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Record W4411260532 · doi:10.1021/acsestwater.5c00039

Effects of Environmental Transformations on the Phototoxicity of Cadmium–Zinc-Based Quantum Dots to Freshwater Algae <i>Chlorella vulgaris</i>

2025· article· en· W4411260532 on OpenAlexafffund
Ziruo Liu, Xiaoyu Gao, Cassandre Béchir, Subhasis Ghoshal, Audrey Moores, Saji George

Bibliographic record

VenueACS ES&T Water · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicRecycling and Waste Management Techniques
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for Innovation
KeywordsChlorella vulgarisCadmiumPhototoxicityZincAlgaeChemistryBotanyBiologyBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

CdSe/ZnS-based quantum dots (QDs) are being increasingly applied in many electronic devices, raising concerns over the ecotoxicity of QDs released into the environment during the end-of-life of such devices. Most (eco)toxicity studies have used pristine QDs with noncommercially relevant coatings or omitted their environmental transformation. We used CdSe/ZnS QDs coated with polyethylenimine, similar to those found in TV screens to examine their transformation and toxicity when aged in the presence of humic acid and/or light. The transformed samples were exposed to Chlorella vulgaris to assess impacts of different aging conditions on oxidative stress and growth inhibition. Light exposure enhanced the dissolution of pristine QDs and the release of Zn and Cd which was 5–10 folds higher than those released under dark conditions. Presence of humic acid, however, decreased the dissolution of QDs when exposed to light because of the light shielding and ion-scavenging effects of humic acid. Pristine QDs aggregated with the algae, which, when exposed to light, caused dissolution and release of metal ions locally around algae cells, causing significant loss of cell viability. However, humic acid in QD exposure media reduced oxidative stress and cell viability loss (by 2.5- fold) as it reduced bioavailability of both QDs and heavy metal ions. These findings highlight the significance of understanding the relationship between environmental transformation and ecotoxicity of QDs.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.419

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.004
GPT teacher head0.203
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes2
Has abstractyes

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