Compressive behaviour of thin porous layers with application to PEM fuel cells
Bibliographic record
Abstract
A key factor in Polymer Electrolyte Membrane (PEM) fuel cell performance is the compression due to expansion, swelling, and force exerted by bipolar plates on Membrane Electrode Assembly (MEA) which changes the porous microstructure and transport properties of layers in MEA. During manufacturing and operation of fuel cell, MEA goes through numerous cycles of compression, temperature, and humidity, which introduce hygrothermal stresses and result in change in properties of the layers which leads to adjustment of performance. Transport properties such as thermal conductivity, electrical conductivity, and gas diffusivity are dependent on mechanical properties and microstructure of MEA layers, which necessitate the study of their mechanical properties. The focus of this work is compression of Gas Diffusion Layer (GDL) and Catalyst Layer (CL) which play important role in dictating fuel cell performance. In this thesis, mechanical properties of GDL are measured and modeled analytically. Compression tests are performed on three GDL samples (SGL 34BA, Freudenberg, TGP-H-060). The results suggest a non-linear behaviour for pressure-strain curves which is because of their porous nature. Also, using effective medium theory, a representative geometry is introduced for GDL and the mechanical deformation of the simplified geometry is found analytically and validated by experimental data. Moreover, mechanical deformation of five different CL is measured under cyclic compressive load up to 5 MPa for the first time. Results show that CL behaves elastically below 2 MPa and no plastic deformation is observed; the Young’s modulus is decreased with increase in porosity, which was expected. More than that, cyclic compression tests for higher pressures show a slight change in Young’s modulus at higher pressures (more than 2 MPa) which is because of the change in microstructure at higher pressures. A geometrical platform for CL is developed in this study and a mechanistic compression model is developed based on the simplified geometry. The model is validated by comparing with the experimental results obtained for five different CLs. Using the model, effect of compressive load on porosity and pore size distribution is studied which shows significant change in larger pores and shift in pore size distribution curves.
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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) | 0.001 | 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".