Ethylcellulose-Stabilized Heat Resistant Chocolate
Bibliographic record
Abstract
The ethylcellulose solvent substitution method was developed which added ethylcellulose solubilized in ethanol to molten chocolate and, after evaporation of the ethanol, produced heat resistance in the chocolate. Chocolate containing 2.17% ethylcellulose 10 cP had hardness of 18 N at 40°C measured by large deformation mechanical testing. The hardness of the chocolate was found to be dependent on the chocolate formulation and concentration of ethylcellulose, and independent of ethylcellulose viscosity. Mechanical testing on model systems revealed that polymer gelation of cocoa butter only played a minor role in the heat resistance observed. Instead, interactions between sucrose and ethylcellulose were responsible for the formation of a network within the chocolate that provided the majority of the mechanical strength and oil trapping at elevated temperatures. Atomic scale molecular dynamics simulations predicted the ability of ethylcellulose to hydrogen bond with sucrose and this was corroborated by Fourier – transform infrared (FTIR) spectroscopy. Scanning electron microscopy and mechanical testing showed the presence of an ethylcellulose - sucrose network that was able to resist deformation. Simulations predicted, and mechanical testing and FTIR, showed that lecithin, typically found at the surface of sucrose in chocolate, reduced heat resistance by impeding ethylcellulose - sucrose interactions. However, fluorescence microscopy revealed that the ethanol used to prepare the chocolate could remove some of the lecithin from the sucrose. Furthermore, ethanol dissolved a small amount of the sucrose and both of these effects positively impact heat resistance. Finally, a solvent-free method of introducing ethylcellulose to food systems was explored by the development of thixotropic ethylcellulose oleogels. It was found that thixotropy could be achieved by matching the Hansen hydrogen bonding solubility parameter of the oil phase to that of ethylcellulose. This was demonstrated with an oleogel made with 8% ethylcellulose 10 cP and vegetable oil and glycerol monooleate at a ratio of 55:45. These two methods represent novel strategies to introduce ethylcellulose to food systems and the solvent substitution method demonstrated how ethylcellulose can be used to provide structure in foods.
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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 | 0.001 |
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".