ArticleNature communications2026
Hybrid ferroelectric-ionic memristive hardware for high scalability in-memory computing.
Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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Authors and funding
29 authors.
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Abstract
In-memory computing using two-terminal memristors offers a promising route to reduce the energy demands of data-intensive computing. However, current devices scale poorly due to sneak currents and materials that are incompatible with standard complementary metal-oxide-semiconductor and very large-scale integration processes. Here we demonstrate a self-rectifying memristor that unifies resistive switching and diode-like rectification in a single device, a hybrid ferroelectric-ionic tunnel diode fabricated using complementary metal-oxide-semiconductor compatible materials and processes. We harness the collective (ferroelectric-antiferroelectric polymorphism) and defective (ionic) switching behaviors of HfO
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