Stimuli‐Responsive Electrochemical Energy Storage Devices
Bibliographic record
Abstract
Electrochemical energy storage (EES) devices have been swiftly developed in recent years. Stimuli-responsive EES devices that respond to different external stimuli are considered the most advanced EES devices. The stimuli-responsive EES devices enhanced the performance and applications of the EES devices. The capability of the EES devices to respond to the various external stimuli due to produced advanced EES devices that distinguished the best performance and interactions in different situations. The stimuli-responsive EES devices have responsive behavior to different external stimuli including chemical compounds, electricity, photons, mechanical tensions, and temperature. All of these advanced responsiveness behaviors have originated from the functionality and specific structure of the EES devices. The multi-responsive EES devices have been recognized as the next generation of stimuli-responsive EES devices. There are two main steps in developing stimuli-responsive EES devices in the future. The first step is the combination of the economical, environmental, electrochemical, and multi-responsiveness priorities in an EES device. The second step is obtaining some advanced properties such as biocompatibility, flexibility, stretchability, transparency, and wearability in novel stimuli-responsive EES devices. Future studies on stimuli-responsive EES devices will be allocated to merging these significant two steps to improve the performance of the stimuli-responsive EES devices to challenge complicated situations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".