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Record W2791593804 · doi:10.1002/cjce.23156

An integrated process of catalytic hydrolysis and membrane separation for fatty acids production from lard oil

2018· article· en· W2791593804 on OpenAlexvenueno aff
Enmin Lv, Shaoxuan Ding, Jie Lu, Lixiong Du, Zhuang Li, Jianxin Li, Shuguang Zhang, Jincheng Ding

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicCatalysis and Hydrodesulfurization Studies
Canadian institutionsnot available
FundersNatural Science Foundation of Shandong ProvinceNational Natural Science Foundation of China
KeywordsUltrafiltration (renal)HydrolysisCatalysisMembraneChemistryYield (engineering)GlycerolChromatographyCationic polymerizationCorn oilOrganic chemistryMaterials scienceBiochemistryFood science

Abstract

fetched live from OpenAlex

Abstract An integrated process of catalytic hydrolysis and membrane separation was developed for fatty acids (FAs) production from lard oil. Both sulphonated cation exchange resin (SCER) and 0.98 g/g H 2 SO 4 as catalysts were used to produce fatty acids (FAs) from lard oil by three‐step hydrolysis, respectively. Simultaneously, polyethersulphone (PES) ultrafiltration membrane was employed to separate glycerol and water from the products. The hydrophilicity and morphology of the pristine and used PES membranes were characterized by contact angle measurement and field‐emission scanning electronic microscopy, respectively. The final optimal yields of FAs obtained by SCER and H 2 SO 4 catalysis at 100 °C and atmospheric pressure were 85.6 % at 16.0 h of operation and 94.5 % at 18.0 h of operation, respectively. Furthermore, the yield of FAs obtained from an integrated process of SCER‐catalyzed hydrolysis and membrane separation achieved up to 99.9 % at 10.0 h, 90 °C, and operating pressure of 100 kPa.

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 score0.004
Threshold uncertainty score0.304

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 head0.008
GPT teacher head0.219
Teacher spread0.211 · 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

Citations8
Published2018
Admission routes1
Has abstractyes

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