PO<sub>4</sub><sup>3−</sup> Tetrahedron Assisted Chelate Engineering for 10.67%‐Efficient Antimony Selenosulfide Solar Cells
Bibliographic record
Abstract
Abstract Anisotropic carrier transport and deep‐level defect of antimony selenosulfide (Sb2(S,Se)3) absorber are two vital auses restraining the photovoltaic performance of this emerging thin‐film solar cell. Herein, chelate engineering is proposed to prepare high‐quality Sb2(S,Se)3 film based on hydrothermal deposition approach, which realizes desirable carrier transport and passivated defects by using tetrahedral PO43− ion in dibasic sodium phosphate (Na2HPO4, DSP). The PO43− Lewis structure, on one hand in the form of [(SbO)3(PO4)] chelate, can adsorb on the polar planes of cadmium sulfide (CdS) layer, promoting the heterogeneous nucleation, and on the other hand, the tetrahedral PO43− inhibits horizontal growth of (Sb4S(e)6)n ribbons due to size effects, thus achieving desirable [hk1] orientation. Moreover, the introduction PO43− effectively passivates the antisite defect SbS1. These synergistic effects have effectively improved carrier transport and reduced non‐radiative recombination of the Sb2(S,Se)3 absorber. Consequently, the DSP‐modified Sb2(S,Se)3 device efficiency increases from 8.59% to 10.67%.
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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".