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Record W4401737195 · doi:10.1002/cplu.202400263

Flakes and Nanoparticles from Waste Ru‐Plated Fashion Items through Food Waste by‐Products

2024· article· en· W4401737195 on OpenAlexafffund
Teresa Cecchi, Zhaojing Gao, Clara Santato

Bibliographic record

VenueChemPlusChem · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicRecycling and Waste Management Techniques
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsRutheniumX-ray photoelectron spectroscopyContext (archaeology)CatalysisMaterials scienceLeachateOxidizing agentChemical engineeringNanoparticleNanotechnologyWaste managementChemistryEnvironmental chemistryOrganic chemistryGeology

Abstract

fetched live from OpenAlex

Abstract Ruthenium is relevant for a broad range of applications, including catalysis and electronics. Like other metals of the platinum group, ruthenium stands out as one of the rarest elements in the Earth's crust. The demand for Ru from the industry is putting pressure on its availability. Hence, its recovery from secondary sources is imperative. Fashion solid residues of the plating industry are an important waste stream for Ru. Within this context, we propose a novel approach to Ru recovery for its safe, sustainable, and economically affordable upcycling. The approach is based on peeling from waste metal wires by a green oxidizing agent, H 2 O 2 , in an environment acidic by lactic acid, a by‐product of the food industry. Peeled flakes were characterized by scanning electron microscopy, energy dispersive spectroscopy, X‐ray photoelectron spectroscopy, and atomic force microscopy for their structure and (surface) chemical composition and bonding. Inductively Coupled Plasma Optical Emission Spectroscopy shows the ultra‐low concentration of noble metals in the leachate, thereby suggesting their quantitative recovery in their metallic state. Further, we observed the colloidal nature of the washing water of the peeled flakes. Therefore, we hypothesized the presence of nanoparticles in the washing water and went for their characterization.

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 score0.030
Threshold uncertainty score0.805

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 head0.017
GPT teacher head0.223
Teacher spread0.206 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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