Results 141 to 150 of about 1,256,700 (250)
Advanced Functional Materials, EarlyView.This study advances SafeWax, a bio‐inspired, fatty‐acids‐based superhydrophobic coating, by identifying an agriculturally compliant solvent and revealing how solvent‐controlled Fatty acid crystallization governs the coating's microscopic structure and performance.
Niv Ben‐Arie +13 more
wiley +1 more source
Entropy-Guided Graph Clustering via Rényi Optimization
Graph clustering is a fundamental task in network analysis, with applications ranging from community detection to protein complex identification. While Graph Neural Networks (GNNs) have shown promising results in this domain, they often struggle to ...
Begga, Ahmed +5 more
core +1 more source
A Graph Clustering Approach to Localization for Adaptive Covariance Tuning in Data Assimilation Based on State-Observation Mapping. [PDF]
Math Geosci, 2021 Cheng S +4 more
europepmc +1 more source
Advanced Functional Materials, EarlyView.Cell therapies typically rely on cold‐chain logistics and cryopreservation, limiting access and compromising cell quality. Here, a dual‐chamber device separates an oxygen‐supplying chamber from a hyaluronic acid cargo chamber, sustaining oxygen delivery for over 70 h and enabling ambient‐temperature shipment.
Daniel A. Domingo‐Lopez +9 more
wiley +1 more source
Clustering Edges Reveals How Vertices Exert Influence in Graph Data
How do vertices and edges collaboratively exert influence in graphs? We develop a framework for edge spectral clustering that reveals how both vertices and edges collaboratively accomplish directed influence in directed graphs.
Premaratne, Kamal, Murthi, Manohar N.
core +1 more source
Potential Arabidopsis thaliana glucosinolate genes identified from the co-expression modules using graph clustering approach. [PDF]
PeerJ, 2021 Harun S +5 more
europepmc +1 more source
Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery
Advanced Functional Materials, EarlyView.Physics‐Grounded Materials AI (PhysMat AI) integrates physical priors, descriptors, constraints, verification, and data infrastructure into a unified full‐stack framework, enabling reliable, interpretable, and autonomous AI‐driven materials discovery.
Yuhang Wang +3 more
wiley +1 more source
Covalent Functionalization of 2D Semiconductors: A Roadmap to Advanced Electronic Devices
Advanced Functional Materials, EarlyView.This Review presents recent advances in the covalent functionalization strategies for two‐dimensional semiconductors and their implementation in modern technologies. Layered materials are modified through diverse molecular chemistries (e.g., thiols, diazonium salts, alkyl halides, and electron‐deficient species) to tailor their surface properties ...
Ramiro Quirós‐Ovies +2 more
wiley +1 more source
Advanced Functional Materials, EarlyView.Versatile guanosine‐quadruplex (GQ) hydrogels are developed as dynamic biomatrices for cell culture. These scaffolds are fabricated under mild aqueous conditions, present improved stability, tunable mechanical properties within physiological ranges; fibrillar, porous microstructure, ion conductivity, and cytocompatibility.
Neha Thakur +10 more
wiley +1 more source
Synergistic Deep Graph Clustering Network [PDF]
Employing graph neural networks (GNNs) to learn cohesive and discriminative node representations for clustering has shown promising results in deep graph clustering.
Xu, Xiao +5 more
core +1 more source