Results 111 to 120 of about 67,341 (246)
A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows +7 more
wiley +1 more source
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
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
Harnessing Machine Learning to Understand and Design Disordered Solids
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
Terrestrial Cyborg Insects for Real‐Life Applications
This article reviews the development of terrestrial cyborg insects from their emergence in 1997 to mid‐2025, examining three key aspects: locomotion control methods, associated challenges with proposed solutions, and practical applications. Framing these biohybrid systems as insect‐scale mobile robots, the review provides foundational insights for new ...
Hai Nhan Le +10 more
wiley +1 more source
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal +6 more
wiley +1 more source
This work details the rapid generation (t ≤ 5 min) of size‐tunable, ultralow dispersity (Ð ≤ 1.01) 2D hexagonal nanosheets by self‐limiting polymerization‐induced crystallization‐driven self‐assembly (SL‐PI‐CDSA) of modular and templating poly(aryl isocyanide) block copolymers, with functions that permit post‐polymerization modifications. Specifically,
Randall A. Scanga +13 more
wiley +2 more sources
Artificial intelligence (AI) is reshaping autonomous mobile robot navigation beyond classical pipelines. This review analyzes how AI techniques are integrated into core navigation tasks, including path planning and control, localization and mapping, perception, and context‐aware decision‐making. Learning‐based, probabilistic, and soft‐computing methods
Giovanna Guaragnella +5 more
wiley +1 more source
Homochiral Cu(I) cyanide complexes based on 2,2’‐bis(diphenylphosphino)‐1,1’‐binaphthyl (BINAP) form melt‐quenched and desolvation‐derived metal–organic glasses that exhibit circularly polarized thermally activated delayed fluorescence (TADF) at room temperature, enabling processable chiroptical materials.
Zeyu Fan +5 more
wiley +2 more sources
Soft-matter-based topological vertical cavity surface emitting lasers. [PDF]
Wang Y +9 more
europepmc +1 more source

