A Family of Heteroleptic Titanium Guanidinates: Synthesis, Thermolysis, and Surface Reactivity
Bibliographic record
Abstract
A family of new mixed-ligand titanium guanidinate compounds was synthesized as potential atomic layer deposition precursors, and the surface chemistry on silica of a promising candidate (Cp(2)Ti[(N(i)Pr)(2)CN(H)(i)Pr]) was explored. Generally, these compounds have very good thermal stability with onsets of volatility between 127 and 168 degrees C, with melting points generally ranging from 147 to 165 degrees C. The reactivity of [(i)PrN(H)C(N(i)Pr)(2)]TiCp(2) was studied with high surface area silica between 180 and 330 degrees C. The surface reactivity was found to differ if the silica was preheated to 350 or 900 degrees C; this was attributed to the hydroxyl nucleation site density of the silica, which is known to vary with the temperature. The surface reaction products were characterized by solid-state NMR, and these agreed well with a calculated model. When the silica was pretreated to 350 degrees C, the precursor appeared to chemisorb primarily through the loss of a Cp ligand, while with a 900 degrees C pretreatment, the chemisorption occurred primarily through a loss of the guanidinate ligand. The adsorption enthalpies to silica were calculated for the different surface species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".