Speaker
Description
The high repetition rate of X-ray free-electron lasers (XFELs) enables the collection of massive single-particle diffraction datasets, providing unprecedented opportunities to investigate nonequilibrium structural dynamics in nanoparticle ensembles. Here, we apply XFEL single-particle imaging to large ensembles of gold nanoparticles undergoing nonequilibrium processes including growth and plasmon-induced melting. The analysis reveals statistically significant distributions of transient particle geometries and evolving shape pathways beyond the capabilities of conventional ensemble-averaged characterization techniques, providing insight into the structural heterogeneity that emerges during dynamical transformations.
To efficiently extract structural information from these heterogeneous datasets, we develop a high-throughput analysis framework based on Monte Carlo sampling of particle shape and orientation parameter spaces under geometry-constrained reconstruction. The approach exploits the fact that nanoparticle structure is independent of overall particle orientation, allowing diffraction patterns from different particle views across the ensemble to collectively constrain otherwise weakly determined structural parameters. Geometric correlations learned from the full dataset further guide the reconstruction toward physically meaningful morphologies and enable rapid identification of subtle shape variations and transient structural features. The methodology has also been successfully transferred to multiple XFEL beamtimes and experimental configurations, demonstrating its broad applicability for high-throughput coherent imaging of heterogeneous nanomaterials.
These results establish geometry-assisted XFEL single-particle imaging as a powerful approach for probing nonequilibrium nanoscale dynamics and highlight the importance of integrating collective statistical information with advanced computational FEL imaging workflows.
[1] Shen, Zhou, et al. "Resolving nonequilibrium shape variations among millions of gold nanoparticles." ACS Nano 18.24 (2024): 15576–15589.
| Scientific Topics | Imaging |
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