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Creators/Authors contains: "Vogiatzis, Konstantinos D."

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  1. Free, publicly-accessible full text available March 21, 2025
  2. This primer helps the reader understand the basic categories of molecular representations and provides computational tools to generate molecular descriptors in each of these categories. After reading this primer, you will be able to use various methods to generate machine and/or human interpretable representations of molecular systems for inputs to machine learning models or for general chemical data science applications. 
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  3. We have explored the ligand topology of high-valent Fe(iv)–oxo complexes for screening a large molecular database with machine learning.

     
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  4. Abstract

    We have performed a series of highly accurate calculations between CO2and the 20 naturally occurring amino acids for the investigation of the attractive noncovalent interactions. Different nucleophilic groups present in the amino acid structures were considered (α‐NH2, COOH, side groups), and the stronger binding sites were identified. A database of accurate reference interactions energies was compiled as computed by explicitly‐correlated coupled‐cluster singles‐and‐doubles, together with perturbative triples extrapolated to the complete‐basis‐set limit. The CCSD(F12)(T)/CBS reference values were used for comparing a variety of popular density functionals with different basis sets. Our results show that most density functionals with the triple‐zeta basis set def2‐TZVPP align with the CCSD(F12)(T)/CBS reference values, but errors range from 0.1 kcal/mol up to 1.0 kcal/mol.

     
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  5. null (Ed.)
  6. Abstract

    Activation of the dinitrogen triple bond is a crucial step in the overall fixation of atmospheric nitrogen into usable forms for industrial and biological applications. Current synthetic catalysts incorporate metal ions to facilitate the activation and cleavage of dinitrogen. The high price of metal‐based catalysts and the challenge of catalyst recovery during industrial catalytic processes has led to increasing interest in metal‐free catalysts. One step toward metal‐free catalysis is the use of frustrated Lewis pairs (FLPs). In this study, we have examined 18 functionalized carbenes as FLPs to elucidate the influence of steric and electronic effects on the activation of dinitrogen. To test the effects of functionalization on dinitrogen activation, we have performed density functional theory (DFT), multireference, non and extended transition state‐natural orbital for chemical valence (ETS‐NOCV) calculations. Our results suggest that functional groups which introduce strong electron‐withdrawing effects and/or engage in extended π/π* systems lead to the lowering of the dissociation energy of the dinitrogen bond, which further contributes to greater nitrogen activation. We conjecture that these effects are due to enhanced back‐bonding capability of the p orbital of the carbene carbon atoms to the adjacent nitrogen atoms (increasing Lewis basicity of the carbene carbon atom) and enhanced stability of dissociated products. Our concluding remarks include opportunities to extend this activation study to explore the entire catalytic cycle with promising functionalized carbenes for experimental evaluation.

     
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