Results 181 to 190 of about 9,725 (264)
Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan +8 more
wiley +1 more source
Discussion themes and emotional expressions on Chinese social media regarding AI virtual companions: a topic modeling and sentiment analysis study. [PDF]
Sun Y, Liu J, Liu T, Wei Z, Shen H.
europepmc +1 more source
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
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
Salience as an Integrative Process in Symptom Formation: A Conceptual Analysis for Generalist Practice. [PDF]
Matsuoka F.
europepmc +1 more source
Short‐range order in 2D transition metal dichalcogenides is revealed as a new design paradigm. Driven by chemical affinity and atomic size, it governs properties across scales. Weak ordering tunes site‐resolved magnetism and d‐band centers, while strong ordering eliminates gap states to open band gaps.
Hanyu Liu +3 more
wiley +1 more source
Maximal Dissipation and Well-Posedness of the Euler System of Gas Dynamics. [PDF]
Feireisl E +2 more
europepmc +1 more source
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan +8 more
wiley +1 more source
Federated analytics for non-communicable disease surveillance in the European health data space: a scoping review and conceptual framework. [PDF]
Carinci F +3 more
europepmc +1 more source
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang +2 more
wiley +1 more source

