MétaCan
Menu
Back to cohort
Record W7008541781

Catalytic Conversion of Glycerol to Glycerol Carbonate Utilizing CO₂ and Dimethyl Carbonate

2024· dissertation· en· W7008541781 on OpenAlexfundno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2024
Typedissertation
Languageen
FieldChemical Engineering
TopicCarbon dioxide utilization in catalysis
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaMinistry of Agriculture - Saskatchewan
KeywordsGlycerolDimethyl carbonateCatalysisCarbonateCarbon dioxideOxideYield (engineering)Carbon fibers
DOInot available

Abstract

fetched live from OpenAlex

The decline in fossil fuels drives research into alternatives like biofuels. Biodiesel production creates a surplus of crude glycerol, a major bottleneck. Scientists are exploring new, cost-effective uses for this abundant by-product. This research focuses on the catalytic conversion of glycerol to value-added glycerol carbonate using CO2, an abundant, non-toxic greenhouse gas, and dimethyl carbonate (DMC), which yields more glycerol carbonate. The catalysts were prepared by co-precipitation method, and characterized by using XPS, FT-IR, XRD, TGA, SEM, and CO2-TPD techniques. Firstly, metal oxide catalysts of Al2O3, CaO, and MgO were used in the carbon dioxide and glycerol reaction. A glycerol conversion of 24.5±2.2 mol%, and glycerol carbonate yield of 12.8±1.2 mol% under optimized conditions of 5.5% catalyst loading, 150°C temperature, and 8 MPa pressure was achieved by using MgO as the catalyst. Subsequently, novel mixed metal oxides (Ca-Al, Mg-Al, and Mg-Ca) are introduced to the same reaction, and Mg0.75Ca0.25O exhibited the highest glycerol carbonate yield of 16 mol%, under optimized reaction parameters of 8.5% catalyst loading, 180°C temperature, and 7 MPa pressure. BET surface area and total basicity of the catalysts had the most effective role in their performance in the reaction. To boost glycerol carbonate yield, various catalysts were designed for the glycerol and DMC reaction. Lithium oxide combined with synthesized activated carbon, using incipient wetness impregnation method, performed best, achieving an 87.9±2.4% yield due to its high basicity and surface area. The activated carbon was microwave-assisted synthesized from flax shive which is an abundant agricultural residue. Using Central Composite Design optimization, a 75% phosphoric acid concentration and 4 minutes of heating time were found to produce the optimal activated carbon pore width of 3.9 nm. The optimal reaction parameters were found as a temperature of 89.1°C, 3.4 DMC/glycerol molar ratio, and 5.6% catalyst dosage, resulting in a glycerol carbonate yield of 97.7%. The reaction kinetics adhered to a pseudo-first-order rate law with an activation energy of 45.5 kJ/mol. The 20%Li2O/AC catalyst exhibited satisfactory reusability across five cycles of the reaction. This comprehensive exploration underscores the potential for a more sustainable biodiesel industry through innovative waste usage processes.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.140
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.006
GPT teacher head0.181
Teacher spread0.175 · 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.

Study designQualitative
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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueUniversity Library (University of Saskatchewan)Same topicCarbon dioxide utilization in catalysisFrench-language works237,207