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Record W4412880649 · doi:10.1016/j.memsci.2025.124512

Lignin depolymerization: A sustainable strategy to enhance the separation performance of biopolymeric polyester membranes

2025· article· en· W4412880649 on OpenAlexafffund
Amirhossein Taghipour, Pooria Karami, Aria Khalili, Maral Bagheri Kaloo, Behzad Ahvazi, Aman Ullah, Jae‐Young Cho, Mohtada Sadrzadeh

Bibliographic record

VenueJournal of Membrane Science · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsNational Institute for NanotechnologyUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaSveriges Kommuner och LandstingAlberta InnovatesUniversity of Alberta
KeywordsDepolymerizationMembraneLigninPolyesterChemical engineeringPolymer scienceChemistryMaterials sciencePolymer chemistryOrganic chemistryEngineeringBiochemistry

Abstract

fetched live from OpenAlex

Membrane technology remains essential for water treatment and desalination. While polyamide thin-film composite (TFC) membranes dominate the industry, their susceptibility to fouling reduces efficiency and shortens operational lifespan. Advanced chemical modification strategies have been developed to overcome this challenge, aiming to improve membrane performance and durability. Polyester-based TFC membranes offer a promising alternative, providing a negatively charged surface. However, their lower salt rejection than polyamide membranes remains a key limitation. In this study, we investigated the application of depolymerized lignin, a naturally abundant biopolymer, as a phenolic monomer for fabricating polyester TFC membranes. The native lignin has a much larger molecular size compared to conventional monomers, which limits its diffusion and reactivity during membrane formation. We utilized a microwave-assisted depolymerization technique to fractionate lignin into smaller moieties, resulting in oligomeric/monomeric lignin with a lower molecular mass and higher reactive sites. This approach enabled faster membrane fabrication and significantly improved membrane performance. The membranes fabricated by depolymerized lignin exhibited substantially improved salt rejection, achieving up to 98.8 % for sodium sulfate and 54 % for sodium chloride removal. The developed membranes exhibited excellent antifouling properties, as demonstrated by sodium alginate fouling tests, with a flux recovery ratio of over 85 %. This research presents an innovative approach to enhancing non-polyamide TFC membranes, opening up new possibilities for eco-friendly and efficient membrane technologies in practical desalination applications. • Depolymerized lignin enables fast fabrication of polyester TFC membranes. • Achieved 98.8 % Na 2 SO 4 and 54 % NaCl rejection with modified membranes. • Microwave-assisted depolymerization enhances lignin reactivity and diffusion. • Membranes show >85 % flux recovery in sodium alginate fouling tests. • Eco-friendly alternative to polyamide membranes with improved antifouling.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.467

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.287
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2025
Admission routes2
Has abstractyes

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