Size‐Tunable Photothermal Germanium Nanocrystals
Bibliographic record
Abstract
Abstract Germanium nanocrystals (ncGe) have not received as much attention as silicon nanocrystals (ncSi). However, Ge has demonstrated superiority over Si nanomaterials in some applications. Examples include, high charge–discharge rate lithium‐ion batteries,[1] small band‐gap opto‐electronic devices,[2] and photo‐therapeutics.[3] When stabilized in an oxide matrix (ncGe/GeOx), its high charge‐retention has enabled non‐volatile memories.[4] It has also found utility as a high‐capacity anode material for Li‐ion batteries with impressive stability.[5] Herein, we report an organic‐free synthesis of size‐controlled ncGe in a GeOx matrix as well as freestanding ncGe, via the thermal disproportionation of GeO prepared from thermally induced dehydration of Ge(OH)2. The photothermal effect of ncGe, quantified by Raman spectroscopy, is found to be size dependent and superior to ncSi. This advance suggests applications of ncGe in photothermal therapy, desalination, and catalysis.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".