Hybrid Nanoplatforms and Silica Nano-hole Particles Intended for Enhanced Energy Modes: Light-Scattering Studies Toward Lasers Developments
Bibliographic record
Abstract
In this short review, it was communicated about the design and synthesis of optical active nanoplatforms for light scattering studies highlighting holed nanoarchitectures as main sources of potential additional resonances and enhanced phenomena. In this regard, the nanoplatforms were based on varied materials such as silicon compounds, silica, modified organosilanes, noble metals, and organic materials as well; such molecular and polymeric spacers, chromophores, etc. Thus, it was discussed how it could be recorded enhanced light-scattering signaling from hybrid nanoplatforms and nano-hole particles; from where it was produced constructive wavelengths with a consequent amplification. In this context, it was afforded to the discussion of examples of laser light-scattering properties and optical approaches already developed. In addition, it was showed new developments within nano-optics to be considered for further studies and applications. And, in this direction, it was considered the study from single nanoplatforms toward higher sized modified surfaces and 3D substrates. In this manner, it was leaded to the design of nano-optical resonators as well as nano-arrays resonators. Thus, it was evaluated varied materials to incorporate and evaluate the next generation of nano-optical platforms by controlling nano-chemistry and beyond for targeted photo-physics. The variable materials showed differences between varied modes of resonances and expected performances. Received: 4 December 2023 | Revised: 18 January 2024 | Accepted: 28 February 2024 Conflicts of Interest The author declares that he has no conflicts of interest to this work. Data Availability Statement The data that support the findings of this study are openly available and it could be provided by the corresponding author.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".