Results 101 to 110 of about 4,333 (278)
Advanced Functional Materials, EarlyView.A programmable interpenetrating double‐network architecture, created via 3D‐TIPS printing and resin infusion, synergistically combines thermoplastic and thermosetting elastomers to balance structural rigidity and surface softness—crucial for paediatric laryngeal stents.
Elizabeth F. Maughan +14 more
wiley +1 more source
Advanced Functional Materials, EarlyView.This review explores functional and responsive materials for triboelectric nanogenerators (TENGs) in sustainable smart agriculture. It examines how particulate contamination and dirt affect charge transfer and efficiency. Environmental challenges and strategies to enhance durability and responsiveness are outlined, including active functional layers ...
Rafael R. A. Silva +9 more
wiley +1 more source
MOFs and COFs in Electronics: Bridging the Gap between Intrinsic Properties and Measured Performance
Advanced Functional Materials, EarlyView.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
Phase‐Stable Palladium Hydride Derived from PdCoO2 for Sustainable Hydrogen Evolution Reaction
Advanced Functional Materials, EarlyView.The exceptionally active β‐PdHx is demonstrated for the hydrogen evolution reaction in acidic media. The fast activation kinetics from the PdCoO2 template are resolved by operando spectroscopy, and isotope‐labeled atom probe tomography quantifies the H content in β‐PdHx. The outstanding stability of the electrocatalyst is attributed to the retention of
Luca Camuti +10 more
wiley +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
Advanced Functional Materials, EarlyView.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
The dominance-based rough set approach to cylindrical plunge grinding process diagnosis [PDF]
, 2016 P. Leżański, Maria Piłacińska
openalex +1 more source
Advanced Functional Materials, EarlyView.A hybrid anode composed of Cl‐functionalized curved nanographene and graphite enables ultra‐fast charging and long cycle life through an engineered morphology and sequential Li+ insertion. It delivers 100 mAh g−1 at 5 C with 70% capacity retention after 1000 cycles and maintains stable performance over 2000 cycles in pouch cells, providing a practical ...
Hyunji Cha +8 more
wiley +1 more source