WeChat Mini Program
Old Version Features

    • Focusing Effects on Laser-Induced Plasma Parameters: Applications to a Graphite Target under Martian Atmospheric Conditions

    Kouider Benbaier,Ahmed Abdelmalek,Zeyneb Bedrane,Noureddine Melikechi

    APPLIED SPECTROSCOPY（2025）

    Tlemcen Univ

    Cited 0|Views3
    Abstract
    Under various atmospheric conditions, laser-induced breakdown spectroscopy (LIBS) is a powerful technique for elemental analysis, including in Earth- and Mars-like environments. However, understanding the plasma behavior and its dependence on ambient pressure and laser parameters remains a challenge. In this study, a numerical model based on a three-temperature Eulerian radiation framework under non-local thermodynamic equilibrium conditions is employed to investigate the interaction of a nanosecond laser pulse with a graphite target under helium (He) and carbon dioxide (CO2 atmospheres. The aim is to provide insights into the effects of focusing conditions and ambient pressure (3 to 9 mbar and 1000 mbar) on plasma parameters relevant to both Earth- and Mars-like settings. Our results show that increased ambient pressure significantly enhances electron and ion densities, while the focusing conditions influence the temperature and fluid velocity of plasma species, as well as the spatial distribution and intensity of the plasma, ultimately affecting its diagnostic potential. These findings are critical for optimizing LIBS applications in planetary exploration and contribute to improving quantitative analyses under varying atmospheric compositions.
    More
    Translated text
    Key words
    Laser-induced breakdown spectroscopy plasma,LIBS plasma,non-local thermodynamic equilibrium,NLTE approach,focusing conditions,ambient gas,plasma parameters
    求助PDF
    上传PDF
    View via Publisher
    Bibtex
    AI Read Science
    AI Summary
    AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
    Example
    Background
    Key content
    Introduction
    Methods
    Results
    Related work
    Fund
    Key content
    • Pretraining has recently greatly promoted the development of natural language processing (NLP)
    • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
    • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
    • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
    • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
    Upload PDF to Generate Summary
    Must-Reading Tree
    Example
    Generate MRT to find the research sequence of this paper
    Data Disclaimer
    The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
    Chat Paper
    Summary is being generated by the instructions you defined