Synthesis, Structure, and Characterization of Two Photoluminescent Zirconium Phosphate−Quinoline Compounds

Liu, Lei; Li, Jinping; Dong, Jinxiang; Šišak, Dubravka; Baerlocher, Christian; McCusker, Lynne B.

doi:10.1021/ic901196f

Cited by 21 publications

(37 citation statements)

References 37 publications

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“…Baerlocher, McCusker & Palatinus (2007) have demonstrated the solution of several structures, ranging from relatively simple ones to quite complex structures like the zeolite ZSM-5 with 38 atoms in the asymmetric unit (288 in the unit cell). This method was then successfully used to solve a number of structures, mainly of zeolites and other framework materials (Massueger et al, 2007;Koyama et al, 2008;Xie et al, 2009;Liu et al, 2009;Park et al, 2011;Gandara et al, 2012).…”

Section: Powder Diffraction Datamentioning

confidence: 99%

The charge-flipping algorithm in crystallography

Palatinus

2013

Acta Crystallogr B Struct Sci Cryst Eng Mater

136

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The charge-flipping algorithm (CFA) is a member of the diverse family of dual-space iterative phasing algorithms. These algorithms use alternating modifications in direct and reciprocal space to find a solution to the phase problem. The current state-of-the-art CFA is reviewed and it is put in the context of related dual-space algorithms with relevance for crystallography. The CFA has found applications in many crystallographic problems. The principal applications in various fields are described with sections devoted to routine structure solution, the solution of complex structures from powder diffraction data, the solution of incommensurately modulated crystals and quasicrystals, macromolecular crystallography and single-particle imaging.

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Section: Powder Diffraction Datamentioning

confidence: 99%

The charge-flipping algorithm in crystallography

Palatinus

2013

Acta Crystallogr B Struct Sci Cryst Eng Mater

136

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“…Hydrated caesium cyanoplatinate (CsPt) (Johnson et al, 1977) and ZSM-5 zeolite crystals (Olson et al, 1981;van Koningsveld et al, 1987) were provided by Dr P. Pattison (EPFL Lausanne, Switzerland) and Professor Henri Kessler (Université de Haute-Alsace, Mulhouse, France), respectively. The zirconium phosphate (ZrPOF) (Liu et al, 2009) and magnesium acetate (MgAc) samples were provided by Dr L. B. McCusker (ETH Zurich, Switzerland). The magnesium acetate structure was refined using single-crystal data collected on the ALS-11.3.1 beamline, and the results agree with the published structure (Scheurell et al, 2015).…”

Section: Sample Tests and Data Acquisitionmentioning

confidence: 99%

Pattern-matching indexing of Laue and monochromatic serial crystallography data for applications in materials science

Dejoie¹,

Tamura²

2020

J Appl Cryst

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Serial crystallography data can be challenging to index, as each frame is processed individually, rather than being processed as a whole like in conventional X-ray single-crystal crystallography. An algorithm has been developed to index still diffraction patterns arising from small-unit-cell samples. The algorithm is based on the matching of reciprocal-lattice vector pairs, as developed for Laue microdiffraction data indexing, combined with threedimensional pattern matching using a nearest-neighbors approach. As a result, large-bandpass data (e.g. 5-24 keV energy range) and monochromatic data can be processed, the main requirement being prior knowledge of the unit cell. Angles calculated in the vicinity of a few theoretical and experimental reciprocal-lattice vectors are compared, and only vectors with the highest number of common angles are selected as candidates to obtain the orientation matrix. Global matching on the entire pattern is then checked. Four indexing options are available, two for the ranking of the theoretical reciprocal-lattice vectors and two for reducing the number of possible candidates. The algorithm has been used to index several data sets collected under different experimental conditions on a series of model samples. Knowing the crystallographic structure of the sample and using this information to rank the theoretical reflections based on the structure factors helps the indexing of large-bandpass data for the largestunit-cell samples. For small-bandpass data, shortening the candidate list to determine the orientation matrix should be based on matching pairs of reciprocal-lattice vectors instead of triplet matching.

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“…Baerlocher, McCusker & Palatinus (2007) have demonstrated the solution of several structures, ranging from relatively simple ones to quite complex structures like the zeolite ZSM-5 with 38 atoms in the asymmetric unit (288 in the unit cell). This method was then successfully used to solve a number of structures, mainly of zeolites and other framework materials Koyama et al, 2008;Xie et al, 2009;Liu et al, 2009;Park et al, 2011;Gandara et al, 2012).…”

Section: Powder Diffraction Datamentioning

confidence: 99%