Modified Sol-Gel Method of Synthesising a Mn4+-Doped Mg2TiO4: A Red Phosphor for Improved LED Performance
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".