Results 211 to 220 of about 641,383 (315)

Cool Kitchen: Processing Starch and Eggshell Powder into Sustainable Coatings for Passive Daytime Cooling

open access: yesAdvanced Functional Materials, EarlyView.
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

Functional Materials for Environmental Energy Harvesting in Smart Agriculture via Triboelectric Nanogenerators

open access: yesAdvanced 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

Universal In Situ Isotope Exchange Raman Spectroscopy (IERS) Methodology for Measuring Oxygen Surface Exchange Dynamics Using a Probe Layer

open access: yesAdvanced Functional Materials, EarlyView.
A bespoke multilayer thin film configuration has been designed, which overcomes the material dependency of conventional isotope exchange Raman spectroscopy (IERS). This universal IERS methodology is efficient, non‐destructive and provides additional structural information and time resolution, which can be further extended to various isotopic elements ...
Zonghao Shen   +7 more
wiley   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

open access: yesAdvanced 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

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