AUTOMATED CRYSTAL QUEUING FOR DATA COLLECTION

用于数据收集的自动水晶排队

• 批准号: 8170005
• 负责人: IRIMPAN I MATHEWS
• 金额: $ 6.1万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-05-01 至 2011-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8170005
• 关键词: Computer Retrieval of Information on Scientific Projects Database; Data; Data Collection; Funding; Grant; Image; Institution; Movement; Process; Productivity; Research; Research Personnel; Resources; Rotation; Running; Sampling; Screening procedure; Source; Testing; Translations; United States National Institutes of Health; beamline; improved; indexing; success

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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