A Cantilever-Based Broadband Acoustoelectric Device with Aligned PVDF-HFP Nanofibers for Self-Powered Sensing and High-Accuracy Speech Recognition
at 170 Hz, 100 dB SPL). It attains a voice capture signal-to-noise ratio of 61.50 dB and a machine learning-based speech recognition accuracy of 98.5%. This work establishes a new paradigm for broadband acoustic device design and advances the practical application of high-fidelity human-computer interaction and intelligent sensing technologies.
Authors
- Like Chen (ORCID: https://orcid.org/0000-0003-0014-4760)
- Qiaoling ZHANG
- Junyun Zhang (ORCID: https://orcid.org/0000-0001-7216-2146)
- Weixu Tian
- Chenhong Lang
- Jinjin Song
- Di Pan
- Lu Peng
- Tong Lin
Institutions
- Zhejiang Sci-Tech University (CN)
- Tiangong University (CN)
- Textile Research Institute (US)
- Guangdong Polytechnic Normal University (CN)
- Artificial Intelligence in Medicine (Canada) (CA)
Publication Details
- Journal
- ACS Applied Materials & Interfaces
- Published
- 2026-04-06
- DOI
- https://doi.org/10.1021/acsami.5c25936
- Primary Topic
- Advanced Sensor and Energy Harvesting Materials
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Zhejiang Sci-Tech University
- Department of Education of Zhejiang Province
- Natural Science Foundation of Zhejiang Province