Under a 1 kOe dc field, the Er analogues generally show 1-2 orders of magnitude longer relaxation time at each selected temperature and a higher relaxation energy barrier than the Dy analogues. And the RECo compounds (3 and 5) show a more suppressed QTM effect than the corresponding REFe (2 and 4) compounds, which may be ascribed to the elimination of the fluctuation field from the neighbouring [FeIII]LS ions. The ab initio calculations indicate the misplacement between the orientation of the main magnetic axis and the structural axis in the Dy analogues, and the relative consistency in the Er analogues, which should be the source of the Er analogues showing better SIM properties than the Dy analogues.The self-assembly of bis-tridentate ligands leads to the spontaneous formation of [2 × 2] grid-like metal complexes. However, the synthesis of such ligands is rather cumbersome. In the work, we demonstrate a straightforward synthesis route to prepare bis-tridentate 4,6-bis((1H-1,2,3-triazol-4-yl)-pyridin-2-yl)-2-phenylpyrimidine ligands through double CuAAC click chemistry with 4,6-bis(6-ethynylpyridin-2-yl)-2-phenylpyrimidine as well as their self-assembly into [2 × 2] grid-like metal complexes. In addition, four macromolecular ligands were synthesized starting from azido-end-functionalized poly(2-ethyl-2-oxazoline) (PEtOx) or poly(ethylene glycol) (PEG). These macromolecular ligands were used in the construction of star-shaped supramolecular polymers through complexation with transition metal ions (e.g., Fe2+ or Zn2+). The successful fabrication of complexes and star-shaped polymers was confirmed by UV-vis titration measurements and MALDI-TOF mass spectrometry. However, the chemical structure of the polymer was found to have a strong influence on the [2 × 2] grid formation, which was successful with the PEG-ligands but not with the PEtOx-ligands, while the molecular weight of the PEG did not interfere with grid formation.A novel difluoroboron derivative (TPEBF) containing α-cyanostilbene and tetraphenylethylene units has been designed and synthesized. TPEBF emits strong fluorescence both in dilute solutions (ΦFL = 19.3% in THF) and in the solid state (ΦFL = 49.3%), which is significantly distinct from the case of the aggregation-caused quenching (ACQ) and aggregation-induced emission (AIE) chromophores. The dual-state emission properties of the compound overcome the limitation of single-state luminescence and enable it to be used in both solid and solution states. TPEBF with strong emission in solution is utilized for sensing picric acid (PA) with high selectivity and sensitivity in THF (LOD = 497 nM) and aqueous media (LOD = 355 nM).  https://www.selleckchem.com/products/srt2104-gsk2245840.html  The mechanism was described for the synergy of fluorescence resonance energy transfer (FRET) and photoinduced energy transfer (PET) based on the UV-vis absorption and fluorescence spectra, 1H NMR and theoretical calculations results. On the other hand, the highly efficient emission in the solid state allows the compound to be cast on paper to switch external acid/base stimuli.When existing experimental data are combined with machine learning (ML) to predict the performance of new materials, the data acquisition bias determines ML usefulness and the prediction accuracy. In this context, the following two conditions are highly common (i) constructing new unbiased data sets is too expensive and the global knowledge effectively does not change by performing a limited number of novel measurements; (ii) the performance of the material depends on a limited number of physical parameters, much smaller than the range of variables that can be changed, albeit such parameters are unknown or not measurable. To determine the usefulness of ML under these conditions, we introduce the concept of simulated research landscapes, which describe how datasets of arbitrary complexity evolve over time. Simulated research landscapes allow us to use different discovery strategies to compare standard materials exploration with ML-guided explorations, i.e. we can measure quantitatively the benefit of using a specific ML model. We show that there is a window of opportunity to obtain a significant benefit from ML-guided strategies. The adoption of ML can take place too soon (not enough information to find patterns) or too late (dense datasets only allow for negligible ML benefit), and the adoption of ML can even slow down the discovery process in some cases. We offer a qualitative guide on when ML can accelerate the discovery of new best-performing materials in a field under specific conditions. The answer in each case depends on factors like data dimensionality, corrugation and data collection strategy. We consider how these factors may affect the ML prediction capabilities and discuss some general trends.A straightforward 2,2,2-trifluoroethylation of acrylamides by Pd-catalyzed C-H bond activation was reported by using a fluorinated hypervalent iodine reagent as a coupling partner. At room temperature, this additive-free approach allowed the synthesis of Z-2,2,2-trifluoroethylated acrylamides (19 examples, up to 73% yield) in a stereoselective manner. Under these mild reaction conditions, the methodology turned out to be functional group tolerant and mechanistic studies gave us a better understanding of the transformation.The reactivity of cationic (C^C)gold(iii) carbonyl complexes was investigated. While the in situ-formed IPrAu(bph)CO+ complex (bph = biphenyl-2,2'-diyl) does not undergo a migratory insertion of CO into the neighboring gold-carbon bond, nucleophiles can attack the coordinated CO moiety intermolecularly. Water as a nucleophile initiates a CO2 extrusion combined with a reductive C,H bond formation. The rapid formation of a gold(i) species from an intermediary gold(iii) carbonyl has not been observed before and shows a significant difference in reactivity between (C^C) and (C^N^C)gold(iii) carbonyls. The latter have been reported to form stable gold(iii) hydrides via the WGS reaction. In the case of methanol acting as a nucleophile attacking the gold(iii) carbonyl, no extrusion of CO2 is observed. Instead an intermediary gold(iii) carboxyl complex forms an aryl carboxylate via reductive C-C bond elimination. Experimental and theoretical studies on the mechanism explain the observed selectivities and give new insights into the reactivity of elusive gold(iii) carbonyls.