Introduction to Data Collection

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
• Backgroundlow 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 Braggs Law Sin(q)nl/2d
• Penetration of X-raysabsorption
• Background
• Copper good sensitivity long separation
• Molybdenumlow 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 rotationfind some
  spotsrequires 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 hkls
  most integral

22
Problems

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

23
Use of 2-theta
24
(No Transcript)