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Record W4387401874 · doi:10.61558/2993-074x.2622

Kinetic Study of Photoelectrochemical Oxidation of Lignin Model Compounds on TiO<sub>2</sub> Nanotubes

2012· article· en· W4387401874 on OpenAlexafffund
Min Tian, Daniel Liba, Aicheng Chen

Bibliographic record

VenueDian hua xue/Dian huaxue · 2012
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsLakehead University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsScanning electron microscopeElectrochemistryScanning electrochemical microscopyAbsorbanceDensity functional theoryReactivity (psychology)Aqueous solutionPhotoelectrochemistryMaterials scienceChemistryPhotochemistryPhysical chemistryElectrodeComputational chemistry

Abstract

fetched live from OpenAlex

In this study, TiO2 nanotubes were prepared via the electrochemical oxidation of titanium substrates in a non-aqueous electrolyte and their morphology and microstructures were examined by scanning electron microscopy (SEM) and X-ray diffraction (XRD). The photoelectrochemical oxidation of two lignin model compounds, 1-(3,4-dimethoxyphenoxy)-2-(2-methoxyphenoxy)-1,3-propanediol (DMP) and 3-hydroxy-1-(3,4-dimethoxyphenoxy)-2-(2-methoxyphenoxy)-1,3-propanone (HDM), was investigated. A new band appeared at ~304 nm during the photoelectrochemical oxidation of DMP. The rate of DMP intermediate formation was amplified with the increase of initial concentrations, while it was diminished with increased temperature. Despite the similarity in structure between HDM and DMP, there are only small increases in absorbance during the oxidation of HDM, suggesting that HDM is less reactive. Quantum chemical calculations based on the density functional theory (DFT) were performed in order to link photoelectrochemical reactivity with specific molecular properties. Relatively higher ELUMO-EHOMO of HDM makes it more stable and thus more refractory to oxidation, which is consistent with our photoelectrochemical results.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.013
GPT teacher head0.238
Teacher spread0.225 · 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
Published2012
Admission routes2
Has abstractyes

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