Amorphous Quantum Nanomaterials
Bibliographic record
Abstract
In quantum materials, macroscopic behavior is governed in nontrivial ways by quantum phenomena. This is usually achieved by exquisite control over atomic positions in crystalline solids. Here, it is demonstrated that the use of disordered glassy materials provides unique opportunities to tailor quantum material properties. By borrowing ideas from single-molecule spectroscopy, single delocalized π-electron dye systems are isolated in relatively rigid ultrasmall (<10 nm diameter) amorphous silica nanoparticles. It is demonstrated that chemically tuning the local amorphous silica environment around the dye over a range of compositions enables exquisite control over dye quantum behavior, leading to efficient probes for photodynamic therapy (PDT) and stochastic optical reconstruction microscopy (STORM). The results suggest that efficient fine-tuning of light-induced quantum behavior mediated via effects like spin-orbit coupling can be effectively achieved by systematically varying averaged local environments in glassy amorphous materials as opposed to tailoring well-defined neighboring atomic lattice positions in crystalline solids. The resulting nanoprobes exhibit features proven to enable clinical translation.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".