Synthesis of Copper Complex and 2D Zinc-Organic Framework with Enhanced Disinfection Properties
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Bibliographic record
Abstract
The growing threat of bacterial contamination, especially by multidrug-resistant bacterial strains, requires the development of effective antibacterial agents. In the present study, we report the synthesis and photocatalytic antibacterial study of two coordination materials, including a copper complex ( Cu-DATiNA ) and a two-dimensional (2D) zinc-organic framework ( Zn-DATBDC ), both driven by unique diaminotriazine-carboxylic acid-based ligands. Experimental and computational analyses confirm the distinctive crystal structures as well as the semiconducting properties of Cu-DATiNA and the highly porous 2D architecture of Zn-DATBDC . Both prepared materials exhibit potent antibacterial activity, particularly under irradiation with low-power LED (light-emitting diode) light. Cu-DATiNA demonstrates a photocatalytic antibacterial performance, achieving more than 99% inactivation of Escherichia coli ( E. coli ) and Staphylococcus epidermidis ( S. epidermidis ) in 90 and 60 min, respectively. Zn-DATBDC exhibits equally potent antibacterial activity against both E. coli and S. epidermidis, with contact times of 90 and 120 min, attributed to its distinctive 2D structure. Further optical characterizations, combined with photodegradation tests, demonstrate the photocatalytic capability of Cu-DATiNA for organic dye degradation and antibacterial activity, arising from its semiconducting nature and visible-light absorption. In contrast, Zn-DATBDC primarily provides a layered structure for photodegradation and antibacterial activities due to its 2D-layered architecture. This work highlights how structural conception and characterization elucidate the mechanisms of antibacterial activity and the photocatalytic performance of metalloorganic materials. It provides critical design principles for developing innovative, effective antibacterial agents to address biological threats.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it