Characterization of high-performance organic dyes for dye-sensitized solar cell: a DFT/TDDFT study
Bibliographic record
Abstract
Dye-sensitized solar cell (DSSC) is currently a promising technology that makes solar energy efficient and cost-effective to harness. In DSSC, metal-free dyes such as indoline-containing D149 and D205 have been proven to be potential alternatives for traditional metal organic dyes. In this work, a DFT/TDDFT characterization for D149 and D205 was carried out using different functionals, including B3LYP, MPW1K, CAM–B3LYP, and PBE0. Three different conformers for D149 and four different conformers for D205 were identified and calculated in a vacuum. The performance of different functionals on calculating the maximum absorbance of the dyes in a vacuum and five common solvents (acetonitrile, chloroform, ethanol, methanol, and THF) were examined and compared to determine the suitable computational setting for predicting properties of these two dyes. Furthermore, deprotonated D149 and D205 in solvents were also considered, and the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) were calculated, which elucidates the substitution effect on the rhodanine ring of D149 and D205 dyes on their efficiency. Finally, D149 and D205 molecules were confirmed to be firmly anchored on ZnO surface by periodic DFT calculations. These results shed light on the design of new, highly efficient metal-free dyes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".