Development of functional inorganic and transition metal compounds is usually based on ad hoc qualified guesses, with computational methods playing a lesser role than in drug discovery. A de novo evolutionary algorithm (EA) is presented that automatically generates transition metal complexes using a search space constrained around chemically meaningful structures assembled from three kinds of fragments: a part shared by all structures and typically containing the metal center itself, one or several parts consisting of ligand skeletons, and unconstrained parts that may grow and vary freely. In EA optimizations, using a cost-efficient fitness function based on a linear quantitative structure-activity relationship model for catalytic activity, we demonstrate the capabilities of the method by retracing the transition from the first-generation, phosphine-based Grubbs olefin metathesis catalysts to second-generation catalysts containing N-heterocyclic carbene ligands instead of phosphines. Moreover, DFT calculations on selected high-fitness, last-generation structures from these evolutionary experiments suggest that, in terms of catalytic activity, the structures arrived at by virtual evolution alone compare favorably with existing, highly active catalysts. The structures from the evolution experiments are, however, complex and probably difficult to synthesize, but a set of manually simplified variations thereof might form the leads for a new generation of Grubbs catalysts.

By using cost-efficient density functional theory accounting for dispersion in combination with an implicit solvent model, for the first time it has been possible to reproduce activation Gibbs free energies for phosphane dissociation from the Grubbs ruthenium olefin metathesis precatalysts in solution with good accuracy (mean unsigned error compared to experiment Ͻ2.5 kcal mol -1 ). The barrier is calculated to be in the range 17.8-25.7 kcal mol -1 for a set of nine catalysts, and is found to be located at intermediate Ru-P distances (ca. 4 Å). The agreement with the experimental activation parameters is gratifying and suggests that the calculations may give insight into these reactions and, in particular, offer reso-

Several denitions of an atom in a molecule (AIM) in three dimensional space, including both fuzzy and disjoint domains, are employed to calculate electron sharing indices (ESI) and related electronic aromaticity measures, namely Iring and multicenter indices (MCI), for a wide set of cyclic planar aromatic and non-aromatic molecules of dierent ring size. The results obtained using the recent iterative Hirshfeld scheme are compared to those derived from the classical Hirshfeld method and from Bader's quantum theory of atoms in molecules. For bonded atoms all methods yield ESI values in very good agreement, especially for C-C interactions. In the case of non-bonded interactions there are relevant deviations, particularly between fuzzy and QTAIM schemes. These discrepancies directly translate into signicant dierences in the values and the trends of the aromaticity indices. In particular, the chemically expected trends are more consistently found when using disjoint domains. Careful examination of the underlying eects reveals the dierent reasons why the aromaticity indices investigated give the expected results for binary divisions of three dimensional space.

With the increase in applications of machine learning methods in drug design and related fields, the challenge of designing sound test sets becomes more and more prominent. The goal of this challenge is to have a realistic split of chemical structures (compounds) between training, validation and test set such that the performance on the test set is meaningful to infer the performance in a prospective application. This challenge is by its own very interesting and relevant, but is even more complex in a federated machine learning approach where multiple partners jointly train a model under privacy-preserving conditions where chemical structures must not be shared between the different participating parties. In this work we discuss three methods which provide a splitting of a data set and are applicable in a federated privacy-preserving setting, namely: a. locality-sensitive hashing (LSH), b. sphere exclusion clustering, c. scaffold-based binning (scaffold network). For evaluation of these splitting methods we consider the following quality criteria (compared to random splitting): bias in prediction performance, classification label and data imbalance, similarity distance between the test and training set compounds. The main findings of the paper are a. both sphere exclusion clustering and scaffold-based binning result in high quality splitting of the data sets, b. in terms of compute costs sphere exclusion clustering is very expensive in the case of federated privacy-preserving setting.

An unconventional chain termination reaction has been explored for the SHOP (Shell higher olefin process)-type, anilinotropone, and salicylaldiminato nickel-based oligo- and polymerization catalysts by using density functional theory (DFT). Starting from the tetracoordinate alkyl phosphine complex, the termination reaction was found to involve a rearrangement of the alkyl chain to form a pentacoordinate β-agostic complex, β-hydride elimination, and olefinic chain dissociation and to compete with propagation at sufficiently high phosphine concentration and/or basicity. It provides the first complete and convincing mechanistic rationale for the decreasing chain lengths observed upon increasing phosphine concentration and basicity. The unconventional reaction was found to be a major termination pathway for the SHOP-type catalyst and is very unlikely to lead to branching and olefin isomerization, which is critical for explaining why the SHOP catalyst, in contrast to the anilinotropone and salicylaldiminato catalysts, tends to lead to the oligomerization of ethylene to form linear α-olefins. Based on our results we have proposed a new and extended catalytic cycle for the SHOP-type ethylene oligomerization catalyst. Finally, the importance of the new termination reaction for the SHOP-type catalyst suggests that this reaction may also operate with other ethylene oligomerization nickel catalysts. This prediction was confirmed for a pyrazolonatophosphine catalyst, for which the new termination route was found to be even more facile, which explains the short oligomers produced by this catalyst.