Conductive printed thermoplastic polyurethane nanofibers for air filter clogging detection
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study investigates the development of strain sensors using electrospun thermoplastic polyurethane (TPU) nanofibers combined with conductive inks. TPU nanofibers were produced under controlled electrospinning conditions, achieving an average diameter of 700 ± 96 nm. Various conductive patterns such as zigzag and star, designed in KiCad, were printed onto the nanofibrous membranes to optimize sensor performance. The membranes were characterized using scanning electron microscopy (SEM) for morphology, burst strength tests for mechanical durability, and tunnel tests to assess airflow resistance and pressure drop at different velocities. The results revealed that printed patterns influenced sensor sensitivity, rupture strength, and pressure drop. Among these, the star-patterned membrane demonstrated a novel configuration that maximized both sensitivity and mechanical durability under airflow stress. This unique design provided the highest sensitivity and rupture resistance at higher velocities compared to other patterns. These TPU-based strain sensors, with enhanced filtration and sensing capabilities, are promising for air filtration systems, with potential applications in detecting clogging and airflow changes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it