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2-Aminobenzothiazoles comprise a valuable structural motif, which prevails in versatile natural products and biologically active compounds. Herein, a switchable and scalable C-N coupling protocol was developed for the synthesis of these compounds from 2-chlorobenzothiazoles and primary amines. Gratifyingly, this protocol was achieved under transition-metal-free and solvent-free conditions. Moreover, introducing an appropriate amount of NaH completely switched the selectivity from mono- toward di-heteroarylation, and further investigations provided a rationale for this new finding. Furthermore, gram-scale synthesis of representative products 3a and 4a was realized by applying operationally simple and glovebox-free procedures, which revealed the practical usefulness of this work. Finally, evaluation of the quantitative green metrics provided evidence that our protocol was superior over the literature ones in terms of green chemistry and sustainability.We investigated the phase separation of dioleoylphosphatidylserine (DOPS) and dipalmitoylphosphatidylcholine (DPPC) in giant unilamellar vesicles in a hypotonic solution using fluorescence and confocal laser scanning microscopy. Although phase separation in charged lipid membranes is generally suppressed by the electrostatic repulsion between the charged headgroups, osmotic stress can promote the formation of charged lipid domains. Interestingly, we observed a three-phase coexistence even in the DOPS/DPPC binary lipid mixtures. The three phases were DPPC-rich, dissociated DOPS-rich, and nondissociated DOPS-rich phases. The two forms of DOPS were found to coexist owing to the ionization of the DOPS headgroup, such that the system could be regarded as quasi-ternary. The three formed phases with differently ionized DOPS domains were successfully identified experimentally by monitoring the adsorption of positively charged particles. In addition, coarse-grained molecular dynamics simulations confirmed the stability of the three-phase coexistence. Attraction mediated by hydrogen bonding between protonated DOPS molecules and reduction of the electrostatic interactions at the domain boundaries stabilized the three-phase coexistence.Surface adsorption is a crucial step in numerous processes, including heterogeneous catalysis, where the adsorption of key species is often used as a descriptor of efficiency. We present here an automated adsorption workflow for semiconductors which employs density functional theory calculations to generate adsorption data in a high-throughput manner. Starting from a bulk structure, the workflow performs an exhaustive surface search, followed by an adsorption structure construction step, which generates a minimal energy landscape to determine the optimal adsorbate-surface distance. An extensive set of energy-based, charge-based, geometric, and electronic descriptors tailored toward catalysis research are computed and saved to a personal user database. The application of the workflow to zinc telluride, a promising CO2 reduction photocatalyst, is presented as a case study to illustrate the capabilities of this method and its potential as a material discovery tool.Dynamic range quantifies the linear operation regime available in nanomechanical resonators. Nonlinearities dominate the response of flexural beams in the limit of very high aspect ratio and very small diameter, which leads to expectation of low dynamic range for nanowire resonators in general. However, the highest achievable dynamic range for nanowire resonators with practical dimensions remains to be determined. We report dynamic range measurements on singly clamped silicon nanowire resonators reaching remarkably high values of up to 90 dB obtained with a simple harmonic actuation scheme. We explain these measurements by a comprehensive theoretical examination of dynamic range in singly clamped flexural beams including the effect of tapering, a usual feature of semiconductor nanowires. Our analysis reveals the nanowire characteristics required for broad linear operation, and given the relationship between dynamic range and mass sensing performance, it also enables analytical determination of mass detection limits, reaching atomic-scale resolution for feasible nanowires.Three unusual austins-type meroterpenoids penicianstinoids C-E (1-3) were obtained from the mangrove-derived fungus Penicillium sp. TGM112. Cytoskeletal Signaling inhibitor The structures of 1-3 including absolute configurations were determined by detailed NMR, MS spectroscopic data, X-ray diffraction analysis, and calculated electronic circular dichroism data. Penicianstinoid C (1) was the first austins-type meroterpenoid with a unique 6/6/6/5 rearranged tetracyclic skeleton possessing two unusual spirocyclic moieties (2-oxaspiro[5.5]undeca-4,7-dien-3-one and 6-methylene-2-oxaspiro[4.5]decane-1,4-dione). Penicianstinoid D (2) was an unusual austins-type meroterpenoid with a 6/6/6/6 tetracyclic skeleton containing an octahydro-2H-chromen-2-one unit. Penicianstinoid E (3) possessed a 6/5/6/6/6/5 fused hexacyclic skeleton with an uncommon five-membered ether ring system. The plausible biosynthetic pathway of 1-3 is also proposed. Compounds 1 and 3 inhibited the growth of newly hatched Helicoverpa armigera Hubner larvae with IC50 values of 100 and 200 μg/mL, respectively.An essential aspect for adequate predictions of chemical properties by machine learning models is the database used for training them. However, studies that analyze how the content and structure of the databases used for training impact the prediction quality are scarce. In this work, we analyze and quantify the relationships learned by a machine learning model (Neural Network) trained on five different reference databases (QM9, PC9, ANI-1E, ANI-1, and ANI-1x) to predict tautomerization energies from molecules in Tautobase. For this, characteristics such as the number of heavy atoms in a molecule, number of atoms of a given element, bond composition, or initial geometry on the quality of the predictions are considered. The results indicate that training on a chemically diverse database is crucial for obtaining good results and also that conformational sampling can partly compensate for limited coverage of chemical diversity. The overall best-performing reference database (ANI-1x) performs on average by 1 kcal/mol better than PC9, which, however, contains about 2 orders of magnitude fewer reference structures.
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