Fabrication of Isotope‐Enriched Nanostructures Using Ultrafast Laser Pulses under Ambient Conditions for Biomolecular Sensing
Bibliographic record
Abstract
Recent advances in the use of stable isotopes necessitate novel synthesis techniques for isotope separation and enrichment that are scalable and offer high throughput. Stable-isotope-enriched nanostructures can offer unique advantages as nanomedicines, safe tracers, and labels and are critical for applications in various industrial processes, metabolic research, and medicine. So far, there exists no method to synthesize miniature isotope-enriched materials at the nanoscale. In this study, an ultrafast Laser-induced isotope enrichment at nanoscale (LIIEN) is put forward to synthesize isotope-enriched nanostructures, eliminating the need for large equipment and expenses, thereby demonstrating a lab-scale isotope enrichment process. A significant isotope enrichment for Carbon nanostructures is observed. The isotope enrichment can be attributed to the redistribution of isotope ions in the plasma plume explained by the plasma centrifuge model. The LIIEN synthesized structures exhibit excellent Surface-Enhanced Raman Scattering (SERS) signal enhancement and reproducibility, making them potential candidates for SERS-based biomolecule sensing. This technique is an efficient method to fabricate nanosized isotope-enriched structures of characteristic properties by carefully tuning laser parameters at ambient conditions.
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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 | 0.000 | 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 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".