Results 171 to 180 of about 10,825 (251)
On the Origin and Evolution of the Material in 67P/Churyumov-Gerasimenko. [PDF]
Rubin M +7 more
europepmc +1 more source
DIVISION G COMMISSION 35: STELLAR CONSTITUTION
M. Limongi +9 more
semanticscholar +1 more source
Efficient water electrolysis in NaBr electrolyte is achieved using TiO2 nanotube supports decorated with Ru nanoparticles. A cooperative “job‐sharing” effect between the TiO2 proton‐storage support that provides protons to the Ru catalyst enhances hydrogen evolution, minimizes Ru demand and polarization losses, and delivers stable performance ...
Matan Sananis +3 more
wiley +1 more source
Atmospheric parameters and chemical composition of the ultra-cool roAp star HD 213637
O. Kochukhov
semanticscholar +1 more source
Band‐Edge Engineering of BiFeO3–KTaO3 Solid Solutions toward Efficient Solar Hydrogen Production
This study reports BiFeO3–KTaO3 solid solutions as efficient photocathodes for solar hydrogen production. Combining experiments with density functional theory, the authors demonstrate composition‐driven band‐edge tuning, achieving high photocurrent density and hydrogen generation rates.
Yassine Nassereddine +5 more
wiley +1 more source
Cosmochemical evidence for astrophysical processes during the formation of our solar system. [PDF]
MacPherson GJ, Boss A.
europepmc +1 more source
Flexible Memory: Progress, Challenges, and Opportunities
Flexible memory technology is crucial for flexible electronics integration. This review covers its historical evolution, evaluates rigid systems, proposes a flexible memory framework based on multiple mechanisms, stresses material design's role, presents a coupling model for performance optimization, and points out future directions.
Ruizhi Yuan +5 more
wiley +1 more source
Calcium isotopes offer clues on resource partitioning among Cretaceous predatory dinosaurs. [PDF]
Hassler A +6 more
europepmc +1 more source
In this work, the Doubao large language model (LLM) is involved in the formula derivation processes for Hubbard U determination regarding the second‐order perturbations of the chemical potential. The core ML tool is optimized for physical domain knowledge, which is not limited to parameter prediction but rather serves as an interactive physical theory ...
Mingzi Sun +8 more
wiley +1 more source
Revealing Protein–Protein Interactions Using a Graph Theory‐Augmented Deep Learning Approach
This study presents a fast, cost‐efficient approach for classifying protein–protein interactions by integrating graph‐theory parametrization with deep learning (DL). Multiscale features extracted from graph‐encoded polarized‐light microscopy (PLM) images enable accurate prediction of binding strengths.
Bahar Dadfar +5 more
wiley +1 more source

