Organic-Inorganic Nanohybrid Materials for Photovoltaic Applications
Bibliographic record
Abstract
Thin film morphology is a key factor determining the performance of bulk heterojunction organic-inorganic solar cells through its influence on charge separation, charge transport and recombination losses in donor-acceptor blends. With this respect, both descriptive and predictive modeling of structural properties of blends of organic-inorganic perovskites of the type CH3NH3PbX3 (X=Cl, Br, or I) with P3HT or P3BT, including adsorption on TiO2 clusters having rutile (110) surface, is presented with the use of a methodo-logy that allows computing the microscopic structure of blends on the nanometer scale. The methodology is based on the integral equation theory of molecular liquids in the reference interaction site model and uses the universal force field. It provides a detailed microscopic insight into the organization of solvent molecules in the solvation shell structure and their contribution to the solvation thermodynamics. The calculated nanoscale morphologies serve as an instrument in rational design of hybrid photovoltaics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.004 | 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 teacher head, 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".