Theoretical study of the electric and the magnetic dipole in UV-Vis and ECD of fluralaner: the folded conformation and the extended conformation

In our contribution, we have carried out a theoretical study of the transition characteristics of one-photon absorption (OPA) spectra of the folded conformation and the extended conformation of fluralaner. The electronic transitions in OPA are visualized with charge difference density (CDD) and transition density matrix (TDM) to explain the charge transfer via hole-electron distribution. We also analyze the transition dipole electric/ magnetic moment by using the isosurface (real space) and TDM diagram in order to determine the portions of molecules which have the most contribution in ECD spectra.

Density functional study on electric structure and optical properties in Na-doped 3C-SiC

Structural stability along with the electronic and the optical properties of intrinsic 3C-SiC, [Formula: see text] and [Formula: see text] are studied by the first-principles calculations. [Formula: see text] system possesses the most considerate stability with lowest binding energy [Formula: see text] and formation energy [Formula: see text] compared to [Formula: see text]. It is observed that the non-filled impurity energy levels in the vicinity of the Fermi level can subsequently give rise to an enhancement of electrical conductivity of 3C-SiC. Through the analysis of charge difference density maps, it is found that covalence of bonds between the Na atom and nearby C atom reduces in varying degrees. In different concentrations of Na doping systems, especially for the supercell of [Formula: see text], the real and imaginary parts of the dielectric constant are visibly added in the energy range of 0–0.5 eV, demonstrating that the dielectric loss property of the 3C-SiC is improved evidently. These features confirm that the Na-doped 3C-SiC semiconductor is propitious to the wide application of 3C-SiC in the field of absorbing materials.

Prediction of models for ordered solvent in macromolecular structures by a classifier based upon resolution-independent projections of local feature data

Current software tools for the automated building of models for macromolecular X-ray crystal structures are capable of assembling high-quality models for ordered macromolecule and small-molecule scattering components with minimal or no user supervision. Many of these tools also incorporate robust functionality for modelling the ordered water molecules that are found in nearly all macromolecular crystal structures. However, no current tools focus on differentiating these ubiquitous water molecules from other frequently occurring multi-atom solvent species, such as sulfate, or the automated building of models for such species. PeakProbe has been developed specifically to address the need for such a tool. PeakProbe predicts likely solvent models for a given point (termed a `peak') in a structure based on analysis (`probing') of its local electron density and chemical environment. PeakProbe maps a total of 19 resolution-dependent features associated with electron density and two associated with the local chemical environment to a two-dimensional score space that is independent of resolution. Peaks are classified based on the relative frequencies with which four different classes of solvent (including water) are observed within a given region of this score space as determined by large-scale sampling of solvent models in the Protein Data Bank. Designed to classify peaks generated from difference density maxima, PeakProbe also incorporates functionality for identifying peaks associated with model errors or clusters of peaks likely to correspond to multi-atom solvent, and for the validation of existing solvent models using solvent-omit electron-density maps. When tasked with classifying peaks into one of four distinct solvent classes, PeakProbe achieves greater than 99% accuracy for both peaks derived directly from the atomic coordinates of existing solvent models and those based on difference density maxima. While the program is still under development, a fully functional version is publicly available. PeakProbe makes extensive use of cctbx libraries, and requires a PHENIX licence and an up-to-date phenix.python environment for execution.

A computational study of the quantum transport properties of a Cu–CNT composite

Electron difference density maps through cross-sections of three differently oriented Cu–CNT (6,6) composites (top) and the electrostatic difference potential along the transport direction (bottom).