A palladium-catalyzed alkylation/direct arylation synthesis of nitrogen-containing heterocycles

A norbornene-mediated palladium-catalyzed sequence is described in which an alkyl-aryl bond and an aryl-heteroaryl bond are formed in one reaction vessel. The aryl-heteroaryl bond-forming step occurs via a direct arylation reaction. A number of six-, seven-, and eight-membered ring-annulated indoles, pyrroles, pyrazoles, and azaindoles were synthesized from the corresponding bromoalkyl azole and an aryl iodide.     

In-silico exploration of noble gas dimer enforced by noncovalent interaction

Density functional calculations have been carried out to investigate the possibility of trapping of noble gas dimers by cyclo[18]carbon dimer. Parallel-displaced conformation of the cyclo[18]carbon dimer is found to be the minimum energy structure. Noncovalent interaction is found to hold the noble gas dimers. The lighter noble gases (He, Ne) posses weaker attractive interactions while the heavier one (Ar, Kr) are held by stronger attractive interactions forming genuine bonds. Each of the noble gas atoms in turn forms noncovalent interaction with the cyclo[18]carbon monomers. The bond dissociation energy of the noble gas dimers dramatically increases inside the cyclo[18]carbon dimer. Energy decomposition analysis reveals that dispersion plays the major role toward the stabilization energy.     

Direct, one-step synthesis of condensed heterocycles: a palladium-catalyzed coupling approach

[reaction: see text] A palladium-catalyzed one-step synthesis of fused aromatic heterocycles from bifunctional bromoenoates or bromoalkyl indoles and iodoarenes is reported. This method provides an efficient route to a wide variety of substituted polycyclic aromatic and heteroaromatic compounds from readily accessible starting materials.     

Silver-catalyzed facile decarboxylation of coumarin-3-carboxylic acids

A simple and highly efficient protocol with mild reaction conditions has been developed that allows the smooth protiodecarboxylation of diversely functionalized coumarin-3-carboxylic acids. In the presence of catalytic amounts of Ag₂CO₃ and acetic acid, even un-activated coumarin-3-carboxylic acids were converted in good to excellent yields and with great preparative ease to the corresponding coumarin derivatives.     

Guided waves characteristics of multi-walled carbon nanotubes

The theoretical analysis of propagation of guided waves in the multi-walled carbon nanotubes is presented within the framework of the classical electrodynamics. Electronic excitations of each wall of the system are modeled as an infinitesimally thin cylindrical layer of the π-electrons, whose dynamics are described by means of the fluid theory. General expressions of dispersion relations are obtained for the electromagnetic wave with the transverse magnetic and transverse electric modes, respectively, by solving Maxwell and fluid equations with appropriate boundary conditions.     

Quantification of Porous Properties of Shear Crystallized Lipids

The aim of this study was to investigate the impact that shear and composition have on the structural properties associated with the porous phases of lipids. To accomplish this aim, we developed eight main crystallized samples using cocoa butter (CB) or trilaurin (TL) in the presence or absence of monostearate (M) (5% w/w). The samples were sheared at 500 s⁻¹ using random (RS) or laminar (LS) shear at a cooling rate of 2 °C/min. Using the maximal ball (MB) algorithm, several empirical void measurements such as connectivity (z), pore and throat volume weighted radii (R₄₃), and void fraction (v) were quantified using 3D X-ray microcomputed tomography images. Most void features were identified as micropores (R ≥ 10 μm) possibly originating from the crystallization process and post-process crystal growth. Likewise, depending on the applied treatments, mechanisms impacting void formation were found to produce noticeable variation in v (0.019 to 0.139) and to determine whether void morphology was spherical, irregular, and/or highly connected.     

Deep generative models for vehicle speed trajectories

Generating realistic vehicle speed trajectories is a crucial component in evaluating vehicle fuel economy and in predictive control of self-driving cars. Traditional generative models rely on Markov chain methods and can produce accurate synthetic trajectories but are subject to the curse of dimensionality. They do not allow to include conditional input variables into the generation process. In this paper, we show how extensions to deep generative models allow accurate and scalable generation. Proposed architectures involve recurrent and feed-forward layers and are trained using adversarial techniques. Our models are shown to perform well on generating vehicle trajectories using a model trained on GPS data from Chicago metropolitan area.