Ultra-Durable Ti<sub>3</sub>O<sub>5</sub>Mo<sub>0.2</sub>Si<sub>0.4</sub> Fuel Cell Catalyst Supports with Enhanced Conductivity
Bibliographic record
Abstract
Polymer electrolyte membrane fuel cells (PEMFCs) are a clean energy technology with potential application in automotive and station power systems. However, the high cost of Pt catalyst and long-term durability of electrode materials is a barrier that hinder market penetration. The support material greatly influences electrocatalytic activity and durability of the Pt nanoparticle catalysts. Carbon black has been the primary catalyst support in fuel cells over the last 30 years due to its high surface area and high electronic conductivity. However, carbon corrosion occurs readily during start-up/shutdown conditions. Therefore, more advanced support materials are need in order to overcome these problems. Many low-cost metal oxide materials like as TiO2, NbOx, WOx, and MoOx have high oxidative and thermal stability. As such, there has been a growing interest to exploit these materials in fuel cell catalysts layers. However, the potential benefits of adding these metal oxides to the catalyst layer are often negated by their inadequate electronic conductivity. Recently, there has been a growing interest in designing metal oxides with sufficient electrical conductivity to be a practical catalyst support. Significant attention has been paid to titanium suboxides (TixO2x−1) materials since they possess acceptable electronic conductivity. Furthermore, the addition of a dopant can further enhance electronic conductivity by creating oxygen vacancies within the lattice structure. Recently, Esfahani and co-worker have reported a process of modifying TiO2 with Mo to form Mo-doped titanium suboxide (Ti3O5-Mo). While this has been shown to be a promising fuel cell catalyst support, the support still had a sizable band gap of (2.6 eV)[1]. We have hypothesized that the introduction of the second dopant could further reduce the electronic band gap and enhance conductivity. Specifically, we have examined the use of Si as the second dopant due to its high stability and the demonstrated compatibility of silicates in fuel cell catalyst layers [2-4]. Therefore we prepared a dual-doped metal oxide support materials with a composition of Ti3O5Mo0.2Si0.4 (hereafter referred to as TOMS). The TOMS support displays a remarkably low band gap of 0.31 eV, leading to a high electronic conductivity compared to other metal oxide supports. We have prepared fuel cell catalysts by depositing Pt nanoparticles onto the TOMS support. The resultant catalysts show remarkable stability and performance, which is due to a strong metal support interaction [5]. In this presentation, I will describe how doping alters the conductivity of metal oxides. In addition, we will demonstrate the performance of Pt/TOMS systems as well as its stability under several accelerated stress test protocols. References [1] R. Alipour Moghadam Esfahani, S.K. Vankova, A.H.A. Monteverde Videla, S. Specchia, Innovative carbon-free low content Pt catalyst supported on Mo-doped titanium suboxide (Ti3O5-Mo) for stable and durable oxygen reduction reaction, Applied Catalysis B: Environmental, 201 (2017) 419-429. [2] J.I. Eastcott, E.B. Easton, Sulfonated silica-based fuel cell electrode structures for low humidity applications, Journal of Power Sources, 245 (2014) 487-494. [3] R. Alipour Moghadam Esfahani, H.M. Fruehwald, F. Afsahi, E.B. Easton, Enhancing fuel cell catalyst layer stability using a dual-function sulfonated silica-based ionomer, Applied Catalysis B: Environmental, 232 (2018) 314-321. [4] R. Alipour Moghadam Esfahani, R.B. Moghaddam, I.I. Ebralidze, E.B. Easton, A hydrothermal approach to access active and durable sulfonated silica-ceramic carbon electrodes for PEM fuel cell applications, Applied Catalysis B: Environmental, 239 (2018) 125-132. [5] R. Alipour Moghadam Esfahani, I.I. Ebralidze, S. Specchia, E.B. Easton, A fuel cell catalyst support based on doped titanium suboxides with enhanced conductivity, durability and fuel cell performance, Journal of Materials Chemistry A, 6 (2018) 14805-14815. Figure 1
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".