1. Role of Theory Model and understand catalytic processes at the electronic/atomistic level. This involves proposing atomic structures, suggesting reaction pathways, computing reaction energetics, in order to model reaction dynamics and identify key parameters controlling a catalytic process; Predict from microscopic theory the basic kinetic parameters that govern catalytic processes in engineering and industrial applications. This requires bridging the large gap in time and size scales separating elementary molecular processes from the statistical behavior that governs chemical kinetics at the macroscale; Identify general trends and unifying principles that are common/specific to different classes of catalytic phenomena – heterogeneous, homogeneous, and bio-catalysis. Create databases of both theoretical and experimental data and develop methodologies to perform data mining and optimization approaches to help design new materials and catalytic systems

2. Current capabilities These include the characterization of the stationary points (minima and transition states) on the multidimensional potential energy surface (PES) and the calculation of the relative energetics and reaction paths using various levels of approximations, which include empirical, semiempirical and first principles quantum mechanical descriptions of the relevant interactions. The calculation results in detailed structural information of reaction intermediates that do not necessarily have gas phase analogs and are therefore elusive as well as spectroscopic properties (IR, Raman, EELS, UPS, XPS, SFG).

3. Limitations of current capabilities Accuracy of the energies computed with DFT. The problem is most severe for weakly interacting (van der Waals) systems. Within the DFT method there are limitations in the accuracy of the excited states. Limitations also exist in simulating the long time dynamics of the system given the potential energy surface. Quantum effects in dynamics (non-adiabatic, electron transfer…) Accuracy of descriptions by QM/MM schemes (e.g. solvation effects)

4. Needed Progress Improve QM descriptors (ground and excited electronic states beyond current DFT approximations) Improve methods for dynamics (classical and quantum, adiabatic and non-adiabatic, electron and proton transfer) Rare events (long time dynamics) Coarse graining and integration of different approaches: from QM at different levels of approximation to model potentials to kinetic models to optimization methods for catlysis design)

5. New promising approaches Linear scaling QM methods [O(N)] Embedding techniques Path searching methods (configurational and dynamic) Kinetic Monte Carlo schemes Evolutionary algorithms

6. Organizational Needs Need programs that foster combined experimental/theoretical efforts Need better cooperation among theorists to develop modeling and simulation tools that should be accessible to the entire community Need access to computational facilities

7. What will we achieve? The ultimate goal of theoretical catalysis is to develop methods that can be used to make predictions about new reactions and catalysts. This will always happen in close conjunction with catalyst synthesis and experimental investigations, but with increasing insight and ever-faster computers theoretical methods will play a more and more important role in this process. Predictions will come from (i)Theoretical methods based on direct solution of the Schrödinger equation will become accurate and fast enough that they can be used directly in elucidating new reactions and catalysts. This may eventually provide the most efficient way of screening new ideas for reactions and catalysts. (ii)Theoretical methods can be used to extract unifying concepts that allow us to think efficiently about catalytic processes and catalysts. If we can identify the most important parameters determining the catalytic activity and selectivity of a catalyst we will have at our disposal very powerful tools for rational catalyst design. (iii)Calculations will become a very powerful tool in providing systematic data-bases for catalyst properties. The calculations can map out materials properties that can form the basis for searches for correlations between catalytic activity/selectivity and other materials properties.