Capillary‐Assisted Self‐Assembly of Carbon Nanotubes for the Self‐Powered Photothermoelectric Detector
Bibliographic record
Abstract
The development of mid‐infrared (MIR) detectors has become a hot research topic with significant progress in low‐dimensional materials and clean‐room fabrication strategies. Some of the applications of MIR detectors include industrial non‐destructive testing, wearable safety monitoring, and other Internet of Things. Photothermoelectric (PTE) mechanism, as a room‐temperature free‐bias conversion mode, is comprehensively developed in the MIR regimes in the last decade. Although carbon nanotubes (CNTs) and their related materials are demonstrated as effective PTE conversion materials, the large‐area scalable detector fabrication based on the Si substrate is still underdeveloped, thus limiting further PTE device designs and industrial applications. Herein, the self‐assembly CNT‐based detectors driven by the capillary force are fabricated to achieve sensitive and rapid IR detection, and photoresponse measurements of PTE detectors are experimentally performed at room temperature and atmospheric conditions. This work reveals that the PTE mechanism can play a key role in the IR response, thereby broadening horizons about high‐performance IR detectors in industrial applications.
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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 | 0.000 | 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) | 0.001 | 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".