Controlled Synthesis of One Dimensional Nanostructured Materials and Their Applications as Catalyst Supports in Proton Exchange Membrane Fuel Cells
Bibliographic record
Abstract
Nanomaterials have attracted significant interest in the past decade due to their unique structure and properties compared to their bulk counterparts. Nanomaterials-based solutions can address challenges in various technologies such as proton exchange membrane fuel cells (PEMFCs). PEMFC is an innovative energy conversion technology to directly convert chemical energy to electrical energy by using hydrogen as fuel. However, the current PEMFC system still faces significant technological roadblocks which have to be overcome before the system can become economically viable. A major impediment to the commercialization of PEMFC is the high cost of materials and manufacturing and stability, which is primarily associated with the cost of Pt catalysts and their support in membrane electrode assembly (MEA). One approach in addressing these issues is the controlled synthesis and application of nanostructured Pt-based catalysts and their support in PEMFCs. The objective of this thesis is to synthesize and characterize various nanostructures (e.g. metal oxides and metal silicides or composites) and evaluate their performance as Pt supports used in the PEMFCs. Various advanced characterization techniques such as high resolution scanning and transmission electron microscopy, X-ray absorption spectroscopy and electrochemical characterization methods have been used to understand growth mechanism of obtained nanostructures and their roles in PEMFCs.\nWe also reported the synthesis of WSi2 and Ta5Si3 heterostructures using a low pressure chemical vapor deposition (LPCVD) method. The morphologies of these nanostructures were found to be sensitive to the concentration of reactive species and silica vapor in the CVD chamber. The results indicated that the morphology of WSi2 and Ta5Si3 nanostructures varied from nanowires, networked nanoribbons to nanosheets with the control of the oxygen concentration. A vapor solid growth mechanism based on silica sheath formation was proposed for the synthesis of these nanostructures.\nTo take advantage of unique properties of carbon nanotubes, metal oxide and metal silicides as catalyst support, a new method was developed for the synthesis of composite nanostructures. TiSi2Ox-NCNTs and TiO2-NCNTs nanocomposites were synthesized using a combination of CVD process and magnetron sputtering and their performance as catalyst supports in PEMFCs were studied. Pt nanoparticles deposited on these nanostructures showed enhanced catalytic activity compared to commercial Pt/carbon electrodes. The electronic structure of Pt on the catalyst supports was investigated using X-ray absorption spectroscopy, to obtain insight into the interaction between the catalyst supports and Pt nanoparticles.\nAs an example of well controlled synthesis of nanostructures, one-dimensional tungsten oxide nanostructures (W18O49) have been synthesized using a conventional chemical vapor deposition method (CVD). The morphology of the nanostructures such as diameter and length, were controlled during the synthesis process via sulfur doping. The dependence of morphology, composition and structure of tungsten oxides on the sulfur flow rate has been studied. Further, one step synthesis of tungsten sulfide/tungsten oxide nanocables (WS2/W18O49) have been achieved for the first time using tungsten and sulfur powder as the starting materials.\nIn summary, the research work presented in this thesis aims at contributing to the development of various novel nanostructured catalyst supports and probing the correlation between synthesis approach, fine structure, and catalytic performance of the nanostructures as well as exploring their potential applications in highly active electrocatalysts for PEMFCs.
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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 | 0.000 | 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 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".