Ir-Ni based mono and bimetallic nanocrystals: synthesis, characterization and effect of cationic, anionic, and non-ionic stabilizers
Bibliographic record
Abstract
Nickel based bimetallic nanocrystals, iridium-nickel play an imperative role in catalysis, electrocatalysis, and magnetic applications. In the present work Ir-Ni bimetallic nanoalloys were synthesized by modified polyol reduction method with different cationic, anionic, and non-ionic surface active agents like CTAB, SDS, TSC, and PVP. The non-ionic surface active agent PVP produced a better effect on nanoparticle size than cationic and anionic surfactants. The synthesized bimetallic nanocrystals were characterized by UV-Vis, XRD, FTIR, FESEM, and HRTEM techniques. XRD and FTIR verify the nature of synthesized bimetallic nanocrystals and the interaction between stabilizers and nanoparticles. HRTEM studies reveal that the PVP stabilized Ir-Ni (3:1) and Ir-Ni (1:1) bimetallic nanocrystals are small in size and less dispersed. Particle size range of these nanoparticles is from (1.77-2.36) nm. FESEM images show that nanoparticles are in quasi spherical shape. EDX analysis indicates that the resultant particles are core shell structure with Ni core and Ir shell.
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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) | 0.000 | 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) | 0.000 | 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".