High-entropy oxide for enhanced supercapacitors and precise electrochemical detection of dopamine at nanomolar levels
Bibliographic record
Abstract
The ability to synthesize multi-metal elements into a single-component material at the nanoscale, known as high entropy oxide (HEO) is earning great attention, especially in the field of electrocatalysis. However, the present methods for the synthesis of HEO often involve non-noble, noble, or refractory elements, which require complicated synthesis methods, making the control of shape and size highly challenging. In this regard, a class of six dissimilar elements (Co, Ni, Mn, Mo, V and Zn) with combination of non-noble and refractory elements has been formed a new type of (Co 0.5 Ni 0.5 Mn 0.5 Mo 0.5 V 0.5 Zn 0.5 )O based HEO. The multi-element interaction and carbonization network enhance ion conductivity, boosting specific capacitance to 698.4 F.g⁻¹ , far surpassing conventional metal oxides. In addition, the HEO on screen printed electrode exhibited a notable increase in the oxidation peak current for the oxidation of dopamine, which can detect dopamine at nanomolar levels.
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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".