ReviewCommunications engineering2026
Oxide semiconductor gain cell-embedded memory: materials and integration strategies for next generation on-chip memory.
Review in Communications engineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
The data processing demands of the digital era have exposed limitations in conventional memory architectures. Gain cell-embedded dynamic random-access memory based on oxide semiconductors is emerging as a solution, addressing scalability, power efficiency, and integration density challenges. Our review highlights that oxide semiconductors offer exceptional properties for gain cell memory applications, including ultra-low leakage currents and wide bandgap characteristics, while their advanced structures like gate-all-around and channel-all-around stacked architectures demonstrate the potential for high-density integration. While challenges in manufacturing and reliability persist, this paradigm shift in memory design holds promise for reshaping computing systems for artificial intelligence and advanced computing applications.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.