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Record W2737281782 · doi:10.1002/slct.201700940

Efficient Reversible Optical Sensing of Water Achieved through the Conversion of H‐Aggregates of a Merocyanine Salt to J‐Aggregates

2017· article· en· W2737281782 on OpenAlexaff
Priya Ranjan Sahoo, Kunal Prakash, Ajeet Kumar, Satish Kumar

Bibliographic record

VenueChemistrySelect · 2017
Typearticle
Languageen
FieldMaterials Science
TopicPhotochromic and Fluorescence Chemistry
Canadian institutionsSt. Stephen's University
Fundersnot available
KeywordsSpiropyranMerocyanineSalt (chemistry)ChemistryFluorescenceNaked eyeMetal ions in aqueous solutionProton NMRMetalAnalytical Chemistry (journal)PhotochemistryPhotochromismOrganic chemistryChromatographyOpticsDetection limit

Abstract

fetched live from OpenAlex

Abstract A stable MC (merocyanine)‐spiropyran as p ‐toluenesulfonate salt was synthesized. The structure of the merocyanine salt form of the spiropyran was established by using IR, 1 H‐NMR, 13 C‐NMR, 2D‐NMR and HR‐MS spectroscopic techniques. The MC salt was employed as an optical probe for the detection of trace water content in the organic media using the naked eye, UV‐Visible and fluorescence spectroscopic techniques. The DLS and TEM measurements were used to support the aggregation and disaggregation of the MC salt form. The results established the conversion of H‐ aggregates to J‐ aggregates can be used for the efficient detection of trace water content in organic media. The optical probe was further used to sense and quantify water molecules associated with the metal salts. The probe can be used multiple times for sensing water. The results provide insightful opportunities for practical applications of sensing trace water content in organic solvents and coordinated to metal ions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.000
Threshold uncertainty score0.001

Distilled classifier scores by category (both heads)

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 head0.252
Teacher spread0.237 · 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 source (direct Gemma or distilled Codex), 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

Citations25
Published2017
Admission routes1
Has abstractyes

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