Computational Catalysis-Past, Present, and Future

Computational Design of Functionalized Metal-Organic Framework Nodes for Catalysis

Recent progress in the synthesis and characterization of metal-organic frameworks (MOFs) has opened the door to an increasing number of possible catalytic applications. The great versatility of MOFs creates a large chemical space, whose thorough experimental examination becomes practically impossible. Therefore, computational modeling is a key tool to support, rationalize, and guide experimental efforts. In this outlook we survey the main methodologies employed to model MOFs for catalysis, and we review selected recent studies on the functionalization of their nodes. We pay special attention to catalytic applications involving natural gas conversion.

Pursuit of Noncovalent Interactions for Strategic Site-Selective Catalysis

Selective reactions on structures of high complexity can move beyond the mind's eye and proof-of-principle. Enhanced understanding of noncovalent interactions and their interdependence, revealed through analysis of multiple parameters, should accelerate the discovery of efficient reactions in highly complex molecular environments.

Diversity of Secondary Structure in Catalytic Peptides with β-Turn-Biased Sequences

X-ray crystallography has been applied to the structural analysis of a series of tetrapeptides that were previously assessed for catalytic activity in an atroposelective bromination reaction. Common to the series is a central Pro-Xaa sequence, where Pro is either l- or d-proline, which was chosen to favor nucleation of canonical β-turn secondary structures. Crystallographic analysis of 35 different peptide sequences revealed a range of conformational states. The observed differences appear not only in cases where the Pro-Xaa loop-region is altered, but also when seemingly subtle alterations to the flanking residues are introduced. In many instances, distinct conformers of the same sequence were observed, either as symmetry-independent molecules within the same unit cell or as polymorphs. Computational studies using DFT provided additional insight into the analysis of solid-state structural features. Select X-ray crystal structures were compared to the corresponding solution structures derived from measured proton chemical shifts, 3J-values, and 1H-1H-NOESY contacts. These findings imply that the conformational space available to simple peptide-based catalysts is more diverse than precedent might suggest. The direct observation of multiple ground state conformations for peptides of this family, as well as the dynamic processes associated with conformational equilibria, underscore not only the challenge of designing peptide-based catalysts, but also the difficulty in predicting their accessible transition states. These findings implicate the advantages of low-barrier interconversions between conformations of peptide-based catalysts for multistep, enantioselective reactions.

Artificial Force Induced Reaction Method for Systematic Determination of Complex Reaction Mechanisms

Nowadays, computational studies are very important for the elucidation of reaction mechanisms and selectivity of complex reactions. However, traditional computational methods usually require an estimated reaction path, mainly driven by limited experimental implications, intuition, and assumptions of stationary points. However, the artificial force induced reaction (AFIR) method in the global reaction route mapping (GRRM) strategy can be used for unbiased and automatic reaction path searches for complex reactions. In this account, we highlight applications of the AFIR method to a variety of reactions (organic, organometallic, enzymatic, and photochemical) of complex molecular systems. In addition, the AFIR method has been successfully used to rationalise the origin of stereo- and regioselectivity. The AFIR method can be applied from small to large molecular systems, and will be a very useful tool for the study of complex molecular problems in many areas of chemistry, biology, and material sciences.

Computational Catalysis Using the Artificial Force Induced Reaction Method

The artificial force induced reaction (AFIR) method in the global reaction route mapping (GRRM) strategy is an automatic approach to explore all important reaction paths of complex reactions. Most traditional methods in computational catalysis require guess reaction paths. On the other hand, the AFIR approach locates local minima (LMs) and transition states (TSs) of reaction paths without a guess, and therefore finds unanticipated as well as anticipated reaction paths. The AFIR method has been applied for multicomponent organic reactions, such as the aldol reaction, Passerini reaction, Biginelli reaction, and phase-transfer catalysis. In the presence of several reactants, many equilibrium structures are possible, leading to a number of reaction pathways. The AFIR method in the GRRM strategy determines all of the important equilibrium structures and subsequent reaction paths systematically. As the AFIR search is fully automatic, exhaustive trial-and-error and guess-and-check processes by the user can be eliminated. At the same time, the AFIR search is systematic, and therefore a more accurate and comprehensive description of the reaction mechanism can be determined. The AFIR method has been used for the study of full catalytic cycles and reaction steps in transition metal catalysis, such as cobalt-catalyzed hydroformylation and iron-catalyzed carbon-carbon bond formation reactions in aqueous media. Some AFIR applications have targeted the selectivity-determining step of transition-metal-catalyzed asymmetric reactions, including stereoselective water-tolerant lanthanide Lewis acid-catalyzed Mukaiyama aldol reactions. In terms of establishing the selectivity of a reaction, systematic sampling of the transition states is critical. In this direction, AFIR is very useful for performing a systematic and automatic determination of TSs. In the presence of a comprehensive description of the transition states, the selectivity of the reaction can be calculated more accurately. For relatively large molecular systems, the computational cost of AFIR searches can be reduced by using the ONIOM(QM:QM) or ONIOM(QM:MM) methods. In common practice, density functional theory (DFT) with a relatively small basis set is used for the high-level calculation, while a semiempirical approach or a force field description is used for the low-level calculation. After approximate LMs and TSs are determined, standard computational methods (e.g., DFT with a large basis set) are used for the full molecular system to determine the true LMs and TSs and to rationalize the reaction mechanism and selectivity of the catalytic reaction. The examples in this Account evidence that the AFIR method is a powerful approach for accurate prediction of the reaction mechanisms and selectivities of complex catalytic reactions. Therefore, the AFIR approach in the GRRM strategy is very useful for computational catalysis.

Photocycloaddition reaction of atropisomeric maleimides: mechanism and selectivity

We report a density functional study on the mechanism of the [2+2] photocyclization of atropisomeric maleimides.

Size-dependent properties of transition metal clusters: from molecules to crystals and surfaces--computational studies with the program ParaGauss

In the so-called scalable regime the size-dependent behavior of the physical and chemical properties of transition metal clusters is described by scaling relationships. For most quantities this scalable regime is reached for cluster sizes between a few tens and a few hundreds of atoms, hence for systems for which an accurate treatment by density functional theory is still feasible. Thus, by invoking scaling relations one is able to obtain properties of very large nanoparticles and even the bulk limit from the results of a series of smaller cluster models. In this invited review we illustrate this strategy by exploiting results from computational studies that mostly were carried out with the density functional theory software ParaGauss. We address mainly the size-dependent behavior of the properties of transition metal clusters. To this end, we first present benchmark studies probing various approximations that are used in such density functional calculations. Subsequently we show how physical insight may be gained by exploring less understood types of systems. These applications range from bare clusters to nanoislands and nanoalloys to adsorption complexes.

Heterogeneous catalysis

A heterogeneous catalyst is a functional material that continually creates active sites with its reactants under reaction conditions. These sites change the rates of chemical reactions of the reactants localized on them without changing the thermodynamic equilibrium between the materials.

Computational organic chemistry: bridging theory and experiment in establishing the mechanisms of chemical reactions

Understanding the mechanisms of chemical reactions, especially catalysis, has been an important and active area of computational organic chemistry, and close collaborations between experimentalists and theorists represent a growing trend. This Perspective provides examples of such productive collaborations. The understanding of various reaction mechanisms and the insight gained from these studies are emphasized. The applications of various experimental techniques in elucidation of reaction details as well as the development of various computational techniques to meet the demand of emerging synthetic methods, e.g., C-H activation, organocatalysis, and single electron transfer, are presented along with some conventional developments of mechanistic aspects. Examples of applications are selected to demonstrate the advantages and limitations of these techniques. Some challenges in the mechanistic studies and predictions of reactions are also analyzed.