Investigation of Macro-Thermal Contact Resistances in the Cathode of PEM Fuel Cells
Bibliographic record
Abstract
Polymer Electrolyte Membrane (PEM) fuel cells are electrochemical energy conversion devices, and have been a main focus of study in the area of renewable energy systems in the past decade. With the potential to generate electricity with zero local greenhouse gas emissions, when fed hydrogen and oxygen from air, PEM fuel cells also have other promising advantages, such as supplying a high power to volume ratio, operating with little to no noise and being able to quickly reach steady state conditions [1]. Although the technology is promising, before PEM fuel cells can reach widespread adoption, effective thermal management must be achieved in order to reach the performance and durability levels required for commercialization. The cathode of the PEM fuel cell, which is composed of the Gas Diffusion Layer (GDL), Micro-Porous Layer (MPL), and Catalyst Layer (CL), houses various processes which affect the performance of the cell. While the inlet fuel and oxidant gases are typically heated, heat is also produced from electrochemical reactions and water phase change, resulting in temperature gradients that can affect the conditions of the cell. These exothermic reactions generate temperature gradients, which in turn affect the cell’s relative humidity levels, water saturation levels, and the cell’s reaction kinetics [2]. Pathways for effective heat conduction are vital for avoiding excessive condensation of water from cooling, or material dry-out from overheating. It is therefore crucial to have a way of measuring how effectively thermal energy can be transferred out of the CL, the region of generation, through the MPL, and finally out of the GDL, in order to have better control of parameters involved in future improvements to cell components. Present thermal conductivity models provide insight for analyzing thermal energy transfer in the through-plane and in-plane directions of the GDL, but do not consider interfacial mechanics at the micro-level caused by surface roughness, waviness, and irregularities. Therefore in order to provide a more realistic representation of the through-plane thermal conductivity of the GDL of a PEM fuel cell, a model will be developed which incorporates information regarding fibre surface morphology measured using atomic force microscopy [3], and will also incorporate polytetrafluoroethylene (PTFE), and binding materials into the thermo-mechanical analysis. The thermal resistance network will be constructed using stochastic relationships derived statistical expressions regarding the contacts in the GDL found in a previous study [2], and it will be informed with experimental data obtained via micro-computed tomography [4]. Secondly, the thermal contact resistance between the MPL and CL will be determined using a modification of Greenwood’s Rough Contact Model. The surface structures of the MPL and CL will be analyzed using a combination of scanning electron microscopy, atomic force microscopy, and micro-computed tomography, from which analysis will be conducted to determine the thermal contact resistance of the interface. A realistic thermal conductivity model representing surface features of carbon fibre at the nanoscale will be presented. The model will incorporate PTFE and binding materials in the thermal analysis, for various compressive loads and GDL sizes/types, from which preliminary results are shown in Figure 1. Also, the thermal contact resistance of the MPL|CL interface will be explored providing insight into a more realistic thermal model of the macro-thermal resistances within the cathode of the PEM fuel cell. Figure 1. Through-plane thermal conductivity with porosity for untreated GDL considering surface features of carbon fibre. References: [1] Feroldi, D., and Basualdo, M., "Description of PEM Fuel Cells System," vol. 87, pp. 49-72, 2012. [2] J. Yablecki and A. Bazylak, "Determining the effective thermal conductivity of compressed PEMFC GDLs through thermal resistance modelling," J. Power Sources, 2012. [3] Botelho, S., and Bazylak, A. (2013) “The Impact of Fibre Surface Morphology on the Effective Thermal Conductivity of a PEM Fuel Cell Gas Diffusion Layer” Electrochemical Society. San Francisco, CA, USA. Pgs: 857 – 866. [4] Challa, P. R., and Bazylak, A., 2012, "Pore space characterization of compressed PEMFC GDLs using 3D micro-computed tomography," ESFuelCell2012-91415, American Society of 31 Mechanical Engineers (ASME), 10th International Fuel Cell Science, Engineering and Technology Conference, San Diego, California, July 23-26, 2012.
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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 | 0.001 | 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".