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EXAFS 2020 - SSRL Summer School on Synchrotron X-Ray Absorption Spectroscopy

Date: 8-10 September 2020
Location: Remote

SSRL will conduct the 2020 SSRL Summer School on Synchrotron X-Ray Absorption Spectroscopy between September 8-10, 2020. The three-day session will provide training in XAS and EXAFS theory, experimental design, data acquisition strategies and FEFF based EXAFS data analysis useful to both new and experienced users. This year's school will include training material for SSRL's expanding Chemical Catalysis user base and a one-day session at the beamlines will focus on sample preparation and advanced experimental instrumentation for standard and in-situ/ in-operando measurements. Data processing and analysis techniques will be covered on subsequent days and will include introductions to EXAFS data fitting on simple systems leading into more involved data analysis methods to tackle difficult problems. The focus of this years analysis sessions will be on advanced EXAFS fitting and interpretation. A half-day session will be targeted towards experienced users and will include lectures on near-edge analysis techniques, combining advanced spectroscopic techniques with EXAFS and guidelines for proper reporting of EXAFS data.

This school is being offered free of charge to all participants. Students and researchers wishing to participate in the Summer School must register through the school web portal and should select either Imaging or EXAFS hands-on data analysis session. All verified participants will receive an email with information on the live zoom sessions between 8-10th September 2020. The deadline to register is August 20th, 2020. Verified participants will be notified by August 30th, 2020.

The Summer School will be chaired by SSRL Staff Scientist Ritimukta Sarangi with extensive support from several SSRL personnel. The Summer School will be held at SSRL with additional facilities used at the SLAC National Acceleratory Laboratory site. Funding for the SMB Summer School program is provided by NIH, DOE-BES, and DOE-BER.