Tunable X-ray sources from a laser-driven wakefield have wide applications. However, due to the difficulty of electron dynamics control, currently the tunability of laser wakefield-based X-ray sources is still difficult. By using three-dimensional particle-in-cell simulations, we propose a scheme to realize controllable electron dynamics and X-ray radiation. In the scheme, a long wavelength drive pulse excites a plasma wake and an off-axis laser pulse with a short wavelength co-propagates with the drive pulse and ionizes the K-shell electrons of the background high-Z gas. The electrons can be injected in the wakefield with controllable transverse positions and residual momenta. These injected electrons experience controllable oscillations in the wake, leading to tunable radiations both in intensity and polarization.
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http://dx.doi.org/10.1364/OE.404723 | DOI Listing |
J Am Chem Soc
January 2025
Chemical Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States.
Hydrogen spillover is an important process in catalytic hydrogenation reactions, facilitating H activation and modulating surface chemistry of reducible oxide catalysts. This study focuses on the unveiling of platinum-induced hydrogen spillover on monoclinic tungsten trioxide (γ-WO), employing ambient pressure X-ray photoelectron spectroscopy, density functional theory calculations and microkinetic modeling to investigate the dynamic evolution of surface states at varied temperatures. At room temperature, hydrogen spillover results in the formation of W and hydrogen intermediates (hydroxyl species and adsorbed water), facilitated by Pt metal clusters.
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Seibersdorf Labor GmbH, Seibersdorf, Austria.
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View Article and Find Full Text PDFJ Gen Intern Med
January 2025
Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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View Article and Find Full Text PDFSci Rep
January 2025
University Paris-Saclay, CEA, CNRS, Neurospin, Baobab UMR 9027, Gif-sur-Yvette, 91191, France.
Recent advances highlight the limitations of classification strategies in machine learning that rely on a single data source for understanding, diagnosing and predicting psychiatric syndromes. Moreover, approaches based solely on clinician labels often fail to capture the complexity and variability of these conditions. Recent research underlines the importance of considering multiple dimensions that span across different psychiatric syndromes.
View Article and Find Full Text PDFSci Rep
January 2025
Physical Chemistry Department, National Research Centre, 33 El Bohouth Street, P.O.12622, Dokki, Giza, Egypt.
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