Controllable Hydrothermal Growth of ZnO Nanowires on Cellulose Paper for Flexible Sensors and Electronics
Bibliographic record
Abstract
Seamless integration of functional nanomaterials on paper can boost the functionality of paper-based flexible sensors and electronics. In this paper, we report the systematic study of a low-cost hydrothermal process for growing zinc oxide nanowires (ZnO NWs) on cellulose paper substrates. To control the competition between homogeneous and heterogeneous nucleation and obtain ZnO NWs with superior morphology and high growth efficiency, we tune the critical growth parameters including temperature, assistant chemicals, and seeding layer. We experimentally confirm the necessity of ammonium hydroxide as assistant chemical in the growth solution, and achieve a condition that generates the highest weight growth percentage of 40% in the tested range. We quantify the weight growth percentage of ZnO NWs over growth time, measure the electrical resistance of the ZnO-NW paper, and eventually establish an experimental guideline for preparing ZnO-NW paper with desired electrical property. To demonstrate potential applications of the ZnO-NW paper, we use the obtained ZnO-NW paper for sensing of ultraviolet light and mechanical touch. This paper provides experimental insights into hydrothermal growth of ZnO NWs on paper, and could further inspire novel utilization of ZnO-NW paper for flexible sensors and electronics.
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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 | 0.000 | 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 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".