Results 151 to 160 of about 949,288 (275)

Analysis of Self-Efficacy Learning Outcomes on Class VII MTSN 01 Pasuruan Viewed Based On Students' Mathematical Ability

open access: yesNoumerico
This study aims to analyze self-efficacy's effect on students' learning outcomes in class VII MTsn 01 Pasuruan. This research is a type of descriptive research with a qualitative approach.
Dewi Fariha, Fajriyah Rachmatika
doaj   +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

Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics

open access: yesAdvanced Functional Materials, EarlyView.
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha   +18 more
wiley   +1 more source

Purcell‐Enhanced Spectrally Precise Emission in Dual‐Microcavity Organic Light‐Emitting Diodes

open access: yesAdvanced Functional Materials, EarlyView.
Spectrally precise emission from broadband organic light‐emitting diodes is realized via a dual‐microcavity strategy. This architecture achieves narrowband emission (full width at half maximum, FWHM = 21 nm) with ultrapure color approaching BT.2020 by enhancing the Purcell effect via coupling of excitons with dual‐microcavity resonance.
Jun Yong Kim   +3 more
wiley   +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

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