Results 221 to 230 of about 1,009,889 (297)

Liquids as Reinforcements for Anisotropic and Tough Soft Matter Composites

Advanced Materials, EarlyView.
Liquid metal droplets are shaped and oriented within soft elastomers to create all‐soft matter composites with programmable mechanical anisotropy. These liquid inclusions act as fiber‐like reinforcements, enabling directional stiffness, enhanced toughness, and controlled crack steering under extreme deformation, offering new routes to resilient soft ...
Gwyneth M. Schloer, Ohnyoung Hur, Ravi Tutika, Aaron Haake, Eric J. Markvicka, Michael D. Bartlett   +5 more
wiley   +1 more source

A pipeline leakage detection method for boiler energy operation system using enhanced SVM-based acoustic emission technology. [PDF]

Sci Rep
Yuan T, Zhang X, Zhang Q, Tan M.
europepmc   +1 more source

Advanced Separators for Liquid and Quasi‐Solid Lithium Rechargeable Batteries: Design and Development

Advanced Materials, EarlyView.
This review traces the evolution of lithium‐ion battery separators from passive barriers to multifunctional components central to cell safety and performance. Polymer‐ceramic hybrids, nanofiber architectures, and bio‐derived membranes deliver ionic conductivities above 3 mS cm−1, thermal stability beyond 200 °C, and effective suppression of lithium ...
Karthik Vishweswariah, Ningaraju Gejjiganahalli Ningappa, Anil Kumar M. R., Jeremy I. G. Dawkins, Thiago M. G. Selva, Karim Zaghib   +5 more
wiley   +1 more source

Deep reinforcement learning for network resource optimization in MIMO-NOMA networks to maximize utilization with minimal overhead. [PDF]

Sci Rep
Lahza HFM, Sreenivasa BR, Lahza H, Nandini G, Laxmi V, Shawly T, Alsheikhy AA.   +6 more
europepmc   +1 more source

A Scalable Perovskite Platform With Multi‐State Photoresponsivity for In‐Sensor Saliency Detection

Advanced Materials, EarlyView.
A scalable in‐sensor computing platform (32 × 32 array) with ultra‐low variability is developed by incorporating ferroelectric copolymers into halide perovskite thin films. These devices achieve 1000 programmable photoresponsivity states and high thermal reliability.
Xuechao Xing, Anubhab Tripathi, Si En Ng, Natalia Yantara, Yue Gong, Qinjie Wu, Yeow Boon Tay, Wen Siang Lew, Yang Chai, Arindam Basu, Nripan Mathews   +10 more
wiley   +1 more source

Research on energy-saving algorithm of HVAC multi-agent system consensus based on event-triggered mechanism. [PDF]

PLoS One
Wu W, Shi S, Lin M, Gong H, Li J.
europepmc   +1 more source

Plasmonic Nanomachines: Creating Local Potential Gradients and Motions

Advanced Materials, EarlyView.
Plasmonic nanomachines can generate optical, thermal, and chemical potential gradients to drive directional rectilinear, rotational, and twisting motions at the nanometer scale. The integration of multimodal plasmonic forces with functional materials and programmed structural distortions enables precise spatiotemporal actuation, thereby providing a ...
Yoonhee Kim, Soohyun Ji, Donghyun Choi, Jwa‐Min Nam   +3 more
wiley   +1 more source

Workshop report-Vulnerability in multi-hazard risks: Addressing its complexity and dynamics. [PDF]

iScience
Santos AP, De Angeli S, Hanf FS, Charlotta M, Nicole VM, Benson V, Marleen Carolijn R, Dunant A, Terzi S, Schweizer PJ, Nunes Carvalho TM, Madruga de Brito M, De Polt K, Šakić Trogrlić R, van den Homberg M.   +14 more
europepmc   +1 more source

Phase Engineering of Nanomaterials (PEN): Evolution, Current Challenges, and Future Opportunities

Advanced Materials, EarlyView.
This review summarizes the synthesis, phase transition, advanced characterization spanning ex situ to in situ and operando techniques, and diverse applications of phase engineering of nanomaterials (PEN). It further outlines key challenges and future opportunities, such as phase stability, architecture control, and artificial intelligence (AI)‐driven ...
Ye Chen, Zhanxi Fan, Jingjie Ge, Qiyuan He, Zhuangchai Lai, Jiawei Liu, Chaoliang Tan, Hua Zhang   +7 more
wiley   +1 more source

Comparative study of machine learning methods for carbon metering in power generation enterprises. [PDF]

Sci Rep
Wang S, Fang B, Zhang J, Xing S, Wu J, Xiao H.   +5 more
europepmc   +1 more source