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Ian J Bruno

Publications and source records attributed to Ian J Bruno.

3 recordsLinked to original sources

New software for searching the Cambridge Structural Database and visualizing crystal structures.

Two new programs have been developed for searching the Cambridge Structural Database (CSD) and visualizing database entries: ConQuest and Mercury. The former is a new search interface to the CSD, the latter is a high-performance crystal-structure visualizer with extensive facilities for exploring networks of intermolecular contacts. Particular emphasis has been placed on making the programs as intuitive as possible. Both ConQuest and Mercury run under Windows and various types of Unix, including Linux.

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Retrieval of crystallographically-derived molecular geometry information.

The crystallographically determined bond length, valence angle, and torsion angle information in the Cambridge Structural Database (CSD) has many uses. However, accessing it by means of conventional substructure searching requires nontrivial user intervention. In consequence, these valuable data have been underutilized and have not been directly accessible to client applications. The situation has been remedied by development of a new program (Mogul) for automated retrieval of molecular geometry data from the CSD. The program uses a system of keys to encode the chemical environments of fragments (bonds, valence angles, and acyclic torsions) from CSD structures. Fragments with identical keys are deemed to be chemically identical and are grouped together, and the distribution of the appropriate geometrical parameter (bond length, valence angle, or torsion angle) is computed and stored. Use of a search tree indexed on key values, together with a novel similarity calculation, then enables the distribution matching any given query fragment (or the distributions most closely matching, if an adequate exact match is unavailable) to be found easily and with no user intervention. Validation experiments indicate that, with rare exceptions, search results afford precise and unbiased estimates of molecular geometrical preferences. Such estimates may be used, for example, to validate the geometries of libraries of modeled molecules or of newly determined crystal structures or to assist structure solution from low-resolution (e.g. powder diffraction) X-ray data.

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Factors affecting d-block metal-ligand bond lengths: toward an automated library of molecular geometry for metal complexes.

Metal-ligand (M-L) bond lengths for a range of ligands (carboxylates, chlorides, pyridines, water, tertiary phosphines, and alkenes) and a variety of metals have been retrieved from the Cambridge Structural Database, CSD. Analysis of the factors which affect M-L bond lengths (for example, ligand coordination mode, oxidation state, metal coordination number and geometry, spin and Jahn-Teller effects, and ligand trans to M-L bond) shows that it is generally possible to subdivide the M-L data sets systematically to obtain better defined, unimodal, bond length distributions with means and sample standard deviations (SSDs) which reflect the nature of the bond in question. Typically, the SSDs for the M-L data sets can be reduced to 0.04-0.05 A by these methods. This work is an extension to tables of bond lengths in organometallic compounds and coordination complexes published in 1989. The importance of the factors which affect M-L bond lengths for particular metal-ligand groups are discussed. From the case studies reported, an algorithm is proposed by which compilation of a library of molecular geometry for metal complexes may be automated. The points that need to be considered to produce such a molecular library from the data stored in the CSD are discussed. The development of such a library would allow users to retrieve chemically well-defined geometric data rapidly and accurately. This should be of use, for example, to crystallographers and molecular modelers.

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