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Record W4392161049 · doi:10.18280/acsm.480102

Modified Sol-Gel Method of Synthesising a Mn4+-Doped Mg2TiO4: A Red Phosphor for Improved LED Performance

2024· article· en· W4392161049 on OpenAlexvenueno aff
Bahaa Wathook, Dhia A. Hassan

Bibliographic record

VenueAnnales de Chimie Science des Matériaux · 2024
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence Properties of Advanced Materials
Canadian institutionsnot available
FundersUniversity of Basrah
KeywordsPhosphorDopingMaterials scienceSol-gelOptoelectronicsChemistryNanotechnology

Abstract

fetched live from OpenAlex

Mn 4+ -doped perovskite Mg2TiO4 holds significant promise for the advancement of LEDbased white light sources, given its cost-effectiveness, abundance, and stability at elevated temperatures.In this study, we present a novel approach employing the sol-gel method for the synthesis of Mg2TiO4:Mn 4+ phosphor.Notably, the gel solution underwent a controlled cooling process at 2℃ for a complete day, resulting in reduced drying time, lower calcination temperature, shortened duration, and optimized concentrations of doped ions in the derived phosphors.We explore the influence of temperature and manganese ions on the crystal structure of the host material, and X-ray diffraction (XRD) analysis confirms the formation of a pure phase.Additionally, the Xray energy dispersion spectroscopy (EDX) technique is employed to ascertain the compound's constituent proportions, revealing a crystallite size of 32.23nm.The photoluminescence study demonstrates an emission spectrum at 480 nm in the red region.Integrating our prepared red phosphor with a commercial yellow phosphor YAG:Ce 3+ , the resulting LED, utilizing a 450 nm blue chip InGaN, exhibits a correlated color temperature (CCT) of 4607 K, presenting a cool white color with chromaticity coordinates of x = 0.3594 and y = 0.3753.The modified sol-gel method thus offers a promising avenue for the efficient synthesis of Mn 4+ -doped Mg2TiO4 red phosphors, enhancing LED performance.

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)0.004
metaresearch head score (Gemma)0.002
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 score0.161
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
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 head0.045
GPT teacher head0.317
Teacher spread0.272 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueAnnales de Chimie Science des MatériauxSame topicLuminescence Properties of Advanced MaterialsFrench-language works237,207