Smartphone-Aided Colorimetric Assay: Enhanced Peroxidase Mimicking Activity of Quasi Cube-Like 2D-Co-MOF/CN Label-Free Nanozyme for Selective/Visual Recognition of 4,4′-(propane-2,2-diyl)diphenol
Bibliographic record
Abstract
To ensure environmental safety, it is essential to monitor bisphenol A (BPA), as it poses health hazards. In this study, we report a novel, sustainable binary 2D Co-MOF/CN nanozyme that functions as a bipurpose material with both peroxidase-mimic activity and BPA-specific detection capability. The Co 2+ sites and sp 2 hybridized carbon demonstrate remarkable Fenton-like reactions, effectively promoting the transformation of 4,4′-diamino-3,3′,5,5′-tetramethylbiphenyl (TMB) into oxidized TMB. The Co 2+ sites in the binary 2D-Co-MOF/CN facilitate the capture of BPA via cobalt–O–H bonding and electrostatic interactions, hence restricting the transfer of e – between 2D-Co-MOF/CN and hydrogen peroxide. Thus, TMB oxidation diminishes and alters the color from a strong blue to pale color, allowing for a visual detection of BPA. A robust linear association has been established between the BPA concentration and the absorbance intensity (λ abs = 652 nm), with a detection limit of 2.1 nM. These limitations are far lower than the European Commission Environment (ECE) criteria. The system was further integrated into a smartphone-assisted platform using RGB color analysis for real-time on-site BPA monitoring. This demonstrated an efficient selectivity and efficacy with actual water samples. This research introduces a novel colorimetric and smartphone-adaptable innovative sensing platform for the visual detection of BPA using a multifunctional nanozyme. The multifunctional nanozyme not only enhances detection performance but also supports portable, green, and cost-effective monitoring strategies for practical environmental applications.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".