Production of Cyclic Anhydride-Modified Starches
Bibliographic record
Abstract
Modified starches offer a biodegradable, readily available, and cost-effective alternative to petroleum-based products. The reaction of alkenylsuccinic anhydrides (ASAs), in particular, is an efficient method to produce amphiphilic starches with numerous applications in different areas. While ASAs are typically derived from petroleum sources, maleated soybean oil can also be used in an effort to produce materials from renewable sources. The reaction of gelatinized waxy maize starch with octenylsuccinic anhydride (OSA), dodecenylsuccinic anhydride (DDSA), a maleated fatty acid (TENAX 2010), phthalic anhydride (PA), 1,2,4-benzenetricarboxylic acid anhydride (trimellitic anhydride, TMA), and three maleated soybean oil samples, was investigated under different conditions. To minimize the reaction time and the amount of water required, the outcome of the esterification reaction was compared for starch dispersions in benchtop dispersed reactions, for starch melts in a heated torque rheometer, and for reactive extrusion in a pilot plant scale twin-screw extruder. The extent of reaction was quantified by 1H NMR analysis, and changes in molecular weight and diameter were monitored by gel permeation chromatography (GPC) analysis. The outcome of the reactions varied markedly in terms of reaction efficiency (RE), molecular weight distribution, and average hydrodynamic diameter, for the products derived from the different maleated reagents used, as well as for the different reaction protocols.
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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 | 0.001 |
| 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".