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Record W4384665987 · doi:10.3390/molecules28145464

Ni(II)-Salophen—Comprehensive Analysis on Electrochemical and Spectral Characterization and Biological Studies

2023· article· en· W4384665987 on OpenAlexfundno aff
Francis Aurelien Ngounoue Kamga, Madalina Hrubaru, Oana Enache, Elena Diacu, Constantin Drăghici, Victorița Tecuceanu, Eleonora‐Mihaela Ungureanu, Stephanie Nkemone, Peter T. Ndifon

Bibliographic record

VenueMolecules · 2023
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsnot available
FundersAgence Universitaire de la Francophonie
KeywordsThermogravimetric analysisLigand (biochemistry)AcetonitrileElectrochemistryChemistryElectrospray ionizationPerchlorateMetalNuclear chemistryMoietyProton NMRInorganic chemistryMass spectrometryElectrodeOrganic chemistryPhysical chemistryChromatographyIon

Abstract

fetched live from OpenAlex

New aspects of the Ni(II)-salophen complex and salophen ligand precursor were found during deep electrochemical and optical characterization, as well as biological studies for new pharmacological applications. Physicochemical and spectroscopic methods (1H- and 13C-NMR, FT-IR and UV-Vis, electrospray ionization mass spectroscopy, thermogravimetric analysis, and molar conductance measurements) were also used to prove that the salophen ligand acts as a tetradentate and coordinates to the central metal through nitrogen and oxygen atoms. The electrochemical behavior of the free Schiff salophen ligand (H2L) and its Ni(II) complex (Ni(II)L) was deeply studied in tetrabutylammonium perchlorate solutions in acetonitrile via CV, DPV, and RDE. Blue films on the surfaces of the electrodes as a result of the electropolymerization processes were put in evidence and characterized via CV and DPV. (H2L) and Ni(II)L complexes were tested for their antimicrobial, antifungal, and antioxidant activity, showing good antimicrobial and antifungal activity against several bacteria and fungi.

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 score0.025
Threshold uncertainty score0.532

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.022
GPT teacher head0.272
Teacher spread0.250 · 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
Published2023
Admission routes1
Has abstractyes

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