Developing more efficient catalysts remains one of the primary targets of organometallic chemists. To accelerate reaching this goal, effective molecular descriptors and visualization tools can represent a remarkable aid. Here, we present a Web application for analyzing the catalytic pocket of metal complexes using topographic steric maps as a general and unbiased descriptor that is suitable for every class of catalysts. To show the broad applicability of our approach, we first compared the steric map of a series of transition metal complexes presenting popular mono-, di-, and tetracoordinated ligands and three classic zirconocenes. This comparative analysis highlighted similarities and differences between totally unrelated ligands. Then, we focused on a recently developed Fe(II) catalyst that is active in the asymmetric transfer hydrogenation of ketones and imines. Finally, we expand the scope of these tools to rationalize the inversion of enantioselectivity in enzymatic catalysis, achieved by point mutation of three amino acids of mononuclear p-hydroxymandelate synthase.

In this communication, an improved perturbative triples correction (T) algorithm for domain based local pair-natural orbital singles and doubles coupled cluster (DLPNO-CCSD) theory is reported. In our previous implementation, the semi-canonical approximation was used and linear scaling was achieved for both the DLPNO-CCSD and (T) parts of the calculation. In this work, we refer to this previous method as DLPNO-CCSD(T₀) to emphasize the semi-canonical approximation. It is well-established that the DLPNO-CCSD method can predict very accurate absolute and relative energies with respect to the parent canonical CCSD method. However, the (T₀) approximation may introduce significant errors in absolute energies as the triples correction grows up in magnitude. In the majority of cases, the relative energies from (T₀) are as accurate as the canonical (T) results of themselves. Unfortunately, in rare cases and in particular for small gap systems, the (T₀) approximation breaks down and relative energies show large deviations from the parent canonical CCSD(T) results. To address this problem, an iterative (T) algorithm based on the previous DLPNO-CCSD(T₀) algorithm has been implemented [abbreviated here as DLPNO-CCSD(T)]. Using triples natural orbitals to represent the virtual spaces for triples amplitudes, storage bottlenecks are avoided. Various carefully designed approximations ease the computational burden such that overall, the increase in the DLPNO-(T) calculation time over DLPNO-(T₀) only amounts to a factor of about two (depending on the basis set). Benchmark calculations for the GMTKN30 database show that compared to DLPNO-CCSD(T₀), the errors in absolute energies are greatly reduced and relative energies are moderately improved. The particularly problematic case of cumulene chains of increasing lengths is also successfully addressed by DLPNO-CCSD(T).