Templating Influence of Molecular Precursors on Pr(OH)<sub>3</sub> Nanostructures
Bibliographic record
Abstract
Four new praseodymium alkoxo and amido compounds ([Pr3(μ3-OtBu)2(μ2-OtBu)3(OtBu)4(HOtBu)2] (1), [Pr{OC(tBu)3}3(THF)] (2), [PrCl{N(SiMe3)2}2(THF)]2 (3), and [PrCl{OC(tBu)3}2(THF)]2 (4)) were synthesized and structurally characterized by single-crystal X-ray diffraction analysis. Application of these compounds in solvothermal synthesis of praseodymium oxide/hydroxide nanostructures showed their templating influence on the morphology and phase composition of the resulting solid-state materials. Differential reactivity of the chosen alkoxide ligands toward water and the different arrangements of metal-oxygen units in the studied precursor compounds strongly influenced the kinetics of hydrolysis and cross-condensation reactions as manifested in the morphological changes and phase composition of the final products. Thermal decomposition studies of 1-4 confirmed their conversion into the corresponding oxide phases. Activation of compounds 1, 2, and 4 by either a base or a stoichiometric amount of water showed the distinct influence of their chemical configuration on the obtained nanopowders: whereas 1 solely produced nanorods of Pr(OH)3, 2 predominantly formed a mixture of rod-shaped and spherical particles. The solvothermal decomposition of 4 resulted in Pr(OH)2Cl or PrOCl due to the presence of Cl ligands in the molecular precursor. The resultant materials were thoroughly characterized to demonstrate the relationship between precursor chemistry and the processing parameters that are clearly manifested in the morphology and phase of the final ceramics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".