Efficient Gate-tunable light-emitting device made of defective boron nitride nanotubes: from ultraviolet to the visible

Boron nitride is a promising material for nanotechnology applications due to its two-dimensional graphene-like, insulating, and highly-resistant structure. Recently it has received a lot of attention as a substrate to grow and isolate graphene as well as for its intrinsic UV lasing response. Similar to carbon, one-dimensional boron nitride nanotubes (BNNTs) have been theoretically predicted and later synthesised. Here we use first principles simulations to unambiguously demonstrate that i) BN nanotubes inherit the highly efficient UV luminescence of hexagonal BN; ii) the application of an external perpendicular field closes the electronic gap keeping the UV lasing with lower yield; iii) defects in BNNTS are responsible for tunable light emission from the UV to the visible controlled by a transverse electric field (TEF). Our present findings pave the road towards optoelectronic applications of BN-nanotube-based devices that are simple to implement because they do not require any special doping or complex growth

Multiple table factor analysis applied to the higher education competences

Due to the recent implantation of the Bologna process, the definition of competences in Higher Education is an important matter that deserves special attention and requires a detailed analysis. For that reason, we study the importance given to severa! competences for the professional activity and the degree to which these competences have been achieved through the received education. The answers include also competences observed in two periods of time given by individuals of multiple characteristics. In this context and in order to obtain synthesized results, we propose the use of Multiple Table Factor Analysis. Through this analysis, individuals are described by severa! groups, showing the most important variability factors of the individuals and allowing the analysis of the common structure ofthe different data tables. The obtained results will allow us finding out the existence or absence of a common structure in the answers of the various data tables, knowing which competences have similar answer structure in the groups of variables, as well as characterizing those answers through the individuals.