Optoelectronic Dual Mode Encryption for High Security Biometric Identification DOI

Zhengwen Yang,

Yuxiao Zhang, Yue Liu

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: May 29, 2025

Abstract Optoelectronic dual-mode devices overcome the environmental sensitivity and flexibility limitations of single-mode systems through co-design, yet face challenges in synchronizing touch/display signals heterogeneous integration. This study presents a self-powered encryption device via cross-modal integration an electrochromic display module piezoresistive sensing array. Ion self-migrating ink liquid metal substrate form unit, eliminating circuit coupling interference. Interfacial charge transfer enables ultrafast coloration (460 ms), precisely matching sub-second response A 1024-unit high-density pressure-sensing array with interfacial microengineering exhibits highly consistent parallel signals, reconstructing complex pressure distributions. multimodal deep learning algorithm achieves cross-domain correlation analysis optical/electrical features, reducing biometric error rates from 11.97% 38.19% (single-mode) to 5.36%. work breaks physical constraints provides co-design solution for multi-physics systems.

Language: Английский

Multifunctional PVA/PNIPAM conductive hydrogel sensors enabled human-machine interaction intelligent rehabilitation training DOI
Yan-Long Zhao,

Xichong Zhang,

Yilin Hao

et al.

Advanced Composites and Hybrid Materials, Journal Year: 2024, Volume and Issue: 7(6)

Published: Nov. 18, 2024

Language: Английский

Citations

10
Triboelectric‐Inertial Sensing Glove Enhanced by Charge‐Retained Strategy for Human‐Machine Interaction DOI Creative Commons

Bo Yang,

Jia Cheng, Xuecheng Qu

et al.

Advanced Science, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 22, 2024

Abstract As technology advances, human‐machine interaction (HMI) demands more intuitive and natural methods. To meet this demand, smart gloves, capable of capturing intricate hand movements, are emerging as vital HMI tools. Moreover, triboelectric‐based sensors, with their self‐powered, cost‐effective, material various characteristics, can offer promising solutions for enhancing existing glove systems. However, a key limitation these sensors is that charge leakage in the measurement circuit results only transient signals, rather than continuous changes. address issue, charge‐retained effectively prevents triboelectric signal attenuation developed, enabling accurate finger movements. This innovation forms foundation highly integrated system, functionality by combining signals inertial sensor data. The system showcases diverse range applications, including complex robotic control, virtual reality interaction, home lighting adjustments, interface operations. Furthermore, leveraging artificial intelligence (AI) techniques, achieves recognition sign language an impressive 99.38% accuracy. work presents approach sensing offering valuable insights developing future multifunctional proposed its dual‐mode AI integration, holds great potential revolutionizing domains user experiences.

Language: Английский

Citations

7
High‐Performance Bimodal Temperature/Pressure Tactile Sensor Based on Lamellar CNT/MXene/Cellulose Nanofibers Aerogel with Enhanced Multifunctionality DOI Open Access
Lin Tian,

Fu‐Lin Gao,

Yu‐Xiao Li

et al.

Advanced Functional Materials, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 23, 2024

Abstract The rapid development of thermoelectric‐piezoresistive dual‐mode sensors has opened new avenues for enhancing the functionality, miniaturization, and integration flexible tactile sensors. However, existing research primarily focuses on decoupling temperature pressure responses, which leaves a significant gap in optimizing sensor performance exploring multifunctional applications. To address this limitation, composite aerogel with layered porous structure is developed, integrating carbon nanotubes MXene as conductive materials reinforced cellulose nanofibers. innovative design, characterized by ultra‐low thermal conductivity along superior electrical thermoelectric properties, allows resulting to monitor stimuli without interference through piezoresistive mechanisms. Demonstrated results reveal exceptional sensing capabilities, including minimum detectable variation 0.03 K detection limit 0.3 Pa. exhibits high sensitivities 33.5 µV −1 −45.2% kPa , stability across both stimuli. Furthermore, unique multi‐modal mechanism supports various applications, such energy harvesting, material recognition, complex information transmission, smart wearable devices, electronic skin, human‐computer interaction interfaces. This presents robust solution designing high‐performance dual‐modal significantly advances their practical applications multiple domains.

Language: Английский

Citations

7
Intelligent Wind Vector Monitoring System Based on Wind Energy Harvesting DOI
Heng Tang,

Wandi Chen,

Zhigang Peng

et al.

ACS Applied Electronic Materials, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 13, 2025

Wind conditions are crucial in agricultural production, and wind vectors play a significant role planting plans. However, traditional anemometers rely on external power sources such as lithium batteries, while energy farmlands is usually neglected. This paper proposes an intelligent vector monitoring system based dual-module triboelectric nanogenerator (DM-TENG), which consists of fan-blade type soft-contact (FBTSC-TENG) disc-shaped (DS-TENG). FBTSC-TENG collects the environment to temperature humidity sensors, determining speed through frequency voltage pulses. DS-TENG can monitor direction, identifying 8 directions output pulse signals deep learning algorithms. Therefore, DM-TENG proposed this study expected field smart agriculture future.

Language: Английский

Citations

1
Highly sensitive and robust soft tri-axial tactile sensors enabled by dual inductive sensing mechanismss DOI Open Access
Si Chen, Li Su, Yiting Zheng

et al.

Soft Science, Journal Year: 2025, Volume and Issue: 5(1)

Published: Jan. 18, 2025

Tri-axial tactile sensors that provide real-time information on both normal and shear forces are enabling technologies for perception, which open up new possibilities in robotics, human-machine interfaces, environmental sensing, health monitoring. Among tri-axial based different mechanisms, inductive possess good robustness against contamination. Their low sensitivity to loads, however, is a critical barrier. This work presents the rational design of soft capable distinguishing static or dynamic with exceptional sensitivity. Dual mechanisms Biot-Savart law Eddy current effect explored overcome long-standing issue. In addition, hybrid coil non-uniform spacing designed generate uniform magnetic fields, addressing limitations traditional coils significantly improving sensor’s The picosecond pulsed laser scribing technique makes it possible pattern silver nanowires into high fidelity. A porous compressible layer adopted enable adjustable sensing range meet diverse application demands. Finally, sensor integrated between user’s leg orthosis, showcasing capability monitoring its objects.

Language: Английский

Citations

1
Bionic Recognition Technologies Inspired by Biological Mechanosensory Systems DOI Open Access
Xiangxiang Zhang, Chang-Guang Wang, Xin Pi

et al.

Advanced Materials, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 21, 2025

Abstract Mechanical information is a medium for perceptual interaction and health monitoring of organisms or intelligent mechanical equipment, including force, vibration, sound, flow. Researchers are increasingly deploying recognition technologies (MIRT) that integrate acquisition, pre‐processing, processing functions expected to enable advanced applications. However, this also poses significant challenges acquisition performance efficiency. The novel exciting mechanosensory systems in nature have inspired us develop superior bionic (MIBRT) based on materials, structures, devices address these challenges. Herein, first strategies pre‐processing presented their importance high‐performance highlighted. Subsequently, design considerations sensors by mechanoreceptors described. Then, the concepts neuromorphic summarized order replicate biological nervous system. Additionally, ability MIBRT investigated recognize basic information. Furthermore, further potential applications robots, healthcare, virtual reality explored with view solve range complex tasks. Finally, future opportunities identified from multiple perspectives.

Language: Английский

Citations

1
Self‐Powered Artificial Neuron Devices: Towards the All‐In‐One Perception and Computation System DOI Open Access
Tong Zheng,

Xinkai Xie,

Qiongfeng Shi

et al.

Advanced Materials, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 18, 2025

Abstract The increasing demand for energy supply in sensing units and the computational efficiency of computation has prompted researchers to explore novel, integrated technology that offers high low consumption. Self‐powered enables environmental perception without external sources, while neuromorphic provides energy‐efficient high‐performance computing capabilities. integration self‐powered presents a promising solution an all‐in‐one system. This review examines recent developments advancements artificial neuron devices based on triboelectric, piezoelectric, photoelectric effects, focusing their structures, mechanisms, functions. Furthermore, it compares electrical characteristics various types discusses effective methods enhancing performance. Additionally, this comprehensive summary systems, encompassing tactile, visual, auditory systems. Moreover, elucidates recently systems combine perception, computing, actuation into configurations, aspiring realize closed‐loop control. seamless holds significant potential shaping more intelligent future humanity.

Language: Английский

Citations

1
Portable and Self-Powered Sensing AI-Enabled Mask for Emotional Recognition in Virtual Reality DOI
Deqiang He, Hongyu Chen, Xinyi Zhao

et al.

ACS Applied Materials & Interfaces, Journal Year: 2025, Volume and Issue: unknown

Published: March 12, 2025

With the increasing development of metaverse and human-computer interaction (HMI) technologies, artificial intelligence (AI) applications in virtual reality (VR) environments are receiving significant attention. This study presents a self-sensing facial recognition mask (FRM) utilizing triboelectric nanogenerators (TENG) machine learning algorithms to enhance user immersion interaction. Various TENG negative electrode materials evaluated improve sensor performance, efficacy single is confirmed. For accurate movement emotion detection, different assessed, leading selection an advanced data processing method with two-layer long short-term memory model, which achieves 99.87% accuracy. The practical FRM system reality, including psychotherapy HMI scenarios, validated through mathematical models. Additionally, digital twin-based monitoring platform developed using 5G, database, visualization technologies oversee status. Overall, these innovative approaches overcome limitations existing face environmental interference high cost, compared other technologies.

Language: Английский

Citations

1
Highly Programmable Haptic Decoding and Self‐Adaptive Spatiotemporal Feedback Toward Embodied Intelligence DOI

Wansheng Lin,

Yijing Xu,

Shifan Yu

et al.

Advanced Functional Materials, Journal Year: 2025, Volume and Issue: unknown

Published: April 14, 2025

Abstract Intelligent robots, equipped with perception, cognition, and learning capabilities, are transforming the manner by which complex tasks approached, enhancing autonomy, efficiency, adaptability. By contrast, conventional robotics typically struggle precision reliability in such as grasping recognition owing to their limited sensing feedback mechanisms. To achieve advanced applications, robots require sophisticated spatiotemporal adjust actions dynamically, poses a significant challenge pressure‐decoupling capability. Herein, high‐performance programmable event‐driven (PED) haptic interface real‐time, self‐regulating feedback, empowering dynamic adaptation force optimization is introduced. The PED features gradient pyramid metasurface‐like structure, emulates perception of human skin decode tactile data. Compared devices, offers improvements detection range sensitivity 300% 350%, respectively. integrating cutting‐edge technology artificial intelligence, conceptualized intelligent agent developed that autonomously understands unstructured environments avoid self‐damage or object damage without external intervention. This breakthrough not only new research avenues but also significantly advances foundation embodied particularly simulating cognition.

Language: Английский

Citations

1
Ultrastretchable, Ultralow Hysteresis, High-Toughness Hydrogel Strain Sensor for Pressure Recognition with Deep Learning DOI
Wei‐Chen Huang, Xi Wang,

Fanchen Luo

et al.

ACS Applied Materials & Interfaces, Journal Year: 2024, Volume and Issue: 16(37), P. 49834 - 49844

Published: Sept. 4, 2024

Hydrogel, as a promising material for wide range of applications, has demonstrated considerable potential use in flexible wearable devices and engineering technologies. However, simultaneously realizing the ultrastretchability, low hysteresis, high toughness hydrogels is still great challenge. Here, we present dual physically cross-linked polyacrylamide (PAM)/sodium hyaluronate (HA)/montmorillonite (MMT) hydrogel. The introduction HA increases degree chain entanglement, addition MMT acts stress dissipation center cross-linking agent, resulting hydrogel with hysteretic properties. This synthesized by simple strategy exhibited ultrahigh stretchability (3165%), breaking (228 kPa), (4.149 MJ/m

Language: Английский

Citations

6