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Lattice Centering and Coordination Number02:33

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The structure of a crystalline solid, whether a metal or not, is best described by considering its simplest repeating unit, which is referred to as its unit cell. The unit cell consists of lattice points that represent the locations of atoms or ions. The entire structure then consists of this unit cell repeating in three dimensions. The three different types of unit cells present in the cubic lattice are illustrated in Figure 1.
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Related Experiment Video

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Multi-material Ceramic-Based Components – Additive Manufacturing of Black-and-white Zirconia Components by Thermoplastic 3D-Printing (CerAM - T3DP)
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Lattice Genome Framework for Regionally Tailored Component-Level Multi-Objective Design in Additive Manufacturing.

Haoyuan Deng1, Yufan Zhao1,2, Mingyang Cao1

  • 1State Key Laboratory of Solidification Processing, Northwestern Polytechnical University, Xi'an, P. R. China.

Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|February 15, 2026
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Summary

This study introduces a data-driven Lattice Genome framework to accelerate the design of advanced lattice structures. This approach enables precise control over mechanical properties for additive manufacturing applications.

Keywords:
additive manufacturinglattice structuresmaterials genome initiativemechanical properties

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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.