Characterization of mechanically synthesized AgInSe<sub>2</sub> nanostructures
Bibliographic record
Abstract
A quantum dot (QD) solar cell is an emerging field in solar cell research that uses QDs as the photovoltaic material. QDs have band gaps that are tunable across a wide range of energy levels by changing the QD size. Embedding different sized dots within the absorbing layer encourages harnessing the maximum spectrum energy. Also, other effects like a very high surface to volume ratio and quantum transport make them attractive for future devices. AgInSe2 (AIS) nanoparticles with tetragonally distorted phase have been prepared by mechanically alloying the synthesized bulk AIS powder at room temperature in a planetary ball mill under Ar in an attempt to create QDs. Nanoparticles are formed of ∼10 nm in size. These ball-milled nanoparticles contain different shapes and the Rietveld analysis of X-ray powder diffraction data reveals their detailed structural features. High resolution transmission electron microscope images also detect the presence of the tetragonal phase in ball-milled samples. Peak broadening (full width at half maximum), the main characteristic of a decrease in size, is observed. X-ray diffraction data reveals the downscaling of crystallite from 103 to 7 nm, and the tetragonally distorted structure of the system was not disturbed by milling. Differential scanning calorimetric study also reveals the phase evolution and crystallization kinetics. Bulk samples show endo melting peak at 134 and 220 °C. The cooling–crystallization complexity of the peaks signifies that crystallization from melt was heterogeneous nucleation and crystallization from multiple types of centers. Unlike this milled samples show two crystallization effects at approximately 135 and 380 °C. Optical properties investigated to find band edges suggest that it is around 1.3 eV, which is encouraging for photovoltaic applications.
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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".