GRAPHERGIA Abstract: Polymer Electrolyte Based Flexible Micro-Supercapacitors for Future Aerospace and Smart e-Textile Applications
Bibliographic record
Abstract
In May 2025, GRAPHERGIA’s partner, the Institute of Materials Research of DLR (German Aerospace Center), presented an abstract at the 247th ECS Meeting (The Electrochemical Society), organised from 18-22 May, in Montréal, Canada. This abstract, entitled “Polymer Electrolyte Based Flexible Micro-Supercapacitors for Future Aerospace and Smart e-Textile Applications”, was presented by Dr. Apurba Ray, who is the co-author of the publication with Professor Bilge Saruhan (both from DLR, Germany). Introduction to the abstract: Advancements of ultra-thin, lightweight microelectronics, portable/wearable technologies and next-generation energy-autonomous systems have significantly increased the development for high-power energy storage systems. Similarly, future aerospace and aviation systems are looking for clean, decentralised power supplies for various quality, safety, low-cost, and system monitoring requirements. Among various energy storage systems, electrochemical energy storage (EES) devices such as batteries and supercapacitors are being widely used in multiple sectors. However, in most cases, the battery cannot meet the requirements due to its high charging time, low power density, safety concerns and limited cycle life. In the last few years, micro-supercapacitors (MSCs) have attracted considerable attention for application as flexible on-chip and microscale devices for peak power energy storage due to several excellent advantages such as fast charge–discharge rate, light weight, high power density, and long cycle-life. On the other hand, solid/gel polymer electrolytes, as an important component of supercapacitors, play a promising role in electrochemical performance.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.032 | 0.013 |
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".