ArticleAdvanced materials (Deerfield Beach, Fla.)2025
Pressure Induced Molecular-Arrangement and Charge-Density Perturbance in Doped Polymer for Intelligent Motion and Vocal Recognitions.
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 4 papers.
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The trial behind it
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Who cites it
4 citing papers in PubMed.
- Advances in flexible wearable pressure/strain sensors for motion monitoring in orthopaedic sports medicine.Journal of orthopaedic translation · 2026Review
- Carbon Nanotube-Induced Enzyme Polymerization for Wearable Multifunctional Biosensors in Sweat Analysis.JACS Au · 2026Article
- Pressure Induced Molecular-Arrangement and Charge-Density Perturbance in Doped Polymer for Intelligent Motion and Vocal Recognitions.Advanced materials (Deerfield Beach, Fla.) · 2025Article
- Highly Stretchable and Reliable Graphene-Based Strain Sensor for Plant Health Monitoring and Deep Learning-Assisted Crop Recognition.Research (Washington, D.C.) · 2025Article
Corrections and comments
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Authors and funding
15 authors.
Funding
Abstract
Conjugated polymers (CPs) show great potential for pressure detection due to the amorphous polymer packing, but a lack of clarity regarding sensing mechanisms hampers the development of further applications. Herein, a sacrificial template-full solution method with both rough surface and high conductivity is described that can be applied to sandwich-structured resistive pressure sensors. Transient absorption measurements demonstrate the significant increase of carrier lifetime (from 1.44 to 2.54 ns) induced by pressure, which directly evidenced the superior sensing mechanism of sidechain doped conjugated polymer. This sensor displayed low-pressure detection limit of 0.7 Pa as well as a rapid response time of 18.8 ms, enabling multi-mode motion analysis including wrist pulse, swallowing, finger bending, grabbing, and typing. Additionally, an intelligent vocal recognition system with convolutional neural networks is used which can achieve >96% classification accuracy across diverse vocal profiles. This general approach is anticipated and enables a new direction for the development of pressure sensors.
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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.