Conformal Electroplating of Azobenzene-Based Solar Thermal Fuels onto Large-Area and Fiber Geometries
Bibliographic record
Abstract
There is tremendous growth in fields where small functional molecules and colloidal nanomaterials are integrated into thin films for solid-state device applications. Many of these materials are synthesized in solution and there often exists a significant barrier to transition them into the solid state in an efficient manner. Here, we develop a methodology employing an electrodepositable copolymer consisting of small functional molecules for applications in solar energy harvesting and storage. We employ azobenzene solar thermal fuel polymers and functionalize them to enable deposition from low concentration solutions in methanol, resulting in uniform and large-area thin films. This approach enables conformal deposition on a variety of conducting substrates that can be either flat or structured depending on the application. Our approach further enables control over film growth via electrodepsition conditions and results in highly uniform films of hundreds of nanometers to microns in thickness. We demonstrate that this method enables superior retention of solar thermal fuel properties, with energy densities of ∼90 J/g, chargeability in the solid state, and exceptional materials utilization compared to other solid-state processing approaches. This novel approach is applicable to systems such as photon upconversion, photovoltaics, photosensing, light emission, and beyond, where small functional molecules enable solid-state applications.
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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) | 0.003 | 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".