Carboxymethyl Tamarind Kernel Gum /ZnO- Biocomposite: As an Antifungal and Hazardous Metal Removal Agent
Bibliographic record
Abstract
ZnO nanoparticles (ZnO NPs) were in situ mixed with carboxymethyl tamarind kernel gum to generate the new biocomposite. High-resolution transmission electron microscopy (HR-TEM), field emission scanning electron microscopy (FE-SEM), Fourier transform infrared (FTIR), x-ray diffraction analysis (XRD), and dynamic light scattering (DLS)were used to characterize the CMTKG/ZnO nanocomposites. Numerous characterizations were utilized to prove that ZnO NPs had been integrated into the biopolymer matrix. The standard size of the CMTKG/ZnO nanocomposites was developed to be greater than 32–40 nm using high-resolution transmission electron microscopy and x-ray analysis de-Scherer methods. Chromium (VI) was removed from the aqueous solution using the nanocomposite (CMTKG/ZnO) as an adsorbent. The nanocomposite reached its maximum adsorption during 80 minutes of contact time, 30 mg/L chromium (VI) concentration, 2.0 g/L adsorbent part, and 7.0 pH. Further research into the antifungal activity of CMTKG/ZnO nanocomposites against Aspergillus flavus MTCC-2799 was conducted.
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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 | 0.001 | 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) | 0.000 | 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".