Functional Microfiber Nonwoven Fabric with Copper Ion-Immobilized Polymer Brush for Detection and Adsorption of Acetone Gas

The detection and removal of volatile organic compounds (VOCs) are emerging as an important problem in modern society. In this study, we attempted to develop a new material capable of detecting or adsorbing VOCs by introducing a new functional group and immobilizing metal ions into a microfiber nonwoven fabric (MNWF) made through radiation-induced graft polymerization. The suitable metal complex was selected according to the data in “Cambridge Crystallographic Data Center (CCDC)”. 4-picolylamine (4-AMP), designated as a ligand through the metal complex data of CCDC, was introduced at an average mole conversion rate of 63%, and copper ions were immobilized at 0.51 mmol/g to the maximum. It was confirmed that degree of grafting (dg) 170% 4-AMP-Cu MNWF, where copper ions are immobilized, can adsorb up to 50% of acetone gas at about 50 ppm, 0.04 mmol/g- 4-AMP-Cu-MNWF, at room temperature and at a ratio of copper ion to adsorbed acetone of 1:10.

On modelling disordered crystal structures through restraints from molecule-in-cluster computations, and distinguishing static and dynamic disorder

Distinguishing disorder into static and dynamic based on multi-temperature X-ray or neutron diffraction experiments is the current state of the art, but is only descriptive, not predictive. Here, several disordered structures are revisited from the Cambridge Crystallographic Data Center `drug subset', the Cambridge Structural Database and own earlier work, where experimental intensities of Bragg diffraction data were available. Using the molecule-in-cluster approach, structures with distinguishable conformations were optimized separately, as extracted from available or generated disorder models of the respective disordered crystal structures. Re-combining these `archetype structures' by restraining positional and constraining displacement parameters for conventional least-squares refinement, based on the optimized geometries, then often achieves a superior fit to the experimental diffraction data compared with relying on experimental information alone. It also simplifies and standardizes disorder refinement. Ten example structures were analysed. It is observed that energy differences between separate disorder conformations are usually within a small energy window of RT (T = crystallization temperature). Further computations classify disorder into static or dynamic, using single experiments performed at one single temperature, and this was achieved for propionamide.

A Computational Study of Metallacycles Formed by Pyrazolate Ligands and the Coinage Metals M = Cu(I), Ag(I) and Au(I): (pzM)n for n = 2, 3, 4, 5 and 6. Comparison with Structures Reported in the Cambridge Crystallographic Data Center (CCDC)

The structures reported in the Cambridge Structural Database (CSD) for neutral metallacycles formed by coinage metals in their valence (I) (cations) and pyrazolate anions were examined. Depending on the metal, dimers and trimers are the most common but some larger rings have also been reported, although some of the larger structures are not devoid of ambiguity. M06-2x calculations were carried out on simplified structures (without C-substituents on the pyrazolate rings) in order to facilitate a comparison with the reported X-ray structures (geometries and energies). The problems of stability of the different ring sizes were also analyzed.

Synthesis and Structure Features of Tetraphenylantimony 2,3-Difluoro- and 2,3,4,5,6-Pentafluorobenzoate

Tetraphenylantimony 2,3-difluorobenzoate (1) and tetraphenylantimony 2,3,4,5,6-pentafluorobenzoate (2) was obtained by the interaction of pentaphenylantimony with 2,3-difluorobenzoic and 2,3,4,5,6-pentafluorobenzoic acids in benzene with a yield of up to 98 %. The compounds were also synthesized by the ligand redistribution reaction between pentaphenylantimony and triphenylantimony dicarboxylates. The compounds have been identified by IR spectroscopy and X-ray diffraction analysis. According to the X-ray diffraction data, the antimony atoms in compounds 1 and 2 have a distorted trigonal-bipyramidal coordination with the oxygen atom in axial positions. X-ray diffraction analysis was performed on a D8 QUEST diffractometer (Bruker). The crystallographic parameters of the unit cell of the compounds: 1 space group Р1 ̅, а = 9.857(5), b = 10.154(7), c = 14.362(11) Å, α = 83.74(4)°, β = 82.59(3), γ = 68.34(2)°, V = 1321.9(16) Å3, ρcalc = 1.475 g/cm3, Z = 2; 2 space group Р21/с, а = 16.186(9), b = 8.771(6), c = 20.413(13) Å, α = 90.00°, β = 113.073(17), γ = 90.00°, V = 2666(3) Å3, ρcalc = 1.597 g/cm3, Z = 4. The OSbO axial angles are slightly different and amount to 177.90(5)º in 1 and 179.00(5)º in 2. The sums of the CSbC equatorial angles are 356.89(9)º (1), 355.85(7)º (2). The Sb–Ceq distances in compounds 1 and 2 are 2.116(2), 2.119(2), 2.118(2) and 2.1073(17), 2.1158(18), 2.1152(19) Å respectively, which are significantly shorter than the Sb–Сax bond lengths (2.169(2) and 2.1617(19) Å). The organization of molecules in the crystals of compounds is due to hydrogen bonds and CHπ-interactions of the aryl and carboxyl ligands. The main difference between structures 1 and 2 is the different Sb–O bond lengths (2.2864(18) and 2.3168(18) Å), which is due to an increase in the electronegativity of the carboxyl ligand in 2, caused by the presence of five electronegative fluorine atoms in the benzoate substituent. Complete tables of atom coordinates, bond lengths and valence angles are deposited at the Cambridge Crystallographic Data Center (No. 1980908 (1); 1977189 (2); [email protected]; http://www.ccdc.cam.ac.uk/data_request/cif).

Intermolecular Interactions in Functional Crystalline Materials: From Data to Knowledge

Intermolecular interactions of organic, inorganic, and organometallic compounds are the key to many composition–structure and structure–property networks. In this review, some of these relations and the tools developed by the Cambridge Crystallographic Data Center (CCDC) to analyze them and design solid forms with desired properties are described. The potential of studies supported by the Cambridge Structural Database (CSD)-Materials tools for investigation of dynamic processes in crystals, for analysis of biologically active, high energy, optical, (electro)conductive, and other functional crystalline materials, and for the prediction of novel solid forms (polymorphs, co-crystals, solvates) are discussed. Besides, some unusual applications, the potential for further development and limitations of the CCDC software are reported.