Results 271 to 280 of about 25,360,752 (379)

Structured, Shaped, or Printed Single‐Atom Catalysts and Their Applications

open access: yesAdvanced Functional Materials, EarlyView.
This paper reviews the design and use of structured single‐atom catalysts, which integrate porous architectures with the exceptional reactivity of isolated catalytic sites. It explores fabrication strategies, advanced characterization methods, and support materials that enhance thermal stability, mechanical robustness, and operational efficiency of ...
Jiachengjun Luo   +4 more
wiley   +1 more source

Complex Formation Between Poly-L-alanine and Copper (II)

open access: bronze, 1969
Nobumasa Hōjō   +3 more
openalex   +2 more sources

Hyperbranched Interpenetrating Hydrogen Bond Network (HIHBN) Proton Exchange Membrane for Fuel Cells Above 220 °C

open access: yesAdvanced Functional Materials, EarlyView.
A novel polymer electrolyte membrane with a hyperbranched interpenetrating hydrogen bond network structure is developed. The unique structure of the hyperbranched polymer contributes to a high glass transition temperature exceeding 400 °C, enabling its operation at elevated temperatures for fuel cell applications.
Lingping Zeng   +10 more
wiley   +1 more source

Solution‐Processable and Ambient‐Stable Highly Conductive p‐Type Polymers Derived from Dihydropyrazine and Ethylenedioxythiophene

open access: yesAdvanced Functional Materials, EarlyView.
This work presents π–conjugated polymers based on dihydropyrazine (DHP) and ethylenedioxythiophene (EDOT), developed to produce highly conductive, flexible films for printed electronics. By optimizing the DHP and EDOT ratio, strong and compact π–π stacking is achieved, resulting in polymer films with conductivities up to 1700 S cm−1 under ambient ...
Sung Jae Jeon   +3 more
wiley   +1 more source

Active Learning‐Driven Discovery of Sub‐2 Nm High‐Entropy Nanocatalysts for Alkaline Water Splitting

open access: yesAdvanced Functional Materials, EarlyView.
High‐entropy nanoparticles (HENPs) hold great promise for electrocatalysis, yet optimizing their compositions remains challenging. This study employs active learning and Bayesian Optimization to accelerate the discovery of octonary HENPs for hydrogen and oxygen evolution reactions.
Sakthivel Perumal   +5 more
wiley   +1 more source

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