Advanced manufacturing approaches for electrochemical energy storage devices
Bibliographic record
Abstract
Advancements in electrochemical energy storage devices such as batteries and supercapacitors are vital for a sustainable energy future. Significant progress has been made in developing novel materials for these devices, but less attention has focused on developments in electrode and device manufacturing. While electrodes are traditionally made through slurry casting of electrochemically active material, advanced manufacturing techniques enable patterning of novel electrode architectures and control of device geometries in real-time, which can potentially result in electrodes with increased loading, improved electrochemical performance, and added functionality, such as flexibility and wearability. These inexpensive methods are particularly suited for lab-scale research and start-up companies, as they enable rapid prototyping without a full device production line. The present review describes three main methods of advanced manufacturing (inkjet printing, direct ink writing, and laser-induced graphene techniques) and evaluates the performance of batteries and supercapacitors fabricated via these methods in comparison to traditionally manufactured devices.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| 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".