Fabrication of MXene integrated superabsorbent polymers composites hydrogels for bacterial enrichment
Bibliographic record
Abstract
Bacterial contamination in water samples, particularly at low concentrations, poses a critical challenge for accurate and efficient water quality monitoring. Existing preconcentration techniques, such as membrane filtration, are effective but often hindered by their labor-intensive nature, reliance on specialized equipment, and limited suitability for field applications. This study introduces a novel Ti 3 C 2 , MXene/superabsorbent polymer (SAP) composite synthesized via a breathing-in/breathing-out (BI-BO) method to enhance bacterial enrichment performance. The composite’s physicochemical and structural properties were comprehensively validated through FTIR, TGA, SEM, and XRD analyses. Swelling characterization demonstrated that MXene incorporation up to 2.3 % (three BI-BO cycles) maintained the SAP’s volumetric swelling ratio (VSR eq ) at ∼111 ± 7 m 3 /m 3 , preserving its water absorption capacity. However, at 3.1 % MXene (seven BI-BO cycles), VSR eq decreased to 90 m 3 /m 3 due to particle agglomeration and increased crosslinking density, highlighting the importance of optimizing MXene content. This leads to a remarkable bacterial recovery efficiency (RE) of 96 % in a single step and achieved a cumulative enrichment factor (EF) of 10-fold over four successive enrichment cycles, significantly surpassing conventional methods. It represents a transformative solution that is robust, portable, and cost-effective for bacterial enrichment, making it particularly suitable for low-resource and remote settings.
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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".