Harmonic maps with torsion

In this article we introduce a natural extension of the well-studied equation for harmonic maps between Riemannian manifolds by assuming that the target manifold is equipped with a connection that is metric but has non-vanishing torsion. Such connections have already been classified in the work of Cartan(1924).The maps under consideration do not arise as critical points of an energy functional leading to interesting mathematical challenges. We will perform a first mathematical analysis of these maps which we will call harmonic maps with torsion.     

The powder X-band electron paramagnetic resonance spectroscopy of septet pyridyl-2,4,6-trinitrene

The first X-band EPR spectrum containing only non-overlapping signals of septet pyridyl-2,4,6-trinitrene and triplet pyridylnitrenes is reported. This spectrum was recorded after photolysis of 2,4,6-triazidopyridine in solid argon at 5 K. The zero-field splitting (ZFS) parameters of this trinitrene as well as of intermediate triplet mononitrenes and quintet dinitrenes formed at early stages of the photolysis were determined using the combination of modern computer line-shape spectral simulations and density functional theory (DFT) calculations. It was found that septet pyridyl-2,4,6-trinitrene has the record negative parameter D_S = −0.1031 cm⁻¹ among all known to date septet pyridyl-2,4,6-trinitrenes and may be of interest as a model multi-qubit spin system for investigations of quantum computation processing.     

Electronic Transitions in Different Redox States of Trinuclear 5,6,11,12,17,18-Hexaazatrinaphthylene-Bridged Titanium Complexes: Spectroelectrochemistry and Quantum Chemistry

Multinuclear transition metal complexes bridged by ligands with extended π-electronic systems show a variety of complex electronic transitions and electron transfer reactions. While a systematic understanding of the photochemistry and electrochemistry has been attained for binuclear complexes, much less is known about trinuclear complexes such as hexaphenyl-5,6,11,12,17,18-hexaazatrinaphthylene-tristitanocene [(Cp₂Ti)₃HATN(Ph)₆]. The voltammogram of [(Cp₂Ti)₃HATN(Ph)₆] shows six oxidation and three reduction waves. Solution spectra of [(Cp₂Ti)₃HATN(Ph)₆] and of the electrochemically formed oxidation products show electronic transitions in the UV, visible and the NIR ranges. Density functional theory (DFT) and linear response time-dependent DFT show that the three formally titanium(II) centers transfer an electron to the HATN ligand in the ground state. The optically excited transitions occur exclusively between ligand-centered orbitals. The charged titanium centers only provide an electrostatic frame to the extended π-electronic system. Complete active self-consistent field (CASSCF) calculation on a structurally simplified model compound, which considers the multi-reference character imposed by the three titanium centers, can provide an interpretation of the experimentally observed temperature-dependent magnetic behavior of the different redox states of the title compound in full consistency with the interpretation of the electronic spectra.     

Hierarchically Structured Allotropes of Phosphorus from Data-Driven Exploration

The discovery of materials is increasingly guided by quantum-mechanical crystal-structure prediction, but the structural complexity in bulk and nanoscale materials remains a bottleneck. Here we demonstrate how data-driven approaches can vastly accelerate the search for complex structures, combining a machine-learning (ML) model for the potential-energy surface with efficient, fragment-based searching. We use the characteristic building units observed in Hittorf's and fibrous phosphorus to seed stochastic (“random”) structure searches over hundreds of thousands of runs. Our study identifies a family of hierarchically structured allotropes based on a P8 cage as principal building unit, including one-dimensional (1D) single and double helix structures, nanowires, and two-dimensional (2D) phosphorene allotropes with square-lattice and kagome topologies. These findings yield new insight into the intriguingly diverse structural chemistry of phosphorus, and they provide an example for how ML methods may, in the long run, be expected to accelerate the discovery of hierarchical nanostructures.