ArticleScience advances2022
Reliable multilevel memristive neuromorphic devices based on amorphous matrix via quasi-1D filament confinement and buffer layer.
Article in Science advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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
9 citing papers in PubMed, 58 citations in OpenAlex.
- Tunable Dynamics via Dual-Ion Modulation for Event-based Data Processing Using a Highly Uniform and Self-Rectifying Memristor Array.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Ultralow energy adaptive neuromorphic computing using reconfigurable zinc phosphorus trisulfide memristors.Nature communications · 2025Article
- Tunable ion energy barrier modulation through aliovalent halide doping for reliable and dynamic memristive neuromorphic systems.Science advances · 2024Article
- Synergistically Modulating Conductive Filaments in Ion-Based Memristors for Enhanced Analog In-Memory Computing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Artificial sensory system based on memristive devices.Exploration (Beijing, China) · 2024Review
- 3D Neuromorphic Hardware with Single Thin-Film Transistor Synapses Over Single Thin-Body Transistor Neurons by Monolithic Vertical Integration.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- Multi-level resistive switching in hafnium-oxide-based devices for neuromorphic computing.Nano convergence · 2023Review
- Two-Terminal Lithium-Mediated Artificial Synapses with Enhanced Weight Modulation for Feasible Hardware Neural Networks.Nano-micro letters · 2023Article
- Conductive Bridge Random Access Memory (CBRAM): Challenges and Opportunities for Memory and Neuromorphic Computing Applications.Micromachines · 2022Review
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Conductive-bridging random access memory (CBRAM) has garnered attention as a building block of non-von Neumann architectures because of scalability and parallel processing on the crossbar array. To integrate CBRAM into the back-end-of-line (BEOL) process, amorphous switching materials have been investigated for practical usage. However, both the inherent randomness of filaments and disorders of amorphous material lead to poor reliability. In this study, a highly reliable nanoporous-defective bottom layer (NP-DBL) structure based on amorphous TiO
Identifiers
What OpenQuestion holds
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.