Studies of ultrafast dynamics in substrate-free nanoparticles at ELI using Timepix3 optical camera

TL;DR

The study demonstrates the use of a Timepix3 optical camera integrated into a velocity map imaging detector to probe ultrafast dynamics of substrate-free krypton nanoparticles irradiated by a high-intensity laser at ELI ERIC. It shows time-stamped, high-resolution ion imaging under a wide range of occupancies and develops a correction method for readout overflow that preserves data integrity. The results include a Kr$^+$ mass spectrum, occupancy-dependent analyses, and a landscape of high-occupancy event handling, illustrating the system's capability to resolve multi-species, time-resolved ion emission. The work highlights the practical impact of time-stamping detectors for complex, stochastic nanoparticle–laser interactions and informs the design of future high-rate ultrafast imaging experiments.

Abstract

We present a novel application of the Timepix3 optical camera (Tpx3Cam) for investigating ultrafast dynamics in substrate-free nanoparticles at the Extreme Light Infrastructure European Research Infrastructure Consortium (ELI ERIC). The camera, integrated into an ion imaging system based on a micro-channel plate (MCP) and a fast P47 scintillator, enables individual time-stamping of incoming ions with nanosecond timing precision and high spatial resolution. The detector successfully captured laser-induced ion events originating from free nanoparticles disintegrated by intense laser pulses. Owing to the broad size distribution of the nanoparticles (10-500 nm) and the variation in laser intensities within the interaction volume, the detected events range in occupancy from near-zero to extremely high, approaching the readout limits of the detector. By combining time-of-flight and velocity map imaging (VMI) techniques, detailed post-processing and analysis were performed. The results presented here focus on the performance of Tpx3Cam under high-occupancy conditions, which are of particular relevance to this study. These conditions approach the limitations imposed by the camera readout capabilities and challenge the effectiveness of standard post-processing algorithms. We investigated these limitations and associated trade-offs, and we present improved methods and algorithms designed to extract the most informative features from the data.

Figures (7)

• Figure 1: Sketch of the experimental setup of the laser interacting with a nanoparticle beam in the gas phase Klimesova2025slides and (d, e) examples of single-shot images. (b) A small nanoparticle hit in a region of lower laser intensity, producing data with low occupancy. (d) An example of single-shot image with low occupancy. Individual ion hits are well resolved. (c) A large nanoparticle hit by a laser beam close to the center of the focal spot. This situation produces a strong signal with a large number of hit pixels. (e) Example of single-shot image with very large occupancy. Blending of individual ion hits is clearly visible.
• Figure 2: Schematic diagram of the ion detector illustrating the use of the Timepix3 camera in conjunction with the velocity map imaging (VMI) technique.
• Figure 3: Time of flight (ToF) mass spectrum of ions detected within the first 10 µs after the laser–nanoparticle interaction. The red histogram shows the ion count distribution as a function of ToF. Distinct peaks are observed, each corresponding to different ion species separated according to their mass to charge ratio. The shaded regions highlight characteristic ToF windows associated with selected ion species. Zoomed images display integrated ion hit patterns on the detector for selected ToF regions, including light fragments from the background gas as well as ions from krypton nanoparticles.
• Figure 4: Histograms of hit occupancies for large sequences. The upper panel displays the overall distribution of hits recorded during the 500 s acquisition. A closer inspection of the peak structure reveals that each peak is composed of several sub-peaks, originating from the 409.6 µs timestamp shift. These sub-peaks correspond to the same physical event, registered with timestamps displaced by integer multiples of 409.6 µs. The algorithm introduced in the text successfully identifies and corrects these shifted contributions, yielding the results presented in Figure \ref{['fig:comparison']}.
• Figure 5: Histogram of the corrected peak for the large sequence. The correction algorithm identifies peaks shifted by 409.6 µs and aligns them by subtracting this offset. The resulting histogram is then shifted back by the laser period (1.000935 ms) to ensure proper temporal alignment, illustrating the effectiveness of the correction procedure.