About this Research Topic
This Research Topic aims to investigate the latest advancements in composite materials, focusing on the integration of fillers and polymers with Machine Learning (ML) technologies to revolutionize the development and application of advanced composites. The primary goal is to explore how ML can streamline the prediction and optimization of composite material behaviors, thereby expediting the design and testing phases. Through such integrations, the research seeks to not only refine the performance of composites but also tailor their properties to meet specific demands in high-stakes applications such as aerospace and automotive components.
To enhance our understanding of the current capabilities and future potential of advanced composites in critical sectors, this topic will limit its focus primarily to the use of Machine Learning in the development and application of these materials. We invite research that addresses themes such as:
- Development of Filler-Based Advanced Composites
- Application of Machine Learning in Predicting Composite Properties
- Mechanical Performance Studies (e.g., Tensile Strength, Flexural Strength, Impact Strength, Hardness)
- Tribo-Performance Analysis of Filler-Based Composites (e.g., Wear, Erosion, Corrosion Resistance)
- Advanced Composite Materials for Aerospace Applications and Their Characterization
- Characterization Techniques for Fillers and Polymers
- Structural Analysis and Predictive Modeling
- Sustainable and Recycled Fillers for Environmentally Friendly Composites
This scope seeks contributions that push the boundaries of traditional and modern composites research, utilizing both novel studies and comprehensive reviews to expand the knowledge base.
Keywords: Advanced Composites, Fillers, Polymers, Machine Learning, Structural Applications, Aerospace, Automotive, Predictive Modeling, Sustainable Materials
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.