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Record W4366492634 · doi:10.5267/j.ccl.2023.2.002

Salicylaldehyde based Schiff base as a selective and sensitive chemosensor for Cd2+ and Ni2+ ions

2023· article· en· W4366492634 on OpenAlexvenueno aff
Unnati P. Patel, Ranjitsinh C. Dabhi, Kartik K. Vaja, Rakesh S. Jani, Jayesh J. Maru

Bibliographic record

VenueCurrent Chemistry Letters · 2023
Typearticle
Languageen
FieldChemistry
TopicMolecular Sensors and Ion Detection
Canadian institutionsnot available
FundersIndian Institute of Technology Indore
KeywordsChemistrySalicylaldehydeSchiff baseDetection limitMetal ions in aqueous solutionMass spectrometryProton NMRIonMetalSpectroscopyUltraviolet visible spectroscopyCarbon-13 NMRAbsorption (acoustics)Nuclear chemistryPhotochemistryAnalytical Chemistry (journal)StereochemistryOrganic chemistryChromatography

Abstract

fetched live from OpenAlex

A new salicylaldehyde-based sensor N'-(5-bromo-2-hydroxybenzylidene)-4-methylbenzohydrazide (P4) was designed, and its sensing ability towards various metal ions was assessed using UV-visible spectroscopy. The structure of P4 was spectroscopically characterized by UV-Visible, Infrared, 1H-NMR, 13C-NMR spectroscopy and mass spectrometry. UV-Visible absorption spectral study showed selective sensing ability of P4 for Cd2+ and Ni2+ ions in presence of diverse transition metal ions. The results revealed that the detection limit for Cd2+ and Ni2+ was 3.14 µM and 0.92 µM, respectively. Moreover, the compound P4 was fully implemented for detection of Cd2+ and Ni2+ in simulated samples.

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 score0.007
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.014
GPT teacher head0.255
Teacher spread0.242 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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