ReviewAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2023
Carbon Nanodots Memristor: An Emerging Candidate toward Artificial Biosynapse and Human Sensory Perception System.
Review in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2023. 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
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
9 citing papers in PubMed.
- Engineering halogen-doped carbon dots for enhanced bioinspired synapses toward neuromorphic computing and neural interfaces.Materials today. Bio · 2026Article
- Ferroelectric Devices for In-Memory and In-Sensor Computing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Printed High-Entropy Prussian Blue Analogs for Advanced Non-Volatile Memristive Devices.Advanced materials (Deerfield Beach, Fla.) · 2025Article
- Atomic Nb-doping of WSMicrosystems & nanoengineering · 2024Article
- Nonvolatile Memristive Materials and Physical Modeling for In-Memory and In-Sensor Computing.Small science · 2024Article
- Spike rate dependent synaptic characteristics in lamellar, multilayered alpha-MoORSC advances · 2024Article
- Antibiotic-Powered Energy Harvesting: Introducing Benzylpenicillin as an Efficient Tribopositive Material for Triboelectric Nanogenerators.Nanomaterials (Basel, Switzerland) · 2023Article
- Article
- Carbon Nanodots Memristor: An Emerging Candidate toward Artificial Biosynapse and Human Sensory Perception System.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
In the era of big data and artificial intelligence (AI), advanced data storage and processing technologies are in urgent demand. The innovative neuromorphic algorithm and hardware based on memristor devices hold a promise to break the von Neumann bottleneck. In recent years, carbon nanodots (CDs) have emerged as a new class of nano-carbon materials, which have attracted widespread attention in the applications of chemical sensors, bioimaging, and memristors. The focus of this review is to summarize the main advances of CDs-based memristors, and their state-of-the-art applications in artificial synapses, neuromorphic computing, and human sensory perception systems. The first step is to systematically introduce the synthetic methods of CDs and their derivatives, providing instructive guidance to prepare high-quality CDs with desired properties. Then, the structure-property relationship and resistive switching mechanism of CDs-based memristors are discussed in depth. The current challenges and prospects of memristor-based artificial synapses and neuromorphic computing are also presented. Moreover, this review outlines some promising application scenarios of CDs-based memristors, including neuromorphic sensors and vision, low-energy quantum computation, and human-machine collaboration.
Indexed as
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.