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Catalytic processes are crucially important for many practical chemical applications. Heterogeneous catalysts are especially appealing because of their high stability and the relative ease with which they may be recovered and reused. Computational modeling can play an important role in the design of more catalytically active materials through the identification of reaction mechanisms and the opportunity to assess hypothetical catalysts in silico prior to experimental verification. Kohn-Sham density functional theory (KS-DFT) is the most used method in computational catalysis because it is affordable and it gives results of reasonable accuracy in many instances. Furthermore, it can be employed in a “black-box” mode that does not require significant a priori knowledge of the system. However, KS-DFT has some limitations: it suffers from self-interaction error (sometime referred to as delocalization error), but a greater concern is that it provides an intrinsically single-reference description of the electronic structure, and this can be especially problematic for modeling catalysis when transition metals are involved. In this perspective, we highlight some noteworthy applications of KS-DFT to heterogeneous computational catalysis, as well as cases where KS-DFT fails accurately to describe electronic structures and intermediate spin states in open-shell transition metal systems. We next provide an introduction to state-of-the-art multiconfigurational (MC; also referred to as multireference (MR)) methods and their advantages and limitations for modeling heterogeneous catalysis. We focus on specific examples to which MC methods have 2 been applied and discuss the challenges associated with these calculations. We conclude by offering our vision for how the community can make further progress in the development of MC methods for application to heterogeneous catalysis.


Originally published as:

Gaggioli, C. A.; Stoneburner, S. J.; Cramer, C. J.; Gagliardi, L. Beyond Density Functional Theory: the Multiconfigurational Approach to Model Heterogeneous Catalysis. ACS Catal., 2019, 9, 8481–8502.