Results 181 to 190 of about 1,171,440 (255)

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

Rapid discovery of functional RNA domains. [PDF]

open access: yesNucleic Acids Res
Latifi B, Cole KH, Vu MMK, Lupták A.
europepmc   +1 more source

Switching of Magnetic Order via Non‐Magnetic Al Addition in FeCoNiMnAlx Films

open access: yesAdvanced Functional Materials, EarlyView.
Non‐magnetic Al addition provides a sensitive handle to switch the magnetic order in high entropy FeCoNiMnAlx thin films via fcc to bcc phase transformation. Films with fcc structure exhibit a large exchange bias, while bcc films exhibit enhanced ferromagnetic properties, reflecting the magnetic ground state of Mn which switches from antiferromagnetic ...
Willie B. Beeson   +6 more
wiley   +1 more source

Interfacial Interaction‐Mediated Regulation of Metal Oxidation States for Enhanced CO2 Reduction

open access: yesAdvanced Functional Materials, EarlyView.
A hybrid strategy is employed to optimize bismuth–oxygen interactions, precisely regulating interfacial bismuth–oxygen bonds during topochemical synthesis. This leads to vanadium oxynitride‐bismuth catalyst exhibiting high Faradaic efficiency and durability for formate production, attributed to enhanced reaction thermodynamics and kinetics.
Zhongyuan Ma   +6 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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