Results 211 to 220 of about 1,744,597 (326)
3D‐Printed Sulfur‐Derived Polymers With Controlled Architectures for Lithium‐Sulfur Batteries
Rheology‐guided formulation design for direct ink writing enables the fabrication of 3D sulfur copolymer cathodes with controlled architectures for lithium‐sulfur batteries. The printed electrodes exhibit multiscale porosity and high sulfur utilization, delivering enhanced electrochemical performance compared to conventional cast electrodes.
Bin Ling +7 more
wiley +1 more source
The impact of inclusive electron ion collider data on the strong coupling determination in a global PDF fit. [PDF]
Harland-Lang LA +4 more
europepmc +1 more source
A food‐grade cooling composite made from starch and recycled eggshell powder offers a scalable, ultra‐low‐cost solution for passive daytime radiative cooling. Easily prepared using basic kitchen tools, this material empowers communities, even in areas with limited infrastructure, to stay cooler during worsening summer heat waves.
Qimeng Song +3 more
wiley +1 more source
Controlled motivation and physics achievement: a serial mediation analysis through self-efficacy and learning strategies in Chinese high school students. [PDF]
Li X, Lin X, Lin J, Yan M.
europepmc +1 more source
(1) Theoretical Physics (2) Lehrbuch der theoretischen Physik [PDF]
E. N. da C. A.
openalex +1 more source
MOFs and COFs in Electronics: Bridging the Gap between Intrinsic Properties and Measured Performance
Metal‐organic frameworks (MOFs) and covalent organic frameworks (COFs) hold promise for advanced electronics. However, discrepancies in reported electrical conductivities highlight the importance of measurement methodologies. This review explores intrinsic charge transport mechanisms and extrinsic factors influencing performance, and critically ...
Jonas F. Pöhls, R. Thomas Weitz
wiley +1 more source
Improving the Precision of First-Principles Calculation of Parton Physics from Lattice Quantum Chromodynamics. [PDF]
Zhao Y.
europepmc +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source

