Dynamics and reactions of molecular Ru catalysts at carbon nanotube

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Dynamics and reactions of molecular Ru catalysts at carbon nanotube-water interfaces Shaoqi Zhan, and Marten S. G. Ahlquist J. Am. Chem. Soc., Just Accepted Manuscript • DOI: 10.1021/jacs.8b00433 • Publication Date (Web): 25 May 2018 Downloaded from http://pubs.acs.org on May 25, 2018

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Journal of the American Chemical Society

Dynamics and reactions of molecular Ru catalysts at carbon nanotube-water interfaces Shaoqi Zhan, Mårten S. G. Ahlquist* Department of Theoretical Chemistry & Biology, School of Engineering Sciences in Chemistry Biotechnology and Health, KTH Royal Institute of Technology, 10691 Stockholm, Sweden KEYWORDS: water oxidation • molecular dynamics • CNT-water interfaces • hydrophobic oxo • surface loading • diffusion rate • activation energy

ABSTRACT: Immobilization of molecular catalysts to electrode surfaces can improve the recyclability and electron transfer rates. The drawback is that most experimental techniques and theoretical methods are not applicable. Here we present a results from a study of a ruthenium water oxidation catalyst [RuVO(bda)L2], in explicit water at a carbon nanotube water interface, forming the key O-O bond between two 128 atom catalysts – all fully dynamically. Our methodology is based on recently developed empirical valence bond (EVB) model. We follow the key steps of the reaction including diffusion of the catalysts at the interface, formation of the prereactive dimer, and the bond formation between the two catalysts. Based on the calculated parameters we compute the turnover frequency (TOF) at the experimental loading, in excellent agreement with the experiments. The key O-O bond formation was significantly retarded at the surface, and limiting components were identified that could be improved by catalyst modification.

INTRODUCTION In the search for catalytic systems to store solar energy in chemical bonds, much focus has been on molecular homogeneous catalysts.1-11 Their advantages include well-defined structure,1-3 high reactivity,7 facile experimental characterization of key intermediates,8,9 straight forward kinetic studies,10 and molecular sizes allowing full high level computational studies of the catalytic cycle.11 However, for practical implementations the stability and recyclability of the catalysts limit their usefulness. As a solution, heterogenization of the molecular catalysts have been applied, by attaching them to substrate materials.12-18 This strategy can be difficult and lead to mass transport limitations and deactivation of the catalyst. Still, very impressive results have been found in both electrochemical and chemical catalysis, even surpassing the efficiency of same catalyst in a homogeneous environment.19 The major drawback with immobilization is that the analysis and insight into the mechanism is very challenging. Once the catalyst is attached to a surface many experimental techniques used for homogenous molecules are no longer applicable. For computational studies the situation is also extremely challenging. Homogeneous catalytic systems are usually studied by combining highly accurate molecular quantum chemical methods with continuum solvation and thermochemical corrections.20 Heterogeneous catalysts are most often studied by periodic density functional theory (DFT) and results can often be interpreted in terms of binding energies of key intermediates.21-23 In principle ab initio molecular dynamics (MD) could also simulate heterogeneous catalysts in small water system.2427 When molecular catalyst of larger size with higher confor-

mational flexibility are immobilized on nanostructured solids, DFT approach meets limitations. Firstly, with the large systems it is not affordable for any quantum chemical or density functional technique with sufficient accuracy. Secondly, the environment is no longer homogeneous and cannot be described by implicit models. The environment also leads to huge conformational spaces, excessive to electronic structure methods. Yet the nature of the chemical bond is related to the electronic structure, and therefore, changes in bonding are difficult to model without explicit description of the electrons. One of the most efficient catalysts for water oxidation is the Ru(bda)L2 (bda = 2,2’-bipyridine-6,6’-dicarboxylate, L = typically nitrogen containing heterocycle e.g. pyridine) complexes by Sun and co-workers.28-30 As one practical development to make an efficient electrocatalyst the axial L-ligands were modified with pyrene groups, which make the adhesion to carbon nanotube (CNT) functionalized electrodes stronger.31 In solution the Ru(bda)L2 class of catalysts has been shown to react by a bimolecular coupling of two [RuV=O(bda)L2]+ radicals (I2M mechanism - interaction of two metal centers),11 where the 7-coordinate species was spectroscopically confirmed recently by Pushkar and coworkers.32 The I2M was recently argued to be the desirable O-O bond forming mechanism by Reek and co-worker.33 The alternative O-O bond forming mechanism is the water nucleophilic attack (WNA), which is limited by scaling relationships limiting rates beyond the normally observed turnover frequency (TOF) of < 1 s-1.2 The I2M mechanism does not have the same scaling relationship. The coupling between two radicals was recently shown to have no intrinsic activation energy.34 Instead

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the activation energy originates from the accommodation of the rest of the catalyst complex to the transition state (TS) geometry. For [RuV=O(bda)L2]+ the O-O bond formation is a combination of diffusion, encountering of two low concentration catalysts in the medium, and the actual O-O bond forming step. We found the oxo fragment of the [RuV=O(bda)L2]+ catalyst is hydrophobic, adding a driving force for the formation of the prereactive dimer.35 Previous studies also showed that more hydrophobic axial L-ligands lead to higher activity of the catalyst under homogenous conditions.7 While the hydrophobic helps the prereactive dimer formation in water, it is unknown how the immobilized catalyst operates. With two hydrophobic catalyst intermediates on a hydrophobic surface at a water interface dimerization tendency is unknown. Herein, we present a fully atomistic and fully dynamical study of two molecular catalysts on CNT water interfaces. The key O-O bond forming step is studied using empirical valence bond (EVB) approach.36 These methods have allowed for a atomistic insight of surface adhered molecular catalyst. O NH

N N

N 1

O

2

O

Ru

O O O7

N

NH O

1

Figure 1. RuV complex 1 used in this study.

RESULTS AND DISCUSSION Diffusion of [RuVO(bda)L2]+ on Nanotubes. We studied complex 1 (Figure 1), where the axial pyridyl ligands have been augmented with pyrene groups, attached via a Nmethylbutanamide linker, which was the catalysts in the 2011 report31 by Sun. The pyrenes enhance the adsorption of the complex on the CNT sidewalls through π-π stacking.37,38 Goldsmith and co-workers demonstrated that pyrene substituted metal catalysts to lead to higher surface loading of electrocatalysts, and thereby, higher current densities.39 For systems such as 1 on CNT surfaces the size is far beyond the capability of standard quantum chemical methods. Recently, we developed force fields for studying the catalyst in explicit water solution,35 and we reasoned that the same methodology could be used to study the catalyst at the CNT-water interface. The previous force field was augmented with standard OPLS-AA bonded40 and van der Waals parameters for the pyrene and Nmethylbutanamide linker.41 Partial charge parameters were calculated using our previously described iterative protocol based on electrostatic potential (ESP) charges.35 Once the force fields were developed we ran 100 ns MD simulation in vacuum, to test the stability. The superposition of the DFT optimized structure and MD equilibrium coincides very well. This was followed by 100 ns MD runs in a 57 × 56 × 57 Å

periodic box filled with TIP3P water molecules and a chloride ion to balance the charge. The chloride ion does not show any preferential position as shown by a radial distribution functions analysis (Figure S13). In water phase, the force field is also proved stable by the root mean square deviation plots with respect to the geometry optimization using DFT (Figure S3). In both environments the complex kept a relatively rigid structure where the pyrene groups folded backwards towards the bipyridine unit of the bda ligand. The force field yielded expected structures in vacuum and water phase and next we simulated the catalyst on a CNT-water interface. The CNT was described as charge neutral carbon tube with standard van der Waals parameters.42 This ignores effects from polarization and metallicity of the nanotube, however, we see the model as the first approximation of the carbon-water interface. The OPLS-AA force field has been shown to describe both adsorption at carbon surfaces,43,44 and solvent/CNT-surface partitioning well in MD simulations.45 In our first model we used a CNT (18, 0) with a diameter of 14.3 Å, which is smaller than the experimental system of 80 Å diameter CNTs. 80 Å is far beyond our capability, but the smaller model could give insight into how the catalyst interacts with the surface, estimates of the diffusion coefficient of the catalyst, and the interaction of two catalysts. These results will then be extrapolated to the experimental conditions. 1 was initially added in the optimization configuration and positioned with the oxo pointing to water and the pyrene groups closer to the surface (Figure 2a). Within 100 ns MD simulation the catalyst unfolded and formed two π-stacking interactions between the pyrene groups and the CNT. These interactions remained throughout the 100 ns MD simulation. The oxo clearly prefer to be oriented towards the hydrophobic surface, strengthening our previous proposal that the oxos are hydrophobic.35 From three trajectories we calculated the diffusion coefficient of the catalyst is 2.2 × 10-8 cm2 s-1. Since there is no experimental value we compare it to other two dimensional diffusion coefficients. The diffusion of the triblock copolymer Pluronics F127 on MWCNT was D = 3-8 × 10-8 cm2 s-1,46 which is in the same range as our calculated value. For pyrene diffusion in lipid membranes diffusion coefficients were measured to ~10-8 cm2 s-1.47 a

b

c


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Journal of the American Chemical Society and after 100 ns MD simulation (right). c, The initial structure of two complex 1 in the large CNT water interfaces (left) and 1 µs MD equilibration structure for complex 1 (right), the graph (bottom) shows the distance between the oxos. d, The initial structure of two complex 1 in the small CNTs water interfaces (left) and 1 µs MD equilibration structure for complex 1 (right), the graph (bottom) shown the distance between the oxos. e, A representative snapshot of the dimeric structure from MD equilibration in the four small CNTs water interfaces. All simulations are performed with TIP3P water, which have been removed in the figures for clarity.

To simulate a qualitatively different situation we performed the same type of MD-run for surface of four smaller CNTs (diameter = 4.9 Å). This surface we view as a model for the CNT-CNT interfacial regions. It can also be seen as a rugged carbon surface. Again the Ru complex rapidly formed πstacking interactions between the pyrenes and the CNT, and the oxo pointed towards the interfacial region between two CNTs (Figure 2b). It also appears that catalyst prefers an aligned configuration where it is situated on one CNT, with a smaller fraction of the configurations with interaction of one pyrene groups on one CNT and the other one on the next CNT. The diffusion coefficient was calculated to be slightly higher 2.5 × 10-8 cm2 s-1. We note that the diffusion appears to be more along the nanotube than between them.

d

[RuIVOH(bda)L2]+ on Nanotubes. In our recent study the RuIV-OH group was found to be hydrophilic in contrast to the hydrophobic RuV=O.35 Placing [RuIVOH(bda)L2]+ at the surfaces lead to structures where the hydroxide points out to the water phase throughout 100 ns MD simulation. The two pyrenes still interact with the surface (Figure S5-S6). The difference in interaction is evidenced by the number of hydrogen bonds to the oxo of the RuV and hydroxide of the RuIV complexes (Table 1). Table 1. Hydrogen bonds analysis to the oxo of the RuV and RuIV complexes.a H-bond

O1

O2

O7b

Large CNT-RuV

0.72

0.03

0.00

0.79

0.01

0.00

0.48

0.21

0.15 (0.55)

0.51

0.20

0.13 (0.54)

Small CNTs-RuV

e

IV

Large OH

CNT-Ru -

Small OH

CNTs-RuIV-

a

The values are the average number of H-bonds over the entire trajectory. bHydrogen bonds between the hydroxide hydrogen of RuIV-OH and water oxygen are provided in parenthesis. Oxygen numbers are shown in Figure 1.

Figure 2. Molecular dynamic simulation for the complex 1. a, The initial structure of complex 1 in the large CNT water interfaces (left) and after 100 ns MD simulation (right). b, The initial structure of complex 1 in the small CNTs water interfaces (left)

Two [RuVO(bda)L2]+ on CNTs. In homogeneous water solution the catalysts form a dinuclear prereactive complex and thereafter form the O-O bond.35 On a surface on the other hand the reaction mechanism is unknown. Since the reaction is highly dependent on hydrophobic driving forces in the homogeneous environment we wanted to investigate if the formation of the prereactive complex could occur on the CNT



surfaces. We used the two environments, of one 14.3 Å CNT and six parallel 4.9 Å CNTs (two more to allow for more free movement). The catalysts were placed with 30 Å between the O7 atoms of the two monomers. The catalysts quickly form adsorbed species on the surface, much like the single catalyst. Quite strikingly, the two catalysts aggregate within 100 ns to form a structure resembling the prereactive dimer that forms in water phase, with O-O distances of approximately 5 Å for the single large CNT (Figure 2c) and 8 Å for the small CNTs (Figure 2d). Once the dimer is formed the configuration remains throughout the remaining 900 ns. To assess the binding free energy, we performed umbrella sampling potential of mean force (PMF) simulations48 for the Ru-Ru distance using MD equilibration configuration as the initial structure (see the Supplementary Information for details). All PMF simulations resulted in smooth dissociation curves and the mean value from 5 simulations was 3.4 kcal mol-1 on the single large CNT and 3.5 kcal mol-1 on the six small CNTs (Figure S13). Dinuclear [(bda)L2RuIV-O-O-RuIV(bda)L2]2+. The augmented force field of product dimer was tested in vacuum, water, and interface simulations, which were all found to be stable. On the interface the product dimer was forced to twist from the geometry of the prereactive complex, since the new O-O bond lead to conformational restrictions. This restriction also leads to somewhat decreased π-stacking interaction between the CNT surface and the pyrene groups. A representative snapshot of the complex on the nanotubes is shown in Figure 2e. O-O Bond Formation at CNT-water Interfaces. As in our previous report,35 the reaction was first simulated in vacuum using DFT for reference values to use in the EVB simulations. The reaction from the prereactive dimer to the TS to the product dimer was found to proceed with an activation energy of 2.5 kcal mol-1, and with a reaction energy of -9.0 kcal mol-1. Using these input values for the EVB we confirmed that the reaction proceeded smoothly from reactants to products in vacuum and in water. In water the barrier increased slightly to 4.0 kcal mol-1, but still the reaction proceeded smoothly with no strong interference of water molecules. Finally, we wanted to study the reaction on the surface1 to get an estimate of the effect of the interface on the activation energy. For the EVB simulations were performed with the Q software package49 with a non-periodic model, and therefore we reduced the size of the systems (See Figure S15). The activation energies were significantly larger at the interfaces compared to both water and vacuum, 9.7 and 9.3 kcal mol-1 for the large and small CNTs, respectively (Figure S16). A likely cause of the higher activation free energy is the larger distortion required to reach the TS (Figure 3). In the initial state the hydrophobic oxo is close to the CNTs, essentially pointing straight at the surface. 1

Under some conditions it has been suggested that the O2 dissociation from the product complex could be rate limiting.29 It was shown, however, that the release is facilitated by further oxidation of the complex to [RuIVO-O·-RuIV]3+, a process that was estimated to have a potential of 1.03 V vs NHE. The reaction we describe herein is run at an over-potential of 0.7, which indicates that once the O-O bond is formed the complex is readily oxidized. At the oxidized complex O2 should be easily released.

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In the TS geometry the favorable catalyst CNT interaction is significantly distorted. The π-stacking interaction between the CNT surface and the complex also decrease from the initial state to TS then to the final state, due to the changed configuration of the central part of the catalysts preventing optimal πstacking. We also note that while the oxos need to be bent away from the surfaces, the bipyridine part of the bda now interacts to some extent with the surface, and thereby, compensates some of the distortion. To test the possibility of the alternative WNA mechanism, we used DFT with three explicit water molecules to estimate the activation energy. The calculated barrier of WNA at complex 1 is 20.3 kcal mol-1 in water phase, which is much larger than the energy barrier of I2M mechanism at the CNT-water phase. Using transition state theory to estimate the rate constant it corresponds to a TOF < 0.01 s-1. At the CNT-water interface, the oxo and water oxygen have a very long avarage distance of ~6 Å from the radial distribution functions analysis (Figure S11-S12). To make the catalyst get a closer interaction with water it would need to bend out of the optimal position at the surface, which would add a penalty to the free energy of activation giving an even slower reaction. While we cannot fully rule out the possibility of a WNA mechanism operating in parallel, we expect the I2M pathway is the preferred O-O bond forming mechanism for the complex 1 at the CNT-water interface.

Figure 3. EVB simulations for the complex 1. The TS structure of complex 1 in the large CNT water interfaces (left) and in the small CNTs water interfaces (right).

Estimation of TOF Based on Simulated Data. For estimation of the rate constant, we use the Arrhenius equation. In the equation (1) we use the values from the PMF and EVB simulations to estimate the activation energy Ea, while the preexponential A-factor is assumed to equal the collision frequency.

kobs = Ae − Ea /( RT )

(1)

To calculate the collision frequency we use the computed diffusion coefficients, and to estimate the catalyst loading we used literature values for the effective surface for 8 nm MWCNT of 200 m2 g-1.50 Experimentally 0.002 g cm-2 of nanotubes were attached to the electrode, equaling 0.4 m2 cm-2 of effective CNT surface area. The total loading was 1.85 nmol cm-2 of electrode,31 yielding a loading coverage of 4.63 × 10-13 mol cm-2 of CNT. The collision frequency is calculated


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Journal of the American Chemical Society by assuming free lateral diffusion over a 2-dimensional surface. This approximation neglects effects from defects, kinks, CNT-CNT interfaces, electric field etc. but it is our first approximation for the diffusion of the catalyst on the surface. The collision rate Φ for lateral diffusion has been derived by Hardt51 (2):

Φ ≈ 2π NC 2 (2 D ) / ln[(π NC ) −1/2 / a ]

(2)

where D is the diffusion coefficient (2.2 × 10-8 cm2 s-1). C is the experimental coverage (4.63 × 10-13 mol cm-2), N is Avogadro’s number and a is the reactive radius of the particle, which we have set to 1 nm. Assuming that Φ is equal to the Afactor in the Arrhenius expression we now need to multiply ‡ with the activation energy factor. In our case we use the ∆GOO from the EVB simulation as the forward activation energy, and the ∆Gdiss from the dissociation of the two catalysts from the ‡ PMF simulation. The combined value is then Ea = ∆GOO - ∆ Gdiss which at the larger CNT is calculated to 6.3 kcal mol-1 (5.8 kcal mol-1 at the small CNTs). Inserting these values in equation (1) yields a second-order rate constant of 1.71 × 1012 cm2 mol-1 s-1. The turnover frequency per catalyst is then calculated as the rate constant kobs multiplied by the loading C.

TOF = kobsC

(3) -1

The calculated value is 0.79 s at the larger CNT and 2 s-1 at the small CNTs, where both are in excellent agreement with the experimental value of 0.84 s-1.31 We note that the calculated TOF is very sensitive to the activation energy in the exponential, the diffusion coefficient in the pre-exponential and loading. Despite the possible sources of error, we can start analyzing the different components of the reaction to get insight into all the parts of the composite reaction. The activation energy was calculated to still be low at the surface, yet 5.7 and 5.3 kcal mol-1 higher than in water due to the significant distortion of the geometry needed to reach the TS geometry. Since the rate is exponentially dependent on the activation energy, even small increases can lead to significantly lower rates. If the rate of the O-O bond formation from the prereactive complex is lower than in solution it must be compensated by more frequent collision. However, the diffusion is relatively slow on the surface. Experimental measurements by Meyer and co-workers showed a diffusion coefficient of 1.6 × 10-6 cm2 s-1 in water solution indicating that the surface restricts the mobility of the catalyst.52 The diffusion on graphene of a tripodal Co(terpy)(terpy*) complex, where the terpy* is functionalized with three alkane arms with pyrene groups from experiment was found to be ~10-9 cm2 s-1,53 which is slightly lower than our number. This is could be due to the larger contact when three pyrene groups could form stronger π-stacking interactions with the surface, compared with two pyrene groups in the Ru(bda) complex. Since surface diffusion is clearly lower than in solvent, it is important to take this effect into account when making catalysts with second order concentration dependent reaction rates, as well as the different reactivity of the catalyst at the interface. The remaining factor in equation (2) that can be manipulated is the loading. We estimate that the TOF would increase from 0.79 s-1 to 15.35 s-1

and 2790 s-1 when the loading is increased 10- and 100-fold, respectively. Note that these values only apply if we assume that no other step than the O-O bond formation can be rate limiting. Table 2. TOF with different surface loading. Loading of electrode (nmol cm2

)

Activation energy Ea

Collision rate (s-1 cm-2)

1

1.85

7.09 1016

×

18.5

1.38 1017

×

185

2.51 1018

×

TOF

(kcal mol-

(s-1)

6.3

0.79

6.3

15.35

6.3

2790

)

CONCLUSIONS We have built a model that allowed us to study the formation of a bond between two surface adhered ruthenium(V)oxo catalysts in a realistic environment. Several key properties could be determined, including surface diffusion coefficient and thereby collision frequency, tendency to form the prereactive dimer, and activation free energy of the two 128 atom molecular transition metal catalysts with full CNT-water models. Combined these listed parameters made it possible to calculate the TOF of the catalyst, which agrees well with experiments. We find that the lower TOF of the surface catalyst relative to the homogeneous chemically driven catalyst is due to two contributions: 1) the activation energy at the surface is higher than in solution, which is due to larger distortion of the catalyst to reach the TS geometry 2) the collision frequency of the catalyst is limited by the slow two-dimensional diffusion on the CNT surface. To overcome the lower surface TOF we propose to address the three components: 1) The catalyst prefers a structure where the oxo is pointing towards the CNT surface, which need to be distorted in the TS. Structural modification could improve the TS-surface interaction. 2) If the diffusion can be enhanced, the rate is linearly dependent on the diffusion coefficient and will increase as the surface mobility increases. 3) The TOF is highly sensitive to the catalyst loading and could in principle be overcome if the catalyst loading level can be increased since the TOF is dependent on the concentration of catalyst. We estimate that a tenfold increase of the catalyst loading would increase the TOF approximately 20 times, which in turn means that the current density would increase 200 times (10 times more catalyst multiplied by 20 times higher activity per catalyst). This report further shows the power of an EVB description for the key step of the catalyst to understand effects of very different environments, allowing for a more complete picture



of the processes with details that are not readily obtained by any other current method. With these results we shed light on a previously obscure area of computational catalysis, where many new aspects of the catalytic process could be studied including diffusion, solvent effects, solid-liquid interface effects, activation energies in different environments, binding affinity of two molecules under realistic conditions.

ASSOCIATED CONTENT Supporting Information. The Supporting Information is available free of charge via the Internet at http://pubs.acs.org. All details of the computational study are included in the supporting information including; force field parameterization, molecular dynamics simulations and empirical valence bond simulations, structures of complexes in water phase and CNT-water interfaces, stability analysis, H-bond analysis, radial distribution functions analysis and potential of mean force analysis, EVB free energy profiles, and overview of EVB parameters (PDF)

AUTHOR INFORMATION Corresponding Author * [email protected]

Present Addresses † Department of Theoretical Chemistry & Biology, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, 10691 Stockholm, Sweden

Notes The authors declare no competing financial interest.

ACKNOWLEDGMENT This work was supported by Vetenskapsrådet and the China Scholarship Council (CSC). All calculations were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) at PDC Centre for High Performance Computing (PDC-HPC), Uppsala Multidisciplinary Center for Advanced Computational Sciemce (UPPMAX) under the project number SNIC2017-1-339, High Performance Computing Center North (HPC2N) in Umeå through the project “Multiphysics Modeling of Molecular Materials” SNIC 2017-12-49 and the National Supercomputing Center in Linköping, Sweden. The authors thank X. Wang and R. Zou for help with MD simulation as well as L. Liang for the advice on the CNT model.

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