Optimisation of measurement and data analysis of time-resolved X-ray absorption spectroscopy of thin film organic semiconductors.

Abstract

Time-resolved X-ray absorption spectroscopy (TR-XAS) at X-ray free-electron lasers enables element-specific probing of ultrafast dynamics, but soft X-ray measurements are often limited by low fluorescence yield, strong shot-to-shot fluctuations, and radiation damage in organic thin films. Here, we present a unified framework combining analytical signal-to-noise ratio (SNR) modelling with regression-based analysis for fluorescence-detected soft X-ray absorption spectroscopy. The SNR model predicts fundamentally different optimal conditions for static and transient measurements, with transient experiments requiring thin films (∼80-100 nm) and substantially higher photon counts. We apply this framework to shot-resolved total fluorescence yield XAS measurements of the non-fullerene acceptor Y6 at the nitrogen K-edge using a high-repetition-rate XFEL source, comparing low-dose and intermediate-dose regimes relevant to transient and static measurements, respectively. A calibration-based flux reconstruction systematically improves the fluorescence-flux correlation, while the dominant improvement arises from reformulating XAS extraction as a shot-resolved regression problem. Compared to the conventional ratio-of-means estimator, the regression-based estimator reduces the run-to-run spectral variability by up to a factor of ∼4.4 in the low-dose regime most relevant for transient measurements. Residual-based outlier rejection was found to systematically degrade reproducibility, indicating that the tails of the shot distribution primarily reflect intrinsic XFEL fluctuations rather than detector artefacts. These results demonstrate that reliable soft X-ray TR-XAS requires the joint optimisation of experimental design and statistical inference, providing a practical framework for extracting robust observables from low-signal XFEL measurements in dose-limited regimes.