ReviewNanoscale advances2026
Two-dimensional layered metal oxides (2D LMOs) for next-generation electronic devices.
Review in Nanoscale advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Two-dimensional layered metal oxides (2D LMOs) have emerged as a rapidly growing class of materials that combine the advantages of reduced dimensionality with the functional diversity of transition metal oxides. Their high surface-to-volume ratio, structural anisotropy, tunable bandgap, and variable oxidation states endow them with unique electrical, optical, and catalytic properties. Recent advances in atomic layer deposition, vapor-phase synthesis, and liquid-phase exfoliation have enabled the scalable fabrication of high-quality 2D LMOs with controlled stoichiometry and thickness. This review provides a comprehensive overview of their structure-property relationships, charge transport mechanisms, and interfacial phenomena, emphasizing how defect engineering, quantum confinement, and interlayer coupling can be exploited to tailor their performance. The integration of 2D LMOs into van der Waals heterostructures further enhances band alignment, charge transfer, and excitonic control, unlocking new opportunities for transistors, sensors, and spintronic and optoelectronic devices. Current challenges such as environmental stability, phase control, and large-scale processability are critically assessed. Finally, emerging computational and machine learning-guided approaches are discussed as pathways to accelerate the rational design of 2D LMOs for flexible, energy-efficient, and multifunctional electronic applications.
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Registered trials
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