Since the discovery of the first "inorganic benzene" (borazine, B3N3H6), the synthesis of other noncarbon derivatives is an ongoing challenge in Inorganic Chemistry. Here we report on the synthesis of the first pnictogen-silicon congeners of benzene, the triarsa- and the triphospha-trisilabenzene [(PhC(NtBu)2)3Si3E3] (E = P (1a), As (1b)) by a simple metathesis reaction. These compounds are formed by the reaction of [Cp″2Zr(η(1:1)-E4)] (E = P, As; Cp″ = C5H3tBu2) with [PhC(NtBu)2SiCl] in toluene at room temperature along with the silicon pnictogen congeners of the cyclobutadiene, [(PhC(NtBu)2)2Si2E2] (E = P (2a), As (2b)), which is unprecedented for the arsenic system 2b. All compounds were comprehensively characterized, and density functional theory calculations were performed to verify the stability and the aromatic character of the triarsa- and the triphospha-trisilabenzene.

The computational discovery and design of zeolites is a crucial part of the chemical industry. Finding highly accurate while computational feasible protocol for identification of hypothetical siliceous frameworks that could be targeted experimentally is a great challenge. To tackle this challenge, we trained neural network potentials (NNP) with the SchNet architecture on a structurally diverse database of density functional theory (DFT) data. This database was iteratively extended by active learning to cover not only low-energy equilibrium configurations but also high-energy transition states. We demonstrate that the resulting reactive NNPs retain DFT accuracy for thermodynamic stabilities, vibrational properties, as well as reactive and non-reactive phase transformations. As a showcase, we screened an existing zeolite database and revealed >20k additional hypothetical frameworks in the thermodynamically accessible range of zeolite synthesis. Hence, our NNPs are expected to be essential for future high-throughput studies on the structure and reactivity of siliceous zeolites.

Global minimum structures of neutral (Fe2O3)n clusters with n = 1-5 were determined employing the genetic algorithm in combination with ab initio parameterized interatomic potentials and subsequent refinement at the density functional theory level. Systematic investigations of magnetic configurations of the clusters using a broken symmetry approach reveal antiferromagnetic and ferrimagnetic ground states. Whereas (Fe2O3)n clusters with n = 2-5 contain exclusively Fe(3+), Fe2O3 was found to be a special case formally containing both Fe(2+) and Fe(3+). Calculated magnetic coupling constants revealed predominantly strong antiferromagnetic interactions, which exceed bulk values found in hematite. The precise magnetization (spin) state of the clusters has only small influence on their geometric structure. Starting from n = 4 also the relative energies of different cluster isomers are only weakly influenced by their magnetic configuration. These findings are important for simulations of larger (Fe2O3)n clusters and nanoparticles.