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Record W2565928826 · doi:10.1515/ijcre-2014-0058

Novelty of <i>Penicillium camembertii</i> Lipase Supported on Glutaraldehyde Activated-SBA-15 Mesoporous Silica for Mono-Esterification of Bioglycerol in Non-Aqueous Media

2016· article· en· W2565928826 on OpenAlexaff
Moreshwar P. Hude, Janusz A. Koziński, Ajay K. Dalai, Ganapati D. Yadav

Bibliographic record

VenueInternational Journal of Chemical Reactor Engineering · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEnzyme Catalysis and Immobilization
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsLipaseGlutaraldehydeMesoporous materialMesoporous silicaImmobilized enzymeChemistryAqueous solutionIonic liquidMonoglycerideOrganic chemistryCatalysisNuclear chemistryMaterials scienceChemical engineeringEnzyme

Abstract

fetched live from OpenAlex

Abstract Hexagonal mesoporous type silica SBA-15 with pore sizes in the range 5.0–8.3 nm was synthesized using non-ionic triblock copolymer and characterized by Accelerated Surface Area Porosimetry (ASAP), FT-IR spectroscopy, X-ray diffraction (XRD) and Scanning Electron Microscopy (SEM). Different lipases were immobilized in glutaraldehyde activated mesoporous SBA-15 support. The resulting supported enzymes were shown to be active and stable catalysts for esterification of glycerol with oleic acid to produce monoglyceride (MG) which is commonly used in food industry. Various parameters were studied systematically to study kinetics. MG Synthesis using enzymatic process is an environmentally friendly approach. Enzyme immobilized on SBA-15 showed the best stability and catalytic activity in organic solvents. Out of various lipases studied penicillium camembertii (Lipase G) produced MG efficiently at low temperature. Reusability was studied on immobilized enzymes. Immobilized lipase maintained 90 % of its esterification activity in non-aqueous media even after 4 cycles of use. The selectivity of Lipase G is found to be 98 % for monoacylglyceride.

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)0.001
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 score0.003
Threshold uncertainty score0.397

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.239
Teacher spread0.232 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

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