Using Phospholipids To Control Interparticle Distance in SERS-Active Substrates
Bibliographic record
Abstract
Control over interparticle distance while creating effective SERS substrates is crucial to exploit an enhanced electromagnetic field. In the present study, phase behaviors of zwitterionic phospholipid 1,2-dipalmitoyl- sn -glycero-3-phosphoethanolamine (DPPE) and of a 1:1 (w/w) mixture of DPPE with DPPE analogue labeled with Rhodamine B (DPPE-RhB) were used to control optical properties of silver nanocube substrates prepared by the Langmuir monolayer technique. A more homogeneous distribution of the nanocubes was observed in the DPPE/DPPE-RhB mixture, compared to DPPE at all surface pressures due to a more fluid nature of the mixed lipid monolayer. As a result, interparticle coupling and corresponding optical properties can be effectively controlled with the DPPE/DPPE-RhB monolayer. Enhancement of the RhB Raman signal is detected and found to increase exponentially with increasing surface pressure due to the creation of an intense electromagnetic field in interparticle regions. Results of the study show that the phospholipid matrix enables effective control over the interparticle spacing in the monolayer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".