Digital Twin Dynamics (DTD) is a peer-reviewed, interdisciplinary journal dedicated to advancing the science, engineering, and applications of digital twin technology across industries. Digital twin, virtual replicas of physical systems that are enabled by real-time monitoring, simulation, and optimization, are transforming fields such as manufacturing, healthcare, smart cities, and aerospace. DTD provides a platform for cutting-edge research on the development, validation, and deployment of digital twins, emphasizing AI-driven modeling, real-time data integration, and cyber-physical system interoperability. View full aims and scope