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Record W2390542282

Composition Analysis of Waste Raney-Nickel Catalyst

2009· article· en· W2390542282 on OpenAlexaff
Hong‐zhen Lian

Bibliographic record

VenueRock and Mineral Analysis · 2009
Typearticle
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsMinistry of Education and Child Care
Fundersnot available
KeywordsCatalysisNickelX-ray photoelectron spectroscopyInductively coupled plasmaRaney nickelMolybdenumScanning electron microscopeCopperNuclear chemistryMaterials scienceChemistryMetallurgyChemical engineeringOrganic chemistryPlasma
DOInot available

Abstract

fetched live from OpenAlex

A typical kind of waste Raney-nickel catalyst was comprehensively analyzed by infrared spectrometry (IR), X-ray powder diffractometry (XRD), inductively coupled plasma-atomic emission spectrometry (ICP-AES), X-ray photoelectron spectrometry (XPS), scanning electron microscopy (SEM), elemental analysis (EA) and gravimetric method. There is a high nickel content in the waste catalyst so that it is worthy of recycling. The quantification for some components in the waste catalyst including nickel, aluminum, calcium, iron, molybdenum, copper and silicon, as well as qualitative analysis for some components has been carried out. The technical protocol of the recycling from waste Raney-nickel catalyst has been put forward.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.403
Threshold uncertainty score0.333

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.216
Teacher spread0.209 · 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 designSimulation or modeling
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
Published2009
Admission routes1
Has abstractyes

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