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Record W4413135912 · doi:10.1139/cjc-2025-0098

Synergistic tri-metallic Ca/Mg/Sr crab shell catalyst for transesterification: probing active site basicity

2025· article· en· W4413135912 on OpenAlexaffvenue
Ali Shafiee, Kevin McEleney, Kelly Hawboldt, Stephanie MacQuarrie

Bibliographic record

VenueCanadian Journal of Chemistry · 2025
Typearticle
Languageen
FieldEngineering
TopicCatalysis and Hydrodesulfurization Studies
Canadian institutionsMemorial University of NewfoundlandQueen's UniversityTrent UniversityCape Breton University
Fundersnot available
KeywordsChemistryTransesterificationCatalysisMetalInorganic chemistryShell (structure)Organic chemistry

Abstract

fetched live from OpenAlex

This study investigates the catalytic potential of crab body powder (CBP) derived from waste crab bodies for the conversion of triglycerides (TG) to fatty acid methyl esters (FAME). CBP is subjected to temperature treatments and characterized using various techniques. Its catalytic activity is compared to that of commercial materials such as CaO and MgO. The results demonstrate that the tri-metallic Ca/Mg/Sr catalyst derived from CBP heated at 900 °C (CBP900) exhibits the highest TG to FAME conversion rate of 96.8%. Interestingly, CaCO 3 heated to 900 °C shows comparable activity to CBP900. The enhanced catalytic performance is attributed to the presence of oxygenated surface functional groups, which enhance the basicity of the catalyst, as well as improved crystallinity, facilitated mass transport, and well-defined active sites within the CBP structure. These findings highlight the potential of waste-derived tri-metallic Ca/Mg/Sr CBP as a sustainable and efficient catalyst for biodiesel production. Further investigations are warranted to optimize reaction conditions and explore the underlying mechanisms, thereby opening avenues for utilizing waste biomass in renewable energy applications.

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 score0.071
Threshold uncertainty score0.618

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 head0.010
GPT teacher head0.208
Teacher spread0.198 · 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
Published2025
Admission routes2
Has abstractyes

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