Lattice Genome Framework for Regionally Tailored Component-Level Multi-Objective Design in Additive Manufacturing

Area of Science:

• Materials Science
• Mechanical Engineering
• Computational Materials Design

Background:

• Additive manufacturing enables complex lattice structures with potential for lightweight design and functional integration.
• Vast design spaces and complex structure-property relationships hinder efficient development of these lattices.

Purpose of the Study:

• To establish a data-driven framework, termed Lattice Genome, for systematic mapping of lattice properties.
• To develop a component-level, regionally programmable, multi-objective design strategy for coordinated structure-property regulation.

Main Methods:

• Integration of high-throughput simulations and performance databases.
• Development of a data-centric platform for intelligent lattice design.
• Application of a multi-objective design strategy for tailored stress distribution and enhanced load capacity.

Main Results:

• Demonstrated tailoring of internal stress distributions to match target values.
• Achieved a 62% increase in load capacity in cavity-containing components compared to conventional designs.
• Redirected failure mechanisms away from critical zones in complex lattice components.

Conclusions:

• The Lattice Genome framework offers a generalizable and scalable paradigm for intelligent lattice design.
• This data-centric platform facilitates efficient and multifunctional applications in additive manufacturing.
• The approach enables coordinated regulation of structure and properties for optimized performance.