In recent years, the tremendous progress in AI is leading a radical shift of AI research from a mainly academic endeavor to a much broader field with increasing industrial and governmental investments. The maturation of AI technology brings about a step change in the scientific research of various domains, especially in the world of materials and design. Machine learning (ML) algorithms enable researchers to analyze extensive datasets on material properties and accurately predict their behavior in different conditions. This subsequently impact the industry to leverage on big data and advanced analytics to build scientific strategies, scale operational performance of processes and drive innovation. In addition, AI and ML are uniquely positioned to enable advanced manufacturing technologies across the value chain of different industries. Integration of multiple and complementary AI techniques, such as ML, search, reasoning, planning, and knowledge representation, will further accelerate advances in scientific discoveries, engineering excellence and the future of cyber-physical systems manufacturing.
This journal focuses on the impact of machine learning on the following topics, but is not limited to:
- AI or machine learning for material discovery
- AI for process optimization
- AI and data-driven approaches for product or systems design
- Application of AI in advanced manufacturing processes such as additive manufacturing, IoT, sensors, robotics
- Cloud-based manufacturing
- Intelligent manufacturing for various applications including biotechnology, energy
- Autonomous experiments
- Material Intelligence
- Energy Intelligence
- AI-linked decarbonization technologies