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Lin Z, Duan S, Liu M, Dang C, Qian S, Zhang L, Wang H, Yan W, Zhu M. Insights into Materials, Physics, and Applications in Flexible and Wearable Acoustic Sensing Technology. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2306880. [PMID: 38015990 DOI: 10.1002/adma.202306880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 11/22/2023] [Indexed: 11/30/2023]
Abstract
Sound plays a crucial role in the perception of the world. It allows to communicate, learn, and detect potential dangers, diagnose diseases, and much more. However, traditional acoustic sensors are limited in their form factors, being rigid and cumbersome, which restricts their potential applications. Recently, acoustic sensors have made significant advancements, transitioning from rudimentary forms to wearable devices and smart everyday clothing that can conform to soft, curved, and deformable surfaces or surroundings. In this review, the latest scientific and technological breakthroughs with insightful analysis in materials, physics, design principles, fabrication strategies, functions, and applications of flexible and wearable acoustic sensing technology are comprehensively explored. The new generation of acoustic sensors that can recognize voice, interact with machines, control robots, enable marine positioning and localization, monitor structural health, diagnose human vital signs in deep tissues, and perform organ imaging is highlighted. These innovations offer unique solutions to significant challenges in fields such as healthcare, biomedicine, wearables, robotics, and metaverse. Finally, the existing challenges and future opportunities in the field are addressed, providing strategies to advance acoustic sensing technologies for intriguing real-world applications and inspire new research directions.
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Affiliation(s)
- Zhiwei Lin
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai, 201620, China
- School of Electrical and Electronic Engineering, Nanyang Technological University (NTU), Singapore, 639798, Singapore
| | - Shengshun Duan
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai, 201620, China
- School of Electrical and Electronic Engineering, Nanyang Technological University (NTU), Singapore, 639798, Singapore
| | - Mingyang Liu
- School of Electrical and Electronic Engineering, Nanyang Technological University (NTU), Singapore, 639798, Singapore
| | - Chao Dang
- School of Electrical and Electronic Engineering, Nanyang Technological University (NTU), Singapore, 639798, Singapore
| | - Shengtai Qian
- School of Electrical and Electronic Engineering, Nanyang Technological University (NTU), Singapore, 639798, Singapore
| | - Luxue Zhang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai, 201620, China
| | - Hailiang Wang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai, 201620, China
| | - Wei Yan
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai, 201620, China
| | - Meifang Zhu
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai, 201620, China
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Wang R, Wang Y, Yang Y, Zhang S, Liu Y, Yao J, Zhang W. A Systematic Study on the Processing Strategy in Femtosecond Laser Scribing via a Two-Temperature Model. MATERIALS (BASEL, SWITZERLAND) 2023; 16:6895. [PMID: 37959492 PMCID: PMC10647803 DOI: 10.3390/ma16216895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/13/2023] [Accepted: 10/17/2023] [Indexed: 11/15/2023]
Abstract
Balancing quality and productivity, especially deciding on the optimal matching strategy for multiple process parameters, is challenging in ultrashort laser processing. In this paper, an economical and new processing strategy was studied based on the laser scribing case. To reveal the temperature evolution under the combination of multiple process parameters in the laser scribing process, a two-temperature model involving a moving laser source was developed. The results indicated that the peak thermal equilibrium temperature between the electron and lattice increased with the increase in the laser fluence, and the temperature evolution at the initial position, influenced by subsequent pulses, was strongly associated with the overlap ratio. The thermal ablation effect was strongly enhanced with the increase in laser fluence. The groove morphology was controllable by selecting the overlap ratio at the same laser fluence. The removal volume per joule (i.e., energy utilization efficiency) and the removal volume per second (i.e., ablation efficiency) were introduced to analyze the ablation characteristics influenced by multiple process parameters. The law derived from statistical analysis is as follows; at the same laser fluence with the same overlap ratio, the energy utilization efficiency is insensitive to changes in the repetition rate, and the ablation efficiency increases as the repetition rate increases. As a result, a decision-making strategy for balancing quality and productivity was created.
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Affiliation(s)
- Rujia Wang
- Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, China; (R.W.); (Y.W.); (Y.Y.); (S.Z.)
- Zhejiang Key Laboratory of Aero Engine Extreme Manufacturing Technology, Ningbo 315201, China
| | - Yufeng Wang
- Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, China; (R.W.); (Y.W.); (Y.Y.); (S.Z.)
- Zhejiang Key Laboratory of Aero Engine Extreme Manufacturing Technology, Ningbo 315201, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yong Yang
- Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, China; (R.W.); (Y.W.); (Y.Y.); (S.Z.)
- Zhejiang Key Laboratory of Aero Engine Extreme Manufacturing Technology, Ningbo 315201, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shuowen Zhang
- Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, China; (R.W.); (Y.W.); (Y.Y.); (S.Z.)
- Zhejiang Key Laboratory of Aero Engine Extreme Manufacturing Technology, Ningbo 315201, China
| | - Yunfeng Liu
- College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China; (Y.L.); (J.Y.)
| | - Jianhua Yao
- College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China; (Y.L.); (J.Y.)
| | - Wenwu Zhang
- Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, China; (R.W.); (Y.W.); (Y.Y.); (S.Z.)
- Zhejiang Key Laboratory of Aero Engine Extreme Manufacturing Technology, Ningbo 315201, China
- University of Chinese Academy of Sciences, Beijing 100049, China
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Hwang TY, Cho J, Kim YD, Park TH, Son JE, Kang J, Lee B. Deep learning-based optical authentication using the structural coloration of metals with femtosecond laser-induced periodic surface structures. OPTICS EXPRESS 2023; 31:1776-1786. [PMID: 36785205 DOI: 10.1364/oe.478670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 12/09/2022] [Indexed: 06/18/2023]
Abstract
Structurally colored materials present potential technological applications including anticounterfeiting tags for authentication due to the ability to controllably manipulate colors through nanostructuring. Yet, no applications of deep learning algorithms, known to discover meaningful structures in data with far-reaching optimization capabilities, to such optical authentication applications involving low-spatial-frequency laser-induced periodic surface structures (LSFLs) have been demonstrated to date. In this work, by fine-tuning one of the lightweight convolutional neural networks, MobileNetV1, we investigate the optical authentication capabilities of the structurally colorized images on metal surfaces fabricated by controlling the orientation of femtosecond LSFLs. We show that the structural color variations due to a broad range of the illumination incident angles combined with both the controlled orientations of LSFLs and differences in features captured in the image make this system suitable for deep learning-based optical authentication.
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