Results 221 to 230 of about 29,335 (305)
Low N/P cells enable controllable lithium plating, allowing the lithium plating degree (DLi) to be quantified and linked to thermal safety. Pressure signals during calibration provide a non‐destructive route to diagnose DLi, while thermal response tests define safety levels and management strategies. The framework remains applicable in commercial 12 Ah
Haonan Liu +10 more
wiley +1 more source
Hydrogen Isotopic Fractionation in the Solar Nebula and Implications for Water in Earth and Inner Solar System Bodies. [PDF]
Asaduzzaman A.
europepmc +1 more source
ABSTRACT Translating dynamic liquid‐liquid phase separation into robust solid‐state architectures remains a challenge in materials engineering. Here, we report a composition‐driven interfacial assembly strategy that couples supramolecular coacervation with metal‐phenolic coordination to engineer tunable fungicide carriers.
Rui Zhang +7 more
wiley +1 more source
Inflammatory Syndrome Regulated by WNT/β-Catenin, Non-Muscle Myosin and α-SMA Is a Self-Organized Dissipative Structure. [PDF]
Lecarpentier Y +3 more
europepmc +1 more source
The thermodynamics of binary decisions: statistical inference in a two-state system
Diego Mora, Gonzalo Gutiérrez
openalex +1 more source
Polymer Concepts in Cellular Function
Advanced Science, EarlyView.
Miao Yu +7 more
wiley +1 more source
A multi‐fidelity framework integrates sparse direct and abundant indirect electrocaloric measurements. Multi‐objective active learning accelerates BaTiO3‐based electrocaloric materials discovery at –70∘C$^{\circ }{\rm C}$. A diffuse transition enables an electrocaloric strength of 0.06×$\times$10−6 Km/V at –70℃ with an operational temperature span of ...
Bo Wang +8 more
wiley +1 more source
Application of Local Approaches to Crack Development in Structural Materials. [PDF]
Kozák V, Vala J.
europepmc +1 more source
Learning Work Function via Implicit Reasoning on Electrostatic Potential Landscapes
StructPot‐CLR establishes a cross‐modal contrastive learning framework that aligns the crystal structures of 2D materials with plane‐averaged electrostatic potential landscapes for physically informed work‐function prediction. The model achieves an MAE of 0.265 eV and an R2 of 0.902 on the held‐out test set while accurately preserving key morphological
Haoyu Wan, Yue Wu, Tianhao Su, Deng Pan
wiley +1 more source

