Shape Control of Electrodeposited Copper Films and Nanostructures through Additive Effects
Bibliographic record
Abstract
The use of electrolyte additives to affect nanocrystallite shape and film morphology in electrodeposited copper films is presented. Linear sweep and cyclic voltammetry, atomic force microscopy (AFM), scanning electron microscopy (SEM), and X-ray diffraction (XRD) methods are employed to investigate the effects of alcohol additives and the organic additive malachite green (MG), on copper electrodeposited onto polycrystalline gold electrodes. The use of additives affects the deposition process by increasing cathodic peak potentials and decreasing corresponding peak currents. Copper films deposited from electrolyte solutions with additives show additive-specific nanostructure and crystallite morphology. Film analysis reveals a greater than five times reduction in both film roughness and grain size in the presence of even small concentrations of the additive MG. Use of MG results in the preferential electrodeposition of oriented, square pyramidal crystallites, while alcohol additives result in tetrahedral crystallite textures. These shape-controlled additive effects are supported by additive adsorption energy calculations, which indicate preferential interactions, and differential growth kinetics on different facets of the film's growing nanostructures during electrodeposition. This approach offers a new and cost-effective route to achieve shape-controlled surface nanostructure.
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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".