The level of detail attained in the computational description of reaction mechanisms can be vastly improved through tools for automated chemical space exploration, particularly for systems of small to medium size. Under this approach, the unimolecular decomposition landscape for indole was explored through the automated reaction mechanism discovery program AutoMeKin. Nevertheless, the sheer complexity of the obtained mechanisms might be a hindrance regarding their chemical interpretation. In this spirit, the new Python library amk-tools has been designed to read and manipulate complex reaction networks, greatly simplifying their overall analysis. The package provides interactive dashboards featuring visualizations of the network, the three-dimensional (3D) molecular structures and vibrational normal modes of all chemical species, and the corresponding energy profiles for selected pathways. The combination of the joined mechanism generation and postprocessing workflow with the rich chemistry of indole decomposition enabled us to find new details of the reaction (obtained at the CCSD­(T)/aug-cc-pVTZ//M06-2X/MG3S level of theory) that were not reported before: (i) 16 pathways leading to the formation of HCN and NH3 (via amino radical); (ii) a barrierless reaction between methylene radical and phenyl isocyanide, which might be an operative mechanism under the conditions of the interstellar medium; and (iii) reaction channels leading to both hydrogen cyanide and hydrogen isocyanide, of potential astrochemical interest as the computed HNC/HCN ratios greatly exceed the calculated equilibrium value at very low temperatures. The reported reaction networks can be very valuable to supplement databases of kinetic data, which is of remarkable interest for pyrolysis and astrochemical studies.

The computational study of catalytic processes allows discovering really intricate and detailed reaction mechanisms that involve many species and transformations. This increasing level of detail can even result detrimental when drawing conclusions from the computed mechanism, as many coexisting reaction pathways can be in close competence. Here, we present a reaction network-based implementation of the energy span model in the form of a computational code, gTOFfee, capable of dealing with any user-specified reaction network. This approach, compared to microkinetic simulations, enables a much easier, simpler, and straightforward analysis of the performance of any catalytic reaction network. In this communication, we will go through the foundations and applicability of the underlying model and will tackle the application to two relevant catalytic systems: homogeneous Co-mediated propene hydroformylation and heterogeneous CO2 hydrogenation over Cu(111).

Valorization of carbon dioxide into organic molecules using catalytic approaches has witnessed an upsurge in recent years. Here, the influence of an Al(III) aminotriphenolate complex on the regio-and stereochemical features of the coupling between carbon dioxide and a cyclic epoxy alcohol has been studied. Three distinct bicyclic carbonate products were produced from a single starting material, depending on the catalytic conditions. The proposed carbonate configurations were examined by solution and solid-phase techniques, including NMR spectroscopic and X-ray crystallographic analyses. Control experiments combined with DFT calculations provide a rationale for the distinct catalytic manifolds observed in the presence and absence of the Al(III) complex.

Heterometallic lanthanide [LnLn’] coordination complexes accessible thermodynamically are very scarce because the metals of this series have very similar chemical behaviour. Trinuclear systems of this category are virtually non-existent. A...