Nature Communications - DFT calculations and theory do not support enantiospecificity in NMR J-coupling constants

We report the synthesis, crystal structure, and spectroscopic and computational electronic-structural characterization of two copper corroles, [Cu(5,15-bis(4-methylcarboxyphenyl)-10-(2-methylcarboxyphenyl)corrole)] (1Cu) and [Cu(5,15-bis(4-nitrophenyl)-10-(2-methylcarboxyphenyl)corrole)] (2Cu), as well as spectroscopic and computational studies on the corrole ligands (H3L1 and H3L2) in their neutral and anionic forms. We have found that the anionic corroles containing the 4-nitrophenyl substituents in positions 5 and 15 of the corrole ring show hypercorrole behavior, where the Q-bands are considerably more intense and red-shifted compared to those in the 4-methylcarboxyphenyl-substituted corroles. Electronic structure calculations using wave function methods (CASSCF/NEVPT2) reveal that the intense Q-bands, which extend slightly into the NIR region, are charge-transfer bands from the anionic corrole core to the strongly electron-withdrawing 4-nitrophenyl substituents. We further show that 2Cu can be reduced indirectly in the presence of excess F– or OH–, and the Q-band shifts toward the red in the polar environment containing the corresponding salts. Our study provides examples of easy-to-prepare anionic corroles, metalated and unmetalated, that show hypercorrole behavior and NIR absorption, and thus could find use in hyperthermal processes.

The Gaussian Electrostatic Model (GEM) is a density-based force field that employs Hermite Gaussian auxiliary basis sets (ABSs) to represent molecular electroni

Understanding and designing active sites in single-atom catalysts (SACs) requires going beyond static models to capture their dynamic evolution under realistic electrochemical conditions. Here, we dev...

Reaction mechanism search tools have demonstrated the ability to provide insights into likely products and rate-limiting steps of reacting systems. However, reactions involving several concerted bond changes─as can be found in many key steps of natural product syntheses─can complicate the search process. To mitigate these complications, we present a mechanism search strategy particularly suited to help expedite exploration of an exemplary family of such complex reactions, cyclizations. We provide a cost-effective strategy for identifying relevant elementary reaction steps by combining graph-based enumeration schemes and machine learning techniques for intermediate filtering. Key to this approach is our use of a neural network potential (NNP), AIMNet2-rxn, for computational evaluation of each candidate reaction pathway. In this article, we evaluate the NNP’s ability to estimate activation energies, demonstrate the correct anticipation of stereoselectivity, and recapitulate complex enabling steps in natural product synthesis.

Nature Chemistry - Alkaline-earth phenoxides show promise as optical cycling centres; however, their properties when connected to larger structures is unclear. Now it has been shown that their...

A protein historian and evolutionary biochemist found that a protein sequence present across all known life didn’t form as researchers previously thought it did.