Development of an EOR-produced petroleum wastewater treatment system through integrated polyacrylonitrile membrane and ZrO2/sericin technologies: revelation of interactive mechanism based on synchrotron and XDLVO analyses
Bibliographic record
Abstract
Ultrafiltration technology is one of the most efficient methods to address the issues of enhanced oil recovery-produced petroleum wastewater (EOR-PW) treatment. However, membrane fouling significantly impairs the efficiency of PW treatment. Moreover, the impacts of the complex components (e.g., salt ions, heavy metal ions, and pH level) in PW on membrane performance and the underlying mechanisms (i.e., fouling modes and interactive force) need further exploration. Herin, a novel ZrO 2 /sericin polyacrylonitrile (ZrSS) ultrafiltration membrane was developed for PW treatment, and the impacts and mechanisms of contaminants in PW on membrane filtration performance were systematically investigated using synchrotron-based technology and extended Derjaguin–Landau–Verwey–Overbeek (XDLVO) analysis. The synchrotron-based characterization results indicate the successful fabrication of the ZrSS membrane and the uniform distribution of ZrO 2 /sericin nanocomposites (ZrSS NCs) within the membrane matrix. Optimization results show that the 3ZrSS membrane exhibits the highest water flux of 337.21 LMH and oil rejection of 99.80%. There are 67.58% and 11.04% improvements compared to the pristine PAN (polyacrylonitrile) membrane. Under alkaline pH, high salt ion (NaCl) strength, and low heavy metal ion (Ba 2+ ) concentration, the 3ZrSS membrane experienced the least fouling (22.68% water flux decline). XDLVO theory elucidates that, under such conditions, there is a strong repulsive U TOT (total interaction force) between oil droplets and the 3ZrSS membrane, which is demonstrated via the strong repulsive EL (electrostatic double layer) force. The 3ZrSS membrane maintained 84.84% of its initial water flux after a 72 h long-term filtration. After four cycled filtration, the 3ZrSS membrane kept an extremely high FRR (flux recovery rate) of 98.83%. This study is anticipated to offer technical, theoretical, and practical insights for the on-demand PW treatment.
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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 | 0.000 | 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 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".