Detailed balance analysis of advanced geometries for singlet fission solar cells
Bibliographic record
Abstract
Singlet fission is a process by which a single photon can be converted into a pair of triplet excitons, making it highly attractive for light harvesting technologies. Maximizing the efficiency of excitonic solar cells is a challenge requiring careful energy alignment among other things. We performed detailed balance calculations on excitonic solar cells that leverage endothermic singlet fission with an endothermicity of up to ten times thermal energy at room temperature. As expected, we find that the design surpasses the single junction (Shockley Queisser) limit, with a maximum at an endothermicity of 0.125 eV. However, the design is susceptible to the effects of exciton binding energy. Calculations suggest that including a third material to form a double heterojunction can help to overcome this challenge. For exciton binding energies of 0.5 eV, the singlet fission double heterojunction design can achieve an efficiency of 40.8%, a nearly 10% improvement over a single heterojunction. Practical implementations of this design are likely to encounter a number of challenges unique to this design, namely, unwanted tunneling currents and exciton-charge annihilation. Their effects on the output characteristics of the cell are described. It appears likely that these issues can be avoided, and that highly efficient, inexpensive solar cells that leverage the full promise of the singlet fission mechanism can be created.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".