Study of Imidazole-Based Proton-Conducting Composite Materials Using Solid-State NMR
Bibliographic record
Abstract
The application of solid-state NMR methods to characterize the structure and dynamics of imidazole-based proton-conducting polymeric materials provides insight into the mechanism (Grotthus vs vehicle) of proton-mobility. The presented materials are built on a siloxane backbone, and are of interest as potential new proton-conducting membranes for fuel cells able to function at temperatures above 130 °C. This is expected to improve the CO tolerance of the catalyst in the fuel cell, as compared to water-based systems. High-resolution solid-state 1 H NMR is achieved under fast magic-angle spinning (MAS) conditions (30 kHz), and provides resolution of resonances in the hydrogen-bonding region. Homonuclear double quantum filtered (DQF) NMR spectra, acquired using the back-to-back sequence, provided identification of mobile protons. It was found that proton conductivity, observed macroscopically using impedance spectroscopy, is correlated with local proton mobility, observed via 1 H NMR line width trends observed for the hydrogen-bonded protons. 1 H MAS and DQF NMR experiments show no crystal packing of these materials in contrast to model oligo-ethyleneoxide-tethered imidazole materials (Imi- n EO) studied previously. Comparisons of macroscopic and microscopic measures of proton mobility are also presented in the activation energies of pure and acid-doped siloxane oligomers and polymers functionalized with imidazole. The acid-doped materials show enhanced proton mobility, and hence higher conductivity, relative to the pure material.
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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) | 0.001 | 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) | 0.001 | 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 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".