Low-temperature plasma-processing technologies are essential for material synthesis and
device fabrication. Not only the utilization but also the development of plasma-related …

Abstract Machine learning (ML) and artificial intelligence have proven to be an invaluable
tool in tackling a vast array of scientific, engineering, and societal problems. The main …

This roadmap reviews the new, highly interdisciplinary research field studying the behavior
of condensed matter systems exposed to radiation. The Review highlights several recent …

Low temperature plasmas (LTPs) enable to create a highly reactive environment at near
ambient temperatures due to the energetic electrons with typical kinetic energies in the …

Managing divertor plasmas is crucial for operating reactor scale tokamak devices due to
heat and particle flux constraints on the divertor target. Simulation is an important tool to …

Machine learning has had an enormous impact in many scientific disciplines. It has also
attracted significant interest in the field of low-temperature plasma (LTP) modeling and …

We study the 2D Orszag–Tang vortex magnetohydrodynamics (MHD) problem through the
use of physics-constrained convolutional neural networks (PCNNs) for forecasting the …

Simulations of Al thin film sputter depositions rely on accurate plasma and surface
interaction models. Establishing the latter commonly requires a higher level of abstraction …

Due to their cost, experiments for inertial confinement fusion (ICF) heavily rely on numerical
simulations to guide design. As simulation technology progresses, so too can the fidelity of …

Bayesian optimization has shown promise for the design optimization of inertial confinement
fusion targets. Specifically, in Vazirani et al.[Phys. Plasmas 28, 122709 (2021)], optimal …