APL Machine Learning

APL Machine Learning is a peer-reviewed open-access journal published by AIP Publishing that serves research at the intersection of machine learning and the physical sciences, launched in 2023, and its 2025 Journal Impact Factor is 4.1《APL 机器学习》（APL Machine Learning）是（AIP Publishing）出版的同行评审开放获取期刊，服务于机器学习与物理科学交叉领域的研究，2023 年创刊，2025 年影响因子为 4.1。

Scope

• It serves researchers who use machine learning and data-driven approaches for the physical sciences and related disciplines该刊面向运用机器学习与数据驱动方法开展物理科学及相关学科研究的科研人员。
• It also serves researchers developing novel materials, devices, systems and algorithms for better machine learning该刊亦面向为改进机器学习而开发新材料、器件、系统与算法的研究者。
• It considers quantitative models and theories, especially when validated with experimental results该刊接收定量模型与理论，尤其是在实验验证情形下的成果。
• Applications span physics, materials science, chemistry and engineering其应用横跨物理学、材料科学、化学与工程学。
• It publishes methodological advances alongside scientific applications of artificial intelligence该刊既发表方法学进展，也发表人工智能的科学应用。
• That includes both methodological and applied contributions at the AI and physical sciences interface这包括人工智能与物理科学交汇处的方法学与应用性成果。

History

• APL Machine Learning published its first issue in 2023《APL 机器学习》于 2023 年出版创刊号。
• It was launched by AIP Publishing as an open-access journal for the machine learning and physical sciences community该刊由（AIP Publishing）作为面向机器学习与物理科学界的开放获取期刊创办。
• Its founding Editor-in-Chief, Dr. Adnan Mehonic, was appointed ahead of the launch其创刊主编（Adnan Mehonic）博士在创刊前即获任命。
• It appears quarterly, with issues dated March, June, September and December该刊为季刊，出版月份为三月、六月、九月与十二月。
• It received its first Journal Impact Factor after beginning to be indexed该刊在开始被收录后获得了首个期刊影响因子。
• Its 2025 Journal Impact Factor is 4.1该刊 2025 年影响因子为 4.1。

Editors

• The Editor-in-Chief is Dr. Adnan Mehonic of University College London, United Kingdom主编为（Adnan Mehonic）博士，任职于英国伦敦大学学院。
• Mehonic works on neuromorphic computing, memristors and hardware for artificial intelligence（Mehonic）研究神经形态计算、忆阻器以及面向人工智能的硬件。
• Associate editors and an editorial board drawn from physics, materials and computer science support the journal来自物理、材料与计算机科学的副编辑与编委会支撑该刊。
• Articles are peer reviewed and are published open access under a Creative Commons licence文章经同行评审，并以知识共享许可协议开放获取出版。
• Authors submit manuscripts through the AIP Publishing online system作者通过（AIP Publishing）在线系统提交稿件。
• The journal aims to bridge the machine learning and physical sciences communities该刊旨在沟通机器学习与物理科学两个学术共同体。