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Introduction to Data Collection

Introduction to Data Collection. What do we need to collect data. hkl index of each datum The integrated intensity of each datum. Note this is NOT the maximum intensity but all the intensity in the spot. The Standard deviation of the intensity

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Introduction to Data Collection

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  1. Introduction to Data Collection

  2. What do we need to collect data • hkl index of each datum • The integrated intensity of each datum. • Note this is NOT the maximum intensity but all the intensity in the spot. • The Standard deviation of the intensity • To determine this we need a background measurement. • All must be numerical.

  3. Other Considerations • Dynamic Range –from 10 to maybe 1,000,000 • Background—low as possible • Linear Accuracy • Time delay between data collection and evaluation • Exposure time

  4. Theta in diffraction

  5. Choice of X-ray • Sensitivity of detector • Separation of spots Bragg’s Law Sin(q)=nl/2d • Penetration of X-rays—absorption • Background • Copper –good sensitivity –long separation • Molybdenum—low absorption

  6. Choice of X-ray Wavlength

  7. Film • High dynamic range • Very low noise • Long Exposures--days • Hard to integrate • Long delay from data collection until data is available • To assign hkl need some work

  8. Laue Photo

  9. Weissenberg Camera

  10. Oscillation/Rotation Photos

  11. Alignment about a real axes

  12. Weissenberg Photo

  13. Burger Precession Camera

  14. Precession Photo

  15. Automatic Data Collection • Can determine the intensity by using some sort of radiation detector • Must find a way to move any given hkl into the position to be detected. Define the diffraction vector d so that it points along the d in the Bragg equation • Need a robot that will orient the crystal and collect the data.

  16. Orientation Matrix

  17. Orientation Matrix • xyz is an arbitrary fixed Cartesian coordinate system. • The length of each column is a reciprocal cell length • The angles between the columns give the reciprocal cell angles. • When A is multiplied into a column matrix of hkl the result is the diffraction vector.

  18. Determination of A • Know cell and axis of rotation—find some spots—requires prealignment • Find spots from a quick rotation photo. Use autoindexing. • Find spots by a random search then autoindex

  19. Autoindexing • Find 15-25 spots • Each spot represents a diffraction vector. • The vector between each spot represents a diffraction vector. • Only diffraction vectors the produce integral hkl for all the spots are possible cell lengths. • Want shortest, most orthogonal axes

  20. Sparks (Syntex) Routine • Print a table of shortest vectors with the cosine (the computer did not have an inverse cos function) of the angle between each vector. • User manually goes through table to find the best cell • Computer used had 4K of memory and no disk drive

  21. Nonius Routine • Sort the vectors by length • Weight by orthogonality • Get best cell • Due “sort of a least squares” to make the hkl’s most integral

  22. Problems • Only finds primitive cells. • One bad point can ruin the whole process. • DIRAX—Albert Duisenberg in the Netherlands defeats this by calculating potential triples and finding which give the most integral indexing.

  23. Use of 2-theta

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