Topic: Multiscale Computational Design of Materials and Components for Targeted Performance

The development of advanced materials and components is increasingly moving beyond traditional sequential approaches, in which material selection, component design, and manufacturing are treated as separate steps. Computational methods now offer the possibility of considering multiple design scales and variables simultaneously, with the targeted performance of the final material or component as the primary design objective.

This Special Topic focuses on multiscale computational approaches for the performance-driven design of materials and components, spanning length scales from material composition and formulation to microstructure, mesoscale architecture, material distribution, and component geometry. At each scale, different design variables can be explored and optimized to achieve targeted functional, structural, thermal, chemical, or multifunctional performance.

A central challenge is to establish effective links between processing, structure, properties, and performance. In this context, manufacturability is an essential element of the design process rather than a constraint to be considered only after optimization. Manufacturing processes, their capabilities and limitations, and the associated processing conditions should therefore be incorporated into the computational design framework whenever relevant. Computational modelling, optimization, materials informatics, artificial intelligence, and data-driven approaches provide increasingly powerful tools to explore these complex design spaces and to translate computational solutions into manufacturable and experimentally validated materials and components.

Contributions are not expected to address the entire multiscale design chain. Rather, the Special Topic welcomes original research and review articles addressing one or more of the following aspects, provided that they contribute to linking material or component design to targeted performance:

● Computational design and optimization of material composition and formulation;

● Microstructure design and process-structure-property relationships;

● Architected materials, metamaterials, graded and multifunctional structures;

● Multiscale and multiphysics modelling for materials and component design;

● Topology, generative, inverse and field-driven design approaches;

● Materials informatics, machine learning and AI-assisted design;

● Manufacturing-aware computational design and process optimization;

● Translation of computational designs into manufacturable components and experimental validation.

Computational design, performance-driven design, materials design, microstructure, architected materials, process-structure-property-performance relationship, artificial intelligence, additive manufacturing