Nitrogen-Doped Graphene-Ti<sub>3</sub>C<sub>2</sub>T<sub><i>x</i></sub> Quasi-3D Heterostructures Interfacial Interaction for High-Temperature Vibrational Piezoelectric Energy Harvesting Application
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
Piezoelectric nanogenerators (PENG) can face challenges when integrated into high-temperature applications because of their high-temperature sensitivity. Heterostructures of specific 2D nanomaterials can potentially enhance the PENG performance for practical applications at high temperatures. Hence, this study incorporates nitrogen-doped graphene (NGr) and Ti 3 C 2 T x MXene heterostructure nanofillers into the polyvinylidene difluoride (PVDF) matrix for energy harvesting in a high-temperature vibration environment. The reproducible and stable all-solution fabrication is achieved by optimizing the appropriate ratio of the NGr-Ti 3 C 2 T x ratio. At room temperature, the nanogenerator showed an optimum output voltage of ∼9.0 V and ∼1.5 μA of current. Thereby, it increased to 24.0 V and 1.75 μA when the temperature increased to 90 °C, obtaining a power density of 3.85 μW/cm 2 . This outstanding performance is attributed to the designed NGr-Ti 3 C 2 T x quasi-3D heterostructure, where its rich interfacial features, excellent electrical conductivity, and localized elastic complexes synergistically promote the piezoelectric output of the energy harvester. Placing the device on the road could be used to collect the mechanical energy generated by the vibration of the car’s movement and convert it into electrical energy, which opens up new development possibilities for addressing emerging energy issues.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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