Bio-inspired organic electrosense transistor for impalpable perception
Data files
Mar 03, 2025 version files 717.87 KB
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Data_Source_(uploaded_to_dryad).zip
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README.md
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Abstract
Artificial sense technologies predominantly rely on visual and tactile input, which often prove inadequate in obscured or opaque environments. Inspired by the natural electrosensory capabilities of electrogenic fishes, we introduce an organic electrosense transistor designed to detect electric fields generated by nearby objects, facilitating the creation of impalpable perception systems. Unlike traditional sensors, our electrosense transistor perceives bipolar electric fields with high sensitivity and stability. We employ compact models and device simulations to elucidate the mechanisms of charge induction and transport within organic electrosense transistors when exposed to spatial electric fields. Demonstrating its practical utility, we show that robots equipped with our electrosense transistor can successfully navigate and detect concealed objects without requiring direct contact. This work not only advances the understanding of charge dynamics in electrosensory systems but also establishes a platform for developing highly sensitive, non-invasive artificial sensing technologies applicable in surveillance, search-and-rescue, and other challenging environments.
https://doi.org/10.5061/dryad.dz08kps7k
Description of the data and file structure
Dataset Title
Bio-inspired organic electrosense transistor for impalpable perception
Date of Data Collection
2020-2024
Contributors
Cong Wang: School of Materials Science and Engineering, Nanyang Technological University
Jiaofu Li: School of Materials Science and Engineering, Nanyang Technological University
Xufan Li: Institute of Microelectronics, Chinese Academy of Sciences
Mingxi Chen: Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR)
Wenping Hu: Department of Chemistry, Institute of Molecular Aggregation Science, Tianjin University
Xiaodong Chen: School of Materials Science and Engineering, Nanyang Technological University
Overview
This data source is the raw data of the main figure in the aricle, so that it can be used by readers and other researchers to better understand the organic sensing transistor. We will give the data that is not easy to read directly from the Figure separately.
Data Formats
Excel Files:
- .xlsx/.csv: Used to organize and display data summaries and metadata, which may include measured time and current, simulated induced charge surface density, energy, total donor trap density.
- Data file "Fig. 2E" represents simulated induced surface charge density of devices with different permittivity.
- Data file "Fig. 3H" represents simulated trap density of states at the grain boundary of organic cyratlline films.
- Data file "Fig. 3I" represents time-dependent fitting model shows that increasing the crystallinity enables the device to transition from a transient to a steady response.
- Data file "Fig. 4A and Fig. 4B" represent dynamic current responses of the electrosense transistor with stepwise electric field strength for negative (A) and positive electric field (B), respectively.
- Data file "Fig. 4C and Fig. 4D" represent response currents with electric field strength show a positive correlation in electrosense transistor.
- Data file "Fig. 4F" represents current response for negatively charged (-) PTFE at different distances from 325 mm to 5 mm to the electrosense transistor.
- Data file "Fig. 4J" represents key performance indicators of electrosense transistor compared to the resistor-type sensor and the sensing electrode.
- Data file "Fig. 5K" represents feedback signals for robots with electrosensory systems crawling from left to right in search of an orange sphere hidden in an opaque box.