ArticleAdvanced materials (Deerfield Beach, Fla.)2026
Bioinspired Electrostatic-Field Perturbated Sensing for General Material Noncontact Perception.
Article in Advanced materials (Deerfield Beach, Fla.), 2026. 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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Who cites it
3 citing papers in PubMed.
- Bio-Inspired Gradient Heterogeneous Architectures for Ultrasensitive and Robust Strain Sensors via Programmable Crack Engineering.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Arch-Shaped Triboelectric Nanogenerator Based on PTFE, Paper, and Aluminum for Sustainable Energy Harvesting.Micromachines · 2026Article
- The Applications of Machine Learning in Micro-Nano Materials Research: From High-Throughput Screening to Intelligent Design.Small (Weinheim an der Bergstrasse, Germany) · 2026Review
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Noncontact sensing is essential for smart manufacturing and safe human-machine interaction, yet existing proximity and inspection sensors are often limited by material selectivity, ambient light, and continuous power consumption. Here, we report a bioinspired electrostatic-field sensor that implements a solid-state analogue of electrolocation using a corona-polarized fluoropolymer electret. The pre-charged electret establishes a quasi-static electric field, and nearby objects reshape this field to induce measurable potential modulation on a grounded electrode, enabling friction-free sensing without active emission or mechanical contact. The sensor detects both conductive and dielectric targets (metals, polymers, glass), while waveform features encode material-dependent electrical signatures. The device achieves a near-field change in separation sensitivity of 1.05 V per 50 µm and maintains stable responses over 10,000 approach-withdraw cycles. Combined with machine-learning models, the platform enables proximity warning, touch-free interaction, material discrimination, coating-defect recognition, gesture decoding, and gesture-to-robot control. This work establishes electrostatic-field perturbation as a robust strategy for low-power, multifunctional noncontact perception.
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Registered trials
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