Results 141 to 150 of about 476,845 (318)

Photoswitching Conduction in Framework Materials

open access: yesAdvanced Functional Materials, EarlyView.
This mini‐review summarizes recent advances in state‐of‐the‐art proton and electron conduction in framework materials that can be remotely and reversibly switched on and off by light. It discusses the various photoswitching conduction mechanisms and the strategies employed to enhance photoswitched conductivity.
Helmy Pacheco Hernandez   +4 more
wiley   +1 more source

A Bespoke Programmable Interpenetrating Elastomer Network Composite Laryngeal Stent for Expedited Paediatric Laryngotracheal Reconstruction

open access: yesAdvanced 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

Understanding and assessing personality across cultures: A scoping review. [PDF]

open access: yesPLoS One
Sheppard H   +3 more
europepmc   +1 more source

Inactivating SARS‐CoV‐2 Virus with MOF‐Composites as Smart Face Masks

open access: yesAdvanced Functional Materials, EarlyView.
In situ preparation and functionalization of MOF@Cotton fabrics as smart face masks for the immobilization of proteins and inactivation viruses, such as SARS‐CoV‐2. Abstract The significant impact of the SARS‐CoV‐2 (COVID‐19) pandemic outbreak on people's lives has highlighted the urgent need for effective personal protective equipment.
Romy Ettlinger   +9 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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