Ferroelectric soft materials formed with alkanolamines and unsaturated fatty acids
Bibliographic record
Abstract
• Aqueous alkanolamine-fatty acid mixtures are viscoelastic. • They exhibit capacitive charging, and gels have higher capacitance. • Mixtures are either lamellar or columnar hexagonal liquid crystal phases. • Water fosters the formation of large-scale structures spanning hundreds of microns. Ferroelectric materials generate electric current when subjected to mechanical stress, and find a broad range of applications, from clean energy production to sensing. We used various alkanolamines and fatty acids to produce viscoelastic ferroelectric materials containing a high proportion of water. Without fatty acids, aqueous solutions of amino methyl propanol (AMP), amino ethoxy ethanol (AEE), and methyldietanolamine (MDEA) are not viscoelastic or ferroelectric. Upon addition of singly (oleic) or doubly unsaturated (linoleic) fatty acids, aqueous amine mixtures are viscoelastic, as shown by shear rheology. Synchrotron small angle X ray scattering (SAXS) and X ray diffraction (XRD) reveal either lamellar or columnar hexagonal self-assembled liquid crystal phases, depending on the composition of the mixture. Computer simulations confirm that aqueous mixtures of AMP and oleic acid self-assemble into lamellar structures. Water fosters the formation of large-scale structures spanning hundreds of microns, as seen with polarized light microscopy. Cyclic voltammetry demonstrates that aqueous alkanolamine-fatty acid mixtures exhibit different capacitive charging. With oleic acid and 91 wt% water, the capacitance follows the order AMP > diethanolamine (DEA) > MDEA > AEE. Also, the capacitance of aqueous AMP mixtures containing 91 wt% water is greater with oleic than linoleic acid. The capacitance is uncorrelated to the mechanical strength of our materials, but with AMP, viscous materials had lower capacitance than gels. Fatty acid–amine interactions in water control the properties of the materials. Fourier transform infrared spectroscopy shows that, upon mixing with amines, fatty acids become ionized and form COO - , which interacts with the NH groups of the amines.
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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".