Nanoparticle Surface Specific Adsorption of Zein and Its Self-assembled Behavior of Nanocubes Formation in Relation to On–Off SERS: Understanding Morphology Control of Protein Aggregates
Bibliographic record
Abstract
Zein, an industrially important protein, is characterized in terms of its food and pharmaceutical coating applications by using surface enhanced Raman spectroscopy (SERS) on Au, Ag, and PbS nanoparticles (NPs). Its specific surface adsorption behavior on Ag NPs produced self-assembled zein nanocubes which demonstrated on and off SERS activity. Both SERS characterization as well as nanocube formation of zein helped us to understand the complex protein aggregation behavior in shape controlled morphologies, a process with significant ramifications in protein crystallization to achieve ordered morphologies. Interestingly, nanocube formation was promoted in the presence of Ag rather than Au or PbS NPs under in situ synthesis and discussed in terms of specific adsorption. Zein fingerprinting was much more clear and enhanced on Au surface in comparison to Ag while PbS did not demonstrate SERS due to its semiconducting nature.
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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) | 0.000 | 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 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".