Water Transport Characterization of Anion and Proton Exchange Membranes
Bibliographic record
Abstract
Proton exchange membrane (PEM) and anion exchange membrane (AEM) fuel cells (FCs) are the two types of fuel cell devices that electrochemically convert the chemical energy of hydrogen into electricity and heat with water as the only by-product. Due to no requirement of precious and non-renewable platinum as the catalyst material, AEMFCs have attracted great attention in recent years [1,2]. However, water balance between anode and cathode in AEMFCs is more crucial than in PEMFCs, as water not only is produced in the anode, hindering hydrogen transport to the anode catalyst layer, but also functions as reactant in the cathode. Water transport properties of AEMs is one of the key factors affecting water balance between anode and cathode [1]. Accurate measurement of AEM water transport properties is paramount for AEM design and manufacturing to improve AEMFC water management and, in turn, performance and durability. AEMFCs with recently developed PiperION AEMs have been shown to achieve good AEMFC performance [3,4]; however, there is no available study in the literature measuring its water transport properties. To the best of the authors' knowledge, there are only a few studies reporting the measurement of AEMs water diffusivity, such as Fumapem FAA-3 [5,6], Aemion [5], Tokuyama A201 [7,8] and SnowPure Excellion I-200 [9]. Even in those limited studies, interfacial transport rates were either not considered in the data analysis [6,8,9] or not given as a function of water activity [5,7,8]. In this work, the interfacial desorption rate of AEMs is determined from a liquid-vapor permeation setup by measuring the water flux through the membrane at different relative humidity (RH). To quantify the interfacial exchange rate and determine which mode of transport is dominant (bulk or interfacial), a novel approach involving three different mathematical models was used: a diffusion-dominant model, a desorption-dominant model, and a combined diffusion-desorption model. By analyzing the sensitivity of the modeling results to the individual transport process, the dominant mode was identified. The model correctly identified the limiting transport mode in Nafion membranes, and suggested that interfacial transport was also limiting in AEMs of Aemion AH1-HNN8-50-X, Fumapem FAA-3-30/50 and PiperION-A40. With the developed model, semi-empirical relationships for the water desorption rate from AEMs and Nafion membranes as functions of the water content and temperature were obtained. These relationships can be readily used in AEMFCs and PEMFCs models. References [1] K. Yassin, et al., Quantifying the critical effect of water diffusivity in anion exchange membranes for fuel cell applications, Journal of Membrane Science 608 (2020) 118206. [2] X. Luo, et al., Structure-transport relationships of poly (aryl piperidinium) anion-exchange membranes: Eeffect of anions and hydration, Journal of Membrane Science 598 (2020) 117680. [3] J. Wang, et al., Poly (aryl piperidinium) membranes and ionomers for hydroxide exchange membrane fuel cells, Nature Energy 4(5) (2019) 392-398. [4] T. Wang, et al., High-performance hydroxide exchange membrane fuel cells through optimization of relative humidity, backpressure and catalyst selection, Journal of The Electrochemical Society 166(7) (2019) F3305. [5] X. Luo, et al., Water permeation through anion exchange membranes, Journal of Power Sources 375 (2018) 442-451. [6] M. Marino, et al., Hydroxide, halide and water transport in a model anion exchange membrane, Journal of Membrane Science 464 (2014) 61-71. [7] Y. Li, et al., Measurements of water uptake and transport properties in anion-exchange membranes, International Journal of Hydrogen Energy 35 (11) (2010) 5656-5665. [8] B. Eriksson, et al., Quantifying water transport in anion exchange membrane fuel cells, International Journal of Hydrogen Energy 44 (10) (2019) 4930–4939. [9] T.D. Myles, et al., Calculation of water diffusion coefficients in an anion exchange membrane using a water permeation technique, Journal of the Electrochemical Society 158(7) (2011) B790.
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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 | 0.000 | 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 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".