Impact of Ionic Strength (Sodium Chloride Concentration) on Homopolymerization and Copolymerization Kinetics of Acrylamide and 2‐Acrylamido‐2‐Methylpropane Sulfonic Acid
Bibliographic record
Abstract
Abstract Anionic polyelectrolytes can be used for a variety of applications, including flocculation and enhanced oil recovery. While it is widely recognized that polyelectrolyte synthesis is impacted by the pre‐polymer formulation and polymerization conditions, the specific relationships between these factors and the subsequent polymer properties are not well understood. Therefore, the current work intends to improve understanding of ionic strength (IS) effects during the copolymerization of 2‐acrylamido‐2‐methylpropane sulfonic acid (AMPS) and acrylamide (AAm). The aims of the study are i) to use in situ H 1 NMR to study copolymerization kinetics, and ii) to determine how increasing IS impacts copolymerization kinetics (and, by extension copolymer microstructure). It is found that altering IS prior to copolymerization has significant impacts on the reactivity ratios, and therefore impacts the microstructure through multiple mechanisms. Increasing IS causes a crowding effect, where the propagating chain develops a random coil conformation and causes steric hindrance of the large AMPS monomer, decreasing the likelihood of AMPS propagation. When the IS is increased further, the ionic shielding effect is more impactful, increasing the likelihood of AMPS propagation. Ultimately, this work will make it possible to manipulate IS to synthesize AMPS/AAm copolymers with specific desirable properties for target applications.
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 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 | 0.000 |
| 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) | 0.000 | 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".