A review of multiscale modeling of metal-catalyzed reactions: Mechanism development for complexity and emergent behavior

We review and provide a perspective on multiscale modeling of catalytic reactions with emphasis on mechanism development and application to complex and emergent systems. We start with an overview of length and time scales, objectives, and challenges in first-principles modeling of reactive systems. Subsequently, we review various methods that ensure thermodynamic consistency of mean-field microkinetic models. Next, we describe estimation of reaction rate constants via quantum mechanical and statistical-mechanical methods as well as semi-empirical methods. Among the latter, we discuss the bond-order conservation method for thermochemistry and activation energy estimation. In addition, we review the newly developed group-additivity method on adsorbate/metal systems and linear free energy or Brønsted-Evans-Polanyi (BEP) relations, and their parameterization using DFT calculations to generate databases of activation energies and reaction free energies. Linear scaling relations, which can enable transfer of reaction energetics among metals, are discussed. Computation-driven catalyst design is reviewed and a new platform for discovery of materials with emergent behavior is introduced. The effect of parameter uncertainty on catalyst design is discussed; it is shown that adsorbate-adsorbate interactions can profoundly impact materials design. Spatiotemporal averaging of microscopic events via the kinetic Monte Carlo method for realistic reaction mechanisms is discussed as an alternative to mean-field modeling. A hierarchical multiscale modeling strategy is proposed as a means of addressing (some of) the complexity of catalytic reactions. Structure-based microkinetic modeling is next reviewed to account for nanoparticle size and shape effects and structure sensitivity of catalytic reactions. It is hypothesized that catalysts with multiple sites of comparable activity can exhibit structure sensitivity that depends strongly on operating conditions. It is shown that two descriptor models are necessary to describe the thermochemistry of adsorbates on nanoparticles. Multiscale and accelerated methods for computing free energies in solution, while accounting explicitly for solvent effects in catalytic reactions, are briefly touched upon with the acid catalyzed dehydration of fructose in water as an example. The above methods are illustrated with several reactions, such as the CO oxidation on Au; the hydrogenation of ethylene and hydrogenolysis of ethane on Pt; the glycerol decomposition to syngas on Pt-based materials; the NH decomposition on single metals and bimetallics; and the dehydration of fructose in water. Finally, we provide a summary and outlook. © 2011 Elsevier Ltd

Understanding mixing of Ni and Pt in the Ni/Pt(111) bimetallic catalyst via molecular simulation and experiments

Molecular dynamics (MD) simulations employing embedded atom method potentials and ultrahigh vacuum (UHV) experiments were carried out to study the mixing process between the Ni and Pt atoms in the Ni/Pt(111) bimetallic system. The barrier for a Ni atom to diffuse from the top surface to the subsurface layer is rather high (around 1.7 eV) as calculated using the nudged elastic band (NEB) method. Analysis of the relaxation dynamics of the Ni atoms showed that they undergo diffusive motion through a mechanism of correlated hops. At 600 K, all Ni atoms remain trapped on the top surface due to large diffusion barriers. At 900 K, the majority of Ni atoms diffuse to the second layer and at 1200 K diffusion to the bulk is observed. We also find that smaller Ni coverages and the presence of Pt steps facilitate the Ni/Pt mixing. By simulated annealing simulations, we found that in the mixed state, the Ni fraction oscillates between layers, with the second layer being Ni-richer at equilibrium. The simulation results at multiple time scales are consistent with the experimental data. © 2010 American Institute of Physics

Evolutionarily Conserved Linkage between Enzyme Fold, Flexibility, and Catalysis

Proteins are intrinsically flexible molecules. The role of internal motions in a protein's designated function is widely debated. The role of protein structure in enzyme catalysis is well established, and conservation of structural features provides vital clues to their role in function. Recently, it has been proposed that the protein function may involve multiple conformations: the observed deviations are not random thermodynamic fluctuations; rather, flexibility may be closely linked to protein function, including enzyme catalysis. We hypothesize that the argument of conservation of important structural features can also be extended to identification of protein flexibility in interconnection with enzyme function. Three classes of enzymes (prolyl-peptidyl isomerase, oxidoreductase, and nuclease) that catalyze diverse chemical reactions have been examined using detailed computational modeling. For each class, the identification and characterization of the internal protein motions coupled to the chemical step in enzyme mechanisms in multiple species show identical enzyme conformational fluctuations. In addition to the active-site residues, motions of protein surface loop regions (>10 Å away) are observed to be identical across species, and networks of conserved interactions/residues connect these highly flexible surface regions to the active-site residues that make direct contact with substrates. More interestingly, examination of reaction-coupled motions in non-homologous enzyme systems (with no structural or sequence similarity) that catalyze the same biochemical reaction shows motions that induce remarkably similar changes in the enzyme–substrate interactions during catalysis. The results indicate that the reaction-coupled flexibility is a conserved aspect of the enzyme molecular architecture. Protein motions in distal areas of homologous and non-homologous enzyme systems mediate similar changes in the active-site enzyme–substrate interactions, thereby impacting the mechanism of catalyzed chemistry. These results have implications for understanding the mechanism of allostery, and for protein engineering and drug design

Global optimization in the 21st century: Advances and challenges

This paper presents an overview of the research progress in global optimization during the last 5 years (1998–2003), and a brief account of our recent research contributions. The review part covers the areas of (a) twice continuously differentiable nonlinear optimization, (b) mixedinteger nonlinear optimization, (c) optimization with differential-algebraic models, (d) optimization with grey-box/black-box/nonfactorable models, and (e) bilevel nonlinear optimization. Our research contributions part focuses on (i) improved convex underestimation approaches that include convex envelope results for multilinear functions, convex relaxation results for trigonometric functions, and a piecewise quadratic convex underestimator for twice continuously differentiable functions, and (ii) the recently proposed novel generalized �BB framework. Computational studies will illustrate the potential of these advances