Enhanced photovoltaic conversion efficiency in bulk heterojunction solar cells upon incorporating nanohybridized PbS quantum dots/multiwall carbon nanotubes
Bibliographic record
Abstract
We report on a modified bulk heterojunction (BHJ) solar cell in which a nanohybridized composition of lead sulfide (PbS) colloidal quantum dots (QDs) and multiwall carbon nanotubes (MWCNTs) were incorporated into a standard regioregular poly(3-hexylthiophene) (rr-P3HT):phenyl-C61-butyric acid methyl ester (PCBM) blend. This hybrid ((P3HT:PCBM):PbS-QD/MWCNT) solar cell exhibits an increased power conversion efficiency (PCE) of 3.40% as compared to that of 2.57% from a controlled P3HT:PCBM standard BHJ solar cell fabricated under similar experimental conditions. The 32% increase in efficiency is effectively attributed to the extended quantum-dot-sensitization in the near-infrared (NIR) due to the absorbance of QDs/CNTs in the spectral range from 700 nm to 1450 nm. The strong conjugation, controlled coupling and nanohybridization of QDs/CNTs played an important role towards the improvement of PCE since it is proposed that excitons generated in the QDs can be efficiently dissociated at the QD/CNT interface by transferring the electrons to the CNTs followed by holes transfer to the P3HT. In this ternary blend, the staggered energy band alignment between P3HT and the QDs allows both electrons and holes transfer from the QDs to the PCBM and the P3HT, respectively. Subsequently, the dissociated carriers have been efficiently transported by the CNTs and P3HT to favorable respective electrodes.
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 | 0.000 |
| 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".