Results 171 to 180 of about 298,840 (319)

Mitigating Structural Degradation in O3‐Layered Sodium‐Ion Cathodes: Insights from Mg Doping in NaNi0.2Fe0.4Mn0.4O2

open access: yesAdvanced Energy Materials, EarlyView.
Selective Mg doping in O3‐layered NaNi0.2Fe0.4Mn0.4O2 unlocks fast Na⁺ transport, stable anionic redox, and structural resilience. At 5% substitution, the cathode delivers improved capacity retention and high‐rate performance, while suppressing oxygen loss.
Akanksha Joshi   +11 more
wiley   +1 more source

Tandem Takeoff: Powering Tomorrow with Industrial‐Grade Perovskite/Silicon Solar Cells

open access: yesAdvanced Energy Materials, EarlyView.
Perovskite/silicon tandem solar cells have recently achieved certified power conversion efficiencies of 34.85%, far exceeding the Shockley‐Queisser limit for single‐junction silicon and standalone perovskite cells. This review highlights the latest advances in the design, integration, and optimization of perovskite top cells for monolithic tandem ...
Maria Vasilopoulou   +19 more
wiley   +1 more source

American Academy of Orthopaedic Surgeons OrthoInfo provides more readable information regarding rotator cuff injury than ChatGPT

open access: hybrid
Catherine Hand   +7 more
openalex   +1 more source

Ruddlesden–Popper Structured Sr3Fe2O7−δ as Redox‐Activated CO2 Sorbents for Green Hydrogen Production

open access: yesAdvanced Energy and Sustainability Research, EarlyView.
A‐site and B‐site doped strontium ferrite‐type Ruddlesden–Popper oxides are evaluated as CO2 sorbents for glycerol‐based hydrogen production via sorption‐enhanced steam reforming. A Sr1.4Ca0.6Fe0.9Ni0.1O4−δ composition forms an active Sr3Fe2O7 phase, achieving ≈95 vol% H2 purity and over sixfold longer CO2 prebreakthrough time (tpb) than its perovskite
Mahe Rukh   +6 more
wiley   +1 more source

Effects of education level on natural language processing in cardiovascular health communication. [PDF]

open access: yesFront Public Health
Joseph S   +5 more
europepmc   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Home - About - Disclaimer - Privacy