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Synthesis, self-organization, and optical properties of supermolecular tripedal liquid crystals incorporating various prototypical mesogenic units such as alkoxy-azobenzene (AZB), alkoxy-biphenylene (BPH) or alkoxy-cyanobiphenyl (OCB) derivatives are reported. Different molecular systems were designed in order to sequentially incorporate the smectogenic-like alkoxy-azobenzene-based chromophore within the molecular structure, whose relative proportion is selectively varied by exchanging with the other mesogens. A divergent synthetic mode was elaborated for their synthesis, starting from the regioselective functionalization of the phloroglucinol-based (PG) inner core. This methodology allowed the preparation of several sets of unconventional tripedal oligomers with conjugated heterolithic structures (made of different blocks, e.g. PG(6)AZB(x)BPH(3-x) and PG(6)AZB(x)OCB(3-x), x = 1 or 2) along the homolithic parents (all identical blocks, e.g. PG(z)AZB(3), z = 6 or 11, z is the number of methylene in the spacer between PG and the protomesogen, PG(6)BPH(3), and PG(6)OCB(3)), respectively. Essentially all the synthesized systems behave as thermotropic liquid crystals and show various types of highly segregated multilayered smectic phases, or, in one case, a nematic phase, depending on the nature of the constitutive anisotropic blocks and on the molecular topology (homolithic versus heterolithic, mesogenic ratio x : 3 - x). The effects of these structural modifications on the mesomorphism (mesophase structures, temperature ranges, and thermodynamic stability) have been investigated by differential scanning calorimetry and small-angle X-ray diffraction experiments combined with dilatometric measurements. Models describing the various supramolecular organizations of these tripedes into such multilayered structures are proposed and discussed. Preliminary results of the investigations of their optical properties will also be presented.
Genomic prediction has revolutionized crop breeding despite remaining issues of transferability of models to unseen environmental conditions and environments. Usage of endophenotypes rather than genomic markers leads to the possibility of building phenomic prediction models that can account, in part, for this challenge. Here, we compare and contrast genomic prediction and phenomic prediction models for 3 growth-related traits, namely, leaf count, tree height, and trunk diameter, from 2 coffee 3-way hybrid populations exposed to a series of treatment-inducing environmental conditions. The models are based on 7 different statistical methods built with genomic markers and ChlF data used as predictors. This comparative analysis demonstrates that the best-performing phenomic prediction models show higher predictability than the best genomic prediction models for the considered traits and environments in the vast majority of comparisons within 3-way hybrid populations. In addition, we show that phenomic prediction models are transferrable between conditions but to a lower extent between populations and we conclude that chlorophyll a fluorescence data can serve as alternative predictors in statistical models of coffee hybrid performance. Future directions will explore their combination with other endophenotypes to further improve the prediction of growth-related traits for crops.