MétaCan
Menu
Back to cohort

Plasma nanofabrication and nanomaterials safety

2011· article· en· W1486698832 on OpenAlexaff
Ziwei Han, Igor Levchenko, Sandeep Kumar, M. M. A. Yajadda, Samuel Yick, DH Seo, Pierre‐Alexandre Martin, Sean Peel, Zdenka Kuncic, Kostya Ostrikov

Bibliographic record

VenueJournal of Physics D Applied Physics · 2011
Typearticle
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNanomaterialsNanolithographyNanotechnologyMaterials scienceFabricationMedicine

Abstract

fetched live from OpenAlex

The fast advances in nanotechnology have raised increasing concerns related to the safety of nanomaterials when exposed to humans, animals and the environment. However, despite several years of research, the nanomaterials safety field is still in its infancy owing to the complexities of structural and surface properties of these nanomaterials and organism-specific responses to them. Recently, plasma-based technology has been demonstrated as a versatile and effective way for nanofabrication, yet its health and environment-benign nature has not been widely recognized. Here we address the environmental and occupational health and safety effects of various zero- and one-dimensional nanomaterials and elaborate the advantages of using plasmas as a safe nanofabrication tool. These advantages include but are not limited to the production of substrate-bound nanomaterials, the isolation of humans from harmful nanomaterials, and the effective reforming of toxic and flammable gases. It is concluded that plasma nanofabrication can minimize the hazards in the workplace and represents a safe way for future nanofabrication technologies.

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 score0.392
Threshold uncertainty score0.514

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 head0.028
GPT teacher head0.240
Teacher spread0.212 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Physics D Applied PhysicsSame topicPlasma Applications and DiagnosticsFrench-language works237,207