Proton Exchange Membranes from Sulfonated Lignin Nanocomposites for Redox Flow Battery Applications
Bibliographic record
Abstract
Abstract Redox flow batteries (RFBs) are increasingly being considered for a wide range of energy storage applications, and such devices rely on proton exchange membranes (PEMs) to function. PEMs are high‐cost, petroleum‐derived polymers that often possess limited durability, variable electrochemical performance, and are linked to discharge of perfluorinated compounds. Alternative PEMs that utilize biobased materials, including lignin and sulfonated lignin (SL), low‐cost byproducts of the wood pulping process, have struggled to balance electrochemical performance with dimensional stability. Herein, SL nanoparticles are demonstrated for use as a nature‐derived, ion‐conducting PEM material. SL nanoparticles (NanoSLs) can be synthesized for increased surface area, uniformity, and miscibility compared with macrosized lignin, improving proton conductivity. After addition of polyvinyl alcohol (PVOH) as a structural backbone, membranes with the highest NanoSL concentration demonstrated an ion exchange capacity of 1.26 meq g −1 , above that of the commercial PEM Nafion 112 (0.98 meq g −1 ), along with a conductivity of 80.4 mS cm −1 in situ, above that of many biocomposite PEMs, and a coulombic efficiency (CE), energy efficiency (EE) and voltage efficiency (VE) of 91%, 68% and 78%, respectively at 20 mA cm −2 . These nanocomposite PEMs demonstrate the potential for valorization of forest biomass waste streams for high value clean energy applications.
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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".