Current data collection trends at the ESRF MX beamlines show clearly that automation has led to a fundamental change in the way that MX data are collected. With the introduction of the automatic sample changer (SC3) at the ESRF MX beamlines in 2005, a dramatic increase in the number of samples that were tested for diffraction quality before any full data collections were carried out was observed (see graph).  Automation has had a spectacular effect on the scientific output of the ESRF MX beamlines. Over the past seven years there has been a more than three-fold increase in the number of structures elucidated using data collected at the ESRF. Although the output has increased - MX beamlines now produce over a quarter of the publications from the ESRF - this has not been at the cost of quality. The scientific impact of the experiments remains extraordinarily high, with around 20% of publications appearing in journals with an Impact Factor greater than 10. Automation of synchrotron beamlines thus not only increases scientific output but it also maintains the high-level impact of the science performed.

 

Our data collections statistics are harvested from the ISPyB database from all experiments scheduled on MX beamlines.  Sample evaluations are defined as <4 images and a data set is defined as >30 images.  The data are updated every hour.

 

 

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MX sample screening and data collection at the ESRF (data harvested from the ISPyB database). A: ESRF MX beamlines and BM14.  The number of total collections, screenings and data sets are shown in the bar chart . The percentage of samples on which data are eventually collected is shown as black line. B: Beamlines ID14-1, 2 and 3 (14-3 was recommissioned as a bio-SAXS beamline at the end of 2007, therefore, statistics for 2008 are for 14-1 and 2 only.) These beamlines are heavily used for sample evaluation. The percentage of samples from which full data sets are collected has fallen steadily to 11% in 2007 [Sample evaluations are defined as <4 images and a data set is defined as >30 images].