13 and 14). A review of current SOM models suggests that the apparently contradictory polymeric and supramolecular views may both contribute in significant ways to the understanding of its structure and functionality.15,16 Increasing evidence suggests that large parts of HSs exist as collections of different rather low molecular mass components structured as dynamic associations, which are stabilized by hydrogen bonds (HB) and hydrophobic interactions.15-19 In the last years an increasing number of molecular modeling investigations on HS have been performed.20-33 These calculations provide information on physical and chemical properties at the molecular level as well as on interaction mechanisms between HSs and other species present in the natural environment such as clay particles,28 organic contaminants,23,24,26,30,31 and ionic species.29,32,33 Methodical studies of the structures of HSs are the first step to understanding how they interact with other substances and elements. Such understanding is important in order to envisage and control the impact of chemical and biological alterations in the environment. As already stated above, the structure of HSs is very complex. The HS backbone consists of connected fragments and branches of aliphatic/aromatic nature, on which a variety of basic organic functional groups such as -COOH, >CdO, -CHO, -NH2, and

10.1021/jp9054796 CCC: $40.75  2009 American Chemical Society Published on Web 08/19/2009

Stabilizing Capacity of Water Bridges -OH are bound. Owing to the enormous structural complexity of HSs, a broad scale of interactions occurs such as hydrogen bonding, cation bridges, anion and cation exchange, ligand exchange, van der Waals, and hydrophobic interactions. Hydrogen bonding, in particular, represents an important interaction type in adsorption processes in soils and in the contact of HSs with natural humidity and soil solutions, as shown in several studies, both experimental and theoretical.31,33-36 The capability of HSs to form hydrogen bonds is derived from the occurrence of the above-listed polar functional groups in the HS structure. A systematic theoretical study of various polar functional groups and their capability to establish hydrogen-bonded complexes has shown that the carboxyl group is one of the most important moieties responsible for forming the stable complexes.37 Differential scanning calorimetry (DSC) experiments performed by one of us38-40 have been used to study the interaction between different subunits within the supramolecular assembly in HSs and to investigate the role of water to mediate these interactions. It was found that a thermal transition in soil and peat samples, even though resembling a glass transition in numerous aspects, reveals among other differences only slowly reversing characteristics and, most importantly, involves the presence of water. Furthermore, water surprisingly acts as an antiplasticizer in the matrix.38,39 To explain this unexpected behavior, Schaumann and LeBoeuf38 suggested the formation of water bridges forming cross-links between individual side chains reducing their mobility and therefore being responsible for this antiplasticizing effect. First NMR spectroscopic measurements support this model, which currently provides the only plausible explanation for the aforementioned unexpected thermal behavior of peat and numerous soil samples.36 Owing to the flexibility of HSs, various nanopores and holes can be formed in their structure. These structural units, depending on the environmental conditions, can be filled by various small molecules such as water, affecting the conformation and stability of the pores. Water molecules can form a stable network of hydrogen bonds within HS structural units, giving rise to the term “wet spots”. The amount of water which can be trapped in HSs depends on the size, shape, concentration, and local distribution of functional polar groups, while the degree of bridging via hydrogen bonds controls the microregional molecular rigidity of the linked HS molecule segments. The aim of the present work is the investigation of the capacity of water molecules to form stable networks of hydrogen bonds confined in the nanopores of a HS matrix. Because of the already mentioned difficulties in the construction of HS models fully reflecting their structural complexity, simpler molecular models have been constructed in this work concentrating on the role of the carboxylic group and the hydrogenbonded interactions including especially the network of the water molecules discussed above. Following the idea of polymer models of HSs, oligomeric segments of poly(acrylic acid) (PAA) up to pentamers were used in our previous density functional theory (DFT) studies on interactions with the herbicide 2-methyl-4-chlorophenoxyacetic acid (MCPA) including cation bridges with Ca2+.31,33 These calculations demonstrated that interaction energies are already described well at the PAA trimer level. This compound is now used as the basic unit for the construction of a nanopore segment containing polar functional groups. In this approach two PAA trimer chains are arranged in parallel, interacting via opposite carboxyl groups and providing the structural example for the supramolecular contact of two HS chains by means of hydrogen bonds. Their interaction with a local network of water molecules represents the influence of

J. Phys. Chem. C, Vol. 113, No. 37, 2009 16469 SCHEME 1

wet spots. The application of quantum mechanical methods is strongly advisible in such cases, particularly because of the great variability of different hydrogen-bonded interactions. However, the goal of constructing models with increasing detail in terms of molecular functionality and solvation structure leads to significant computational bottlenecks even in connection with time-efficient DFT methods. Thus, even more efficient methods are required in order to cope with the large structural complexity. The semiempirical density functional tight-binding (DFTB) method41-43 is a good candidate for extended simulations. In combination with previous results,33,43,44 this work will show the range of applicability of DFTB in the present molecular context, opening up the possibilities for not only extended static investigations but especially also dynamics simulations on detailed molecular soil models. II. Structural and Computational Details In our previous investigation33 poly(acrylic acid) oligomers were selected as models representing sections of humic acids (HAs) with a prevailing concentration of carboxyl groups bound to aliphatic chains. It had been shown by comparison of computed Gibbs free energies of association of PAA oligomers with a series of adsorbents (such as MCPA) that already the trimer contains sufficient length to minimize edge effects for the central carboxylic group. It is also small enough to allow sufficient computational capacity for explicit inclusion of water molecules. On the basis of this experience, the PAA trimer has been chosen in this work as well. The PAA trimer consists of three >CH-COOH units linked in the chain, which is terminated on both ends with -CH3 groups (Scheme 1). To simulate the interactions in segments of nanopores or nanochannels in HAs, two trimer chains were arranged in parallel as displayed in Scheme 1. In this configuration a stable hydrogen-bonded complex of two trimers (TC) is formed as each carboxyl group of one trimer is bound via two hydrogen bonds to the opposite carboxyl group of the second trimer. An increasing number of water molecules is added to this aggregate, which are used to study their above-mentioned capacity of holding the two chains together even though their distance is too far for direct hydrogen bonding between the carboxyl groups. Static Calculations. Initially, the trimer complex, TC, was fully optimized without any structural constrains. Taking the optimized structure, displaced TC structures were constructed by horizontal motion of the two chains relative to each other in steps of 0.15 Å. In case i, the geometry of the carbonyl groups was optimized only at each displacement, keeping the Cartesian coordinates of the carbon chain and connected hydrogen atoms fixed in space (CCC fixation). In case ii, the same procedure was applied as before but keeping only the four carbon atoms of the terminal -CH3 groups fixed during geometry optimization (4C fixation). This latter case allows for the flexibility of the carbon chain and its distortions to enhance the stability of the formed complexes.

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Consecutive hydration of TC was studied at different distances between the trimer chains by adding 1-10 water molecules to the TC structure (TCWx, x ) 1-10) as explained in the following. The water molecules were consecutively placed outside of the trimer complex, close to the hydrogen-bonded carboxyl groups. Each complex was optimized by fixing at different interchain distances as before (i) the carbon backbone and (ii) only the four C atoms of the terminal methyl groups. The fixed distances between the two carbon chains in TC aim at modeling different sizes of nanopores or nanochannels occurring in the HA structures. The consecutive partial hydration of the trimer complex represents the simulation of different wetting conditions in HAs and is intended to model trapping of the water molecules in nanopores which will lead to the postulated stabilization of HAs. The geometry optimizations were carried out using two quantum chemical approaches, DFT and DFTB. DFT calculations were performed with the PBE45 functional and the SVP basis set46 in order to obtain benchmark results. The PBE functional was combined with the resolution of identity (RI) approach for reducing the computer time needed for the expensive two-electron integrals.47 The second approach, DFTB, is considerably faster than the standard DFT method. Details on DFTB can be found in refs 41-43, 48, and 49. The selfconsistent extension of the DFTB method (SCC-DFTB) used in this work is described in ref 43. Besides the speed, another advantage of the DFTB method is that for interaction energies of molecular complexes basis set superposition errors (BSSE) need not be considered as compared to full quantum chemical calculations.50 The DFTB method has been well tested for applications to organic molecules and hydrogen-bonded interactions.43,44 Nevertheless, in the first part of this work additional comparisons of the DFTB and DFT results were performed with the goal of verifying the applicability of DFTB for the present class of applications. For this purpose the acetic acid dimer (HAc)2 and the complex of the PAA trimer with the MCPA molecule are used as test cases since they contain the carboxyl group, which is the main functional group studied in this work. Moreover, the (HAc)2 dimer was already extensively investigated in numerous papers by means of several quantum chemical methods, and hence, many theoretical results are available.37,51-55 The DFT calculations were performed using the Turbomole program suite56 and the DFTB calculations using the DFTB+ program.57 DFTB Dynamics. In addition to the geometry optimizations, molecular dynamics (MD) simulations were performed. The main purpose of these calculations was to include thermal effects into the calculation and to average over multiple minima. Such MD calculations are computationally not feasible with DFT methods. However, the DFTB method has sufficient computational efficiency to allow MD calculations with reasonable simulation times. The MD simulations were carried out at a temperature of T ) 300 K using a canonical ensemble employing the Anderson thermostat.58 A time step of 1 fs was used in the velocity Verlet integration algorithm,59 and the total length of the MD run was 30 ps. Molecular systems with an even number of water molecules and with the rigid CCC backbone were investigated by MD. The DFTB-optimized structure was used as an initial geometry. After an equilibration phase of 5 ps, energy averaging was performed for 25 ps. These DFTB calculations were performed with the DFTB+ code as well.

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Figure 1. Calculated dissociation curves of the acetic acid dimer.

Results and Discussion Comparison of DFT/PBE and DFTB: Acetic Acid Dimer and PAA Trimer-MCPA Complex. The acetic acid dimer structure was fully optimized using the DFT (PBE/SVP) and DFTB methods. Details of structural features of the dimer and a collection of results from various quantum chemical methods can be found, e.g. in ref 37. For better comparison with the following calculations on the interaction between carboxyl groups of the TC complex, the potential-energy curve for (HAc)2 is displayed in Figure 1 in terms of the CC distance between the two carboxyl C atoms. At each CC distance the remaining geometry was optimized. An association energy of -18.6 kcal/ mol is obtained at the PBE/SVP level including BSSE corrections. Similar to previous results37 obtained for several QM methods using the SVP basis set, the BSSE amounts to ∼6 kcal/ mol. For comparison, the association energy computed at the Møller-Plesset perturbation theory to second order (MP2)60 using the TZVPP basis set61 and BSSE corrections (MP2/ TZVPP/BSSE) is -14.8 kcal/mol. The calculated DFTB association energy is -13.5 kcal/mol. The comparison of results shows that the DFTB method underestimates the HAc complexation energy by 1.3 kcal/mol while the PBE/SVP/BSSE value is larger by 3.8 kcal/mol with respect to the MP2/TZVPP/ BSSE reference result. The DFTB and DFT curves have similar shapes. The DFTB method only reaches the dissociation plateau somewhat earlier than the DFT method. The PBE/SVP, DFTB, and MP2/TZVPP HB distances are 1.527, 1.700, and 1.649 Å, respectively. Systematic comparison of interaction energies and hydrogen bond distances has been made for the complexes between MCPA and the PAA trimer. The interaction energy is -19.4 kcal/mol at the BSSE-corrected PBE/SVP level and -15.7 kcal/ mol for DFTB. Two hydrogen bonds, one between the carbonyl oxygen (trimer) and the hydroxyl hydrogen (MCPA) and the other between the carbonyl oxygen (MCPA) and the hydroxyl hydrogen (trimer), are formed. These HB distances are of 1.711, 1.693 and 1.534, 1.497 Å at DFTB and PBE/SVP, respectively. The hydrogen bond distances agree within 0.18 Å. Thus, in conclusion a quite acceptable accuracy for the DFTB method is obtained, well justifying its use in the MD simulations. Consecutive Hydration of the Acrylic Acid Trimer Complex (TC). Figure 2 presents two views on the RI-PBE/SVPoptimized structures of complexes TCxW with a representative number of water molecules (x ) 0, 2, 4, 6, 8, and 10). Two choices of interchain distances (8.6 and 13.0 Å) are shown. The distances are given between the carbon atoms of the terminal -CH3 groups on different chains. The first distance corresponds

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Figure 2. RI-PBE/SVP-optimized structures of the consecutively hydrated TC complex using CCC fixation. Distances are given between the carbon atoms of the terminal -CH3 groups.

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Figure 3. RI-PBE/SVP-optimized TC complex hydrated with 10 water molecules with 4C fixation at two selected distances.

to the optimized distance between the isolated trimers. The larger one was selected as a characteristic value representing the minima for the interaction with 10 water molecules (TC10W model). As expected, in the fully optimized isolated complex TC, cyclic hydrogen-bonded rings between opposite carboxyl groups are formed with O · · · H distances of 1.4-1.6 Å depending on the position of the carboxylic group in the PAA trimer chain. The addition of water molecules at the outside of the complex (see cases with 2, 4, 8, and 10 water molecules at shorter distance in Figure 2) and the subsequent constrained geometry optimization (rigid CCC backbone) resulted in the distribution of water molecules around the hydrogen-bonded carboxyl groups. The water molecules form hydrogen bonds with the carboxyl oxygen atoms of the hydroxyl groups and/or among themselves. These hydrogen bonds are longer than those between carboxyl groups in the isolated TC0W complex and assume values typical for hydrogen bonds of moderate strength (about 1.9 Å). With increasing number of water molecules the complexity of the system increases considerably. At short distances (about 8-10 Å) the water molecules are positioned only at the outside of the carboxyl groups and do not disturb significantly the cyclic structure of the hydrogenbonded rings. The same situation was observed also when only the 4C fixation was applied. In this case the optimization resulted in a small distortion of the CCC backbone, but the system of cyclic carboxyl bridges between both oligomers was still preserved at short interchain distances. This situation is shown in Figure 3 where the TC complex with 10 water molecules is displayed at the same distances as shown in Figure 2. The geometry optimization with the DFTB approach did not lead to any qualitative change of the picture for the formation of TC hydrated from the outside. Generally, the hydrogen bonds formed are somewhat longer as compared to the RI-PBE/SVPoptimized structures. A similar trend was found already for the acetic acid dimer. At short distances insertion of a higher number of water molecules (x > 6) resulted in a stronger perturbation of the TC, but nevertheless, the cyclic configuration of the hydrogenbonded carboxyl groups still remained stable. The situation of the hydrogen bonds structures started to change with increasing distance between the trimers. At a distance of ∼9.5 Å, water molecules change their arrangement drastically during the geometry optimization and penetrate into the interchain region. At an interchain distance of ∼13 Å (see Figure 2) the penetration of water molecules is practically complete. For higher numbers of water molecules this penetration starts earlier than in the case of smaller numbers.

Figure 4 shows the dependence of the energy of the TC/water complexes on the distance between the oligomers for an even number of water molecules. Energies are calculated relative to the energy minimum of the isolated dimer. The energy curve of the isolated complex is very similar to the curve obtained for the acetic acid dimer (Figure 1). The association energy is about -63.2 kcal/mol (no BSSE correction), which is approximately 3 times higher than in the (HAc)2 complex. With increasing number of water molecules the curves display in some cases relatively large and sudden changes. This is the result of a larger reconfiguration of the water molecules during the geometry optimization even though the starting geometry was taken at each interchain distance from the final optimized geometry of the previous point. In Figure 4 a barrier is observed at distances of 9-10 Å for a number of 2-6 water molecules. The analysis of the geometry at these distances shows that in spite of the fact that carboxyl groups are already relatively distant from each other the cyclic structure of the hydrogenbonded rings is still preserved and water molecules stay located outside of the complexes not able to penetrate into an opening space between both trimers. With further increase of the distance between the two trimers, water molecules start to penetrate into the space between carboxyl groups and form hydrogen bonds with them. A network of hydrogen bonds among water molecules themselves still remains. The penetration of the water molecules into the space between the trimers leads to an energetic stabilization of the whole complex showing an energy minimum at distances of ∼11 Å. Starting with six water molecules the energy minimum is located lower than the reference point, and thus, this configuration becomes more stable than solvation of TC from the outside. Increasing the interchain distance further, the relative energy starts to increase again since hydrogen bonds begin to break. The region of the stability is relatively broad, ranging within an interval of interchain distances of 10.5-13.5 Å. This is especially evident for the system with 10 water molecules. This “inner” hydration of the trimers or, in other words, the filling of the nanopore space by water molecules significantly stabilizes the whole system by about 20 kcal/mol. The process of consecutive hydration with increasing distance between the trimers did not change significantly when the frozen carbon chains were relaxed and only the terminal C atoms of the methyl groups of the trimers were fixed. The barriers at shorter distances almost disappeared (see Figure 4b). During the geometry optimization the cyclic structure of the hydrogenbonded carboxyl groups of both trimers became much stronger perturbed by the hydration than in the case of the fixed CCC

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Figure 4. Distance dependence of relative energies of TC complexes with an even number of water molecules calculated at the RI-PBE/SVP level.

Figure 5. Distance dependence of the relative energy of TC complexes with an even number of water molecules calculated at the DFTB level.

backbone. This is especially evident from Figure 3 for the interchain distance of 8.6 Å in comparison with the respective picture in Figure 2. At 13 Å the water configurations are almost the same as those with the CCC fixation. For the 4C fixation the CCC chain can make torsional movements and can also bend at larger interchain distances due to interactions through the hydrogen-bonded network between the trimers. The increased stabilization of the complexes for larger hydration (x > 6) is found also in the case of 4C fixation. The largest stabilization is once more observed for the TC10W system, and stabilization energies of 9.5-13.5 Å are observed, somewhat smaller than in the case of the CCC fixation. A similar procedure of consecutive hydration of TC performed at a set of increasing interchain distances has also been performed with the DFTB approach. It was found that DFTB gives similar trends concerning the hydrogen bond network as the PBE/SVP approach (compare Figures 4 and 5). This similarity is observed for both types of geometry optimization

(CCC and 4C fixation). The water molecules penetrated into the space between the trimers at a distance of about -9.5 Å, similar to the PBE/SVP results. The DFTB energy curves of higher hydration numbers show similar discontinuities as those observed with the RI-PBE/SVP method. The energy barriers located at smaller distances and the broad minima at larger distances for the models with CCC fixation are similar to the RI-PBE results (cf. Figures 4 and 5). A difference between RI-PBE and DFTB is observed in terms of the range of stabilization energies. The RI-PBE method gives larger stabilization energies than the DFTB approach. This is mainly due to the fact that RI-PBE relative energies contain BSSE, and consequently, this method overestimates hydrogen bonding as it was shown in the test case of the acetic acid dimer. Similar good agreement between DFTB and RI-PBE results are also observed for the 4C fixation. The release of the CCC chain results in larger and faster perturbation of the cyclic structures of the carboxyl groups by water molecules. The water molecules

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Figure 6. Distance dependence of the averaged relative potential energy of TC complexes with an even number of water molecules computed from DFTB dynamics simulations.

penetrate more easily into the space between the trimers and water bridges with the multiple hydrogen bonds formed stabilizing the whole system. This stabilization is similar as in the case of CCC fixation (Figure 5). MD-DFTB Simulations. Figure 6 displays a plot of relative averaged potential energies obtained from the MD simulation for models containing 0, 2, 4, 6, 8, and 10 water molecules. The reference energy is computed for the same distance between trimers as that used for the optimized structures shown in Figure 5. The graphs plotted in Figure 6 closely resemble those in Figure 5 (left). This similarity is observed concerning the range of the relative energies, the shape of the curves, and their energetic ordering. The system with no water molecule has a dissociation limit for the two hydrogen-bonded trimers of about 43 kcal/mol, which is practically the same as the one obtained in the geometry optimization. The curves for systems with no and/or two water molecules have no significant minimum or maximum. The maxima/minima begin to appear when four or more water molecules are used. The maxima at short distances (up to ∼10 Å) correspond to the case when the distances between carboxyl groups are already stretched but water molecules still do not penetrate into the opening space between the trimers. Due to the nuclear motions, hydrogen bonds formed among water molecules alone and those between water molecules and carboxyl groups change dynamically. When the distance between the trimers reaches a value of ∼10 Å the water molecules start to penetrate into the space between both trimers for a short period of time, forming hydrogen bonds with the OH groups of the carboxyl groups. The frequency of the penetration increases with increasing interchain distance until all water molecules have entered into the space between the trimers, a situation which is more stable than the one where the water molecules are located on the outside (Figure 6). The width, depth, and shape of the observed minima depend on the number of water molecules confined between the trimers. The most stable configuration is observed for the highest water content with an energy gain of about -12 kcal/mol. Conclusions In this work the intrusion of water molecules into a model of nanopore segments within a humic acid and the energetic

Aquino et al. stability of the hydrogen-bonded network was studied. A complex of two poly(acrylic acid) trimers was chosen for the representation of polar interactions in the humic acid matrix. Consecutive hydration of this complex was investigated by means of quantum chemical calculations. Static geometry optimizations have been performed under two different conditions: by freezing the entire CCC backbone of the polyacrylic chains and freezing only the four carbon atoms of the terminal methyl groups of both trimers. All models were computed by means of two DFT-based methods using the RI-PBE functional set and the approximate DFTB approach, respectively. The latter one is significantly faster that standard DFT methods. This computational efficiency gave the possibility of performing DFTB molecular dynamics simulations. The starting point of all geometry optimizations and MD simulations was the outer solvation case where water molecules were located at the outside of the trimer complex. At shorter distances between the trimer chains (8-10 Å) the outer solvation was found to be most stable and no breaking of the hydrogen bonds between the carboxyl groups of the two trimers was observed. With increasing distance of the two polyacrylic trimers (about 9.5-10.0 Å) the water molecules penetrated into the inside of the created free space and stable water bridges via a hydrogen-bonded network were formed. This process led to the energetic stabilization of such inner networks as compared to the outer hydration. At larger distances between both trimers and for models with more than 6 water molecules the inner hydration was found to be energetically favored relative to the outer hydration. Stabilization effects amounted to 10-20 kcal/ mol. This finding documents that in humic acid segments with a high concentration of polar groups stable substructures connected by a hydrogen-bonded network can be formed for specific water concentrations. This water network is able to keep together polymer chains which are too far apart to establish direct binding. The present model therefore strongly supports the hypothesized bridging function of water molecules in humic substances depending on the local distribution of appropriate functional groups in the HS matrix. This work has also shown that dynamics simulations on specific aspects of humic acid models based on quantum chemical methods are feasible and that they can be extended to even more sophisticated and extended systems including synthetic organic polymers (e.g., poly(acrylic acid)) or to other natural organic polymers like polygalacturonic acid, the key compound of plant mucilage. It is expected that the present results will aid further experimental verification concerning the role of the local distribution of hydrophilic functional groups for the postulated stabilizing mechanism as well as the relevance of the type of functional groups for this mechanism. Combination of computational analysis, differential scanning calorimetry, and NMR analysis on systems with varying types and density of functional groups will help to unravel the process it causes in soil organic matter and its quantitative relevance in organic matter in general. Acknowledgment. We are grateful for financial support from the Austrian Sciences Fund (project P20893-N19) and the German Research Foundation, the priority program SPP 1315, project nos. GE 1676/1-1 and SCHA849/8-1. The support by the grant from the Ministry of Education of the Czech Republic (Center for Biomolecules and Complex Molecular Systems, LC512) and the Praemium Academiae of the Academy of Sciences of the Czech Republic, awarded to Pavel Hobza in 2007, is gratefully acknowledged by H. Lischka. This work was also part of the research project Z40550506 of the Institute of Organic Chemistry and Biochemistry of the Academy of

Stabilizing Capacity of Water Bridges Sciences of the Czech Republic. We are thankful for technical support and computer time at the Linux-PC cluster Schro¨dinger III of the computer center at the University of Vienna. References and Notes (1) Baldock, J. A.; Masiello, C. A.; Gelinas, Y.; Hedges, J. I. Mar. Chem. 2004, 92, 39. (2) von Luetzow, M.; Kogel-Knabner, I.; Ludwig, B.; Matzner, E.; Flessa, H.; Ekschmitt, K.; Guggenberger, G.; Marschner, B.; Kalbitz, K. J. Plant Nutr. Soil Sci. 2008, 171, 111. (3) Mikutta, R.; Schaumann, G. E.; Gildemeister, D.; Bonneville, S.; Kramer, M. G.; Chorover, J.; Chadwick, O. A.; Guggenberger, G. Geochim. Cosmochim. Acta 2009, 73, 2034. (4) Kile, D. E.; Wershaw, R. L.; Chiou, C. T. EnViron. Sci. Technol. 1999, 33, 2053. (5) Ghabbour, E. A.; Davies, G. Humic Substances-Versatile components of plants, soils and water; Royal Society of Chemistry: Cambridge, U.K., 2000. (6) Schuurmann, G. Prediction of Sorption of Organic Compounds to Soil from Molecular Structure. Quo Vadis EnVironmental Science? From the “end of pipe” strategy towards sustainability. Conference of Environmental Chemistry and Toxicology group of GdCh, Halle, Germany, 2006. (7) Niederer, C.; Goss, K.-U.; Schwarzenbach, R. P. EnViron. Sci. Technol. 2006, 40, 5368. (8) Goss, K. U. Crit. ReV. EnViron. Sci. Technol. 2004, 34, 339. (9) Xing, B. EnViron. Pollut. 2001, 111, 303. (10) Poerschmann, J.; Kopinke, F. D. EnViron. Sci. Technol. 2001, 35, 1142. (11) Leboeuf, E. J.; Weber, W. J. EnViron. Sci. Technol. 1997, 31, 1697. (12) Kopinke, F. D.; Porschmann, J.; Stottmeister, U. EnViron. Sci. Technol. 1995, 29, 941. (13) Graber, E. R.; Borisover, M. D. EnViron. Sci. Technol. 1998, 32, 258. (14) Borisover, M.; Graber, E. R. Langmuir 2002, 18, 4775. (15) Schaumann, G. E. J. Plant Nutr. Soil Sci. 2006, 169, 145. (16) Schaumann, G. E. J. Plant Nutr. Soil Sci. 2006, 169, 157. (17) Simpson, A. J.; Kingery, W. L.; Hayes, M. H. B.; Spraul, M.; Humpfer, E.; Dvortsak, P.; Kerssebaum, R.; Godejohann, M.; Hofmann, M. Naturwissenschaften 2002, 89, 84. (18) Piccolo, A. Soil Science 2001, 166, 810. (19) Sutton, R.; Sposito, G. EnViron. Sci. Technol. 2005, 39, 9009. (20) Schulten, H.-R.; Leinweber, P. J. Anal. Appl. Pyrol. 1996, 38, 1. (21) Schulten, H. R.; Leinweber, P.; Schnitzer, M. Analytical pyrolysis and computer modeling of humic and soil particle. In Structure and Surface Reactions of Soil Particles; John Wiley & Sons Ltd.: New York, 1998; p 281. (22) Sein, L. T.; Varnum, J. M.; Jansen, S. A. EnViron. Sci. Technol. 1999, 33, 546. (23) Kubicki, J. D.; Apitz, S. E. Org. Geochem. 1999, 30, 911. (24) Schulten, H. R. EnViron. Toxicol. Chem. 1999, 18, 1643. (25) Schulten, H. R. J. Anal. Appl. Pyrol. 1999, 49, 385. (26) Negre, M.; Schulten, H. R.; Gennari, M.; Vindrola, D. J. EnViron. Sci. Health, Part B: Pesticides Food Contaminants and Agricultural Wastes 2001, 36, 107. (27) Sutton, R.; Sposito, G.; Diallo, M. S.; Schulten, H. R. EnViron. Toxicol. Chem. 2005, 24, 1902.

J. Phys. Chem. C, Vol. 113, No. 37, 2009 16475 (28) Sutton, R.; Sposito, G. Geochim. Cosmochim. Acta 2006, 70, 3566. (29) Xu, X.; Kalinichev, A. G.; Kirkpatrick, R. J. Geochim. Cosmochim. Acta 2006, 70, 4319. (30) Koglin, E.; Meier, R. J.; Vereecken, H. J. Mol. Struct.: Theochem 2006, 759, 133. (31) Aquino, A. J. A.; Tunega, D.; Haberhauer, G.; Gerzabek, M. H.; Lischka, H. Eur. J. Soil Sci. 2007, 58, 889. (32) Kalinichev, A. G.; Kirkpatrick, R. J. Eur. J. Soil Sci. 2007, 58, 909. (33) Aquino, A. J. A.; Tunega, D.; Pasalic, H.; Haberhauer, G.; Gerzabek, M. H.; Lischka, H. Chem. Phys. 2008, 349, 69. (34) Piccolo, A.; Celano, G. EnViron. Toxicol. Chem. 1994, 13, 1737. (35) Schaumann, G. E.; Hobley, E.; Hurrass, J.; Rotard, W. Plant Soil 2005, 275, 1. (36) Schaumann, G. E.; Bertmer, M. Eur. J. Soil Sci. 2008, 59, 423. (37) Aquino, A. J. A.; Tunega, D.; Haberhauer, G.; Gerzabek, M. H.; Lischka, H. J. Phys. Chem. A 2002, 106, 1862. (38) Schaumann, G. E.; Leboeuf, E. J. EnViron. Sci. Technol. 2005, 39, 800. (39) Schaumann, G. E. Colloids Surf. A: Physicochemi. Eng. Aspects 2005, 265, 163. (40) Hurrass, J.; Schaumann, G. E. EnViron. Sci. Technol. 2005, 39, 9534. (41) Porezag, D.; Frauenheim, T.; Kohler, T.; Seifert, G.; Kaschner, R. Phys. ReV. B 1995, 51, 12947. (42) Seifert, G.; Porezag, D.; Frauenheim, T. Int. J. Quantum Chem. 1996, 58, 185. (43) Elstner, M.; Porezag, D.; Jungnickel, G.; Elsner, J.; Haugk, M.; Frauenheim, T.; Suhai, S.; Seifert, G. Phys. ReV. B 1998, 58, 7260. (44) Hu, H.; Lu, Z. Y.; Elstner, M.; Hermans, J.; Yang, W. T. J. Phys. Chem. A 2007, 111, 5685. (45) Perdew, J. P.; Burke, K.; Ernzerhof, M. Phys. ReV. Lett. 1996, 77, 3865. (46) Schafer, A.; Horne, H.; Ahlrichs, R. J. Chem. Phys. 1992, 97, 2571. (47) Ha¨ttig, C. J. Chem. Phys. 2003, 118, 7751. (48) Elstner, M. J. Phys. Chem. A 2007, 111, 5614. (49) Seifert, G. J. Phys. Chem. A 2007, 111, 5609. (50) Boys, S. F.; Bernardi, F. Mol. Phys. 1970, 19, 553. (51) Colominas, C.; Teixido, J.; Cemeli, J.; Luque, F. J.; Orozco, M. J. Phys. Chem. B 1998, 102, 2269. (52) Nakabayashi, T.; Kosugi, K.; Nishi, N. J. Phys. Chem. A 1999, 103, 8595. (53) Chocholousova, J.; Vacek, J.; Hobza, P. J. Phys. Chem. A 2003, 107, 3086. (54) Allouche, A.; Bahr, S. J. Phys. Chem. B 2006, 110, 8640. (55) Chen, J.; Brooks, C. L.; Scheraga, H. A. J. Phys. Chem. B 2008, 112, 242. (56) Ahlrichs, R.; Ba¨r, M.; Ha¨ser, M.; Horn, H.; Ko¨lmel, C. Chem. Phys. Lett. 1989, 162, 165. (57) Aradi, B.; Hourahine, B.; Frauenheim, T. J. Phys. Chem. A 2007, 111, 5678. (58) Andersen, H. C. J. Chem. Phys. 1980, 72, 2384. (59) Ferrario, M.; Ryckaert, J. P. Mol. Phys. 1985, 54, 587. (60) Møller, C.; Plesset, M. S. Phys. ReV. 1934, 46, 618. (61) Scha¨fer, A.; Huber, C.; Ahlrichs, R. J. Chem. Phys. 1994, 100, 5829.

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