Results 231 to 240 of about 2,692,217 (346)
This article explores high‐entropy‐stabilized oxides (HEOs) as novel functional materials for addressing critical issues in lithium–sulfur (Li–S) batteries, including lithium polysulfide (LPS) shuttling, inadequate conductivity, and slow redox kinetics.
Hassan Raza +10 more
wiley +1 more source
A sensor-fused BIM-based ıntelligent control system for energy-efficient ındoor environmental regulation using deep actor-critic reinforcement learning (DACRL). [PDF]
Tong L.
europepmc +1 more source
This study investigates Spanish broom (Spartium junceum) as a renewable source for electrospun composite membranes in sustainable water purification. MCC and biochar were functionalized with eco‐friendly precursors and nanomaterials (i.e., HNT, β‐CDs) to develop hybrid PVA nanofiber composites.
Giulia Rando +7 more
wiley +1 more source
Automated modeling to high level-of-detail composite object using spatial BIM objects and properties. [PDF]
Lee JK, Cho D, Kim Y, Mo Y.
europepmc +1 more source
A one‐step gas‐phase synthesis directly assembles amorphous Si nanoparticles with few‐layer graphene heterostructures via in‐flight mixing. Compositions with only 15 wt.% FLG deliver ~2800 mAh g−1 (Si + FLG) at 0.05 C and retain ~1400 mAh g−1 after 100 cycles at a high cycling rate of 1 C, enabled by a percolated, strain‐buffering graphene network that
Muhammad Ali +5 more
wiley +1 more source
Knowledge Architecture for Race and Ethnic Group Defining in Learning Health Systems. [PDF]
Hudson MF +3 more
europepmc +1 more source
For the Few, Not the Many: Tracing the Residualist and Compensatory Nature of British Energy Support
ABSTRACT Drawing on extensive documentary analysis, this article traces the evolution of British energy policy support since World War II. It analyses shifts in policy design through two interpretive lenses: eligibility (residualist vs. universalist) and function (compensatory vs. preventive).
T. M. Croon +4 more
wiley +1 more source
Machine learning models for predicting rural residential carbon emissions and optimising spatial forms. [PDF]
Cui X, Xu Y, Sun L, Yao T.
europepmc +1 more source
AI‐driven circular economy optimization in waste management: A review of current evidence
Abstract The integration of artificial intelligence (AI) and machine learning (ML) in waste management has the potential to significantly advance circular economy objectives by enhancing efficiency, reducing waste, and optimizing resource recovery. However, realising these benefits depends on addressing significant technical, economic, and systemic ...
David Bamidele Olawade +3 more
wiley +1 more source

