Nanocrystal-sensitized triplet-fusion upconversion photochemistry
Why this work is in the frame
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Bibliographic record
Abstract
The ability to efficiently up-convert broadband, low-intensity light would be an enabling technology for background-free biomedical imaging, volumetric 3D printing, and sensitizing silicon focal plane arrays to the short-wave infrared. Our approach uses colloidal quantum dots—size-tunable spin-mixing fluorophores—to absorb low-energy photons and sensitize the spin-triplet excitonic states of nearby conjugated molecules. Once there, pairs of these long-lived excitations can combine via triplet fusion (triplet-triplet annihilation) to generate shorter-wavelength fluorescence. I will discuss our ongoing efforts to harness our recent advances in the synthesis of ultra-small PbS quantum dots (d~1.7 nm, hν_peak,abs=2.2eV) to sensitize ‘red-to-blue’ triplet-fusion upconversion in solution. We show that the long (>µs) photoluminescence lifetimes of these particles enable max-efficiency upconversion at modest light intensities (I_th=220 mW/cm2), overcoming a mildly endothermic sensitization scheme that maximizes the anti-Stokes shift (1.04 eV). This architecture facilitates the photo-initiated polymerization of methylmethacrylate using only long-wavelength light (λ: 637 nm); a demonstration of nanocrystal-sensitized upconversion photochemistry. Finally, from the quasi-equilibrium dynamics of triplet energy transfer, we infer that the chemical potential of photoexcited, ultra-small PbS quantum dots is surprisingly high—completing an advantageous suite of properties for upconversion photochemistry, but reinforcing questions regarding the emissive state.
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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) | 0.012 | 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 it