77 research outputs found
Post-Modification of the Electronic Properties by Addition of Ï-Stacking Additives in N-Heterocyclic Carbene Complexes with Extended Polyaromatic Systems
A series of iridium complexes containing phenanthro[4,5-abc]phenazino[11,12-d]imidazol-2-ylidene and acetonaphtho[1,2-b]quinoxaline[11,12-d]imidazol-2-ylidene ligands have been obtained and fully characterized. These complexes display highly extended polyaromatic systems attached to the backbone of the N-heterocyclic carbene. The presence of this extended polyaromatic system makes the electron-donating character of these ligands sensitive to the presence of Ï-stacking additives, such as pyrene and hexafluorobenzene. The computational studies predict that the addition of pyrene affords an increase of the electron-donating character of the polyaromatic ligand (TEP decreases), while the addition of hexafluorobenzene has the opposite effect (TEP increases). This prediction is experimentally corroborated by IR spectroscopy, by measuring the shift of the CO stretching bands of a series of IrCl(NHC)(CO)2 complexes, where NHC is the N-heterocyclic carbene ligand with the polyaromatic system. Finally, the energy of the Ï-stacking interaction of one of the key Ir(I) complexes with pyrene and hexafluorobenzene has been estimated by using the Benesi-Hildebrand treat-ment, based on the ÎŽ-shifts observed by 1H NMR spectroscopy.MEC of Spain (CTQ2011-24055/BQU
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4
While the increasing availability of global databases on ecological communities has advanced our knowledge
of biodiversity sensitivity to environmental changes,5â7 vast areas of the tropics remain understudied.8â11 In
the American tropics, Amazonia stands out as the worldâs most diverse rainforest and the primary source of
Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13â15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazonâs biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus
crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced
environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian
Amazonia, while identifying the regionâs vulnerability to environmental change. 15%â18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by
2050. This means that unless we take immediate action, we will not be able to establish their current status,
much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio
- âŠ