Surface Science and Electrochemical Analysis of Nickel Foams
Bibliographic record
Abstract
Open-pore nickel (Ni) foams are characterized using surface science and electrochemical techniques. A scanning electron microscopy analysis reveals interconnected Ni struts that generate small and large pores of ca. 50 and 500 μm in size, respectively. An X-ray photoelectron spectroscopy (XPS) analysis of the surface-chemical composition of the Ni foams shows that there are oxidized and metallic sections within their surfaces despite being prepared by sintering in an oxidizing atmosphere at a high temperature and being stored in moist air. The ratio of the areas of oxidized and metallic sections is evaluated using XPS data. Chemical etching of the Ni foams results in removal of the native surface oxide/hydroxide without altering the three-dimensional structure; it also increases the roughness (R) of the surfaces of Ni struts giving rise to an increase in the electrochemically active surface area (Aecsa). Thermal treatment of Ni foams in an H2(g) atmosphere at 500 °C reduces the native surface oxide/hydroxide but does not increase R or Aecsa. Electrochemical behavior of the Ni foams is examined in 0.5 M aqueous KOH solution using cyclic-voltammetry (CV) and electrochemical impedance spectroscopy (EIS). As-received, chemically etched, thermally reduced and electro-oxidized Ni foams generate distinct CV profiles; their features are assigned to oxidized and metallic surface states. The observations made on the basis of XPS measurements are corroborated by the results of CV analyses. The application of CV and XPS or EIS allows in situ determination of Aecsa and the specific surface area (As) of the chemically etched and thermally reduced Ni foams. The values of As determined on the basis of joint CV and XPS measurements are 227 ± 74 and 149 ± 48 cm(2) g(-1) for the etched and reduced Ni foams, respectively. The values of As determined on the basis of CV, XPS and EIS measurements are 241 ± 80 and 160 ± 23 cm g(-1) for the etched and reduced Ni foams, respectively.
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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 | 0.001 | 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) | 0.001 | 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".