Results 131 to 140 of about 7,231 (184)

High‐Performance Transparent, Deformable, and Recoverable Biomimetic Stevia–PVA Hydrogel Triboelectric Nanogenerator with Machine Learning‐Assisted Motion Recognition

Advanced Materials, EarlyView.
A transparent, deformable stevia–PVA hydrogel triboelectric nanogenerator delivers significantly enhanced mechanical strength and electrical output through biomimetic hydrogen‐bonded networks. Coupled with machine learning–assisted signal recognition, the self‐powered hydrogel enables accurate human‐motion sensing for intelligent wearable and IoT ...
Thien Trung Luu, Bui Minh Quang, Toan Minh Pham, Jinsoo Kim, Kyungwho Choi, Dukhyun Choi   +5 more
wiley   +1 more source

Psychological and physiological moderators of perceived exertion in aerobics: a repeated-measures study. [PDF]

Front Psychol
Gao X, Zhao J, Zhao T, Song YG, Zhi Y, He X.   +5 more
europepmc   +1 more source

Rational Tuning of Hygroscopic Oscillation of Stacked Nanoflake Assemblies for Continuous Ambient Energy Harvesting

Advanced Materials, EarlyView.
Stacked nanoflake assembly (SNA) membranes can oscillate autonomously, offering opportunities for soft actuation and energy harvesting. This work uncovers the physical mechanism behind the sustained oscillation of SNA membranes in gradient humidity and identifies three governing dimensionless parameters, enabling rational design for optimizing SNA ...
Zijing Zhang, Jimin Fu, Gesa Zhang, Zhihua Liang, Boxun Zhang, Haimin Yao   +5 more
wiley   +1 more source

Application of Dang Van Model Based on Critical Plane Approach for Rolling Contact Problems. [PDF]

Materials (Basel)
Romanowicz PJ.
europepmc   +1 more source

Leaf‐Inspired Eutectic Skin With Extreme Fatigue Resistance and Robust Wet Adhesion for Amphibious Epidermal Electronics

Advanced Materials, EarlyView.
Inspired by Acorus calamus leaves, a heterogeneous eutectic skin integrates an aligned fibrous network within a hydrophobic eutectogel matrix. This hierarchical architecture triggers strain‐induced crystallization to achieve exceptional mechanical toughness and durable wet adhesion.
Jiayu Hou, Jiancheng Dong, Je Hyeong Kim, Chang Zhou, Shiyin Lin, Xingyu Liu, Hao Qiu, Mengting Zheng, Yuduo Zhang, Haijun Zhu, Kangjia Geng, Yidong Peng, Haoran Liu, Yunpeng Huang, Yongsheng Luo, Steve Park, Tianxi Liu   +16 more
wiley   +1 more source

Grid resilience enhancement of photovoltaic systems via Lyapunov-validated active-reactive power coordination and inverter oversizing. [PDF]

Sci Rep
Kotla RW, Ganji S, Lagudu J, Yarlagadda SR, Bolli S.   +4 more
europepmc   +1 more source

Ultrathin Li Metal Anodes: Quantitative Design Principles and Manufacturability Across Liquid and Solid‐State Batteries

Advanced Materials, EarlyView.
Ultrathin lithium metal anodes (≤15 µm) offer a promising route to high‐energy‐density batteries due to their high capacity and low potential. This review presents design principles for ultrathin Li, evaluates fabrication strategies, and discusses challenges in liquid and solid‐state cells.
Cheng Wang, Caoyu Wang, Shuixin Xia, Jodie A. Yuwono, Mingnan Li, Yanqiu Lyu, Ruizhi Zhang, Jun Wang, Jianfeng Mao, Zaiping Guo   +9 more
wiley   +1 more source

Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles

Advanced Materials, EarlyView.
Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung, Jiaxiang Yi, Hieu Nguyen‐Duc, Tien Nu Hoang Lo, Weili Zhao, Chaoqun Dong, Fabien Sorin, Baris Caglar, Lei Wei, Tung Nguyen‐Dang   +9 more
wiley   +1 more source

Blockchain consensus mechanism and method for peer-to-peer electricity trading. [PDF]

Sci Rep
Wang N, Chen Y, Zhai F, Li B.
europepmc   +1 more source

Ferroelectric Dynamic‐Field‐Driven Nucleation and Growth Model for Predictive Materials‐To‐Circuit Co‐Design

Advanced Materials, EarlyView.
This study presents a compact dynamic‐field‐driven nucleation and growth (DFNG) model that captures ferroelectric switching behavior under arbitrary voltage waveforms. It enables extraction of time‐dependent domain wall velocity and growth dimensionality, which can then be extended to device‐level modeling.
Yi Liang, Soohyeon Kim, Tony Chiang, Megan K. Lenox, Ian Mercer, John J. Plombon, Jon‐Paul Maria, Jon F. Ihlefeld, Wenhao Sun, Wei Lu, John T. Heron   +10 more
wiley   +1 more source