Interdisciplinary Undergraduate Laboratory for an Integrated Chemistry/Biology Program: Synthesis of Silver Nanoparticles (AgNPs)-Cellulose Composite Materials with Antimicrobial Activity
Bibliographic record
Abstract
This laboratory exercise integrates chemistry and biology concepts to give third/fourth-year undergraduate students an opportunity to apply knowledge from different subject areas to address a real-world biomedical issue such as pathogen inhibition using composite materials. It involves the preparation of a bacteria-derived cellulosic biopolymer through microbial cultivation, impregnation of the bacterial cellulose (BC) with silver nanoparticles (AgNPs), followed by the analysis of the materials and the antimicrobial properties of the biomaterial-AgNPs composites. The methods are relatively simple and use inexpensive chemicals. A Tollens type approach is adopted to produce silver nanoparticles-bacterial cellulose (AgNPs-BC) composites by the reduction of [Ag(NH 3 ) 2 ] + complex embedded in the cellulose matrix. The samples were dried by two different methods: freeze-drying or vacuum-drying. The dried AgNPs-BC films were evaluated for antimicrobial properties against a test organism, in this example, Pseudomonas aeruginosa, a Gram-negative biosafety containment level 2 (BSL 2) bacterium, using an agar diffusion test. For additional flexibility and customization, options for dividing the chemistry/biology content of this laboratory into smaller units with an emphasis on characterization techniques of nanomaterials for chemistry majors are also discussed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.012 |
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".