A convenient and quantitative route to Sn(<scp>iv</scp>)–M [M = Ti(<scp>iv</scp>), Nb(<scp>v</scp>), Ta(<scp>v</scp>)] heterobimetallic precursors for dense mixed-metal oxide ceramics
Bibliographic record
Abstract
The strategy of reacting SnCl4 with M(OR)x provided a convenient and quantitative approach to new heterobimetallics with a simple addition formula, [SnCl4M(OR)x(HOR)y] (M = Ti, Nb, Ta; R = Et, Pr(i), x = 4, 5; y = 0-2) or sometimes an oxo complex [SnCl3(O)Ti2(OPr(i))7(HOPr(i))2]. The alcoholysis reactions of these heterometallics afforded mixed alkoxo complexes [SnCl4(μ-OEt)2M(Pr(i)O)x(Pr(i)OH)y] [M = Ti (x = y = 2), Nb, Ta (x = 3, y = 1)] under mild conditions, or a planar rectangular oxo product [SnCl3(μ-OEt)2Nb(OEt)2(EtOH)(μ-O)]2 at refluxing/extended stirring time. DFT calculations shed light on the stability and reactivity of these complexes. The use of these thoroughly characterized heterometallics as sol-gel precursors suppresses the formation of the undesired SnO2 grains, which are difficult to be sintered to a high density. The combined approach of using bottom-up synthesis of mixed Ti0.5Sn0.5O2 nanoparticles and Spark Plasma Sintering allowed the successful densification of chloride-free mixed-metal oxide ceramics. The influence of thermal treatment before sintering on the density and spinodal decomposition of the TiO2-SnO2 pellets is reported.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".