TY - JOUR
T1 - Lattice Genome Framework for Regionally Tailored Component-Level Multi-Objective Design in Additive Manufacturing
AU - Deng, Haoyuan
AU - Zhao, Yufan
AU - Cao, Mingyang
AU - Yang, Haiou
AU - Wang, Pan
AU - Wang, Hongze
AU - Wang, Hao
AU - Chiba, Akihiko
AU - Lin, Xin
N1 - Publisher Copyright:
© 2026 The Author(s). Advanced Science published by Wiley-VCH GmbH.
PY - 2026/4/17
Y1 - 2026/4/17
N2 - Lattice structures fabricated by additive manufacturing provide unprecedented opportunities for lightweight design, mechanical regulation, and functional integration. However, their efficient development remains constrained by vast design spaces and complex structure–property relationships. Inspired by the Materials Genome Initiative, we propose a Lattice Genome framework, a data-driven approach that integrates high-throughput simulations and performance databases to systematically map lattice properties. Specifically, we develop a component-level, regionally programmable, multi-objective design strategy for coordinated structure–property regulation. The efficacy of the proposed framework is demonstrated through two representative cases: (1) tailoring internal stress distributions to match preset targets under constant relative density, and (2) enhancing load capacity (62% higher than the conventional design) while redirecting failure away from critical zones in cavity-containing components. Overall, this work establishes a generalizable and scalable paradigm for intelligent lattice design and provides a transferable, data-centric platform that lays the groundwork for efficient, multifunctional applications in additive manufacturing.
AB - Lattice structures fabricated by additive manufacturing provide unprecedented opportunities for lightweight design, mechanical regulation, and functional integration. However, their efficient development remains constrained by vast design spaces and complex structure–property relationships. Inspired by the Materials Genome Initiative, we propose a Lattice Genome framework, a data-driven approach that integrates high-throughput simulations and performance databases to systematically map lattice properties. Specifically, we develop a component-level, regionally programmable, multi-objective design strategy for coordinated structure–property regulation. The efficacy of the proposed framework is demonstrated through two representative cases: (1) tailoring internal stress distributions to match preset targets under constant relative density, and (2) enhancing load capacity (62% higher than the conventional design) while redirecting failure away from critical zones in cavity-containing components. Overall, this work establishes a generalizable and scalable paradigm for intelligent lattice design and provides a transferable, data-centric platform that lays the groundwork for efficient, multifunctional applications in additive manufacturing.
KW - additive manufacturing
KW - lattice structures
KW - materials genome initiative
KW - mechanical properties
UR - https://www.scopus.com/pages/publications/105030214431
U2 - 10.1002/advs.202522126
DO - 10.1002/advs.202522126
M3 - 文章
AN - SCOPUS:105030214431
SN - 2198-3844
VL - 13
JO - Advanced Science
JF - Advanced Science
IS - 22
M1 - e22126
ER -