Results 231 to 240 of about 25,002,706 (305)

Semi-Analytical Large-Strain Bending of Thermoviscoplastic SMP Beams with Plastic Softening. [PDF]

Polymers (Basel)
Khashabi H, Baniassadi M, Choi E, Baghani M.   +3 more
europepmc   +1 more source

Characterizing Biopolymer Electrolytes in Zinc–Air Batteries: Challenges, Best Practices, and a Robust Workflow Guiding Future Research Paths

Advanced Energy Materials, EarlyView.
Bio‐based gel polymer electrolytes promise sustainable, mechanically adaptable zinc–air batteries, yet their progress is constrained by inconsistent characterization. This review critically links formulation, structure, interfaces, and cell performance, identifies methodological gaps under alkaline operating conditions, and proposes application ...
Matteo Milanesi, Hiba Ali, Barbara Belza, Mattia F. Palermo, Claudio Gerbaldi, Giuseppe Antonio Elia, Nagore Ortiz‐Vitoriano   +6 more
wiley   +1 more source

Free vibration behaviour of pomelo peel-inspired sandwich composite plates with additively manufactured cores: an explainable machine learning approach. [PDF]

Sci Rep
Mani S, Krishnamoorthy A.
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

A General Tensorial Formulation of Acoustoelasticity and Its Representation in Cylindrical Coordinates. [PDF]

Sensors (Basel)
Ma Y, Xu C, Yang S, Chen C.
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

4D imaging of a porous carbonate rock under triaxial loading: quantitative correlation between local porosity and strain. [PDF]

J Synchrotron Radiat
Doré-Ossipyan C, Quacquarelli A, Bornert M, Sulem J, Dimanov A, Aimedieu P, De Greef V, King A.   +7 more
europepmc   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

A Review of Mechanical Degradation, Interfacial Nonlinear Dynamics and Multi-Bolt Coupling Degradation Mechanisms of Flange-Bolted Joints. [PDF]

Sensors (Basel)
Feng X, Guo M, Wang S, Lu X, Liu Y, Li Z, Wang W, Xu Z, Liu Y.   +8 more
europepmc   +1 more source

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

Advanced Intelligent Discovery, EarlyView.
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi, Kazuki Ishizaki, Ryo Fukasawa   +2 more
wiley   +1 more source