Photothermal response in thin metal films deposited onto silica aerogelsupports via magnetron sputtering
Bibliographic record
Abstract
The photothermal effect, whereby light energy is converted into thermal energy when absorbed in a material, is a phenomenon that has many potential applications including solar-driven water heating and purification, and radiative heat transfer. Recently, porous materials have been tailored to exhibit the photothermal effect to be used for interfacial water evaporation and sterilization. In this work we investigate the solar-driven photothermal effect on nanocomposite aerogel materials. Aerogels exhibit a unique combination of properties that can enhance their utility as a photothermal material. Due to their inherently low density and thermal conductivity, and their exceptional insulative properties, photothermal heat generated within an aerogel can remain trapped for a prolonged period of time. Herein we present the photothermal effect in nanocomposite aerogels fabricated by sputtering metal and metal oxide films onto and into aerogels materials. By sputtering metal and metal oxides in a high vacuum environment and directing it towards an aerogel substrate using a magnetron, we were able to deposit thin films onto the surface of an aerogel. The composite aerogels are characterized using scanning electron microscopy (SEM) to assess the depth of the sputtered material into the aerogel pores. The reflectance and transmittance of the aerogel composites are measured using UV-Vis spectroscopy. The photothermal effect in aerogel composites is measured using thermal imaging. Our results show that the photothermal response of the composite aerogels can be tuned by varying the thickness and composition of the deposited films. Overall, our study demonstrates the potential of using magnetron sputtering to create composite aerogels with tailored photothermal properties. This opens new opportunities for a wide range of applications such as water and air heating and purification, water desalination, and solar energy harvesting devices.
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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".