Results 161 to 170 of about 89,086 (217)

On‐Surface Indigo‐Based Bimolecular Coordination Networks with Programmable Regular or Vitreous Structure

open access: yesAdvanced Functional Materials, EarlyView.
A previously unreported coordination motif stabilising single Fe atoms by indigo chelation and pyridyl coordination on Au(111) has been revealed. By using planar tritopic pyridyl linkers (TPyB), extended 2D porous networks of indigo3(TPyB)2Fe6 form. These networks can be crystalline or vitreous and offer an environment where individual coordination ...
Hongxiang Xu   +9 more
wiley   +1 more source

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

3D‐Printed Sulfur‐Derived Polymers With Controlled Architectures for Lithium‐Sulfur Batteries

open access: yesAdvanced Functional Materials, EarlyView.
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

Beyond wind speed: Integrating oceanic indices and time-lagged features for superior wind energy prediction. [PDF]

open access: yesPLoS One
Rathnayake N   +5 more
europepmc   +1 more source

MOFs and COFs in Electronics: Bridging the Gap between Intrinsic Properties and Measured Performance

open access: yesAdvanced 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

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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