Epitaxial growth of visible to infra-red transparent conducting In<sub>2</sub>O<sub>3</sub>nanodot dispersions and reversible charge storage as a Li-ion battery anode
Bibliographic record
Abstract
Unique bimodal distributions of single crystal epitaxially grown In2O3 nanodots on silicon are shown to have excellent IR transparency greater than 87% at IR wavelengths up to 4 μm without sacrificing transparency in the visible region. These broadband antireflective nanodot dispersions are grown using a two-step metal deposition and oxidation by molecular beam epitaxy, and backscattered diffraction confirms a dominant (111) surface orientation. We detail the growth of a bimodal size distribution that facilitates good surface coverage (80%) while allowing a significant reduction in In2O3 refractive index. This unique dispersion offers excellent surface coverage and three-dimensional volumetric expansion compared to a thin film, and a step reduction in refractive index compared to bulk active materials or randomly porous composites, to more closely match the refractive index of an electrolyte, improving transparency. The (111) surface orientation of the nanodots, when fully ripened, allows minimum lattice mismatch strain between the In2O3 and the Si surface. This helps to circumvent potential interfacial weakening caused by volume contraction due to electrochemical reduction to lithium, or expansion during lithiation. Cycling under potentiodynamic conditions shows that the transparent anode of nanodots reversibly alloys lithium with good Coulombic efficiency, buffered by co-insertion into the silicon substrate. These properties could potentially lead to further development of similarly controlled dispersions of a range of other active materials to give transparent battery electrodes or materials capable of non-destructive in situ spectroscopic characterization during charging and discharging.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".