エピソード

  • Proxima Fusion and the Transition to Industry

    Proxima Fusion and the Transition to Industry
    2023/11/13
    An inspiring conversation with Dr. Francesco Sciortino, co-founder and CEO of Proxima Fusion, which is a start-up company aiming to design and build an optimized stellerator fusion device. Join us as he illuminates the reasoning behind their bold conceptual design and their vision of a sleek optimization stack combining simulation software and hardware manufacturing. He also shares some personal wisdom and stories about moving beyond the scientific domain and into entrepreneurship. For those wishing to learn more about or get involved with Proxima, check out their website: https://www.proximafusion.com.

    Hosted on Acast. See acast.com/privacy for more information.
    続きを読む 一部表示
    46 分
  • A Novel Data Platform for Plasma Physics

    A Novel Data Platform for Plasma Physics
    2023/10/29
    In this episode, Daan J. Boer (PhD student at TU Eindhoven) talks about a novel data platform called LXCat-3. The platform is supposed to replace the current version of the well-established LXCat to provide atomic and molecular data, such as electron impact cross sections and measured transport parameters, that are fundamental for the low temperature plasmas (LTP) community. The conversation starts by defining standards for plasma modeling and simulations. We talk about the importance of LXCat for the LTP community and novel approaches for improving this platform. Then, we present the first tutorial of the LXCat-3 platform and we discuss future developments of databases for sets of reaction mechanisms beyond charged-neutral particles interaction.

    Hosted on Acast. See acast.com/privacy for more information.
    続きを読む 一部表示
    56 分
  • Containing a Star: A Control Problem?

    Containing a Star: A Control Problem?
    2023/08/29
    This episode features Dr. Simon van Mulders, a recent graduate from École Polytechnique Fédérale de Lausanne (EPFL) who specialized in model-based optimization of tokamak plasma scenarios. After the release of the DeepMind article about using ML models for plasma shape control, a new wave of interest has surged into the development of advanced plasma control algorithms, which take advantage of model-based techniques for plasma state estimation. Join us as we delve into the world of control engineering, the application of plasma physics models within, and its contributions towards the goal of harnessing the power of the sun.

    Hosted on Acast. See acast.com/privacy for more information.
    続きを読む 一部表示
    56 分
  • A Pedestal Worth Keeping

    A Pedestal Worth Keeping
    2023/06/26
    This episode features Dr. Teobaldo Luda, a plasma physicist at IPP Garching who specializes in the modelling of a enigmatic aspect of a high-performance fusion plasma, the plasma pedestal. Join us as he lays out the known facts about this feature, why it is still an open field of research, and his approach to modelling it without the existence of a generalized theory to describe it.

    Hosted on Acast. See acast.com/privacy for more information.
    続きを読む 一部表示
    47 分
  • Machine Learning in Surface Science

    Machine Learning in Surface Science
    2023/06/05
    In this episode, Tobias Gergs (Ruhr University Bochum, Germany) talks about machine learning (ML) in low temperature plasmas. First, we introduce the concepts of ML and deep learning. Then, we give some examples of work on ML for plasma processing applications focusing on plasma sputtering and deposition. At the end of the episode, we discuss about the role of ML for plasma science and give some suggestions for students and researchers interested on these topics.

    Hosted on Acast. See acast.com/privacy for more information.
    続きを読む 一部表示
    55 分
  • Experiences from Women in Science

    Experiences from Women in Science
    2023/05/11
    This episode brings on two PhD students from the DIFFER institute, Maria Morbey and Laura Fumagalli, who have taken a brave step in agreeing to openly share their experiences about being women in the (currently) largely male-dominated field of STEM research. This represents our effort to bring more honest conversations in the realm of gender disparity within the scientific field, with the intent of constructively discussing these potentially controversial topics with the nuance they deserve. We hope that this conversation proves enlightening to all researchers and encourage any and all to contribute via comments and feedback, especially as the future of scientific collaboration begins to depend more and more on successfully addressing these issues.

    Hosted on Acast. See acast.com/privacy for more information.
    続きを読む 一部表示
    1 時間 27 分
  • Accelerating Fusion with Machine Learning

    Accelerating Fusion with Machine Learning
    2023/03/29
    This episode features Lorenzo Zanisi, a data scientist working at the United Kingdom Atomic Energy Authority (UKAEA) to apply machine learning models to accelerate fusion computations. Our conversation covers some brief introduction to the concepts of machine learning (ML), its distinction from artificial intelligence (AI) and traditional statistical modelling, and finally some examples of how it is being / could be applied to accelerate fusion science. With the emergence of more and more powerful ML models, we both envision this topic becoming more and more prevalent in the coming decade

    Hosted on Acast. See acast.com/privacy for more information.
    続きを読む 一部表示
    1 時間 11 分
  • The Outer Rim of the Plasma

    The Outer Rim of the Plasma
    2023/03/15
    In this episode, we talk about turbulent transport in tokamak boundaries with Dr. Maurizio Giacomin (University of York, UK). We introduce the main equations, assumptions, and numerical methods that are used to describe transport in tokamaks boundaries. Furthermore, a novel theory-based density scaling law is explained and its importance for design of future machines is discussed. At the end of the episode, we share our opinions on teaching and student supervisions.

    Hosted on Acast. See acast.com/privacy for more information.
    続きを読む 一部表示
    1 時間 11 分