Milestone reflects growing influence of two emerging AIP Publishing journals

MELVILLE, N.Y., June 18, 2026 — AIP Publishing is celebrating a major milestone for two of its newest open access journals, APL Energy and APL Machine Learning, which have each received their first Journal Impact Factor™ (JIF™) in the 2025 edition of Clarivate’s Journal Citation Reports™.

APL Energy received an inaugural Journal Impact Factor of 4.4, while APL Machine Learning received an inaugural Impact Factor of 4.1. This is an important achievement for both journals and reflects the growing visibility and citation impact of the research they publish.

Published annually by Clarivate, the Journal Impact Factor is one of the most widely recognized journal metrics in scholarly publishing. It measures the average number of citations received by a journal’s recent articles and is often used by researchers, institutions, and funders as one indicator of a journal’s influence within its field, alongside other qualitative and quantitative measures.

Launched in 2023, APL Energy publishes interdisciplinary research advancing the science and technology needed to address global energy challenges. The journal brings together discoveries spanning energy generation, conversion, storage, and utilization.

“We are proud to celebrate APL Energy’s first Journal Impact Factor, an important milestone for our journal,” said Mónica Lira-Cantú, founding editor-in-chief of APL Energy. “This achievement reflects the dedication of all our authors and the quality and impact of the research we publish. Thank you everyone for your support and for being part of the APL Energy community.”

APL Machine Learning, also launched in 2023, serves as a venue for research at the intersection of machine learning, artificial intelligence, and the physical sciences, including both methodological advances and scientific applications enabled by data-driven approaches.

“While no single metric tells the whole story, receiving our first Journal Impact Factor is an encouraging sign that the research published in APL Machine Learning is being read, used, and built upon by researchers across disciplines,” said Adnan Mehonic, founding editor-in-chief of APL Machine Learning. “This milestone reflects the creativity of a growing community bringing machine learning and the physical sciences together in new ways.”

“The first Journal Impact Factor is a defining moment for any new journal,” said Melissa Patterson, Head of Journal Portfolio Development at AIP Publishing. “These results demonstrate the strength of the communities that have embraced APL Energy and APL Machine Learning and the outstanding contributions of the authors, reviewers, editors, and editorial board members who have helped establish these journals.”

Both journals were launched as part of the APL family of open access publications, which provides high-impact platforms for emerging and interdisciplinary areas of research.

About APL Energy

APL Energy publishes high-quality, interdisciplinary research spanning the science and technology of energy generation, conversion, storage, and utilization. The journal serves researchers working to develop solutions to the world’s evolving energy needs and disseminates work that bridges fundamental research and technological innovation.

About APL Machine Learning

APL Machine Learning publishes timely research advancing machine learning and artificial intelligence methods, as well as their applications across the physical sciences, engineering, and related disciplines.

About AIP Publishing

AIP Publishing’s mission is to advance, promote, and serve the physical sciences for the benefit of humanity by breaking barriers to open, fair research communication and empowering researchers to accelerate global progress. AIP Publishing is a wholly owned not-for-profit subsidiary of the American Institute of Physics (AIP) and supports the charitable, scientific, and educational purposes of AIP through scholarly publishing activities on its behalf and on behalf of our publishing partners.