Faster data collection without loss of precision. An extension of the learnt profile method

Abstract

The method of fitting a learnt and continually revised profile to X-ray diffraction step-scan measurements, previously described for protein crystals and a linear diffractometer, has been modified and extended for a wider range of samples and a four-circle diffractometer. Variation of peak width is dealt with by assuming an anisotropic functional form, the parameters for which are derived by least-squares refinement from measurements of selected strong reflexions. The effect of the α doublet on the reflexion shape is treated by an empirical method, which extracts α1 and α2 components from the observed profile with a minimum of assumptions. Several internal consistency tests are made to test the validity of the method for every measured reflexion, and possible errors are flagged. Application of the method enables a considerable increase in data-collection speed over conventional methods, without corresponding loss of precision. Typical rates of data collection by this method are 100 reflexions per hour, or 2-3 medium-sized structures per week, for a Stoe-Siemens AED diffractometer and a 2 kW tube (Mo Kα radiation, graphite monochromator).