AUTOMATED CRYSTAL QUEUING FOR DATA COLLECTION
AUTOMATED CRYSTAL QUEUING FOR DATA COLLECTION
批准号:
8170005
负责人:
IRIMPAN I MATHEWS
金额:
$6.1万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-05-01 至 2011-02-28
关键词:
Computer Retrieval of Information on Scientific Projects DatabaseDataData CollectionFundingGrantImageInstitutionMovementProcessProductivityResearchResearch PersonnelResourcesRotationRunningSamplingScreening procedureSourceTestingTranslationsUnited States National Institutes of Healthbeamlineimprovedindexingsuccess
中文摘要
点击翻译按钮获取中文摘要
英文摘要
This subproject is one of many research subprojects utilizing the
resources provided by a Center grant funded by NIH/NCRR. The subproject and
investigator (PI) may have received primary funding from another NIH source,
and thus could be represented in other CRISP entries. The institution listed is
for the Center, which is not necessarily the institution for the investigator.
In order to provide a completely automated process for collecting data from pre-screened crystals, the samples must be repositioned on the goniometer in an automated fashion. In an ideal setup, the users will be able to select good crystals during the screening, assign proper phi values for the data collection, and queue them for the data collection runs. If the users can select all good crystals during screening and set them for data collection, it will improve the beamline efficiency and users productivity. The movements of the crystal in the Hampton tong and other factors of the automated mounting process introduce various amounts of rotation and translation to the crystal between different mountings. Therefore, it is difficult to use the phi values (start and end phi for data collection) selected from the screening process after remounting of the sample. The success of the sample queuing process depends on how accurately the crystal can be repositioned during the second mounting. Repositioning of the sample using the diffraction images and video shots of the sample was explored. The phi shift between two mountings is predicted using the indexing information. Then, sample_x, sample_y, and sample_z translations between the two mountings are calculated by comparing video snapshots at the same phi value. If the space group introduce several equivalent phi values, further analysis of the video images are performed to predict the actual phi shift between the different mountings. Test of this approach indicate that the above analysis provides sufficient information for the queuing of the crystals during the automated screening process, guiding further developemnts.
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