Results 141 to 150 of about 69,376 (247)

Netarsudil-Induced Honeycomb Keratopathy in an Eye With Iridocorneal Endothelial Syndrome. [PDF]

Case Rep Ophthalmol Med
Ferguson AN, Bojikian KD, Nguyen MT.
europepmc   +1 more source

From Materials to Systems: Challenges and Solutions for Fast‐Charge/Discharge Na‐Ion Batteries

Advanced Energy Materials, EarlyView.
This review systematically analyzes the key characteristics limiting the fast‐charge/discharge capability of Na‐ion batteries (SIBs) from a multi‐scale perspective encompassing electrode materials, the electrode‐electrolyte interface, and the system. Furthermore, it presents practical solution strategies for the fundamental issues arising at each scale,
Bonyoung Ku, Sangbin Park, Sunha Hwang, Sunghyun Lim, Won‐Sub Yoon, Jongsoon Kim   +5 more
wiley   +1 more source

Homogenization Equivalence Modeling of Honeycomb Bending Considering Regional Deformation Differences. [PDF]

Polymers (Basel)
Liu W, Huang G, Wang X, Yu Y, Liu Z, Guan H, Zhu J, Wang Y.   +7 more
europepmc   +1 more source

Multi‐modal Operando Analysis of Lithium–Sulfur Batteries: A Comparative Study on the Influence of Electrolyte Composition

Advanced Energy Materials, EarlyView.
The influence of different electrolytes on Lithium–sulfur batteries is investigated. Multimodal operando analysis, including Raman, UV–vis, and Impedance spectroscopy is used to study degradation mechanisms. The solubility of polysulfides in the electrolyte is crucial for battery capacity and lifetime.
Oliver Löhmann, Pouya Partovi‐Azar, Mirco Ruttert, Sebastian Risse   +3 more
wiley   +1 more source

Quasi-Static Penetration Resistance of Bio-Inspired Helicoidal Honeycomb Sandwich Panels: Experiments, Simulations, and Damage Mechanisms. [PDF]

Materials (Basel)
Du X, Lian X, Wan C, Yu Z.
europepmc   +1 more source

Evolution of Physical Intelligence Across Scales

Advanced Intelligent Discovery, EarlyView.
By following the evolution of physical intelligence across scales, this article shows how intelligence arises from materials, structures, physical interactions, and collectives. It establishes physical intelligence as the evolutionary foundation upon which embodied intelligence is built.
Ke Liu, Tianyun Huang, Aming Li, Pengyu Lv, Tingting Qin, Wenhui Chen, Hui Wei, Huiling Duan   +7 more
wiley   +1 more source

Mechanism and Optimization of Quasi-Static Compression Performance in Hexagonal Honeycomb Sandwich Structures. [PDF]

ACS Omega
Hong A, Li H, Song X, Fu Y, Yang Y, Liu Z, Ye X, Yang J.   +7 more
europepmc   +1 more source

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

Numerical Study on the Acoustic Transmission Performance of New Hierarchical Honeycomb Sandwich Panel. [PDF]

Materials (Basel)
Zhou B, He Q.
europepmc   +1 more source

AI‐BioMech: Deep Learning Prediction of Mechanical Behavior in Aperiodic Biological Cellular Materials

Advanced Intelligent Discovery, EarlyView.
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia, Marcelo A. Dias, Parvez Alam   +2 more
wiley   +1 more source