Induction of the Columnar Phase of Unconventional Dendrimers by Breaking the C2 Symmetry of Molecules

[[abstract]]Two triazine-based unconventional dendrimers were prepared and characterized by 1H and 13C NMR spectroscopy, mass spectrometry, and elemental analysis. Differential scanning calorimetry, polarizing microscopy, and powder XRD studies showed that these dendrimers display columnar liquid-crystalline phases during thermal treatment. This is ascribable to breaking of their C2 symmetry. The molecular conformations of prepared dendrimers were obtained by computer simulation with the MM3 model of the CaChe program in the gas phase. The simulation showed that the conformations of the prepared dendrimers are rather flat and disfavor formation of the LC phase. However, due to C2-symmetry breaking, the prepared dendrimers have structural isomers in the solid state and thus show the desired columnar phases. This new strategy should be applicable to other types of unconventional dendrimers with rigid frameworks.[[journaltype]]國外[[incitationindex]]SCI[[ispeerreviewed]]Y[[booktype]]電子版[[booktype]]紙本[[countrycodes]]DE

A Metal-free Multicomponent Strategy for Amidine Synthesis

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Reactive intermediates are key to halting and promoting chemical transformations, however due to their elusive nature, they are seldom harnessed for reaction design. Herein, we describe studies aimed at stabilizing reactive intermediates in the N-heterocyclic carbene (NHC) catalytic cycle, which enabled fully shutting down the known benzoin coupling pathway, while rerouting its intermediates toward deuteration. The reversible nature of NHC catalysis and the selective stabilization of reaction intermediates facilitated clean hydrogen-deuterium exchange reactions of aromatic aldehydes by D2O, even for challenging electron withdrawing substrates. The addition of catalytic amounts of phenyl boronic acid was used to further stabilize highly reactive intermediates and mitigate the formation of benzoin coupling by-products. The mechanistic understanding at the foundation of this work resulted in unprecedented mild conditions with base and catalyst loadings as low as 0.1 mol%, and a scalable deuteration reaction applicable to a broad substrate scope with outstanding functional group tolerance. More importantly, adopting this approach enabled the construction of a machine-learning derived guideline for identifying the appropriate catalyst and conditions for different substrates based on a logistic regression classification model. Experimental studies combined with machine learning and computational methods shed light on the non-trivial mechanistic underpinnings of this reaction