Bibliographic record
Abstract
A hyperbranched polysilazanes(HBP) with multifunctionality of allyl end groups was prepared by polymerization reaction via hydrosilylation of AB_2 type monomer(N-diallyamine) dimethlsilane,which was synthesized by aminolysis of Me_2HSiCl.The molecular structure of HBP was characterized and determined by FT-IR,1H-NMR spectra analysis and GPC.Further more,the photo-initiated curing kinetics of HBP with thiol compound was studied by differential photo-scanning calorimetry(DPC) technology.The comparing analysis among HBP,HBP-thiol compound and low-functionality monomer of B_2M-thiol compound indicated that thiol functional group reacts with allyl functional group quickly under lower amount of photoinitiator(0.1 wt%) and lower light intensity(about 5 mW/cm2) in ambient condition.The curing rate and ultimate conversion of allyl group in HBP-thiol compound is higher than that in HBP,however,the ultimate conversion of allyl group in HBP-thiol compound is lower than that in B_2M-thiol compound due to the unique hyperbranched structure and high multifunctionality.The effects of photoinitiator concentration [A],UV light intensity(I_0) and reaction temperature on the UV curing rate and the final allyl bond conversion of HBP-thiol compound system were also investigated by DPC.The results indicate that the effects of photoinitiator concentration([A]),UV light intensity(I_0) and temperature on kinetics of HBP-thiol compound reveal that the curing rate(R_p) is directly proportion to square root of [A] and I_0,respectively,which is found to fit with theoretical predictions very well at [A] no more than 0.50 wt% and I_0 lower than 19.40 mW/cm2.Kinetics parameters were determined for HBP-thiol compound according to an autocatalytic model with a diffusion coefficient attached.The total apparent reaction exponent and apparent activation energy are 8.76 and 13.49 kJ/mol,respectively.
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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 | 0.000 | 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".