Cellulose Nanocrystal Aerogels as Electrolyte Scaffolds for Glass and Plastic Dye-Sensitized Solar Cells
Bibliographic record
Abstract
Abstract The fabrication, thickness, and structure of aerogel films composed of covalently cross-linked cellulose nanocrystals (CNCs) and poly(oligoethylene glycol methacrylate) (POEGMA) were optimized for use as electrolyte absorbers in dye-sensitized solar cells (DSSCs). The aerogel films were cast directly on transparent conducting counter electrode substrates (glass and flexible poly(ethylene terephthalate) plastic) and then used to absorb drop-cast liquid electrolyte, thus providing an alternative method of filling electrolyte in DSSCs. This approach eliminates the use of electrolyte-filling holes, which are a typical pathway of electrolyte leakage, and furthermore enables a homogeneous distribution of electrolyte components within the photoelectrode. Unlike typical in situ electrolyte gelation approaches, the phase inversion method used here results in a highly porous (>99%) electrolyte scaffold with excellent ionic conductivity and interfacial properties. DSSCs prepared with CNC?POEGMA aerogels reached similar power conversion efficiencies as compared to liquid electrolyte devices, indicating that the aerogel does not interfere with the operation of the device. These aerogels retain their structural integrity upon bending, which is critical for their application in flexible devices. Furthermore, the aerogels demonstrate impressive chemical and mechanical stability in typical electrolyte solvents because of their stable covalent cross-linking. Overall, this work demonstrates that the DSSC fabrication process can be simplified and made more easily upscalable by taking advantage of CNCs, being an abundant and sustainable bio-based material.
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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".