PILATUS 6M Detector

PILATUS 6M

Images summation/merging

ID29 is now equipped with a Pilatus 6M detector which has an active area of 424 x 435 mm² (2463 x 2527 pixels, which are 172 microns in size).

The readout time per frame is 3ms and the maximum speed is 12Hz. In this way 12 images per second are collected while operating in shutterless mode, allowing to collect a complete dataset in less than 2 minutes.

To cope with the high data collection speed we recommend that you bring enough samples to be measured

Diffraction quality is higher than a normal CCD detector thanks to: the absence of readout noise, the zero background counts and the 20bit dynamic range.

New: Continuous Helican Scan (4d scan)

Continuous helical scan is now enable on ID29. It is set in the same way as a normal helical, but the crystal is translated at constant speed along the user defined direction while spindle is rotating

How to collect the best data

For better data quality it is recommended that you collect data with fine phi slicing (i.e. Oscillation range smaller than half of the estimated mosaicity of the crystal). Usually an Oscillation range of 0.1 is a good choice, in combination with a low Transmission. This is particularly relevant for experimental phasing experiments.

Data below were collected from the same Trypsin crystal with the same oscillation wedge (120 degrees) and the same total x-ray dose.

DELTA PHI = 0.1 DEGREES
 
SUBSET OF INTENSITY DATA WITH SIGNAL/NOISE >= -3.0 AS FUNCTION OF RESOLUTION
 RESOLUTION     NUMBER OF REFLECTIONS    COMPLETENESS R-FACTOR  R-FACTOR COMPARED I/SIGMA   R-meas  Rmrgd-F  Anomal  SigAno   Nano
   LIMIT     OBSERVED  UNIQUE  POSSIBLE     OF DATA   observed  expected                                      Corr

     4.47        7247    1288      1290       99.8%       3.5%      4.0%     7241   39.43     3.9%     1.9%    -1%   0.816     836
     3.17       12981    2146      2155       99.6%       3.8%      4.1%    12975   40.44     4.1%     1.9%   -11%   0.772    1681
     2.59       16916    2736      2747       99.6%       4.2%      4.4%    16907   35.43     4.6%     2.3%    -8%   0.784    2221
     2.24       20540    3200      3203       99.9%       4.7%      4.9%    20537   31.11     5.2%     2.7%    -7%   0.766    2721
     2.01       22598    3589      3594       99.9%       5.2%      5.7%    22589   25.85     5.7%     3.1%    -3%   0.730    2998
     1.83       21585    3908      3962       98.6%       6.4%      7.3%    21532   18.37     7.1%     4.3%    -5%   0.680    2872
     1.70       12011    3853      4267       90.3%       7.1%      9.5%    11472    9.84     8.4%     6.4%    -1%   0.614    1433
     1.59        6576    3096      4618       67.0%       8.7%     13.0%     5549    5.76    11.1%    10.8%     8%   0.630     431
     1.50        2085    1333      4869       27.4%      13.9%     18.6%     1345    3.52    18.6%    20.2%    12%   0.660      53
    total      122539   25149     30705       81.9%       4.1%      4.5%   120147   22.23     4.5%     3.1%    -5%   0.730   15246

DELTA PHI = 0.5 DEGREES

 SUBSET OF INTENSITY DATA WITH SIGNAL/NOISE >= -3.0 AS FUNCTION OF RESOLUTION
 RESOLUTION     NUMBER OF REFLECTIONS    COMPLETENESS R-FACTOR  R-FACTOR COMPARED I/SIGMA   R-meas  Rmrgd-F  Anomal  SigAno   Nano
   LIMIT     OBSERVED  UNIQUE  POSSIBLE     OF DATA   observed  expected                                      Corr

     4.47        7248    1287      1290       99.8%       4.1%      4.2%     7242   38.52     4.5%     2.0%     2%   0.828     839
     3.17       13072    2147      2155       99.6%       3.8%      4.2%    13066   39.79     4.2%     1.9%     5%   0.806    1680
     2.59       16884    2732      2745       99.5%       4.2%      4.5%    16875   35.77     4.5%     2.2%     5%   0.821    2216
     2.24       20378    3198      3203       99.8%       4.5%      4.8%    20377   32.18     4.9%     2.5%     7%   0.822    2706
     2.01       22446    3589      3594       99.9%       5.2%      5.4%    22436   27.47     5.6%     3.1%    10%   0.827    2994
     1.83       21371    3902      3956       98.6%       6.2%      6.7%    21320   20.21     6.9%     4.4%     9%   0.803    2858
     1.70       11984    3853      4274       90.1%       7.5%      8.5%    11447   11.16     8.9%     7.1%     9%   0.765    1421
     1.59        6551    3091      4613       67.0%       9.4%     11.3%     5528    6.70    11.9%    12.0%    10%   0.711     422
     1.50        2071    1333      4872       27.4%      14.6%     15.9%     1317    4.10    19.5%    22.6%    29%   0.927      51
    total      122005   25132     30702       81.9%       4.3%      4.6%   119608   23.17     4.7%     3.2%     8%   0.810   15187

DELTA PHI = 1.0 DEGREES

 SUBSET OF INTENSITY DATA WITH SIGNAL/NOISE >= -3.0 AS FUNCTION OF RESOLUTION
 RESOLUTION     NUMBER OF REFLECTIONS    COMPLETENESS R-FACTOR  R-FACTOR COMPARED I/SIGMA   R-meas  Rmrgd-F  Anomal  SigAno   Nano
   LIMIT     OBSERVED  UNIQUE  POSSIBLE     OF DATA   observed  expected                                      Corr

     4.47        7185    1281      1288       99.5%       5.2%      5.0%     7179   32.53     5.7%     2.6%    -1%   0.817     836
     3.17       13270    2151      2159       99.6%       4.7%      5.1%    13265   34.03     5.1%     2.3%     0%   0.794    1699
     2.59       17181    2738      2745       99.7%       4.6%      5.2%    17169   31.44     5.1%     2.5%     3%   0.796    2228
     2.24       20742    3195      3199       99.9%       5.1%      5.5%    20741   29.13     5.5%     2.8%     2%   0.800    2700
     2.01       22746    3599      3606       99.8%       5.7%      6.0%    22736   25.45     6.3%     3.3%     2%   0.814    2997
     1.83       21406    3902      3956       98.6%       6.9%      7.0%    21355   19.37     7.6%     4.7%     6%   0.837    2822
     1.70       11960    3852      4276       90.1%       8.3%      8.5%    11409   11.13     9.9%     8.1%     3%   0.793    1425
     1.59        6534    3079      4613       66.7%      10.4%     11.0%     5522    6.90    13.2%    13.4%     6%   0.772     418
     1.50        1986    1288      4874       26.4%      16.1%     15.8%     1244    4.29    21.5%    26.4%     0%   0.831      47
    total      123010   25085     30716       81.7%       5.0%      5.4%   120620   21.16     5.5%     3.7%     3%   0.808   15172

 

Images visualisation

from Dectris is available on ID29 to visualize diffraction images. For remote experiments type "albula" in a terminal to start it

Diffraction images can be viewed with adxv (version 1.9.7 or superior) or MOSFLM (version 7.0.7 or superior). Older versions of MOSFLM work with a minimal input file (mosflm_view.inp).

On ID29 you can start ADXV follow which will update every 10-15 images showing in (quasi) real time the data collected.

Remotely you can start start_adxv_socket (same as ADXV follow).

The message in spec(exp) "Can't connect to id29gate: Connection refused" indicates that ADXV follow is not running and spec cannot update the image shown.

Data processing

Diffraction data can be processed with MOSFLM and XDS. iMOSFLM should be version 1.0.5 or superior.

Input files for processing with MOSFLM and XDS are created automatically for each data collection. Examples of these input files can be found here mosflm.inp, XDS.INP

XDS needs two additional files for geometrical correction (x_geo_corr.cbf and y_geo_corr.cbf updated on the 28.06.2010) which are copied into the process directory. These files are detector specific and they will not change (unless a major hardware intervention is done on the detector).

Images summation/merging

In some cases, to save disk space, you might want to merge more 'fine-sliced' images together (for example, merging 10 images of 0.1 degree oscillation to one of 1 degree). The program MERGE2CBF, that belong to XDS suite can be used for this purpose with input file MERGE2CBF.INP

NEW: images can be summed automatically at the end of the data collection using MERGE2CBF checking the box in mxCuBE. Merged images have a corrected header with the total oscillation. Merged images will be written in a specific directory SUMMED_DATA at the same level or RAW_DATA and PROCESSED_DATA.

Data Backup

Collecting data in fine slicing mode, together with the high data collection speed will result in a very high amount of data. Each image size is about 6MB and an average data-set is composed by about 1000 images. Images can be zipped but this may take time. Linux machine lid29io (first one from left in the control cabin) can be used for fast backup. It is connect to NICE through a 10 Gbit and sopport USB3.0 external disks. Disks must be FAT32 or NTFS (faster option) formatted. It is recommended to start the backup as soon as experiment starts and run a rsync job to be sure all the images are copied. Refer to the general backup page for additional information. Other backup machine (wid29io and pc29data) are still available for low priority backup.

We recommend that you bring enough storage memory to backup all your data.

We recommend to keep your data organised (one directory per dataset for example). NICE Filesystem performance drops drastically over 3000 images per directory.

Troubleshooting