論文 High-throughput micro-indentation method for temperature-dependent static and dynamic characterization of structural adhesives

Chao Kang ; Yoichi Okamoto ; Ming Ji ; Keiyu Ikeda ; Yu Sekiguchi ; Masanobu Naito SAMURAI ORCID (National Institute for Materials Science) ; Chiaki Sato

コレクション

引用
Chao Kang, Yoichi Okamoto, Ming Ji, Keiyu Ikeda, Yu Sekiguchi, Masanobu Naito, Chiaki Sato. High-throughput micro-indentation method for temperature-dependent static and dynamic characterization of structural adhesives. POLYMER TESTING. 2026, 155 (), 109093. https://doi.org/10.1016/j.polymertesting.2026.109093

説明:

(abstract)

Characterizing the temperature-dependent mechanical properties of polymeric
materials is critical for industrial applications in aerospace, automotive, and electronics.
The increasing integration of artificial intelligence (AI) in material discovery has
amplified the demand for large, high-quality datasets, which conventional mechanical
testing methods often cannot efficiently provide. In this study, we introduce a novel
micro-indentation method that enables rapid and accurate evaluation of static and
dynamic mechanical properties of polymeric materials across a wide temperature range.
The technique enables independent and precise temperature control of the indenter and
bulk samples, ensuring reliable measurements with minimal preparation. Static
indentation tests on epoxy and acrylic samples demonstrated that the elastic modulus can
be accurately obtained from unloading data, even with plastic deformation, using the
Oliver–Pharr method. Dynamic testing further revealed that the epoxy exhibited higher
storage and loss moduli than the acrylic adhesive, indicating superior mechanical
performance at elevated temperatures. Conversely, the acrylic adhesive exhibited a lower
glass transition temperature, indicating a narrower operational temperature range, and a
higher loss factor, reflecting greater energy dissipation. The proposed method enhances
the efficiency and accuracy of mechanical characterization, enabling the high-throughput
testing necessary to generate datasets for AI-driven material development. By enabling
rapid design and optimization of polymers, this technique is promising for advancing
material discovery with tailored properties.

権利情報:

キーワード: Indentation , Materials informatics, Dynamic mechanical analysis , Viscoelasticity , High-throughput Polymer mechanics

刊行年月日: 2026-01-09

出版者: Elsevier BV

掲載誌:

  • POLYMER TESTING (ISSN: 01429418) vol. 155 109093

研究助成金:

  • Japan Science and Technology Agency
  • National Natural Science Foundation of China

原稿種別: 出版者版 (Version of record)

MDR DOI:

公開URL: https://doi.org/10.1016/j.polymertesting.2026.109093

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更新時刻: 2026-01-20 10:50:27 +0900

MDRでの公開時刻: 2026-01-20 12:22:54 +0900

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