ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025
Bio-Inspired SA-FA Bionic Dual Receptor Electronic Skin for Intelligent Gesture and Material Cognition Systems Enhanced by Static-Dynamic Mutual Interaction.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed.
- Bio-Inspired SA-FA Bionic Dual Receptor Electronic Skin for Intelligent Gesture and Material Cognition Systems Enhanced by Static-Dynamic Mutual Interaction.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Traditional electronic skins (e-skins) face significant challenges in system integration and practical usability demonstrations, limiting their ability to meet the development demands of robot intellectualization under future artificial intelligence (AI) frameworks. Here, a bionic dual receptor (BDR) e-skin motivated by AI-based hardware-software coordination is proposed, which consists of electrospinning fiber triboelectric unit inspired by fast-adapting receptors and micropyramid ionic hydrogel iontronic unit inspired by slow-adapting receptors. Benefiting from the iontronic effect and micropyramid structure, the iontronic unit yields impressive features: a linear sensitivity of 172 kPa
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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.