System design of large-area vertical photothermoelectric detectors based on carbon nanotube forests with MXene electrodes
Bibliographic record
Abstract
Photothermoelectric (PTE) detectors that combine photothermal and thermoelectric conversion have emerged in recent years. They can overcome bandgap limitations and achieve effective infrared detection. However, the development of PTE detectors and the related system design are in the early phases. Herein, we present vertical PTE detectors utilizing the active layer of carbon nanotube forests with MXenes acting as top electrodes. The detector demonstrates its capacity for sensitive infrared detection and rapid infrared response. We also investigated the relationship between photoresponse and different MXene electrode types as well as their thickness, which guides the PTE detector configuration design. Furthermore, we packed the PTE detectors with a polytetrafluoroethylene (PTFE, Teflon) cavity. The photoresponse is improved and the degradation is significantly delayed. We also applied this PTE detector system for non-destructive tracking (NDT) applications, where the photovoltage mapping pattern proves the viability of the imaging track. This work paves the way toward infrared energy harvesters and customized industrial NDT measurement.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".