Results 221 to 230 of about 25,746,526 (333)
Knowledge‐based atomistic workflows are presented for mechanical and thermodynamic properties. By coupling modular simulations with ontology‐aligned metadata and provenance, Fe case studies on elastic behavior, defects, thermal properties, and Hall–Petch strengthening reveal how FAIR, queryable, and reusable simulation data can be generated. Mechanical
Abril Azócar Guzmán +5 more
wiley +1 more source
A vision language model for generating XML-based organ-level plant architecture representations of cowpea from simulated images. [PDF]
Yun H +6 more
europepmc +1 more source
This study reports the development of antibacterial ceramic scaffolds derived from natural bovine bone. The bones were processed through sequential boiling and hydrogen peroxide treatment to remove organic matter, producing porous, mineral‐rich scaffolds.
Mohamad Hassan Taherian +6 more
wiley +1 more source
A Unified AI-Driven Multimodal Framework Integrating Visual Sensing and Wearable Sensors for Robust Human Motion Monitoring in Biomedical Applications. [PDF]
Chen Q +6 more
europepmc +1 more source
Coarse‐grained (left) and atomistic (right) models of the shape memory polymer ESTANE ETE 75DT3 are shown schematically. The two representations bridge molecular detail and mesoscopic description. Both models capture shape memory behavior, linking segmental mobility and conformational relaxation of anisotropic chains to macroscopic recovery, and ...
Fathollah Varnik
wiley +1 more source
Decoding garden design language via semantic segmentation for social aesthetic interaction. [PDF]
Wang Y, Zhai Y, Qu C, Zhang F, Li W.
europepmc +1 more source
A distinct semi‐confined inner‐tube chemical vapor deposition geometry enables reproducible, large‐area growth of phase‐pure 2D β′‐In2Se3 from InI + Se precursors. Engineering local vapor transport and optimizing precursor delivery and temperature–time conditions yield uniform continuous films.
Dasun P. W. Guruge +8 more
wiley +1 more source
Ancient architecture image classification with progressive stacking pseudoinverse learning. [PDF]
Cai Z, Sun X, Zhang S, Zhao Z, Wu P.
europepmc +1 more source

