ReviewNano-micro letters2025
High-Entropy Oxide Memristors for Neuromorphic Computing: From Material Engineering to Functional Integration.
Review in Nano-micro letters, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Engineering ScAlN Polar Properties for Advanced Electronic and Synaptic Applications.Small methods · 2026Review
- Analysis and Applications of Neuromorphic Memristors in Artificial Intelligence Computing.Nano-micro letters · 2026Review
- Anomalous Crystallinity and Magnetism in Chemically Disordered Coherent Heterostructures.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- 2D Materials Powering Neuromorphic Intelligence.Nano-micro letters · 2026Review
- In-Sensor-Memory Computing for Post-Von Neumann Intelligence: A Perspective.Nano-micro letters · 2026Article
- Flexible Polymer-Based Electronics for Human Health Monitoring: A Safety-Level-Oriented Review of Materials and Applications.Nano-micro letters · 2026Review
- A Corticotectal Pathway Regulates Vibrissal Somatosensory-Mediated Predatory Hunting Learning.Research (Washington, D.C.) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High-entropy oxides (HEOs) have emerged as a promising class of memristive materials, characterized by entropy-stabilized crystal structures, multivalent cation coordination, and tunable defect landscapes. These intrinsic features enable forming-free resistive switching, multilevel conductance modulation, and synaptic plasticity, making HEOs attractive for neuromorphic computing. This review outlines recent progress in HEO-based memristors across materials engineering, switching mechanisms, and synaptic emulation. Particular attention is given to vacancy migration, phase transitions, and valence-state dynamics-mechanisms that underlie the switching behaviors observed in both amorphous and crystalline systems. Their relevance to neuromorphic functions such as short-term plasticity and spike-timing-dependent learning is also examined. While encouraging results have been achieved at the device level, challenges remain in conductance precision, variability control, and scalable integration. Addressing these demands a concerted effort across materials design, interface optimization, and task-aware modeling. With such integration, HEO memristors offer a compelling pathway toward energy-efficient and adaptable brain-inspired electronics.
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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.