材料科学中的科学AI：通往可持续和可扩展范式的道路
Scientific AI in materials science: a path to a sustainable and scalable paradigm
摘要：
最近，在材料科学、凝聚态物理和化学社区中，机器学习（ML）和人工智能（AI）方法的使用有不断增长的趋势。这篇观点文章确定了材料界必须优先考虑的关键科学，技术和社会机会，以持续开发和利用科学人工智能，为推进当前材料有限的技术提供可靠的途径。在这里，我们强调了这些机会的交叉点，并提出了一系列前进的道路。机会大致从科学/技术（例如，发展鲁棒的、物理上有意义的多尺度材料表示）到社会（例如，促进人工智能就绪的劳动力）。拟议的前进道路包括开发新的基础设施和能力，以及在工业和学术界部署它们。我们简要介绍了人工智能在材料科学和工程中的应用，然后详细讨论了每一个机会和前进的道路。
英文摘要：
Recently there has been an ever-increasing trend in the use of machine learning (ML) and artificial intelligence (AI) methods by the materials science, condensed matter physics, and chemistry communities. This perspective article identifies key scientific, technical, and social opportunities that the materials community must prioritize to consistently develop and leverage Scientific AI to provide a credible path towards the advancement of current materials-limited technologies. Here we highlight the intersections of these opportunities with a series of proposed paths forward. The opportunities are roughly sorted from scientific/technical (e.g., development of robust, physically meaningful multiscale material representations) to social (e.g., promoting an AI-ready workforce). The proposed paths forward range from developing new infrastructure and capabilities to deploying them in industry and academia. We provide a brief introduction to AI in materials science and engineering, followed by detailed discussions of each of the opportunities and paths forward.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
