Thursday, October 29, 2026

Ewha uses AI to make a material weakened by vibration damping 19 times stronger

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2026-10-28 16:38:28
Updated
2026-10-28 16:38:28
Photo of the joint research team led by Professor Lee Sang-ryun at Ewha Womans University. From left: Professor Lee Sang-ryun, doctoral student Yoon Hyo-ui, master’s student Park Chae-won, doctoral student Lee Tae-geon of the Korea Research Institute of Standards and Science (KRISS), and KRISS researcher Choi Won-jae. Courtesy of Ewha Womans University.

[Financial News] A new type of metamaterial has been developed using artificial intelligence (AI) to effectively block vibrations while dramatically increasing its strength, or how sturdy an object is.
A team led by Professor Lee Sang-ryun of the Department of Human-Machine-Bio Engineering at Ewha Womans University said on the 28th that, in a joint study with the Korea Research Institute of Standards and Science (KRISS), it had developed a lightweight elastic metamaterial that blocks vibrations across a wide frequency range while significantly improving its ability to withstand loads.
Vibrations are a major cause of fatigue damage to components and reduced equipment performance in fields such as aerospace, automobiles and precision machinery. Special artificial structures that suppress the transmission of vibrations have been used to address this problem. However, existing technologies required structures to be made thinner or separate weights to be added in order to effectively block vibrations. This weakened the structures themselves, limiting their practical use in industry.
The research team overcame these limitations by applying a machine-learning-based AI optimization technique. Without adding separate weights, the team designed the shape itself so that the thickness within the structure changes smoothly, achieving both vibration-blocking performance and structural stiffness.
Tests on actual structures made using 3D printing showed that the metamaterial developed by the team blocked vibrations across a frequency range at least twice as wide as that of existing structures. At the same time, its strength in withstanding loads was found to be up to 18.9 times that of existing structures.
Ewha Womans University Professor Lee Sang-ryun said, “This study demonstrates that AI-based shape optimization can improve vibration-blocking performance and structural stability at the same time.” He added, “I expect it to be widely applied in various industrial settings, including aerospace, automobiles and precision machinery, where both lightweighting and vibration control are required.”
The findings were recently published online in the international mechanical engineering journal Thin-Walled Structures.

[email protected] Kim Man-gi Reporter