Core-level spectroscopy, spanning soft and hard X-ray regimes such as X-ray absorption spectroscopy (XAS) and resonant inelastic X-ray scattering (RIXS), provides critical insights into electronic, chemical, and structural properties of materials. However, concurrent with advancements in spectroscopic techniques and their expanding scope of applications, traditional spectral analysis methodologies—reliant on manual lineshape comparisons or heuristic interpretations—face increasing limitations when dealing with extensive experimental datasets. Addressing these challenges necessitates the assimilation of contemporary computational and machine learning (ML) based approaches into established spectroscopic protocol.
Agenda
8:00 WELCOME AND REGISTRATION
8:30 XAS/RIXS @ the ALS
RIXS group, ALS
9:00 Computing Progress & Goals for the AMBER Beamline @ALS
Wiebke Koepp, ALS
9:30 Accelerating XAS Material Classification and Alignment at ALS Beamlines with Human-in-the-Loop AI
Franklin Liou, LBNL
10:00 BREAK
10:30 Ultrahigh-resolution 2D-RIXS at NanoTerasu BL02U: New Capabilities and Emerging Data Analysis Challenges
Jun Miyawaki, Nano Terasu
11:00 RIXS at SLAC (Coming Soon)
Thomas Kroll, SLAC
11:30 Data Flow in Time-Resolved RIXS at LCLS
Lingjia Shen, LCLS
12:00 PHOTO
12:15 LUNCH
1:30 Resolving local structure characteristics in complex materials with x-ray absorption spectroscopy and machine learning
Deyu Lu, BNL
2:00 Digital Twin for Chemical Sciences (DTCS) and Its Demo
Jin Qian, LBNL
2:30 High-throughput generation and interpretation of X-ray absorption spectroscopy
Yiming Chen, ANL
3:00 BREAK
3:30 Computing Discussion
4:30 Wrapup