Estimation of Lattice Strain in Lanthanum Hexa Aluminate Nanoparticles Using X-Ray Peak Profile Analysis
Bibliographic record
Abstract
This work confers to the preparation of Lanthanum Hexa Aluminate (LHA) nanoparticles by chemical precipitation and filtration technique followed by characterization studies conducted through X-ray peak profile analysis (XPPA) and Field Emission Scanning Electron Microscopy (FESEM) supported by Energy Dispersive Spectroscopy (EDS). From the X-ray diffraction (XRD) analysis, it has been observed that the prepared powder has hexagonal crystal structure. Further, Scherrer Method (S-M), modified Williamson–Hall (W-H), and Size–Strain Plot (SSP) methods have been implemented to all LHA reflection peaks for the comprehensive crystalline analysis. The influence of crystallite size, stress, strain, and energy density values on the peak broadening of LHA nanoparticles has been critically examined and discussed in the current work. In addition to regular mathematical models this paper also provides an insight into the calculation of Youngs modulus without tedious experimental procedure. The predicted crystallite size estimated from Scherrer’s formula, and W-H models are correlated to scanning electron microscopy results and observed that the average grain size of LHA nano particles estimated from SEM analysis, and models have less deviation in the present study.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 0.000 |
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.
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".