ArticleACS applied materials & interfaces2026
Bio-Inspired Spike-Timing-Dependent Plasticity Learning with Metal Halide Perovskites: Toward Artificial Synaptic Functionality.
Article in ACS applied materials & interfaces, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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.
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Who cites it
6 citing papers in PubMed.
- Boosted Photocatalytic COMolecules (Basel, Switzerland) · 2026Article
- Terahertz Time-Domain Spectroscopy as a Defect Fingerprinting Tool for Halide Perovskite Solar Cells: Toward a Universal Framework.Nanomaterials (Basel, Switzerland) · 2026Review
- Beyond SrTiOMaterials (Basel, Switzerland) · 2026Review
- Ion Migration in Two-Dimensional Organic-Inorganic Hybrid Perovskite Heterostructures: Interface Evolution, Migration Mechanisms and Device Implications.Nanomaterials (Basel, Switzerland) · 2026Review
- CHSensors (Basel, Switzerland) · 2026Article
- Spiking Neuron with Sensing Coil Based on a Volatile Memristor.Sensors (Basel, Switzerland) · 2026Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent advances in neuromorphic engineering have sparked a convergence between nanotechnology and neuroscience, where emerging devices such as memristors are being explored to replicate fundamental learning mechanisms observed in the brain. One such mechanism, spike-timing-dependent plasticity (STDP), encodes synaptic changes based on the precise timing between pre- and postsynaptic spikes, and has been widely adopted in machine intelligence and computational neuroscience. In this work, we demonstrate that a halide perovskite memristor (Cs
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Registered trials
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