Low‐dose Ir‐doped TiO <sub>2</sub> supported Pt‐Co bimetallic nanoparticles: A highly active and CO‐tolerant electrocatalyst towards methanol oxidation reaction
Bibliographic record
Abstract
Highly stable and cost-effective electrocatalysts are of importance in regulating energy conversion efficiency and commercial feasibility of direct methanol fuel cells (DMFCs). So far, integrating transition metals into Pt-based catalysts to enhance their catalytic performances for methanol electro-oxidation reaction (MOR) at the anode of DMFCs has received significant interest. This study witnessed the first time of depositing Pt3Co1 alloy nanoparticles (NPs) on robust Ti0.9Ir0.1O2 supports utilizing a modified reduction method that used NaBH4 as a reducing agent in the absence of surfactants or stabilizers. This novel combination not only reduces the usage of costly and easily-deactivated Pt but also significantly improves catalytic activity and poisoning tolerance for MOR. Regarding electrocatalytic performance, the onset potential and the mass activity of the Pt3Co1/Ti0.9Ir0.1O2 catalyst are ~0.1 V vs NHE and 316.16 mA/mgPt, respectively, which are 4.5-fold lower and 1.5-fold higher than the corresponding figures for the commercial Pt/C (E-TEK) catalyst, ~0.45 vs NHE and 206.83 mA/mgPt, indicating superior catalytic activity and CO-tolerance of the former over the latter. Furthermore, the superior anti-poisoning ability and stability of the Pt3Co1/Ti0.9Ir0.1O2 catalyst are demonstrated by its 2.2-fold higher If/Ib ratio in MOR and lower degradation rate in the 60-min chronoamperometry (CA) and 3000-cycle scanning tests than the Pt/C counterpart. These enhancements could be abscribed to synergistic influence between the Pt-Co alloy NPs and the robust Ti0.9Ir0.1O2 support. The addition of Co into the catalyst to promote removal of Pt-poisoning species as well as the use of highly corrosion-resistant Ir-doped TiO2 as a catalyst support play a decisive role in boosting electrochemical behaviors of the Pt3Co1/ Ti0.9Ir0.1O2 catalyst. Generally, the success of this work in synthesizing high-performance Pt3Co1/Ti0.9Ir0.1O2 catalyst could serve as groundwork for further development of TiO2-based material supported bimetallic catalysts for applications in the electrochemical catalysis field.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".