Calculating solution redox free energies with <i>ab initio</i> quantum mechanical/molecular mechanical minimum free energy path method

Zhang, Xiancheng; Hu, Hao; Hu, Xiangqian; Yang, Weitao

doi:10.1063/1.3120605

Cited by 35 publications

(62 citation statements)

References 80 publications

(105 reference statements)

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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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“…The QM optimization and the MM sampling are sequentially performed until convergence. 42,62,68,70,72,73 This improvement obviates the QM/MM-FE requirement of defining a minimum energy reaction path prior to free energy calculations. 65,66,68,69 Recently, conical intersections of potential energy surfaces for reactions in solution or macromolecules have received much attention.…”

Section: Introductionmentioning

confidence: 99%

“…42,62,66,68,70,72 According to Eqs. (7) and (8), the potential of mean force of the QM subsystem at electronic state I with the QM/MM-MFEP method is expressed…”

Section: Free Energy Gradientmentioning

confidence: 99%

“…44,68 Details of the sequential optimizations and their applications can be found in recent papers. 42,44,65,66,[68][69][70] In general the region that is relevant to electronicstructure change is placed into the QM subsystem; thereby, decoupling the QM conical intersection optimizations from the MM minimizations is reasonable.…”

Section: B Sequential Qm Conical Intersection Optimization and MM Mimentioning

confidence: 99%

“…13,26,[44][45][46][63][64][65][66][67] In order to make the QM/MM minimization in solution or macromolecules efficient, we have developed a sequential optimization method where the QM and MM optimizations are sequentially, not concurrently, carried out. 44,[64][65][66][68][69][70] In this method, expensive but accurate optimization methods, such as Newton-Raphson and rational functional optimization methods, are used for optimizations of the QM subsystem, while efficient optimization methods, such as steepest descent and conjugated gradient methods, are used for minimizations of the MM subsystem. 44 As chemical reactions mainly proceed in the QM subsystem, transition state optimizations mainly depend on degrees of freedom of the QM subsystem.…”

Section: Introductionmentioning

confidence: 99%

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Conical intersections in solution: Formulation, algorithm, and implementation with combined quantum mechanics/molecular mechanics method

Cui

Yang

2011

The Journal of Chemical Physics

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The significance of conical intersections in photophysics, photochemistry, and photodissociation of polyatomic molecules in gas phase has been demonstrated by numerous experimental and theoretical studies. Optimization of conical intersections of small-and medium-size molecules in gas phase has currently become a routine optimization process, as it has been implemented in many electronic structure packages. However, optimization of conical intersections of small-and medium-size molecules in solution or macromolecules remains inefficient, even poorly defined, due to large number of degrees of freedom and costly evaluations of gradient difference and nonadiabatic coupling vectors. In this work, based on the sequential quantum mechanics and molecular mechanics (QM/MM) and QM/MM-minimum free energy path methods, we have designed two conical intersection optimization methods for small-and medium-size molecules in solution or macromolecules. The first one is sequential QM conical intersection optimization and MM minimization for potential energy surfaces; the second one is sequential QM conical intersection optimization and MM sampling for potential of mean force surfaces, i.e., free energy surfaces. In such methods, the region where electronic structures change remarkably is placed into the QM subsystem, while the rest of the system is placed into the MM subsystem; thus, dimensionalities of gradient difference and nonadiabatic coupling vectors are decreased due to the relatively small QM subsystem. Furthermore, in comparison with the concurrent optimization scheme, sequential QM conical intersection optimization and MM minimization or sampling reduce the number of evaluations of gradient difference and nonadiabatic coupling vectors because these vectors need to be calculated only when the QM subsystem moves, independent of the MM minimization or sampling. Taken together, costly evaluations of gradient difference and nonadiabatic coupling vectors in solution or macromolecules can be reduced significantly. Test optimizations of conical intersections of cyclopropanone and acetaldehyde in aqueous solution have been carried out successfully.

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Theoretical estimation of redox potential of biological quinone cofactors

et al. 2017

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Redox potentials are essential to understand biological cofactor reactivity and to predict their behavior in biological media. Experimental determination of redox potential in biological system is often difficult due to complexity of biological media but computational approaches can be used to estimate them. Nevertheless, the quality of the computational methodology remains a key issue to validate the results. Instead of looking to the best absolute results, we present here the calibration of theoretical redox potential for quinone derivatives in water coupling QM + MM or QM/MM scheme. Our approach allows using low computational cost theoretical level, ideal for long simulations in biological systems, and determination of the uncertainties linked to the calculations. © 2017 Wiley Periodicals, Inc.

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Calculating solution redox free energies with ab initio quantum mechanical/molecular mechanical minimum free energy path method

Cited by 35 publications

References 80 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

Conical intersections in solution: Formulation, algorithm, and implementation with combined quantum mechanics/molecular mechanics method

Theoretical estimation of redox potential of biological quinone cofactors

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