Deep‐Learning Enhanced SrAl<sub>2</sub>O<sub>4</sub>: (Eu<sup>2+</sup>, Dy<sup>3+</sup>, Nd<sup>3+</sup>) Mechanoluminescence Film for Distributed Perception of Mechanical Deformation and Fracture
Abstract Mechanoluminescence (ML) sensor‐derived distributing measurement urgently needs to overcome the trade‐off between luminous intensity and afterglow duration. In this article, a strontium aluminate (SrAl 2 O 4 ) based ML sensing candidate is controllably synthesized by solid‐solution reaction of powdered precursors of SrCO 3 and Al 2 O 3 under hybrid doping of rare earth cations (Eu 2+ , Dy 3+ , Nd 3+ ) at 1400 °C. Compared with traditional SrAl 2 O 4 : Eu 2+ , SrAl 2 O 4 : (Eu 2+ , Dy 3+ , Nd 3+ ) (SAOEDN) has demonstrated highly enhanced luminous intensity (over two orders increase), robust ML behavior (300 cycles), and tunable afterglow performance (50 to 325 s) after synergistic regulation of trap depth (from 0.2 to 0.88 eV). After in situ compounding of SAOEDN with epoxy resin matrix, a flexible ML sensing film is created for distributed detection of engineering strain distribution. The ML effect triggered by mechanical deformation presented an approximately linear dependence between strain and luminous intensity with a higher spatiotemporal resolution. As a result, the engineering strain field is reconstructed via a deep learning‐derived image‐to‐image mapping process after eliminating the disturbance of afterglow. Moreover, the SAOEDN based ML film is capable of accurately detecting and capturing fracture propagation of engineering materials. It is suggested promising potential for distributed non‐contact detection of stress and strain fields in engineering applications.
Authors
- Yantang Zhao
- Qiangqiang Zhang (ORCID: https://orcid.org/0000-0002-6082-6782)
- Hui Li (ORCID: https://orcid.org/0000-0001-9198-3951)
- Peng He (ORCID: https://orcid.org/0000-0003-0606-8762)
- Xin Jing (ORCID: https://orcid.org/0000-0003-0670-5733)
- Yongjie Ma (ORCID: https://orcid.org/0009-0002-9410-3133)
Institutions
- Harbin Institute of Technology (CN)
- Lanzhou University (CN)
Publication Details
- Journal
- Advanced Optical Materials
- Published
- 2025-03-17
- DOI
- https://doi.org/10.1002/adom.202403516
- Citations
- 4
- Primary Topic
- Acoustic Wave Resonator Technologies
- Type
- article
- Field-Weighted Citation Impact
- 2.70
Funders
- National Natural Science Foundation of China
- Fundamental Research Funds for the Central Universities
- Science and Technology Program of Gansu Province