Special Issue "Plasma Spectroscopy and Plasma Diagnostics: From Classical to Sophisticated Methods"

A special issue of Atoms (ISSN 2218-2004).

Deadline for manuscript submissions: 31 March 2023 | Viewed by 60

Special Issue Editor

Dr. Mohammed Koubiti
E-Mail Website
Guest Editor
Physics of Ionic and Molecular Interactions (PIIM), UMR7345, Aix-Marseille Université—CNRS, Centre Saint Jérôme, Case 232, CEDEX 20, 13397 Marseille, France
Interests: plasma physics; plasma spectroscopy; stark broadening; Zeeman effect; magnetic fusion; diagnostics; machine learning
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Special Issue Information

Dear Colleagues,

The objective of this Special Issue of Atoms, entitled “Plasma Spectroscopy and Plasma Diagnostics: From Classical to Sophisticated Methods”, is to summarize in a single issue all the major techniques and methods which are used in spectroscopy and diagnostics of plasmas from traditional/classical methods to the latest and sophisticated ones, including those combining physical models with artificial intelligence, e.g., machine learning.  It is intended to cover all kinds of plasmas, from astrophysical low-density low-temperature plasmas to high-density high-energy plasmas which are produced in laboratories using intense and ultra-fast laser beams. This Special Issue concerns both magnetized and non-magnetized plasmas, as well as plasmas at thermal equilibrium and those deviating from it. In addition to providing in a single issue/volume all major spectroscopic and diagnostics techniques used in various plasmas for researchers and students, this Special Issue has other aims.  One of these aims is to increase the interactions between communities by sharing the various techniques and ideas related to plasma spectroscopy and plasma diagnostics between these various plasma communities and others, such as atomic physicists. The issue is not limited to plasma physicists but is open to other research and interdisciplinary fields if connected to the topics of this issue. Therefore, we welcome original manuscripts concerning plasma spectroscopy, plasma diagnostics, atomic physics in plasmas, as well as manuscripts connected to these fields.  Manuscripts introducing machine learning in spectroscopic methods and other innovative spectroscopic methods will be appreciated, as well as those describing the state of the art of diagnostic or spectroscopic methods. 

Dr. Mohammed Koubiti
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atoms is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • spectroscopic technics and methods
  • plasma diagnostics
  • atomic physics in plasmas
  • modern diagnostic techniques
  • low-density plasmas
  • low-temperature plasmas
  • high-energy density plasmas
  • machine learning
  • artificial intelligence
  • magnetic fusion
  • astrophysical plasmas

Published Papers

This special issue is now open for submission.
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