High‐accuracy dynamic gesture recognition: A universal and self‐adaptive deep‐learning‐assisted system leveraging high‐performance ionogels‐based strain sensors DOI Creative Commons
Yuqiong Sun, Jinrong Huang, Yan Cheng

et al.

SmartMat, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 15, 2024

Abstract Gesture recognition utilizing flexible strain sensors is a highly valuable technology widely applied in human–machine interfaces. However, achieving rapid detection of subtle motions and timely processing dynamic signals remain challenge for sensors. Here, resilient durable ionogels are developed by introducing micro‐scale incompatible phases macroscopic homogeneous polymeric network. The compatible network disperses conductive ionic liquid to form stretchable skeleton, while phase forms hydrogen bonds dissipate energy thus strengthening the ionogels. ionogels‐derived show sensitivity, fast response time (<10 ms), low limit (~50 μm), remarkable durability (>5000 cycles), allowing precise monitoring human motions. More importantly, self‐adaptive program empowered deep‐learning algorithms designed compensate sensors, creating comprehensive system capable gesture recognition. This can comprehensively analyze both temporal spatial features sensor data, enabling deeper understanding process underlying gestures. accurately classifies 10 hand gestures across five participants with impressive accuracy 93.66%. Moreover, it maintains robust performance without need further training even when different or subjects involved. technological breakthrough paves way intuitive seamless interaction between humans machines, presenting significant opportunities diverse applications, such as human–robot interaction, virtual reality control, assistive devices disabled individuals.

Language: Английский

Multi‐Modal Melt‐Processing of Birefringent Cellulosic Materials for Eco‐Friendly Anti‐Counterfeiting DOI
Xinkai Li, Xiaoyan Qiu, Xin Yang

et al.

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

Published: July 8, 2024

Abstract Ubiquitous anti‐counterfeiting materials with a rapidly rising annual consumption (over 10 m 2 ) can pose serious environmental burden. Biobased cellulosic birefringence offer attractive sustainable alternatives, but their scalable solvent‐free processing remain challenging. Here, dynamic chemical modification strategy is proposed for multi‐modal melt‐processing of birefringent eco‐friendly anti‐counterfeiting. Relying on the thermal‐activated covalent‐locking spatial topological structure preferred oriented cellulose, balances contradiction between strong confinement long‐range ordered structures and molecular motility required entropically‐driven reconstruction. Equipped customizable forms including mold‐pressing, spinning, direct‐ink‐writing, blade‐coating, exhibit wide color gamut, self‐healing efficiency (94.5%), recyclability, biodegradability. Moreover, diversified flexible elements facilitate fabrication compatibility universal techniques, thereby enabling versatile programmable The expected to provide references cellulose promote innovation in industry.

Language: Английский

Citations

40
Supramolecular metallic foams with ultrahigh specific strength and sustainable recyclability DOI Creative Commons

Xin Yang,

Xin Huang,

Xiaoyan Qiu

et al.

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: May 29, 2024

Language: Английский

Citations

35
Covalent Adaptable Networks with Dual Dynamic Covalent Bonds for Self‐Repairing Infrared Transmitting Materials DOI
Chenhui Cui, Fang Wang, Xingxing Chen

et al.

Advanced Functional Materials, Journal Year: 2024, Volume and Issue: 34(24)

Published: Feb. 12, 2024

Abstract Infrared transmitting materials (IRTMs) are prone to mechanical and corrosion damage during long‐time exposure harsh outside environments. However, conventional IRTMs frequently lack self‐repairability that limit their lifespan. To address the limitation, thioctic acid‐based epoxy resins (TAEs) developed from natural acid commercial monomers. The double ring‐opening polymerization (ROP) reactions of groups result in dual dynamic covalent bonds with varying bond energies containing relatively weak disulfide strong ester bonds. As compared adaptable networks (CANs) present rapid creep properties when heated, TAEs maintain geometric stability self‐repairing at a mild temperature 80 °C by enhancing network integrity through stable crosslinking points. feature renders capability while maintaining precise geometrical dimensions, which is suitable for infrared devices. On other hand, exhibit high near‐infrared transmittance (>80%). Therefore, demonstrate they can be used as superior polymeric IRTM.

Language: Английский

Citations

33
Mechanical Durability and Flexibility in Perovskite Photovoltaics: Advancements and Applications DOI
Fei Song,

Dexu Zheng,

Jiangshan Feng

et al.

Advanced Materials, Journal Year: 2024, Volume and Issue: 36(18)

Published: Jan. 14, 2024

Abstract The remarkable progress in perovskite solar cell (PSC) technology has witnessed a leap efficiency within the past decade. As this continues to mature, flexible PSCs (F‐PSCs) are emerging as pivotal components for wide array of applications, spanning from powering portable electronics and wearable devices integrating seamlessly into electronic textiles large‐scale industrial roofing. F‐PSCs characterized by their lightweight, mechanical flexibility, adaptability cost‐effective roll‐to‐roll manufacturing, hold immense commercial potential. However, persistent concerns regarding overall stability robustness these loom large. This comprehensive review delves recent strides made enhancing F‐PSCs. It covers spectrum crucial aspects, encompassing material optimization, precise crystal grain regulation, film quality enhancement, strategic interface engineering, innovational developed transparent electrodes, judicious substrate selection, integration various functional layers. By collating analyzing dedicated research endeavors, illuminates current landscape addressing challenges surrounding stability. Furthermore, it provides valuable insights obstacles bottlenecks that demand attention innovative solutions field

Language: Английский

Citations

28
High‐accuracy dynamic gesture recognition: A universal and self‐adaptive deep‐learning‐assisted system leveraging high‐performance ionogels‐based strain sensors DOI Creative Commons
Yuqiong Sun, Jinrong Huang, Yan Cheng

et al.

SmartMat, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 15, 2024

Abstract Gesture recognition utilizing flexible strain sensors is a highly valuable technology widely applied in human–machine interfaces. However, achieving rapid detection of subtle motions and timely processing dynamic signals remain challenge for sensors. Here, resilient durable ionogels are developed by introducing micro‐scale incompatible phases macroscopic homogeneous polymeric network. The compatible network disperses conductive ionic liquid to form stretchable skeleton, while phase forms hydrogen bonds dissipate energy thus strengthening the ionogels. ionogels‐derived show sensitivity, fast response time (<10 ms), low limit (~50 μm), remarkable durability (>5000 cycles), allowing precise monitoring human motions. More importantly, self‐adaptive program empowered deep‐learning algorithms designed compensate sensors, creating comprehensive system capable gesture recognition. This can comprehensively analyze both temporal spatial features sensor data, enabling deeper understanding process underlying gestures. accurately classifies 10 hand gestures across five participants with impressive accuracy 93.66%. Moreover, it maintains robust performance without need further training even when different or subjects involved. technological breakthrough paves way intuitive seamless interaction between humans machines, presenting significant opportunities diverse applications, such as human–robot interaction, virtual reality control, assistive devices disabled individuals.

Language: Английский

Citations

25