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Record W3167399080 · doi:10.3390/pr9061049

Porous Anion Exchange Membrane for Effective Acid Recovery by Diffusion Dialysis

2021· article· en· W3167399080 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProcesses · 2021
Typearticle
Languageen
FieldEngineering
TopicMembrane-based Ion Separation Techniques
Canadian institutionsDalhousie University
FundersNational Natural Science Foundation of China
KeywordsMembranePorosityDiffusionDialysisIon exchangeChemical engineeringSalt (chemistry)ChemistryMaterials scienceFabricationWastewaterChromatographyIonOrganic chemistryWaste managementSurgeryBiochemistryEngineering

Abstract

fetched live from OpenAlex

Diffusion dialysis (DD) employing anion exchange membranes (AEMs) presents an attractive opportunity for acid recovery from acidic wastewater. However, challenges exist to make highly acid permeable AEMs due to their low acid dialysis coefficient (Uacid). Here, a series of porous and highly acid permeable AEMs fabricated based on chloromethyl polyethersulfone (CMPES) porous membrane substrate with crosslinking and quaternization treatments is reported. Such porous AEMs show high Uacid because of the large free volume as well as the significantly reduced ion transport resistance relative to the dense AEMs. Compared with the commercial dense DF-120 AEM, our optimal porous AEM show simultaneous 466.7% higher Uacid and 75.7% higher acid/salt separation factor (Sacid/salt) when applied to acid recovery at the same condition. Further, considering the simple and efficient fabrication process as well as the low cost, our membranes show great prospects for practical acid recovery from industrial acidic wastewater.

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 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)0.000
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: none
Teacher disagreement score0.555
Threshold uncertainty score0.734

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.008
GPT teacher head0.233
Teacher spread0.225 · 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