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Updated: Jun 4, 2026

Investigating the Potential of Singly Curved Thin Piezoelectric Transducers for Energy Harvesting and Structural Health Monitoring
Published on: November 14, 2025
Uncovering Local Piezoelectric Field Effect in Mechanoluminescent Materials
Yuhe Shao1, Jia Shi2, Hongzhen Liu1
1The Beijing Municipal Key Laboratory of New Energy Materials and Technologies, School of Materials Sciences and Engineering, University of Science and Technology Beijing, Beijing, China.
None:
Elastic mechanoluminescent (ML) materials have significant potential in intelligent sensing, dynamic displays, and artificial intelligence. However, concrete experimental evidence of localized piezoelectric fields has long been missing in piezoelectrically controlled elastic ML materials. In this work, we propose a strategy for uncovering the local piezoelectric field effect in ML materials and demonstrate that crystallographic site symmetry and local structure determine the local piezoelectric field, which further profoundly influences the ML properties of the material. We screen and design multisite deep‑red to near‑infrared (NIR) self‑recoverable ML materials, Mn2+-activated MGa2S4 (M = Ca, Sr). Beyond the report of ultrabroadband ML performance, we have defined and calculated, for the first time, the centrosymmetry deviation degree (CDD) of a polyhedron, and elucidated the correlation among site symmetry, CDD, polyhedral distortion degree, local piezoelectric responses, and ML intensity. With the assistance of DFT and DFPT calculations, we have clarified the contribution of local polarization at specific sites and established a dynamic model for local‑piezoelectric‑field‑induced ML in multisite materials. Furthermore, leveraging the ultrabroadband ML emission of this material series, we fabricated various flexible devices, which demonstrated promising application potential in fields such as rehabilitation medicine, deep-tissue bioimaging, and NIR information encryption. This work holds potential to offer valuable insights for discovering, designing, and yielding novel ML materials.
