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Record W4392628125 · doi:10.18311/jmmf/2023/36051

Facile Synthesis of Spinel Zinc Aluminate Using Biofuel For Effective Photocatalytic Dye Degradation And Electrochemical Sensor Studies

2023· article· en· W4392628125 on OpenAlex
K. Gurushantha, K. Keshavamurthy, S Shashidhar, S. Meena

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Mines Metals and Fuels · 2023
Typearticle
Languageen
FieldEngineering
TopicGas Sensing Nanomaterials and Sensors
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsSpinelPhotocatalysisDegradation (telecommunications)ZincElectrochemistryMaterials scienceAluminateChemical engineeringCatalysisChemistryMetallurgyComputer scienceElectrodeOrganic chemistry

Abstract

fetched live from OpenAlex

Zinc aluminate nanomaterial provide a potential candidate for photocatalytic and sensor applications. Using biofuel (banana peel powder), zinc aluminate was synthesized by SCM (solution combustion method) in the current study. The properties of the phase structures, chemical composition, morphologies, and photocatalytic sensors were characterized by utilizing powder X-ray diffraction, scanning electron microscope, CH analyzer, UV-Visible spectroscopy, and photocatalytic reactor. Indigo Carmine (IC) dye degradation under UV light was used to assess the photocatalytic activity. The results showed that zinc aluminate makes a superior photocatalyst for degrading organic dyes like indigo carmine. In a potassium hydroxide electrolyte medium, zinc aluminate was also an effective substance for paracetamol and lead metal sensing. The results confirm that the novel material could be used for various industrial applications.

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.

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 score0.008
Threshold uncertainty score0.434

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.030
GPT teacher head0.273
Teacher spread0.243 · 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