Thomas Jonathan E, Stapelmann Katharina
Department of Nuclear Engineering, North Carolina State University, Raleigh, NC 27695, USA.
Plasma (Basel). 2024 Jun;7(2):386-426. doi: 10.3390/plasma7020022. Epub 2024 May 27.
Cold atmospheric plasmas (CAPs) within recent years have shown great promise in the field of plasma medicine, encompassing a variety of treatments from wound healing to the treatment of cancerous tumors. For each subsequent treatment, a different application of CAPs has been postulated and attempted to best treat the target for the most effective results. These treatments have varied through the implementation of control parameters such as applied settings, electrode geometries, gas flow, and the duration of the treatment. However, with such an extensive number of variables to consider, scientists and engineers have sought a means to accurately control CAPs for the best-desired effects in medical applications. This paper seeks to investigate and characterize the historical precedent for the use of plasma control mechanisms within the field of plasma medicine. Current control strategies, plasma parameters, and control schemes will be extrapolated through recent developments and successes to gain better insight into the future of the field and the challenges that are still present in the overall implementation of such devices. Proposed approaches, such as data-driven machine learning, and the use of closed-loop feedback controls, will be showcased as the next steps toward application.
近年来,低温大气等离子体(CAPs)在等离子体医学领域展现出了巨大的潜力,涵盖了从伤口愈合到癌症肿瘤治疗等多种治疗方法。对于每一种后续治疗,人们都提出并尝试了不同的CAPs应用方式,以最佳地治疗目标,从而获得最有效的结果。这些治疗方法通过应用设置、电极几何形状、气体流量和治疗持续时间等控制参数的实施而有所不同。然而,由于需要考虑如此众多的变量,科学家和工程师们一直在寻求一种方法,以便在医疗应用中准确控制CAPs,以达到最理想的效果。本文旨在研究和描述等离子体医学领域中使用等离子体控制机制的历史先例。通过近期的发展和成功案例,将推断当前的控制策略、等离子体参数和控制方案,以便更好地洞察该领域的未来以及此类设备全面实施中仍然存在的挑战。诸如数据驱动的机器学习和闭环反馈控制等拟议方法将作为迈向应用的下一步展示出来。