A Versatile Route for Synthesis of Metal Nanoalloys by Discharges at the Interface of Two Immiscible Liquids
Bibliographic record
Abstract
Discharge in liquid is a promising technique to produce nanomaterials by electrode erosion. Although its feasibility was demonstrated in many conditions, the production of nanoalloys by in-liquid discharges remains a challenge. Here, we show that spark discharge in liquid cyclohexane that is in contact with conductive solution, made of a combination of Ni-nitrate and/or Fe-nitrate and/or Co-nitrate, is suitable to produce nanoalloys (<10 nm) of Ni-Fe, Ni-Co, Co-Fe, and Ni-Co-Fe. The nanoparticles are synthesized by the reduction of metal ions during discharge, and they are individually embedded in C-matrix; this latter originates from the decomposition of cyclohexane. The results open novel ways to produce a wide spectrum of nanoalloys; they are needed for many applications, such as in catalysis, plasmonic, and energy conversion.
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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 | 0.001 |
| 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".