SearcharxivSearch

arXiv subjects

Kristina Dingel

Publications and source records attributed to Kristina Dingel.

7 recordsLinked to original sources

Attosecond soft X-ray pulses generated by chirp-dispersed manipulation in an XFEL reveal nonlinear core-electron dynamics in neon

Free-electron lasers have demonstrated their capability of generating intense attosecond X-ray pulses, which are the key to studying electron dynamics at their natural time scale and in specifically targeted electronic states, but come at the expanse of complicated generation schemes and stochastic pulse shapes. Here, we demonstrate a novel and simple operation concept based on the manipulation of the electron-bunch chirp-dispersion and working with the full 4.5 MHz repetition rate at the European XFEL in Germany. With a high-fidelity single-shot temporal characterisation, we detect X-ray pulses with durations of down to 200 attoseconds and peak powers reaching into the terawatt regime at ~1 keV photon energy. As a direct application, we present simultaneous measurements of nonlinear X-ray-matter interaction via time-resolved electron spectroscopy. Using the derived temporal pulse information and restricting the durations to a regime where individual X-ray pulses are shorter than the single-core-hole life time in neon atoms, we reveal an otherwise hidden peak-intensity dependence in the nonlinear dynamics of double-core-hole formation. Our results open the field of attosecond science to the investigation of electronic processes not only in the ground state but also in systems driven far off their equilibrium. They shed light on highly transient intermediate steps in complex electronic dynamics and thus promise to help build the conceptual bridge between fundamental physical processes and chemical photo-reactions.

physics.optics

Unraveling the Complexity of Splitting Sequential Data: Tackling Challenges in Video and Time Series Analysis

Splitting of sequential data, such as videos and time series, is an essential step in various data analysis tasks, including object tracking and anomaly detection. However, splitting sequential data presents a variety of challenges that can impact the accuracy and reliability of subsequent analyses. This concept article examines the challenges associated with splitting sequential data, including data acquisition, data representation, split ratio selection, setting up quality criteria, and choosing suitable selection strategies. We explore these challenges through two real-world examples: motor test benches and particle tracking in liquids.

cs.LG

Artificial intelligence for online characterization of ultrashort X-ray free-electron laser pulses

X-ray free-electron lasers (XFELs) as the world's brightest light sources provide ultrashort X-ray pulses with a duration typically in the order of femtoseconds. Recently, they have approached and entered the attosecond regime, which holds new promises for single-molecule imaging and studying nonlinear and ultrafast phenomena such as localized electron dynamics. The technological evolution of XFELs toward well-controllable light sources for precise metrology of ultrafast processes has been, however, hampered by the diagnostic capabilities for characterizing X-ray pulses at the attosecond frontier. In this regard, the spectroscopic technique of photoelectron angular streaking has successfully proven how to non-destructively retrieve the exact time-energy structure of XFEL pulses on a single-shot basis. By using artificial intelligence techniques, in particular convolutional neural networks, we here show how this technique can be leveraged from its proof-of-principle stage toward routine diagnostics even at high-repetition-rate XFELs, thus enhancing and refining their scientific accessibility in all related disciplines.

physics.data-an

Three-dimensional close-to-substrate trajectories of magnetic microparticles in dynamically changing magnetic field landscapes

The transport of magnetic nano- or microparticles in microfluidic devices using artificially designed magnetic field landscapes (MFL) is promising for the implementation of key functionalities in Lab-on-a-chip (LOC) systems. A close-to-substrate transport is hereby instrumental to use changing particle-substrate interactions upon analyte binding for analytics and diagnostics. Here, we present an essential prerequisite for such an application, namely the label-free quantitative experimental determination of the three-dimensional trajectories of superparamagnetic particles (SPP) transported by a dynamically changing MFL above a topographically flat substrate. The evaluation of the SPP sharpness within defocused video-recorded images, acquired by an optical bright-field microscope, was employed to obtain a vertical z-coordinate. This method applied to a prototypical transport scheme, using the static MFL of parallel-stripe domains superposed by a particular magnetic field pulse sequence, revealed a hopping-like motion of the magnetic particles, previously predicted by theory. Maximum vertical particle jumps of several micrometers have been observed experimentally, corroborating theoretical estimates for the particle-substrate distance. As our findings pave the way towards precise quantification of particle-substrate separations in the discussed transport system, they bear deep implications for future LOC detection schemes using only optical microscopy.

physics.app-ph

Translatory and rotatory motion of Exchange-Bias capped Janus particles controlled by dynamic magnetic field landscapes

Magnetic Janus particles (MJPs), fabricated by covering a non-magnetic spherical particle with a hemispherical magnetic in-plane exchange-bias layer system cap, display an onion magnetization state for comparably large diameters of a few microns. In this work, the motion characteristics of these MJPs will be investigated when they are steered by a magnetic field landscape over prototypical parallel-stripe domains, dynamically varied by superposed external magnetic field pulse sequences, in an aqueous medium. We demonstrate, that due to the engineered magnetization state in the hemispherical cap, a comparably fast, directed particle transport and particle rotation can be induced. Additionally, by modifying the frequency of the applied pulse sequence and the strengths of the individual field components, we observe a possible separation between a combined or an individual occurrence of these two types of motion. Our findings bear importance for lab-on-a-chip systems, where particle immobilization on a surface via analyte bridges shall be used for low concentration analyte detection and a particle rotation over a defined position of a substrate may dramatically increase the immobilization (and therefore analyte detection) probability.

physics.app-ph

Transport efficiency of biofunctionalized magnetic particles tailored by surfactant concentration

Controlled transport of surface functionalized magnetic beads in a liquid medium is a central requirement for the handling of captured biomolecular targets in microfluidic lab-on-chip biosensors. Here, the influence of the physiological liquid medium on the transport characteristics of functionalized magnetic particles and on the functionality of the coupled protein is studied. These aspects are theoretically modeled and experimentally investigated for prototype superparamagnetic beads, surface functionalized with green fluorescent protein immersed in buffer solution with different concentrations of a surfactant. The model reports on the tunability of the steady-state particle substrate separation distance to prevent their surface sticking via the choice of surfactant concentration. Experimental and theoretical average velocities are discussed for a ratchet like particle motion induced by a dynamic external field superposed on a static locally varying magnetic field landscape. The developed model and experiment may serve as a basis for quantitative forecasts on the functionality of magnetic particle transport based lab-on-chip devices.

cond-mat.soft

AdaPT: Adaptable Particle Tracking for Spherical Microparticles in Lab on Chip Systems

Due to its rising importance in science and technology in recent years, particle tracking in videos presents itself as a tool for successfully acquiring new knowledge in the field of life sciences and physics. Accordingly, different particle tracking methods for various scenarios have been developed. In this article, we present a particle tracking application implemented in Python for, in particular, spherical magnetic particles, including superparamagnetic beads and Janus particles. In the following, we distinguish between two sub-steps in particle tracking, namely the localization of particles in single images and the linking of the extracted particle positions of the subsequent frames into trajectories. We provide an intensity-based localization technique to detect particles and two linking algorithms, which apply either frame-by-frame linking or linear assignment problem solving. Beyond that, we offer helpful tools to preprocess images automatically as well as estimate parameters required for the localization algorithm by utilizing machine learning. As an extra, we have implemented a technique to estimate the current spatial orientation of Janus particles within the x-y-plane. Our framework is readily extendable and easy-to-use as we offer a graphical user interface and a command-line tool. Various output options, such as data frames and videos, ensure further analysis that can be automated.

physics.data-an