Results 91 to 100 of about 4,078 (232)
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
Advanced Science, EarlyView.The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source
Light‐Imprinted Chirality in Nanomaterials: From Principles to Applications
Advanced Science, EarlyView.Light‐induced chirality represents a transformative paradigm for fabricating chiral nanostructures. This review provides a comprehensive framework encompassing light‐based strategies for imprinting and tuning chirality in nanomaterials, which guides researchers in harnessing light to create next‐generation functional materials.
Xinru Jin +3 more
wiley +1 more source
Advanced Science, EarlyView.First‐principles calculations reveal that monolayer In2O${\rm In}_2{\rm O}$ hosts type‐II Dirac fermions near the Fermi level, which split into Weyl points under spin‐orbit coupling. The material exhibits negative and giant magnetoresistance, a pronounced spin Hall effect, and phonon‐mediated superconductivity at 1.5 K, establishing it as a unique ...
Qing‐Bo Liu +6 more
wiley +1 more source
This comprehensive treatise formalizes the foundational mechanics of generative recursive architectures driven by the non-linear expansion function $G(n)=\mathbf{I}_0\cdot(k\cdot\psi)^n$. Moving beyond localized mathematical models, this article establishes the structural invariants of recursive information systems across all branches of the natural ...
openaire +1 more source
Advanced Science, EarlyView.By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin +12 more
wiley +1 more source
The historical scaling of deep learning models and decentralized multi-agent routing networks has relied almost exclusively on linear operations mapped within flat, Euclidean geometric spaces. However, as the dimensionality of representations and the topological complexity of agentic networks scale, these Cartesian coordinate systems suffer from severe
openaire +2 more sources
Two‐Dimensional Triferroics: From Fundamental Couplings to Multifunctional Applications
Advanced Science, EarlyView.This graphic summarizes the three main types of currently reported 2D triferroic couplings. From the structural perspective, existing systems can be broadly classified into two categories, which exhibit distinct symmetry features and coupling behaviors. Beyond the lattice difference, a third type involves the interplay among ferroelectricity, magnetism,
Yang Li, Jialin Gong, Zhiqing Li
wiley +1 more source
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Network BiologyNetwork Biology ISSN 2220-8879
Network Biology (ISSN 2220-8879)
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Diverse Landscape of Tunable Magnetic, Topological, and Ferroelectric States in 2D Ti3Se3Te2
Advanced Science, EarlyView.Ti3Se3Te2 emerges as a multifunctional 2D van der Waals platform. The monolayer is a dynamically stable ferromagnetic quantum anomalous Hall insulator. In bilayers, two stacking configurations yield distinct phases: AA‐stacking hosts an altermagnetic quantum spin Hall insulator, while AA′‐stacking exhibits three‐state in‐plane ferroelectricity ...
Jiangtao Yu +5 more
wiley +1 more source