Determination of Shell Thickness of Spherical Core-Shell Ni<sub>x</sub>Mn<sub>1-x</sub>(OH)<sub>2</sub>Particles via Absorption Calculations of X-Ray Diffraction Patterns
Bibliographic record
Abstract
Two core-shell materials were made in a continuously stirred tank reactor, one with a Ni(OH) 2 core and a Ni 1/2 Mn 1/2 (OH) 2 shell and the other with a Ni 1/2 Mn 1/2 (OH) 2 core and a Ni 0.17 Mn 0.83 (OH) 2 shell. X-ray diffraction measurements (Cu K α radiation) of the core-shell materials were compared to reference materials which were physical mixtures with the same overall composition. The smaller core peaks in the XRD patterns of the core-shell materials were attributed to absorption of X-rays due primarily to the high manganese contents of the shells. Calculations were performed assuming spherical particles of radius matching results from SEM/EDS measurements. For a 5.5 μm radius particle with a Ni(OH) 2 core, the shell thickness was calculated from XRD patterns to be 0.47 ± 0.03 μm. For a 7.9 μm particle of the material with the Ni 1/2 Mn 1/2 (OH) 2 core, the shell was determined to be 1.77 ± 0.15 μm thick. Both these results were found to agree well with the overall composition of the samples as determined by elemental analysis and with spatial EDS measurements. This X-ray absorption modeling technique provides an experimentally simple way to measure the thickness of micron scale shell coatings while sampling all particles, unlike methods such as EDS.
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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 | 0.001 |
| 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) | 0.001 | 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".