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Record W2334226814 · doi:10.1021/ef4018288

Direct Infusion Mass Spectrometric Analysis of Bio-oil Using ESI-Ion-Trap MS

2013· article· en· W2334226814 on OpenAlexafffund
Eid Alsbou, Bob Helleur

Bibliographic record

VenueEnergy & Fuels · 2013
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaMemorial University of Newfoundland
KeywordsChemistryMass spectrometryIonIon trapElectrospray ionizationFractionationChromatographyQuadrupole ion trapLigninAnalytical Chemistry (journal)ElectrosprayFormic acidMass spectrumOrganic chemistry

Abstract

fetched live from OpenAlex

Direct infusion-electrospray ionization (ESI)-Ion-Trap MS and ESI-Ion-Trap MS 2 were used for direct analysis of bio-oil from forest residue and reference bio-oils from cellulose and hardwood lignin. It was found that the bio-oil concentration and mode of MS analysis are important parameters in obtaining reproducible and structurally informative data. In order to study sensitivity and selectivity with ESI-Ion-Trap MS, a selection of model compounds were studied with and without dopants. Dopants included NaCl, formic acid and NH 4 Cl in positive ion mode and NaOH and NH 4 Cl in negative ion mode. NH 4 Cl addition can be used to distinguish carbohydrate-derived products from other bio-oil components. NaOH and NaCl additives produced the highest peak intensities in negative ion mode as deprotonated adducts and in positive mode as sodiated adducts, respectively. ESI-MS 2 was used successfully for confirmation of individual target ions such as levoglucosan and cellobiosan, as well for some structural products of lignin. Simple bio-oil fractionation into hydrophilic and hydrophobic components provided less complex and more interpretive ion spectra.

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 score0.040
Threshold uncertainty score0.630

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.197
Teacher spread0.190 · 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

Citations22
Published2013
Admission routes2
Has abstractyes

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