Bio-Sourced and Biodegradable Membranes
Bibliographic record
Abstract
Biodegradable membranes with innovative antifouling properties are emerging as possible substitutes for conventional membranes. These types of membranes have the potential to be applied in a wide range of applications, from water treatment to food packaging and energy production. Nevertheless, there are several existing challenges and limitations associated with the use of biodegradable membranes in large scale applications, and further studies are required to determine the degradation mechanisms and their scalability. Biodegradable membranes can be produced from either renewable natural resources or synthesized from low-molecular monomers that increase the number of possible structures and, as a result, greatly expand the membrane application possibilities. This study focused on bio-sourced and synthesized biodegradable polymers as green membrane materials. Moreover, the article highlighted the excellent antifouling properties of biodegradable membranes that assist in improving membrane lifetime during filtration processes, preventing chemical/biological disposal due to frequent cleaning processes and ultimately reducing the maintenance cost. The industrial and biomedical applications of biodegradable membranes were also summarized, along with their limitations. Finally, an overview of challenges and future trends regarding the use of biodegradable membranes in various industries was thoroughly analyzed.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".