SA-XPCS at APS-U: Unraveling non-equilibrium dynamics in soft materials with hierarchical spatial structures
ORAL
Abstract
Unraveling the interplay between the microscopic fluctuation, mesoscale reconfiguration, and macroscopic material properties is a grand challenge in many soft materials. Small-angle X-ray Photon Correlation Spectroscopy (SA-XPCS), a technique that combines the hierarchical spatial coverage of Small-Angle X-ray Scattering (SAXS) and the temporal resolution of Photon Correlation Spectroscopy (PCS), is an ideal match for this challenge.
Beamline 8-ID-I, the dedicated SA-XPCS beamline of the Advanced Photon Source (APS), is currently being completely rebuilt as part of the APS Upgrade (APS-U) project and will resume operation in April 2024. In addition to the 100-fold increase of coherent X-ray flux, 8-ID-I will also feature continuously tunable photon energy of 7~25 keV, beam size of 3~10 µm, spatial scale coverage of 0.1 nm to 1 µm, as well as million-pixel single-photon-counting detectors with the highest time resolution of 1 µs. The sample environments include a multi-temperature zone sample chamber and a twin-drive rheometer, which can be rapidly swapped to reduce the turnaround time. The high-throughput sample environments can be further combined with robotic sample exchange and AI-assisted XPCS to pave the road to autonomous design of soft materials.
Beamline 8-ID-I, the dedicated SA-XPCS beamline of the Advanced Photon Source (APS), is currently being completely rebuilt as part of the APS Upgrade (APS-U) project and will resume operation in April 2024. In addition to the 100-fold increase of coherent X-ray flux, 8-ID-I will also feature continuously tunable photon energy of 7~25 keV, beam size of 3~10 µm, spatial scale coverage of 0.1 nm to 1 µm, as well as million-pixel single-photon-counting detectors with the highest time resolution of 1 µs. The sample environments include a multi-temperature zone sample chamber and a twin-drive rheometer, which can be rapidly swapped to reduce the turnaround time. The high-throughput sample environments can be further combined with robotic sample exchange and AI-assisted XPCS to pave the road to autonomous design of soft materials.
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Presenters
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Qingteng Zhang
Argonne National Laboratory
Authors
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Qingteng Zhang
Argonne National Laboratory