ArticleAdvanced materials (Deerfield Beach, Fla.)2025
One-Shot Remote Integration of Macromolecular Synaptic Elements on a Chip for Ultrathin Flexible Neural Network System.
Article in Advanced materials (Deerfield Beach, Fla.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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
3 citing papers in PubMed.
- Laser-Defined States and Hydration-Driven Relaxation in PEDOT:PSS.Small (Weinheim an der Bergstrasse, Germany) · 2026Article
- Synaptic Plasticity Engineering for Neural Precision, Temporal Learning, and Scalable Neuromorphic Systems.Nano-micro letters · 2026Review
- One-Shot Remote Integration of Macromolecular Synaptic Elements on a Chip for Ultrathin Flexible Neural Network System.Advanced materials (Deerfield Beach, Fla.) · 2025Article
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Authors and funding
10 authors.
Funding
Abstract
The field of biomimetic electronics that mimic synaptic functions has expanded significantly to overcome the limitations of the von Neumann bottleneck. However, the scaling down of the technology has led to an increasingly intricate manufacturing process. To address the issue, this work presents a one-shot integrable electropolymerization (OSIEP) method with remote controllability for the deposition of synaptic elements on a chip by exploiting bipolar electrochemistry. Condensing synthesis, deposition, and patterning into a single fabrication step is achieved by combining alternating-current voltage superimposed on direct-current voltage-bipolar electropolymerization and a specially designed dual source/drain bipolar electrodes. As a result, uniform 6 × 5 arrays of poly(3,4-ethylenedioxythiophene) channels are successfully fabricated on flexible ultrathin parylene substrates in one-shot process. The channels exhibited highly uniform characteristics and are directly used as electrochemical synaptic transistor with synaptic plasticity over 100 s. The synaptic transistors have demonstrated promising performance in an artificial neural network (NN) simulation, achieving a high recognition accuracy of 95.20%. Additionally, the array of synaptic transistor is easily reconfigured to a multi-gate synaptic circuit to implement the principles of operant conditioning. These results provide a compelling fabrication strategy for realizing cost-effective and disposable NN systems with high integration density.
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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 Socratic graph.