High Temperature Capable Ionic Polymer-Metal Composite Capacitors and Power Storage Systems
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">The need for reduced system size and weight while increasing performance for military and commercial systems will require high-temperature electronics capable of running the actuators, high-speed motors and generators of the future. Of the many passive devices necessary to satisfy the need for a complete high temperature system, perhaps none has been more problematic than that of the capacitor, particularly for larger devices requiring values of several micro- to milli-farads. In this paper we introduce an ionic polymer metal composite (IPMC) we have recently developed that can operate well above the standard 125°C. These capacitors have the potential to meet all other typical aerospace and automotive design constraints of high reliability, robustness, and light weight as well as having additional features of being flexible, scalable, and customizable in shape. Our recent discovery of the capacitive behavior in specially treated perfluorinated sulfonic acid polymers sandwiched between metal electrodes has lead to the exciting development of high temperature capable high-density passive storage components. These composites exhibit capacitance per unit planar area of ~1.0 mF cm-₂ or 40 mF/g for a ~100 μm thick polymer substrate, with only a minor decrease in capacitance observed after heating above 125°C followed by constant capacitance up to 300°C. The simple microfabrication process for depositing high surface metal electrodes onto these polymers allows for easy and low cost integration of other systems. Here we present one application of these polymer capacitors integrated with organic (i.e., polymer) photovoltaic cells in a 2D design and discuss how this could be incorporated in a seamless monolithic 3D fabrication to provide a single power supply, conditioning and storage unit.</div></div>
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".