Results 151 to 160 of about 68,051 (242)

Electrochemical Activation of LiGaO2: Implications for Ga-Doped Garnet Solid Electrolytes in Li-Metal Batteries. [PDF]

open access: yesACS Appl Mater Interfaces
Windmüller A   +14 more
europepmc   +1 more source

Tuning the Electronic Structure and Spin State of Fe─N─C Catalysts Using an Axial Oxygen Ligand and Fe Clusters for High‐Efficiency Rechargeable Zinc–Air Batteries

open access: yesAdvanced Functional Materials, EarlyView.
A FeN4─O/Clu@NC‐0.1Ac catalyst containing atomically‐dispersed FeN4─O sites (medium‐spin Fe2+) and Fe clusters delivered a half‐wave potential of 0.89 V for ORR and an overpotential of 330 mV at 10 mA cm−2 for OER in 0.1 m KOH. When the catalyst was used in a rechargeable Zn–air battery, a power density of 284.5 mW cm−2 was achieved with excellent ...
Yongfang Zhou   +8 more
wiley   +1 more source

Atomically Revealing Bulk Point Defect Dynamics in Hydrogen‐Driven γ‐Fe2O3 → Fe3O4 → FeO Transformation

open access: yesAdvanced Functional Materials, EarlyView.
In situ TEM uncovers the atomic‐scale mechanisms underlying hydrogen‐driven γ‐Fe2O3→Fe3O4→FeO reduction. In γ‐Fe2O3, oxygen vacancies cluster around intrinsic Fe vacancies, leading to nanopore formation, whereas in Fe3O4, vacancy aggregation is suppressed, preserving a dense structure.
Yupeng Wu   +14 more
wiley   +1 more source

Trap‐Modified Inverted Organic Photodetectors via Layer‐by‐Layer Processing with Poly(N‐vinylcarbazole) Additives

open access: yesAdvanced Functional Materials, EarlyView.
Trap state engineering in inverted organic photodetectors (OPDs) is achieved via combined layer‐by‐layer (LbL) processing and poly(N‐vinylcarbazole) (PVK) incorporation. LbL reduces the trap density while PVK additives gradually shift trap states from shallow band‐edge to deep mid‐gap levels, tailoring the energy distribution.
Jingwei Yi   +10 more
wiley   +1 more source

Electrochemical Activation of Fe-LiF Conversion Cathodes in Thin-Film Solid-State Batteries. [PDF]

open access: yesACS Nano
Casella J   +5 more
europepmc   +1 more source

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

open access: yesAdvanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee   +17 more
wiley   +1 more source

Home - About - Disclaimer - Privacy