The Effect of Controlled Polymer Architecture on VI and Other Rheological Properties
Bibliographic record
Abstract
Controlled architecture polymers, including block copolymers, have been an area of interest for a number of years. Block copolymers have been shown to be useful as viscosity index improvers, for example; block copolymers of poly (dienes or hydrogenated dienes) and poly(styrene). However, anionic polymerization, the method used to produce commercial styrenic block copolymers, has limitations on the types of monomers that can be used. Controlled Radical Polymerization (CRP) uses a free radical initiating system and a polymerization controller. This technology results in block copolymers containing a wider range of monomer compositions and leads to predictable structures, molecular weights and polydispersities. Furthermore, these block copolymers can be produced using standard free-radical polymerization techniques by virtue of a new nitroxide capable of controlling a wide range of monomers including acrylic and methacrylic monomers. We have found that acrylic block copolymers formed via CRP, produce excellent viscosity index (VI) improvement in lubricating oils. These acrylic block polymers, in some cases, can exhibit greater than 50% viscosity index improvement as compared to random copolymers or other block compositions. Reported are the results of an experimental design study investigating the composition of the acrylic blocks, molecular weight, and block architecture (diblock, triblock, and gradient) on the resultant VI.
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 | 0.001 |
| 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) | 0.002 | 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".