AI-Thermal Fluids (AITF) is an international, peer-reviewed academic journal published by Elsevier B.V. It focuses on research at the intersection of artificial intelligence, thermal-fluid science, and engineering. Launched in 2025, the journal provides a platform for researchers, academics, and engineers to explore how AI techniques can improve the understanding, prediction, design, optimization, and control of thermal and fluid systems.

The journal covers a broad range of research areas, including machine learning, deep learning, neural networks, computational fluid dynamics, heat transfer, turbulence, multiphase flows, thermophysical properties, energy conversion, materials discovery, and sustainable engineering. It encourages the application of AI methods to experimental research, numerical simulations, engineering design, and complex physical processes.

AI-Thermal Fluids publishes research articles, rapid communications, review articles, letters to the editor, vision articles, original software articles, and data articles. Its interdisciplinary scope supports collaboration between artificial intelligence specialists, thermal engineers, computational scientists, and researchers working on energy and environmental challenges.

The journal aims to advance AI-driven methods in thermal-fluid science and engineering while encouraging innovative solutions for energy efficiency, industrial processes, environmental sustainability, and the development of next-generation engineering technologies.