Using density functional theory calculations, ultrathin films of SrVO3(d1) and SrCrO3(d2) on SrTiO3 substrates have been studied as possible multiferroics. Although both are metallic in the bulk limit, they are found to be insulating as a result of o
rbital ordering driven by lattice distortions at the ultrathin limit. While the distortions in SrVO3 have a first-order Jahn-Teller origin, those in SrCrO3 are ferroelectric in nature. This route to ferroelectricity (FE) results in polarizations comparable with conventional ferroelectrics.
The microscopic origin of the high Neel temperature (T_N) observed experimentally in SrTcO_3 has been examined using a combination of ab-initio electronic structure calculations and mean-field solutions of a multiband Hubbard model. The G-type antife
rromagnetic state is found to be robust for a large region of parameter space, with large stabilization energies found, surprisingly, for small values of intraatomic exchange interaction strength as well as large bandwidths. The microscopic origin of this is traced to specific aspects associated with the d3 configuration at the transition-metal site. Considering values of interaction strengths appropriate for SrTcO3 and the corresponding 3d oxide SrMnO_3, we find a ratio of 4:1 for the TN as well as magnitudes consistent with experiment.
Network motifs are small building blocks of complex networks. Statistically significant motifs often perform network-specific functions. However, the precise nature of the connection between motifs and the global structure and function of networks re
mains elusive. Here we show that the global structure of some real networks is statistically determined by the probability of connections within motifs of size at most 3, once this probability accounts for node degrees. The connectivity profiles of node triples in these networks capture all their local and global properties. This finding impacts methods relying on motif statistical significance, and enriches our understanding of the elementary forces that shape the structure of complex networks.
