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Machine learning-enabled inverse design of bimaterial thermoelastic lattice metamaterials
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DOI：10.1016/j.compstruct.2026.120398.png)
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Abstract
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• Machine learning-enabled inverse design of thermoelastic lattice metamaterials is proposed. • High-throughput computational homogenization is integrated with machine learning methods. • Forward and inverse machine learning models with good performance are attained. • Multiple inverse design scenarios are demonstrated through representative examples.
Keywords:
inverse design
machine learning
thermoelastic lattice metamaterials
computational homogenization
bimaterial
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