1 / 10

Using e-Science to probe structure and bonding in metal complexes: Database mining and computation

Using e-Science to probe structure and bonding in metal complexes: Database mining and computation. Jonathan Charmant, Frederik Claeyssens, Natalie Fey, Mairi Haddow, Stephanie Harris, Jeremy Harvey, Tom Leyssens, Ralph Mansson, A. Guy Orpen and Athanassios Tsipis. CombeDay 2005 Southampton.

Download Presentation

Using e-Science to probe structure and bonding in metal complexes: Database mining and computation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Using e-Science to probe structure and bonding in metal complexes: Database mining and computation Jonathan Charmant, Frederik Claeyssens, Natalie Fey, Mairi Haddow, Stephanie Harris, Jeremy Harvey, Tom Leyssens, Ralph Mansson, A. Guy Orpen and Athanassios Tsipis CombeDay 2005 Southampton

  2. Reactivity e-Science Properties Structure

  3. Metal-ligand binding Tsipis, Orpen and Harvey, Dalton Trans. submitted

  4. Metal-ligand binding 2 Database mining: correlation between: Oxidation-Reduction and M–P–X angle and P–X distance Cause: π back-bonding? Leyssens, Orpen, Peeters and Harvey, to besubmitted

  5. He8 steric probe [Cl3PdP(Me)2(CF3)]- Metal-ligand binding: a systematic approach 61 ligands, ca. 10 calculations on each  Ligand Knowledge Base

  6. Locate unusual ligands: Map of Chemical Space NR2 OR Hal Ar R

  7. Fey, Tsipis, Harris, Harvey, Orpen & Mansson, to besubmitted Model Building • Predict experimental data from calculated variables. • Multiple linear regression: Solid State Rh-P Distance (Rh(I), CN=4) Tolman Electronic Parameter

  8. Adding value to the structural database Query Geometry Library for User-Defined Fragment retrieval of matching data Output of Statistical Data apply outlier criteria Outliers Fey, Harris, Harvey and Orpen, to besubmitted DFT geometry optimisation Optimised Geometries compare with crystal structures Crystal Structure and DFT agree Crystal Structure and DFT disagree

  9. Adding value to the structural database – 2

  10. Conclusions • Structural database is full of data • Data Mining already known to yield valuable insight • Combine database with computation to yield more insight • Probe structure and reactivity of individual species • Generate ligand knowledge base • Probe structural trends and outliers

More Related