Further considerations on the thermodynamics of chemical equilibria and reaction rates

Evans, M. G.; Polanyi, Michael L.

doi:10.1039/tf9363201333

Cited by 651 publications

(411 citation statements)

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“…These states are easier to both measure and compute, and can be related to the transition state by linear free energy relationships (LFERs). LFERs are a phenomenological model used to describe the linear behavior that may exist between the logarithm of the reaction rates and equilibrium constants for a series of reactions: [49][50][51] ln ln k a K b  , where k denotes the kinetic rate constant, K denotes the thermodynamic equilibrium constant, and a and b are constants. These can be equivalently written in terms of the activation free energies…”

mentioning

confidence: 99%

Toward the rational design of non-precious transition metal oxides for oxygen electrocatalysis

Hong

Risch

Stoerzinger

et al. 2015

Energy Environ. Sci.

1,817

1,491

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REVIEWThis journal is © The Royal Society of Chemistry 2013 J. Name., 2013, 00, 1-3 | 1 In this Review, we discuss the state-of-the-art understanding of non-precious transition metal oxides that catalyze the oxygen reduction and evolution reactions. Understanding and mastering the kinetics of oxygen electrocatalysis is instrumental to making use of photosynthesis, advancing solar fuels, fuel cells, electrolyzers, and metal-air batteries. We first present key insights, assumptions and limitations of well-known activity descriptors and reaction mechanisms in the past four decades. The turnover frequency of crystalline oxides as promising catalysts is also put into perspective with amorphous oxides and photosystem II. Particular attention is paid to electronic structure parameters that can potentially govern the adsorbate binding strength and thus provide simple rationales and design principles to predict new catalyst chemistries with enhanced activity. We share new perspective synthesizing mechanism and electronic descriptors developed from both molecular orbital and solid state band structure principles. We conclude with an outlook on the opportunities in future research within this rapidly developing field. Broader ContextThe formation of chemical bonds is an energy dense mode of storing energy. In both nature and technology, the electrochemical generation and consumption of fuels is one of the most efficient routes for energy usage. Solar and electrical energy can be stored in chemical bonds by splitting water or metal oxides to produce hydrogen and metal. These compounds can then be oxidized to produce energy when coupled to the reduction of oxygen. However, these device efficiencies are severely limited by the catalysis of oxygen electrochemical processes -namely the oxygen reduction reaction and oxygen evolution reaction, which have slow kinetics. Non-precious transition metal oxides show promise as cost-effective substitutes for noble metals in commercially viable renewable energy storage and conversion devices. Furthermore, this class of materials has ben efitted from a wealth of spectroscopic and first-principles studies in the past few decades, providing the frameworks and theories needed to understand the electronic structure and design optimal catalysts. The incredibly diverse range of chemistries and physical properties that can be explored in oxide families afford numerous degrees of freedom for conducting systematic investigations relating intrinsic mat erial properties to catalytic performance. Here, we present background on the fundamental concepts in catalysis for the rational design of transition metal perovskite oxide catalysts for oxygen electrocatalysis and critically examine the current understanding a nd its impact on future directions of perovskite catalysts.

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mentioning

confidence: 99%

Toward the rational design of non-precious transition metal oxides for oxygen electrocatalysis

Hong

Risch

Stoerzinger

et al. 2015

Energy Environ. Sci.

1,817

1,491

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“…[73] Based on the reactions of Table 7, the group additive method outperforms models such as Evans-Polanyi correlations. [15,16] Applying an Evans-Polanyi relation obtained from the reactions in Tables 3 and 4 for the prediction of the 300 K activation energies of Table 7, an average overestimation of the ab initio activation energies of 4.3 kJ mol -1 is found, compared to an overestimation by 1.3 kJ mol -1 for the group additive method (see Figures S1-S2 in Supporting Information). Group additivity clearly improves the agreement with the ab initio activation energy, and the method is moreover capable of predicting pre-exponential factors in contrast to the Evans-Polanyi method.…”

Section: Ab Initio Validationmentioning

confidence: 99%

“…Therefore a variety of methods for rate prediction of radical reactions has been developed. These methods range from correlating the activation energy to the reaction enthalpy, such as Evans-Polanyi correlations and its variations, [15][16][17] to more sophisticated methods based on the structure of the transition state. Several of the latter methods are related to Benson group 2 additivity.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore a variety of methods for rate prediction of radical reactions has been developed. These methods range from correlating the activation energy to the reaction enthalpy, such as Evans-Polanyi correlations and its variations, [15][16][17] Sabbe et al ChemPhysChem 11:195-210 (2010) -pre-reviewed version 2 additivity. [18,19] Among these are: 1. the structural group contribution method of Willems and Froment, [20,21] in which correction terms on the Arrhenius parameters of a reference reaction account for structural differences between the latter and the considered reaction; 2. methods that calculate the thermochemistry of the transition state, such as the method described by Sumathi et al, [22][23][24] 3. the Reaction Class Transition State Theory developed by Truong et al [25,26] and 4. the group additive (GA) method for activation energies as described by Saeys et al [27,28] Experimental determination of all the kinetic and thermodynamic parameters required for these methods is not possible due to scarcity of experimental data.…”

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confidence: 99%

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Hydrogen Radical Additions to Unsaturated Hydrocarbons and the Reverse β‐Scission Reactions: Modeling of Activation Energies and Pre‐Exponential Factors

et al. 2010

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The group additivity method for Arrhenius parameters is applied to hydrogen addition to alkenes and alkynes and the reverse β-scission reactions, an important reaction family in thermal processes based on radical chemistry. A consistent set of group additive values for 33 groups is derived to calculate the activation energy and preexponential factor for a broad range of H-addition reactions. The group additive values are determined from CBS-QB3 ab initio calculated rate coefficients. A mean factor of deviation between the CBS-QB3 and the experimental rate coefficients for 7 reactions of only 2 in the range 300-1000 K is found. Tunneling coefficients for these reactions were found to be significant below 400 K and a correlation accounting for tunneling is presented. Application of the obtained group additive values to predict the kinetics for a set of 11 additions and β scissions yields rate coefficients within a factor 3.5 from the CBS-QB3 results except for 2 β scissions with severe steric effects. The mean factor of deviation with experimental rate coefficients is 2.0, showing that the group additive method with tunneling corrections can accurately predict the kinetics, at least as accurate as the most commonly used density functional methods. The constructed group additive model can hence be applied to predict the kinetics of hydrogen radical additions to a broad range of unsaturated compounds. IntroductionThe addition of hydrogen radicals to alkenes and its reverse β scission, are important elementary steps in radical processes such as polymerization, pyrolysis, steam cracking, partial oxidation and combustion.[1] Therefore, the reaction family of hydrogen addition/β scission forms an indispensable part of any radical reaction network.A reliable reactor optimization requires an accurate kinetic model based on elementary reactions. For radical chemistry, on which many of the world largest scale chemical processes are based, the reactive nature of the radical intermediates results in huge reaction networks typically involving hundreds of species and thousands of elementary reactions. [2][3][4] Currently, most elementary reaction networks are automatically generated using advanced algorithms for the selection of the relevant reactions. [5][6][7][8][9][10][11] Sensitivity studies on these reaction networks point out that the main part of the uncertainty on the product yields stems from inaccurate knowledge of kinetic data. [12,13] Therefore, accurate kinetic data are essential to obtain reliable process simulations. Moreover, if rate-based network construction algorithms are applied, [14] accurate rate data are even more important as inaccuracies can result in the construction of an incomplete network that is not capable of grasping the underlying chemistry of the process.A quantitative description of radical processes thus requires that rate parameters be known for all of the different reactions comprising the reaction network. However, it is very difficult to measure kinetic parameters for individual radical r...

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“…In fact, similar parabola models can be used for the explanation of the Bell-Evans-Polanyi principle (a linear model is sufficient, though), the Marcus equation, Hammond's postulate, and the relationship of low-curvature directions with low barrier energies. [39][40][41][42][43][44][45] In such a parabola model, the transition state is given by the intercept (ξ, E(ξ)) of both parabolas. From Fig.…”

Section: Correlating Transition State Energies With Structural DImentioning

confidence: 99%

Computationally efficient characterization of potential energy surfaces based on fingerprint distances

Schaefer

Goedecker

2016

The Journal of Chemical Physics

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An analysis of the network defined by the potential energy minima of multi-atomic systems and their connectivity via reaction pathways that go through transition states allows us to understand important characteristics like thermodynamic, dynamic, and structural properties. Unfortunately computing the transition states and reaction pathways in addition to the significant energetically low-lying local minima is a computationally demanding task. We here introduce a computationally efficient method that is based on a combination of the minima hopping global optimization method and the insight that uphill barriers tend to increase with increasing structural distances of the educt and product states. This method allows us to replace the exact connectivity information and transition state energies with alternative and approximate concepts. Without adding any significant additional cost to the minima hopping global optimization approach, this method allows us to generate an approximate network of the minima, their connectivity, and a rough measure for the energy needed for their interconversion. This can be used to obtain a first qualitative idea on important physical and chemical properties by means of a disconnectivity graph analysis. Besides the physical insight obtained by such an analysis, the gained knowledge can be used to make a decision if it is worthwhile or not to invest computational resources for an exact computation of the transition states and the reaction pathways. Furthermore it is demonstrated that the here presented method can be used for finding physically reasonable interconversion pathways that are promising input pathways for methods like transition path sampling or discrete path sampling. Published by AIP Publishing. [http://dx

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Further considerations on the thermodynamics of chemical equilibria and reaction rates

Cited by 651 publications

References 0 publications

Toward the rational design of non-precious transition metal oxides for oxygen electrocatalysis

Toward the rational design of non-precious transition metal oxides for oxygen electrocatalysis

Hydrogen Radical Additions to Unsaturated Hydrocarbons and the Reverse β‐Scission Reactions: Modeling of Activation Energies and Pre‐Exponential Factors

Computationally efficient characterization of potential energy surfaces based on fingerprint distances

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