Electrodeposited Gold Nanoparticles on a Screen-Printed Carbon Electrode Exhibit Distinct Electrochemical and Catalytic Properties Compared to Drop-Cast Gold Nanoparticles
Bibliographic record
Abstract
The utilization of Au nanoparticles (AuNPs) for electrode fabrication often relies on the drop-casting of the chemically synthesized AuNP or electrochemically reducing Au 3+ directly onto a carbon electrode support. Such AuNP-functionalized electrodes have been extensively and ubiquitously used for various applications, including sensing and catalysis. However, there is no systematic study focusing on comprehensively evaluating the two types of electrode surfaces (drop-cast AuNPs vs electrochemically deposited eAuNPs) in terms of their electrochemical properties and electrocatalytic activity. In this study, we modified the screen-printed carbon electrodes (SPEs) to fabricate two distinct electrode surfaces, AuNP/SPE and eAuNP/SPE, for the extensive comparison of their electrochemical and catalytic properties. Specifically, both electrodes were characterized in acidic and basic electrolytes by cyclic voltammetry (CV) and exhibited similar electroactive surface area (ECSA), surface roughness, and AuO layer coverage, as well as spherical morphologies with different particle sizes. CV and electrochemical impedance spectroscopy (EIS) uncovered the complex nature of the surfaces. The AuNP/SPE surface was heterogeneous, deviated from the linearity expected for potential vs square-root of scan rates, and exhibited lower current, slower diffusion, and smaller observed rates of electron transfer related to the solution redox probe, ferri/ferrocyanide. Notably, the significant differences in electrochemical properties of AuNP/SPE and eAuNP/SPE electrodes resulted in stark variances in their electrocatalytic activities as oxidase-mimics with glucose as a substrate. Higher anodic onset potential was required for glucose oxidation with AuNP/SPE, which also resulted in lower current and lower activity. Altogether, we identified specific electrochemical properties, such as surface heterogeneity and electron transfer, as the dominant determinants of the electrocatalytic activities of (e)AuNP-functionalized carbon electrodes. The unique surface properties observed for often interchangeably used electrodes explain the differential catalytic activities, which may be transferrable to other surfaces and substrates.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".