Innovation in Textile Electrode of Electrochemical Devices: Water Transport and Thread-Based Temperature and Humidity Sensors
Bibliographic record
Abstract
Wearable health monitoring utilizing advances in textile technologies has already been demonstrated for transport of biomarkers and physiological sensing. These advances can potentially be translated to textile electrodes of electrochemical devices to allow managing reactants and by-products transport and for monitoring environmental parameters. Herein, a wicking properties and flexibility of threads are used (1) to control transport of water (by-product) within a textile gas diffusion layer (GDL) of the electrode of polymer electrolyte membrane fuel cells (PEMFCs), and (2) to develop thread-based sensors for local temperature and humidity monitoring. By means of ex-situ and in-situ characterizations, it was found that the threads can be introduced in the GDL structure to inscribe water highways within the GDL with minimal impact on GDL microstructure (i.e. porosity, porosity distributions) and transport properties (i.e. permeability, diffusivity and conductivity). Furthermore, a low-cost procedure was developed to transform a commodity thread into temperature and humidity sensors by dip-coating the thread with carbon nanotubes (CNTs) ink. The resistance of CNT coated threads is responsive to both parameters. In this work, the response to humidity was cancelled by coating fluorinated ethylene propylene (FEP) on top of the CNT coated thread to develop a temperature sensor independent of humidity. In addition, a second thread was coated with polydimethylsiloxane (PDMS) to monitor the relative humidity (RH). Thread-based sensors were characterized in an environmental chamber simulating environmental conditions in an operating fuel cell. A linear change of resistance with increasing temperature (~-0.31 %/T) was achieved for the temperature sensor, and the resistance of the thread coated with PDMS showed more sensitivity in high humidity regions (RH > 60%) and followed a quadratic function of RH. The thread-based temperature sensor capability was assessed via ex-situ experiments, and showed rapid response to change of temperature, and also the ability to map temperature in non-uniform temperature distributions. The combinations of both threads can allow simultaneous monitoring of local temperature and RH in the textile GDL of PEMFCs. This work enables local sensing and monitoring within textile electrodes without compromising the performance of PEMFCs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".