Acoustic Analysis of Photothermal Boiling in Nanofluids
Bibliographic record
Abstract
Solar energy harvesting and utilization are critical components of the green energy transition, though the fundamental understanding of the solar boiling process in nanofluids is lacking. In this study, auditory acoustic-emission spectra from photothermal boiling in carbon black nanofluids up to 2 wt % were measured. Frequency peaks and boiling modalities were investigated to determine the effects of nanoparticle addition on bubble number and size distribution. Steam flow rates were maximally enhanced by 90% (at 0.5 wt %) compared to surface boiling in water due to improved heat and mass transfer and incident radiation. As concentration rose, flow rates decreased due to shielding and thermal losses. Moreover, acoustic spectra for photothermal boiling exhibited higher amplitudes and more high-frequency peaks, indicating more small bubbles and bubbles in total for the nanofluid. Using a coherence analysis, two new peaks were found for the highest flow rate concentrations: 17 (new bubbles) and 14.5 (new bubble coalescence) kHz. The behavior of these new peaks correlated with steam flow rates. Finally, experimental results were compared with existing boiling models for theory validation, with volumetric boiling theory matching closely. Bubble size predictions from theory overlapped with the new peaks, lending theoretical backing to the finding. Therefore, auditory acoustic spectra can be a reliable tool for investigating mechanistic changes in bubble formation in optically occluded systems.
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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 | 0.001 | 0.002 |
| 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 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".