标题： 机器学习在材料离子束分析中的应用 显示英文标题

标题： Applications of machine learning in ion beam analysis of materials

摘要： 离子束分析（IBA）是一组经过验证的分析技术，利用快速离子束（动能通常在数百keV到几十MeV范围内）与物质的相互作用，以获得材料近表面区域的元素组成和深度分布。 机器学习是材料科学领域最重要的工具之一，它可以提取有价值的见解，做出数据驱动的决策，并提高整体生产力，使其成为当今快速发展的科学中的关键工具。 在本文中，我总结了机器学习算法（MLA）在IBA中的应用现状，并展示了采用这项技术可能带来的好处。 显示英文摘要

摘要： Ion beam analysis (IBA) is a set of well-established analytical techniques that exploit interactions of swift ion beams (with kinetic energy typically in the order of hundreds of keV up to tens of MeV) with matter, in order to obtain elemental composition and depth profiles in the near-surface region of materials. Machine learning is one of the most important tools in the field of material science, where it can extract valuable insights, make data-driven decisions, and improve overall productivity, making it a vital tool in today's rapidly evolving science. In this paper, I summarize the current status of application of Machine Learning Algorithms (MLA) on IBA and demonstrate what kind of benefits we may have by embracing this technology.