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Record W4388453059 · doi:10.21203/rs.3.rs-3452707/v1

Sustainable Synthesis of Dibutyl Itaconate from Biomass Derived Acid via Esterification Reaction over Hierarchical Zeolite H-BEA Catalysts

2023· preprint· en· W4388453059 on OpenAlexaff
Aayushi Lodhi, Ajay K. Dalai, Kalpana C. Maheria

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldEngineering
TopicCatalysis for Biomass Conversion
Canadian institutionsUniversity of Saskatchewan
FundersDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsZeoliteCatalysisMesoporous materialChemistryMaterials scienceChemical engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The current study concentrates on the synthesis of dibutyl itaconate (DBI) via esterification reaction of itaconic acid (ITA) and n-butanol over the synthesized novel hierarchical zeolite and the parent H-BEA acid catalysts. ITA is among the top platform scaffolds which are derived from biomass. DBI, has numerous industrial applications as, plasticizers, gelation accelerators, lubricants, antirust additives, adhesives, detergent additives etc. In the present study, tetradecyltrimethylammonium bromide (TTAB) surfactant is used as a structure directing agent and yeast as an additional modifier to create hierarchical zeolite H-BEA. Several characterization techniques [XRD, SEM-EDX, N 2 -sorption isotherms, NH 3 -TPD, FT-IR, solid-state NMR ( 27 Al, 29 Si, 1 H)] were used to characterise the synthesized hierarchical structure involving both, microporosity and mesoporosity. Under optimal reaction conditions, hierarchical zeolite shows a higher % ITA yield as compared to its counterpart, parent H-BEA zeolite catalyst. This may be attributed to the enhanced physicochemical and catalytic properties of the resulting hierarchical zeolite catalyst.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.072
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.030
GPT teacher head0.308
Teacher spread0.277 · 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 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
Published2023
Admission routes1
Has abstractyes

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