2022 review of data-driven plasma science
Data-driven science and technology offer transformative tools and methods to science. This
review article highlights the latest development and progress in the interdisciplinary field of …
review article highlights the latest development and progress in the interdisciplinary field of …
The 2020 plasma catalysis roadmap
Plasma catalysis is gaining increasing interest for various gas conversion applications, such
as CO 2 conversion into value-added chemicals and fuels, CH 4 activation into hydrogen …
as CO 2 conversion into value-added chemicals and fuels, CH 4 activation into hydrogen …
Atmospheric Pressure Plasma Deposition of TiO2: A Review
S Banerjee, E Adhikari, P Sapkota, A Sebastian… - Materials, 2020 - mdpi.com
Atmospheric pressure plasma (APP) deposition techniques are useful today because of their
simplicity and their time and cost savings, particularly for growth of oxide films. Among the …
simplicity and their time and cost savings, particularly for growth of oxide films. Among the …
The 2022 Plasma Roadmap: low temperature plasma science and technology
The 2022 Roadmap is the next update in the series of Plasma Roadmaps published by
Journal of Physics D with the intent to identify important outstanding challenges in the field of …
Journal of Physics D with the intent to identify important outstanding challenges in the field of …
Foundations of machine learning for low-temperature plasmas: methods and case studies
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 …
tool in tackling a vast array of scientific, engineering, and societal problems. The main …
Machine learning for modeling, diagnostics, and control of non-equilibrium plasmas
Abstract Machine learning (ML) is a set of computational tools that can analyze and utilize
large amounts of data for many different purposes. Recent breakthroughs in ML and artificial …
large amounts of data for many different purposes. Recent breakthroughs in ML and artificial …
Interpreting convolutional neural network for real-time volatile organic compounds detection and classification using optical emission spectroscopy of plasma
CY Wang, TS Ko, CC Hsu - Analytica Chimica Acta, 2021 - Elsevier
This study presents the investigation of optical emission spectroscopy of plasma using
interpretable convolutional neural network (CNN) for real-time volatile organic compounds …
interpretable convolutional neural network (CNN) for real-time volatile organic compounds …
Machine learning for advancing low-temperature plasma modeling and simulation
J Trieschmann, L Vialetto… - Journal of Micro …, 2023 - spiedigitallibrary.org
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 …
attracted significant interest in the field of low-temperature plasma (LTP) modeling and …
Efficient plasma-surface interaction surrogate model for sputtering processes based on autoencoder neural networks
T Gergs, B Borislavov, J Trieschmann - Journal of Vacuum Science & …, 2022 - pubs.aip.org
Simulations of thin film sputter deposition require the separation of the plasma and material
transport in the gas phase from the growth/sputtering processes at the bounding surfaces …
transport in the gas phase from the growth/sputtering processes at the bounding surfaces …
Physics-separating artificial neural networks for predicting initial stages of Al sputtering and thin film deposition in Ar plasma discharges
T Gergs, T Mussenbrock… - Journal of Physics D …, 2023 - iopscience.iop.org
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 …
interaction models. Establishing the latter commonly requires a higher level of abstraction …