Aqueous, Screen-Printable Paste for Fabrication of Mesoporous Composite Anatase–Rutile TiO<sub>2</sub>Nanoparticle Thin Films for (Photo)electrochemical Devices
Bibliographic record
Abstract
Mesoporous TiO 2 films are employed in solar cells, lithium ion batteries, and air and water purification systems, to name a few applications. Film fabrication via coating the substrate with an organic suspension or paste carrying TiO 2 nanoparticles is a common method. To lessen the adverse environmental impact, use of water as a solvent and nontoxic chemicals is being preferred over commonly used organic components. In this research, a water-based, nano-TiO 2 printable paste formulation with polyethylene glycol (MW 20 000) and propylene glycol was developed and seamlessly interfaced with TiO 2 aqueous synthesis for sustainable manufacturing. The innovative combination of propylene glycol and polyethylene glycol is demonstrated to lead to improved paste rheology and sintered film properties. Dye-sensitized solar cells were assembled from the screen-printed films, and the effect of film surface area and porosity on photovoltaic performance was studied. The new aqueous-based paste yielded comparable power conversion efficiency to benchmark organic-based paste made of α-terpineol, ethyl cellulose, and ethanol, opening the avenue for lower cost, green fabrication of mesoporous thin film electrodes.
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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 | 0.001 |
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".