Toxicity and safety study of Cd-based and Cd-free quantum dots in third-gen PV and scaled-up processing platforms
Bibliographic record
Abstract
Quantum dots (QDs) are being incorporated at an accelerated rate into Third-Gen photovoltaic (PV) and scaled-up PV processing platforms for production of high efficiency devices. As a result, studies are needed to examine QD toxicity in workplace environment. Herein, we report on a rapid and sensitive detection methods to examine risk of QD exposure in PV processing. QD-associated toxic elements were detected in slight amounts using gold nanoparticles (Au NPs) probe, followed by photoluminescence and Inductively Coupled Plasma-Mass Spectroscopy (ICP-MS) analyses, which indicated the possibility of QD aerosolization during deposition, transferring and testing of the QD film. Cytotoxicity effects of different type QDs were also studied using cell culture viability. The results indicate that QD material and their coating are important factors in producing cytotoxicity effects. It was also demonstrated that CIS QDs have less cytotoxic effects on HeLa and CHSE cells than CdSe QDs, and may be considered non-toxic in comparison.
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".