Upcycling Plastic Waste into Porous Activated Carbon As Cathode Material for Lithium-Selenium Batteries
Bibliographic record
Abstract
Selenium (Se) has a high specific capacity, rendering it a promising cathode material for rechargeable lithium (Li) batteries. Yet, challenges arise due to irreversible reactions and the shuttle effect in contact with electrolytes. This study addresses these issues by confining Se within a microporous carbon derived from non-recyclable plastic waste through a two-step carbonization/activation process. The resulting plastic waste-derived carbon (PWC) serves as a host for Se, forming cathode composites through a melt diffusion process. The cathode electrode was fabricated using a slurry casting method, comprising PWC/Se composite, carbon black, and sodium alginate (8:1:1 mass ratio). The evolution of the porous structure in PWC and its impact on the electrochemical performance of PWC/Se electrode were investigated for different activation temperatures (500, 600, 700, and 800 °C). The study revealed that the structure of PWC activated below 800 °C consists of mainly micropores. Moreover, by increasing the activation temperature, the specific surface area and pore volume increased, and pore size distribution shifted towards mesoporous structure. The Li-Se coin cell made from PWC activated at 600 °C (PWC600) demonstrated superior discharge capacity (640 mAh g –1 at 0.1C after 400 cycles), rate capability, and long cycling stability at higher current densities. The microporous features of PWC600 were crucial for effective Se confinement, lithium-ion diffusion, and charge transfer. This work emphasizes the sustainable development of microporous carbon from upcycled plastic waste as a promising cathode material for high-energy Li-Se batteries. Our findings contribute to environmentally friendly energy storage solutions and the circular economy by repurposing non-recyclable plastic waste into valuable materials.
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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) | 0.000 | 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) | 0.000 | 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".