Bio-Based PLA Membranes for Ion Transport and Ion Filtration
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Lithium-ion batteries require battery separators for both safety and electrochemical performance. Due to that, they have received a lot of attention. In order to prevent any electronic current from moving within the negative and positive electrodes and allow ions to flow through while avoidance of electric contact between them, a porous membrane used as a separator is positioned between the electrodes with opposing polarities. Accordingly, the objective of the present work is to build a biodegradable PLA based battery separator, which has exceptional thermal capabilities and can endure temperatures of up to 300°C. They also seem to serve as the least degree of barrier for the flow of an ionic current. In this study bio-polymer battery separator membranes were developed using PLA as matrix material and fillers such as Copper slag (CS) and Cardanol resin (CNSL). CS and CNSL were preferred for the reason to realize the concept of a wealth reclaimed from wastes that act as toughening and pore forming agent for PLA matrix. It is found that at PLA-CS film has more brittleness when compared to neat PLA and PLA-CNSL resin. On the other hand, PLA-CNSL films are the toughest ones. Overall, it has been demonstrated that obtaining more sustainable and high-performance is possible by the usage of such sustainable materials for futuristic developments.
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.
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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it