Time-resolved, physics-informed neural networks for tokamak total emission reconstruction and modelling

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Future large tokamaks will operate at high plasma currents and high stored plasma energies. To ensure machine protection in case of a sudden loss of plasma confinement (major disruption), a large fraction of the magnetic and thermal energy must be radiated ...

Valorizing CO2 into chemical building blocks via efficient electrified processes could significantly decrease carbon emissions. In this work, a device that allows generation of tunable micro‐plasma modes (arc, pulsed, pulsed arc) on a chip for efficient, l ...

Novel power exhaust solutions are being developed to address the challenge of integrating a high performance fusion core plasma with a well-protected divertor, if the single null configuration does not scale to a reactor device. This work aims to elucidate ...

Differentiable rendering (DR) is an emerging field that facilitates the calculation and propagation of gradients of 3D objects through images. In contrast to deep neural networks (DNNs), which generally lack the understanding of 3D objects that form the im ...

Isolated attosecond pulses from an X-ray free-electron laser are in high demand for attosecond science, which enables the probing of electron dynamics by X-ray nonlinear spectroscopy and single-particle imaging. The aim of this thesis is to simulate attos ...

DT operations at JET gave a unique and invaluable opportunity to design, develop and test real -time controllers that will be applied in future burning plasma devices, as ITER and SPARC. Among them, the dud detector [L. Piron et al. 2019 Fusion Eng. Design ...

Flashover is a major limiting factor for the transmission and miniaturization of high-power microwave (HPM) devices. We conducted a study to investigate the developmental process of surface flashover on HPM dielectric windows through particle-in-cell-Monte ...

Interacting systems are ubiquitous in nature and engineering, ranging from particle dynamics in physics to functionally connected brain regions. Revealing interaction laws is of fundamental importance but also particularly challenging due to underlying con ...

This article presents the development of a neutron noise calculation technique with a reduced calculation time based on the TFM (Transient Fission Matrix) approach. The latter contains different information such as the system transfer function (fission and ...

Purpose: To develop a self-navigated motion compensation strategy for 3D radial MRI that can compensate for continuous head motion by measuring rigid body motion parameters with high temporal resolution from the central k-space acquisition point (self-enco ...

Cavities concentrate light and enhance its interaction with matter. Confining to microscopic volumes is necessary for many applications but space constraints in such cavities limit the design freedom. Here we demonstrate stable optical microcavities by cou ...

Time-resolved, physics-informed neural networks for tokamak total emission reconstruction and modelling

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Low‐Power Tunable Micro‐Plasma Device for Efficient and Scalable CO2 Valorization

X-point radiator and power exhaust control in configurations with multiple X-points in TCV

Inverse Rendering for PET Image Reconstruction

Numerical Study of the Attosecond Free-Electron Laser Pulse Generation in the Soft X-ray Regime at the SwissFEL

Innovative dud detection based on JET DT experience

Investigation of sheath structure in surface flashover induced by high-power microwave

Collective relational inference for learning heterogeneous interactions

Fast simulation of neutron noise using the Transient Fission Matrix approach and validation on the CROCUS reactor

Rapid motion estimation and correction using self-encoded FID navigators in 3D radial MRI

Metasurface-stabilized optical microcavities