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Record W4290595664 · doi:10.3390/lubricants10080176

Toxicity Analysis of Nano-Minimum Quantity Lubrication Machining—A Review

2022· article· en· W4290595664 on OpenAlex
Ibrahim Nouzil, Abdelkrem Eltaggaz, Salman Pervaiz, Ibrahim Deiab

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLubricants · 2022
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticles: synthesis and applications
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsLubricationNanoparticleToxicityMachiningNanotechnologyNano-Materials scienceChemistryMetallurgyComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

The lubrication properties of nanoparticles are of great interest to the manufacturing industry and led to the development of the nano-minimum quantity lubrication (NMQL) cooling strategy. To evaluate the sustainability characteristics of nano-minimum quantity lubrication, apart from analyzing the benefits of increasing machining efficiency, it is also essential to evaluate the potential detrimental effects of nanoparticles on human health and the environment. Existing literature provides substantial data on the benefits of nano-minimum quantity lubrication machining. However, the current literature does not provide researchers in the machining sector a comprehensive analysis of the toxicity of the nanoparticles used in nano-minimum quantity lubrication. This study aims to provide a comprehensive review that addresses the toxicity levels of the most frequently used nanoparticles in NMQL machining. To understand the impacts of nanoparticles on the human body and the environment, in vitro studies that evaluate the nanoparticles’ toxicity on human cells and in vitro/in vivo studies on other living organisms are considered. The results from toxicity studies on each of the chosen nanoparticles are summarized and presented in chronological order. The reviewed studies indicate transition metal dichalcogenides (MoS2 and WS2) exhibit very low toxicity when compared to other nanoparticles. The toxicity of hBN and AL2O3 nanoparticles varies depending on their lengths and crystalline structures, respectively. In conclusion, a chart that maps the toxicity levels of nanoparticles on seven different human cell lines (human lung epithelial cells (A549), human bronchial epithelial cells (Nl-20), AGS human gastric cells, human epidermal cells (HEK), human liver-derived cells (HepG2), human endothelial cells and human peripheral cells), representing exposures by inhalation, ingestion and dermal contact, was developed for easy and quick insights. This is the first attempt in open literature to combine the results of the experimental investigations of nano-minimum quantity lubrication cooling and the toxicity studies of nanoparticles, allowing researchers to make informed decisions in the selection of the most sustainable nanoparticles in the nano-minimum quantity lubrication machining process.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.143
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.293
Teacher spread0.265 · 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