MétaCan
Menu
Back to cohort
Record W2024002027 · doi:10.14356/kona.2011025

Pilot Plants for Industrial Nanoparticle Production by Flame Spray Pyrolysis

2011· article· en· W2024002027 on OpenAlex

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

VenueKONA Powder and Particle Journal · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicCoagulation and Flocculation Studies
Canadian institutionsInstitute of Particle Physics
FundersJapan Society for the Promotion of ScienceSeventh Framework ProgrammeUniversity of TokyoBanaras Hindu University
KeywordsPyrolysisNanoparticlePilot plantNanomaterialsMaterials scienceSCALE-UPProcess engineeringCeramicProduction (economics)NanotechnologyWaste managementEngineeringMetallurgy

Abstract

fetched live from OpenAlex

With the rapid advancement of nanotechnology and with nanoparticles beginning to enter into products, the demand for production-level quantities of advanced nanopowders such as multi-component or coated oxides is rising. Such advanced nanoparticles can be effectively made by flame spray pyrolysis (FSP), and research with laboratory reactors yielded a spectrum of new nanomaterials for catalysis, pigments, ceramics, optics, energy and biomaterials, among others. Here, the transfer of FSP nanopowder synthesis from gram-level lab-scale to pilot reactors with up to 10 metric tons annual production rate is investigated by the example of FSP pilot plants that were realized in industrial-oriented settings. Design considerations for such pilot-scale systems are addressed and guides to production cost estimates are given. Special attention is brought to safe and contained nanoparticle manufacture in order to address the growing awareness of the potential health and environmental effects of nanoparticles.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score1.000

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)0.0010.000

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 head0.093
GPT teacher head0.260
Teacher spread0.166 · 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