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Record W2508574426 · doi:10.1002/ceat.201600046

Mechanochemical Synthesis of CPM‐5: A Green Method

2016· article· en· W2508574426 on OpenAlex
Mitra Bahri, Hossein Kazemian, Sohrab Rohani, Fariborz Haghighat

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemical Engineering & Technology · 2016
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsWestern UniversityUniversity of Northern British ColumbiaConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGrindingMaterials sciencePorosityDimethylformamideChemical engineeringSpecific surface areaOscillation (cell signaling)Process engineeringMetallurgyComposite materialSolventChemistryOrganic chemistryCatalysisEngineering

Abstract

fetched live from OpenAlex

Abstract The development of green technologies for the manufacture of various materials is considered as one of the approaches to address some of the environmental issues of commercializing new materials. A mechanochemical (MC) method is developed to synthesize crystalline porous material‐5 (CPM‐5). The effect of different mechanical parameters, including oscillation frequency and time and the number of metal balls used for milling is studied. Results revealed that CPM‐5 crystals are successfully formed under optimized conditions. It was noted that the thermal treatment of the samples after grinding is very crucial for the formation of CPM‐5 under the studied conditions. Moreover, washing of samples with a 1:1 solution of dimethylformamide (DMF):H 2 O remarkably enhanced the surface area of the final product.

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 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 score0.142
Threshold uncertainty score0.381

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 head0.007
GPT teacher head0.228
Teacher spread0.221 · 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