Redox free energies and one-electron energy levels in density functional theory based ab initio molecular dynamics

VandeVondele, Joost; Ayala, Regla; Sulpizi, Marialore; Sprik, Michiel

doi:10.1016/j.jelechem.2007.01.009

Cited by 38 publications

(58 citation statements)

References 59 publications

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“…In order to calculate the free energy of a redox process, the thermodynamic integration method [84][85][86][87][88][89][90][91][92][93][94][95] is employed. The relation between the reduced and oxidized species of the redox reaction can be expressed using a coupling parameter (η) as shown below.…”

Section: Molecular Dynamics Simulationsmentioning

confidence: 99%

Computational Redox Potential Predictions: Applications to Inorganic and Organic Aqueous Complexes, and Complexes Adsorbed to Mineral Surfaces

Arumugam

Becker

2014

Minerals

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Abstract:Applications of redox processes range over a number of scientific fields. This review article summarizes the theory behind the calculation of redox potentials in solution for species such as organic compounds, inorganic complexes, actinides, battery materials, and mineral surface-bound-species. Different computational approaches to predict and determine redox potentials of electron transitions are discussed along with their respective pros and cons for the prediction of redox potentials. Subsequently, recommendations are made for certain necessary computational settings required for accurate calculation of redox potentials. This article reviews the importance of computational parameters, such as basis sets, density functional theory (DFT) functionals, and relativistic approaches and the role that physicochemical processes play on the shift of redox potentials, such as hydration or spin orbit coupling, and will aid in finding suitable combinations of approaches for different chemical and geochemical applications. Identifying cost-effective and credible computational approaches is essential to benchmark redox potential calculations against experiments. Once a good theoretical approach is found to model the chemistry and thermodynamics of the redox and electron transfer process, this knowledge can be incorporated into models of more complex reaction mechanisms that include diffusion in the solute, surface diffusion, and dehydration, to name a few. This knowledge is important to fully understand the nature of redox processes be it a geochemical process that dictates natural redox reactions or one that is being used for the optimization of a chemical process in industry. In addition, it will help identify materials that will be useful to design catalytic OPEN ACCESSMinerals 2014, 4 346 redox agents, to come up with materials to be used for batteries and photovoltaic processes, and to identify new and improved remediation strategies in environmental engineering, for example the reduction of actinides and their subsequent immobilization. Highly under-investigated is the role of redox-active semiconducting mineral surfaces as catalysts for promoting natural redox processes. Such knowledge is crucial to derive process-oriented mechanisms, kinetics, and rate laws for inorganic and organic redox processes in nature. In addition, molecular-level details still need to be explored and understood to plan for safer disposal of hazardous materials. In light of this, we include new research on the effect of iron-sulfide mineral surfaces, such as pyrite and mackinawite, on the redox chemistry of actinyl aqua complexes in aqueous solution.

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Section: Molecular Dynamics Simulationsmentioning

confidence: 99%

Computational Redox Potential Predictions: Applications to Inorganic and Organic Aqueous Complexes, and Complexes Adsorbed to Mineral Surfaces

Arumugam

Becker

2014

Minerals

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“…For the CPMD/BOMD calculations, error sources include the shortcomings of DFT methods in terms of electron correlation (including dispersion), affecting both bulk water properties [121][122][123][124][125][126][127][128][129][130] and ion-water interactions, 66,67,105,131 the small system sizes considered (resulting in a high weight for the approximate finite-size correction term), the very limited sampling times, the ambiguity in defining the appropriate reference potential within DFT water, 21,112,[132][133][134][135][136] and the numerical problems (see, e.g., footnotes 42 and 45 in Ref. 111) associated with creating a species or injecting electrons when applying computational alchemy in a QM framework [137][138][139][140][141][142][143] (see, however, Refs. 114 and 144-149 for possible grandcanonical alternatives).…”

Section: Introductionmentioning

confidence: 99%

Absolute proton hydration free energy, surface potential of water, and redox potential of the hydrogen electrode from first principles: QM/MM MD free-energy simulations of sodium and potassium hydration

Hofer

Hünenberger

2018

The Journal of Chemical Physics

104

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The absolute intrinsic hydration free energy G • H + ,wat of the proton, the surface electric potential jump χ • wat upon entering bulk water, and the absolute redox potential V • H + ,wat of the reference hydrogen electrode are cornerstone quantities for formulating single-ion thermodynamics on absolute scales. They can be easily calculated from each other but remain fundamentally elusive, i.e., they cannot be determined experimentally without invoking some extra-thermodynamic assumption (ETA). The Born model provides a natural framework to formulate such an assumption (Born ETA), as it automatically factors out the contribution of crossing the water surface from the hydration free energy. However, this model describes the short-range solvation inaccurately and relies on the choice of arbitrary ion-size parameters. In the present study, both shortcomings are alleviated by performing first-principle calculations of the hydration free energies of the sodium (Na + ) and potassium (K + ) ions. The calculations rely on thermodynamic integration based on quantum-mechanical molecular-mechanical (QM/MM) molecular dynamics (MD) simulations involving the ion and 2000 water molecules. The ion and its first hydration shell are described using a correlated ab initio method, namely resolution-of-identity second-order Møller-Plesset perturbation (RIMP2). The next hydration shells are described using the extended simple point charge water model (SPC/E). The hydration free energy is first calculated at the MM level and subsequently increased by a quantization term accounting for the transformation to a QM/MM description. It is also corrected for finite-size, approximate-electrostatics, and potentialsummation errors, as well as standard-state definition. These computationally intensive simulations provide accurate first-principle estimates for G • H + ,wat , χ • wat , and V • H + ,wat , reported with statistical errors based on a confidence interval of 99%. The values obtained from the independent Na + and K + simulations are in excellent agreement. In particular, the difference between the two hydration free energies, which is not an elusive quantity, is 73.9 ± 5.4 kJ mol 1 (K + minus Na + ), to be compared with the experimental value of 71.7 ± 2.8 kJ mol 1 . The calculated values of G • H + ,wat , χ • wat , and V • H + ,wat ( 1096.7 ± 6.1 kJ mol 1 , 0.10 ± 0.10 V, and 4.32 ± 0.06 V, respectively, averaging over the two ions) are also in remarkable agreement with the values recommended by Reif and Hünenberger based on a thorough analysis of the experimental literature ( 1100 ± 5 kJ mol 1 , 0.13 ± 0.10 V, and 4.28 ± 0.13 V, respectively). The QM/MM MD simulations are also shown to provide an accurate description of the hydration structure, dynamics, and energetics. Published by AIP Publishing.

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“…For example, the response of the solvent to the ionization of the solute can be analyzed, [10] the contribution of particular residues to the solvent reorganization energy estimated, [15,30] or the correlation between one-electron energies levels and redox potentials obtained. [14] In this paper, we focused on the computation of key parameters in Marcus theory and compared these results with experiment where available. The results presented here are a good indication that the method is quantitative and predictive, and that our approach can thus be applied in cases where experiments might be difficult or more approximate theories inappropriate.…”

Section: Resultsmentioning

confidence: 99%

“…Nevertheless, these simulations remain challenging and a number of issues that might affect their accuracy have been discussed in more detail in ref. [14] Errors arise from the approximate nature of DFT and from the limited length and timescales that can be assessed by ab initio techniques. The most serious DFT error is likely to come from the self-interaction error, despite the fact that our half-cell approach avoids the difficulties associated with a computational setup where both donor and acceptor are present in the same simulation cell.…”

Section: Atomistic Theory Of Electron Transfermentioning

confidence: 99%

“…differences in redox potentials), and the rate of electron transfer between them are of particular interest, as they reflect directly what is thermodynamically and kinetically feasible. In this paper, we will summarize some of our previous work [3][4][5][6][7][8][9][10][11][12][13][14][15] aimed at computing these quantities directly from doi: 10.2533/chimia.2007.155 k ET …”

Section: Introductionmentioning

confidence: 99%

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Electron Transfer Properties from Atomistic Simulations and Density Functional Theory

VandeVondele

Sulpizi²,

Sprik³

2007

Chimia

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Marcus theory of electron transfer is the quintessential example of a successful theory in physical chemistry. In this paper, we describe the theoretical approach we have adopted to compute key parameters in Marcus theory. In our method, based on molecular dynamics simulations and density functional theory, the redox center and its environment are treated at the same level of theory. Such a detailed atomistic model describes specific solvent-solute interactions, such as hydrogen bonding, explicitly. The quantum chemical nature of our computations enables us to study the effect of chemical modifications of the redox centers and deals accurately with the electronic polarization of the environment. Based on results of previous work, we will illustrate that quantitative agreement with experiment can be obtained for differences in redox potentials and solvent reorganization energies for systems ranging from small organic compounds to proteins in solution. Keywords: Density functional theory · Electron transfer · Marcus theory · Molecular dynamicsatomistic models using density functional Theory (DFT). The quantum chemical nature of DFT allows the effects of chemical modifications of the redox centers to be studied without a need for prior knowledge or empirical parameterization. This can thus make our method truly predictive. A key feature of ET reactions, or redox reactions in general, is the crucial role played by the environment. Indeed, oxidation (reduction) potentials are the condensed phase equivalents of ionization potentials (electron affinities) in the gas phase, and these quantities can differ significantly. Our atomistic models explicitly include the environment ( e.g. solvent and/or protein) so that not only dielectric properties but also specific interactions, such as hydrogen bonding or conformational changes are taken explicitly into account. Furthermore, the environment is far from being a static spectator. Its fluctuations bring donor and acceptor sites in an energy resonant state, triggering ET, and its ability to relax after ET influences significantly the energetics. In order to probe these fluctuations and relaxations in our computational setup, molecular dynamics is employed to generate a sufficiently large number of representative configurations of solute and solvent.A major step in the understanding of ET reactions was the formulation by Marcus [16,17] of the rate of electron transfer (k ET ) as a simple function of the reaction free energy ( Δ G), the solvent reorganization energy ( λ ) and a proportionality constant ( κ ) depending on the quantum coupling between donor and acceptor states.The fruitful concept that underlies this formula is the assumed harmonic nature of the free energy surface with respect to the reaction coordinate of electron transfer. This restricts the validity of this formula to the range of systems that fall in the linear response regime, which might thus exclude systems that undergo significant changes in conformation or solvation upon electron transfer. Ulti...

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Redox free energies and one-electron energy levels in density functional theory based ab initio molecular dynamics

Cited by 38 publications

References 59 publications

Computational Redox Potential Predictions: Applications to Inorganic and Organic Aqueous Complexes, and Complexes Adsorbed to Mineral Surfaces

Computational Redox Potential Predictions: Applications to Inorganic and Organic Aqueous Complexes, and Complexes Adsorbed to Mineral Surfaces

Absolute proton hydration free energy, surface potential of water, and redox potential of the hydrogen electrode from first principles: QM/MM MD free-energy simulations of sodium and potassium hydration

Electron Transfer Properties from Atomistic Simulations and Density Functional Theory

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