Patterning Planar, Flexible Li-S Battery Full Cells on Laser-Induced Graphene Traces
Bibliographic record
Abstract
Laser conversion of commercial polymers to laser-induced graphene (LIG) using inexpensive and accessible CO2 lasers has enabled the rapid prototyping of promising electronic and electrochemical devices. Frequently used to pattern interdigitated supercapacitors, few approaches have been developed to pattern batteries—in particular, full cells. Herein, we report an LIG-based approach to a planar, interdigitated Li-S battery. We show that sulfur can be deposited by selective nucleation and growth on the LIG cathode fingers in a supersaturated sulfur solution. Melt imbibition then leads to loadings as high as 3.9 mg/cm2 and 75 wt% sulfur. Lithium metal anodes are electrodeposited onto the LIG anode fingers by a silver-seeded, pulse-reverse-pulse method that enables loadings up to 10.5 mAh/cm2 to be deposited without short-circuiting the interdigitated structure. The resulting binder/separator-free flexible battery achieves a capacity of over 1 mAh/cm2 and an energy density of 200 mWh/cm3. Unfortunately, due to the use of near stoichiometric lithium, the cycle-life is sensitive to lithium degradation. While future work will be necessary to make this a practical, flexible battery, the interdigitated structure is well-suited to future operando and ex situ studies of Li-S and related battery chemistries.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 0.001 |
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".