Designing, modeling and performance investigation

i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y x x x ( 2 0 1 7 ) 1 e1 3

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Designing, modeling and performance investigation of bio-inspired flow field based DMFCs Adnan Ozden a, Mustafa Ercelik b, David Ouellette c, C. Ozgur Colpan b,c,*, Hadi Ganjehsarabi d, Feridun Hamdullahpur a a

Department of Mechanical and Mechatronics Engineering, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada b Dokuz Eylul University, The Graduate School of Natural and Applied Sciences, Mechanical Engineering Department, Tinaztepe Campus, 35397, Buca, Izmir, Turkey c Dokuz Eylul University, Faculty of Engineering, Mechanical Engineering Department, Tinaztepe, Buca, Izmir, 35397, Turkey d Erzincan University, Department of Mechanical Engineering, Faculty of Engineering, Erzincan, Turkey

article info

abstract

Article history:

In an attempt to improve upon conventional flow fields (e.g., serpentine flow field), Murray's

Received 15 September 2016

Law was applied to design two different bio-inspired, leaf-shaped flow fields. This law

Received in revised form

governs the dimensions of natural networks, such as: the veins within plant leaves and

29 December 2016

human lungs. In this study, the serpentine, the lung, and the two leaf-shaped flow fields

Accepted 3 January 2017

were used to form seven different anodeecathode combinations. The experiments focused

Available online xxx

on the effects of methanol concentration (0.50 M, 0.75 M, and 1.00 M) and the combined effect of methanol and oxygen flow rates (1.3 ml/min methanol and 400 ml/min oxygen, as

Keywords:

well as 2 and 3 times both of these flow rates). An analytical model was also developed to

Direct methanol fuel cells

help understand the experimental results. The results show that the highest performance

Bio-inspired flow field configuration

could be achieved when the bio-inspired configurations were used on the cathode. The best

Flow field design

configuration was the serpentine (anode) e second leaf design (cathode), with a peak power

Murray's Law

density of 888 W/m2. For comparison, a peak power density of 824 W/m2 was achieved

Experimental

when the serpentine flow field was used on the anode and cathode. Furthermore, of all the tested configurations, the lung-based flow field provided the lowest performance in all tests. © 2017 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

Introduction Currently, the demand for energy is on the rise, which unfortunately leads to concerns, such as: over-consumption of

available energy sources, which also leads to fossil fuel depletion, and air pollution and climate change. To help circumvent this issue, alternative energy technologies have been examined. One of these technologies is fuel cell technology, which efficiently converts the chemical energy of a

* Corresponding author. Dokuz Eylul University, Faculty of Engineering, Mechanical Engineering Department, Tinaztepe, Buca, Izmir, 35397, Turkey. E-mail address: [email protected] (C.O. Colpan). http://dx.doi.org/10.1016/j.ijhydene.2017.01.007 0360-3199/© 2017 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved. Please cite this article in press as: Ozden A, et al., Designing, modeling and performance investigation of bio-inspired flow field based DMFCs, International Journal of Hydrogen Energy (2017), http://dx.doi.org/10.1016/j.ijhydene.2017.01.007

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fuel and oxidant into electricity, with low overall emissions [1,2]. A promising fuel cell type is the direct methanol fuel cell (DMFC), which has recently garnered considerable attention due to its large number of potential applications, such as: backup power for recreational activities, portable chargers, and range extender for vehicles [3,4]. In spite of the fact that DMFCs offer some important advantages, there are still some barriers that prevent the largescale commercialization of DMFCs; these include effects, such as: the sluggish electrochemical reaction kinetics on both the anode and cathode, undesired methanol crossover from the anode to cathode, low durability and stability, cathode water flooding, and high material costs due to using precious metal catalysts [5e8]. Over the last decade, improvements have been made in the development of novel designs, materials, and manufacturing techniques for the major components of DMFCs, to circumvent the abovementioned constraints. Among these components, the anode and cathode flow fields (AFF and CFF, respectively) play an important role, as they can help mitigate each of the previously mentioned issues, by providing uniform reactant distributions, efficient by-product removal, and minimal and stable pressure drops across the inlet and outlet. These effects allow for uniform current distributions that would otherwise cause local temperature variations on the membrane electrode assembly (MEA), leading to decreased durability. In addition, they allow for the efficient use of catalyst material, within the anode and cathode catalyst layers, thus providing decreased material costs. As such, the AFFs and CFFs are commonly considered to be performance-limiting components [9e12]. Until now, conventional flow fields, such as the serpentine and parallel flow fields, have been primarily used for the AFF and CFF configurations [13e16]. Some literature studies (e.g., [11,17]) have indicated that the serpentine flow field possesses a more stable and improved performance due to its enhanced mass transfer and reactant distribution capabilities across the flow channels. These superior properties are mainly linked to the pressure difference between the two consecutive channels, leading to under-rib convection. This contributes to the enhanced reactant distributions, even underneath the channels' ribs [18], which mitigates the performance deteriorations caused by mass-transport limitations [19]. However, the serpentine flow field has several drawbacks, which include: the localized flooding at the channel bends and inlet and outlet, and a significant pressure drop between the inlet and outlet [13,19e21]. In addition to the serpentine flow field, the parallel flow field has gained attention due to its ability to transport reactants through the entire flow field with negligible pressure drops. Some studies have been conducted to compare the performance of these two conventional flow field designs (serpentine and parallel) [22e25]. For instance, Hwang et al. [23] investigated the effect of the AFF on the performance of a single DMFC and found that the serpentine design provides better performance, compared to the parallel design. This was found to be due to: i) large inactive areas under the rib portion of the design; ii) blockage of the channels with the accumulation of the water droplets; and iii) maldistribution of the reactants within the flow channels.

An alternative approach for developing an appropriate flow field design is to use patterns from natural networks (e.g., leaf vein system and blood vessels of human lungs, as shown in Fig. 1) due to their significant potential to efficiently and homogeneously transport fluids [26,27]. An analogy between the natural structures and the flow field designs could be made, in reference to both function and structure. Therefore, these natural structures could be applied to the flow field design of bipolar plates. Many researchers hold the opinion that bioinspired flow fields have a tremendous potential for distributing the reactants efficiently and for improving the performance of the fuel cells. There are some research studies which have been conducted to investigate the effects of bioinspired flow field designs on the fuel cell performance. For instance, Refs. [21,27e29] investigated the effects of different bio-inspired designs on the performance of proton exchange membrane fuel cells (PEMFCs), and their investigation demonstrated that bio-inspired designs provide uniform reactant concentrations in the diffusion layer as compared to the conventional serpentine flow field design. Furthermore, the fuel cell's performance with the bio-inspired flow field was found to be more promising than that with the conventional flow field design, due to the more uniform pressure and velocity distribution within the flow channels, and more homogeneous diffusion of the reactants into the electrochemical reaction region (ERR). An approach to design a bio-inspired flow field is to use Murray's Law, which relates the dimensions of the parent channel to the dimensions of the daughter channels [30,31]. This approach has been applied to microfluidic devices [32,33] and fuel cells [34,35]. In fuel cell literature, Guo et al. [36] developed a series of flow field designs inspired by the venation structure of a tree leaf and used Murray's Law to determine the relationships between the channel dimensions in their bio-inspired flow field designs. Arvay et al. [35] designed some bio-inspired flow field configurations using Murray's Law, and their aim for using Murray's Law was to design a flow channel configuration, which could keep the gas distribution over the reaction area in balance and optimize the pressure drop inside the flow channels. The results of their investigation revealed that it is possible to distribute the reactants more effectively with negligible pressure drop by employing the nature-inspired flow field designs. Zografos et al. [37] used Murray's Law to predict the optimum ratio between the diameters of the parent and daughter vessels in networks with circular cross section; in consequence, they proposed an improved design. The objective of this study is to determine the effects that the bio-inspired and conventional (serpentine) flow field has on the performance of the DMFC, by comparing the performance of the DMFC with different anode and cathode bioinspired and conventional flow field configurations. For this purpose, as seen from Fig. 2(a) and (b), two new bio-inspired leaf flow field configurations were designed using Murray's Law, whereas the bio-inspired lung flow field configuration (Fig. 2(c)) was designed inspiring from the study conducted by Kloess et al. [21]. The serpentine design (Fig. 2(d)) is used as a reference, since it is a conventional flow field design. From these flow fields, seven different anodeecathode combinations

Please cite this article in press as: Ozden A, et al., Designing, modeling and performance investigation of bio-inspired flow field based DMFCs, International Journal of Hydrogen Energy (2017), http://dx.doi.org/10.1016/j.ijhydene.2017.01.007


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Fig. 1 e Examples of natural networks: (a) leaf vein system and (b) human lung system. (Table 1) were determined and a set of experiments were conducted to evaluate their performance. In each of the tests, a constant operating temperature of 70 C was used. The methanol concentrations were varied from 0.50 M, 0.75 M, and 1.00 M. In other cases, different flow rates of oxygen and methanol were examined, at a constant methanol concentration of 1.00 M. To understand the internal transport processes and the differences in performance between each flow field arrangement, a simple analytical model was developed.

sum of the cubes of the hydraulic diameters of the daughter channels [30,32]. d3p ¼

In this study, Murray's Law was used to calculate the required channel diameters for the first and second bio-inspired leaf flow fields, as given by Eq. (1) [30]. This law reveals that when a parent channel branches into daughter channels, the cube of the hydraulic diameter of the parent channel is equal to the

d3di

(1)

where dp and ddi are the hydraulic diameters of the parent channel and ith daughter channel, respectively. The hydraulic diameters of the daughter channels, which are rectangular in cross-section, were calculated using Eq. (2). dd ¼

Bio-inspired flow field design and manufacturing

X

4Ac 2$W$D ¼ WþD P

(2)

here, Ac is the channel's cross-sectional area, P is the perimeter, W is the width, and D is the depth of the daughter channel. The daughter channels within the leaf shaped flow fields (configurations 1 and 2 shown in Fig. 3(a) and (b)) were considered to have the same width in order to maintain a uniform velocity distribution within the channel. Therefore, Eq. (1) can be rearranged to form Eq. (3), which is used to calculate the hydraulic diameter of the parent channel. d3p ¼ 2d3d1 þ d3d3

(3)

To determine the width of each channel, the daughter channels were kept constant, whereas the parent channel's dimensions were calculated using Eqs. (2) and (3). Configurations 1 and 2 had daughter channel widths of 0.75 mm and 0.65 mm, respectively, whereas the depths of all channels were kept constant at 1 mm. The designed flow field plates were composed of graphite (SG-3215) and manufactured using the Selective Laser Sintering (SLS) process. Photographs of each of the manufactured flow field plates are shown in Fig. 3.

Experimental

Fig. 2 e (a) The first bio-inspired leaf flow field configuration, (b) the second bio-inspired leaf flow field configuration, (c) the bio-inspired lung flow field configuration, and (d) the serpentine flow field configuration.

To investigate the performance differences of the AFFs and CFFs separately, seven different anodeecathode combinations were examined as summarized in Table 1. A commercially available MEA (Alfa Aesar® 45364) was used in this study, which was composed of a Nafion® 115 membrane, with an anode Pt-Ru catalyst loading of 4 mg/cm2, and cathode Pt catalyst loading of 2 mg/cm2. The active area of the MEA is 25 cm2. The cell was sealed with two 0.1 mm Teflon gaskets and a torque of 2.6 N m was applied to tighten the bolts. This approach maintained the fuel cell's compression ratio within 20 ± 5% [38]. The polarization curves were


4


Table 1 e Summary of the anodeecathode channel configurations considered in this study. Combination number 1 2 3 4 5 6 7

Anode

Cathode

Abbreviated name

Serpentine Serpentine Serpentine First bio-inspired leaf Second bio-inspired leaf Bio-inspired lung Serpentine

First bio-inspired leaf Second bio-inspired leaf Bio-inspired lung Serpentine Serpentine Serpentine Serpentine

S-L1 S-L2 S-LG L1-S L2-S LG-S S-S

Fig. 3 e The photographs of the manufactured flow field plates with (a) the first bio-inspired leaf configuration, (b) the second bio-inspired leaf configuration, (c) the bio-inspired lung configuration, and (d) the serpentine configuration.

obtained using a computer aided test station, the details of which are given in a previous study [39]. After assembly, the MEA was hydrated by setting the cell temperature to 70 C (using two heating pads and a PID controller) and by supplying deionized water to the anode and humidified oxygen to the cathode, at a flow rate of 5 ml/min and 1000 ml/min, respectively for at least 24 h. Afterwards, the anode was supplied with methanol, with a concentration dictated by the test of interest, whereas the cathode was supplied with humidified oxygen at a back pressure of 1.35 bar absolute. The anode and cathode flow rates were altered according to the test of interest. The polarization curves were measured potentiostatically from open circuit voltage (OCV) to 0.20 V, with 0.05 V increments. The current density was measured once a steady value was obtained, which typically required 4 min to 5 min. Each polarization curve is the average of 4 repeated measurements.

Computational model To help understand the experimental results, a simplified 1D analytical model was developed. The cell voltage, Vcell, was calculated by subtracting the anode and cathode activation polarizations and the Ohmic polarization from the reversible cell voltage, Vrev, as shown below. Vcell ¼ Vrev ha hc iR

(4)

where, h is the activation polarization of the anode (a) and cathode (c), i is the current density and R is the overall Ohmic resistance of the cell. The reversible cell voltage is assumed to be sole function of temperature. The anodic and cathodic activation polarizations are estimated from the non-Tafel (anode) and Tafel (cathode) kinetics, as shown below [40].

# " i$CM RT l;ACL ln ha ¼ aa F ia;ref $CM l;ACL i$Ka

(5)

" !# 2 COg;ref RT i þ ixover ln hc ¼ $ O2 ac F ic;ref Cg;CCL

(6)

here, R is the universal gas constant, T is the cell temperature, F is the Faraday constant, Ka is the methanol oxidation reaction constant, ixover is the crossover current density, and iref is the reference exchange current density. The methanol and oxygen concentrations are measured at the catalyst layer (CL) surface, with the subscript ref referring to the reference concentration at which the reference exchange current density is measured [41,42]. To determine the methanol and oxygen concentrations within their respective CL, a mass balance is performed around the respective flow field and a mass transfer coefficient is applied to determine the reactant's surface concentration at the channel e backing layer (BL) interface. The reactant concentration within the flow field is assumed to be the arithmetic average of the inlet and outlet concentrations [43]. Considering that the species transport is primarily diffusion-driven within the BLs, the methanol and oxygen concentrations at their respective CL surfaces take the form shown below. M CM l;ACL ¼ Cl;inlet

ilim;a i M ilim;a þ 6FuM xover Cl;inlet

i þ ixover 2 2 COg;CCL ¼ COg;inlet 1 ilim;c

! (7)

(8)

here, ilim refers to the limiting current density, uM xover is the methanol crossover velocity, and the subscript inlet refers to the inlet concentration. The crossover current density, ixover,


5


was assumed to be composed of a diffusive, convective and electro-osmotic component, each of which was referenced to the methanol concentration at the anode CL (ACL). This is given by Eq. (9), where the terms within the square brackets represent uM xover from Eq. (7). Here, D is the diffusion coefficient, tmem is the thickness of the membrane, K is the absolute permeability of the membrane, ml is the dynamic viscosity, DP is the pressure difference between the anode and cathode compartments, and ndH2 O is the coefficient of electro-osmotic drag (EOD). # nH2 O i DM K DP e þ þ dH2 O tMem ml tMem Cl F

" ixover ¼ 6FCM l;ACL

(9)

The anode and cathode limiting current densities were estimated in the same manner as Eqs. (10) and (11), for the case, where the corresponding reactant concentration at the CL is zero. The final form is shown below. Here, A is the MEA's active area, Q_ is the inlet volumetric flow rate, d is the channel's open area ratio, and h is the channel's mass transfer coefficient, which is used as a calibration factor. The methanol and oxygen diffusivities are corrected using the Bruggeman correlation [40]. " ilim;a ¼ 6FCM l;inlet

tABL M;eff

Dl;ABL "

2 ilim;c ¼ 4FCOg;inlet

tCBL O ;eff

2 Dg;CBL

þ

A 1 þ 2Q_ AFF dAFF hM AFF

A 1 þ þ 2Q_ CFF dCFF hO2

(10) #1 (11)

Since the anode and cathode operate with different fluids, the flow field's mass transfer coefficient will be different depending on which side of the fuel cell the flow field is used. To account for this effect, each of the mass transfer coefficients was scaled by setting the methanol and oxygen Sherwood Numbers equal to each other, as shown below. Here, Sc and Pr are the Schmidt and Prandtl Numbers, respectively [44]. (12)

The Ohmic resistance is considered to be composed of the contact resistance and the ionic resistance within the electrolyte phase of the membrane and the CLs. The scaling factor, bU, accounts for the change in rib area in contact with the BLs of each flow field configuration, relative to the serpentineeserpentine (anodeecathode) flow field configuration. In the flow fields considered in this work, bU ranged from 1 to ~1.05. The contact resistance, Rcontact, is taken as a calibration parameter. " # 1 tACL tCCL tMem þ 1:5 þ 1:5 R ¼ Rcontact bU þ se εe;ACL εe;CCL

exp: points

cell;exp

cell;model

Within the model, the fuel cell's contact resistance, Rcontact , and the cathode mass transfer coefficients for each of the flow fields, h, were considered to be the calibration factors. The corresponding anode mass transfer coefficients were corrected using Eq. (12). The converged values for each calibration parameter are summarized in Table 2. The thermophysical properties were obtained from tabulated data within Refs. [45,46], whereas the remaining parameters (i.e., diffusion coefficients and correlations for electro-osmotic drag) can be found in Ouellette [40]. The geometry and porous properties of each layer within the MEA is summarized in Table 3. All electrochemical properties can be obtained from Garcı´a-Salaberri et al.'s study [47], with the exception of the reference oxygen concentration which was considered to be pure oxygen at the cathode inlet conditions.

#1

CFF

2 DOg 2 ScO2 PrM hOCFF ¼ M $ M $ O2 M hAFF Dl Sc Pr

found to provide better parameter estimation at high and low current densities. 2 3 2 2 6 X Vcell;exp Vcell;model 7 7 (14) Q ¼ min6 5 4 ;V min V

(13)

The model is calibrated using a constrained genetic algorithm with a convergence criterion set to 106. The objective of this optimization procedure was to minimize the squared difference between the experimental and modeled cell voltages, divided by the smaller of the two local cell voltages. This equation was summed over each experimental data point to form the objective function shown below. This function was

Results and discussion In this section, the analytical and experimental results are discussed for the case of different AFF and CFF configurations, as summarized in Table 1. The discussions focus on the influence that the inlet methanol concentration and the anode and cathode flow rates have on the DMFC performance.

Effect of methanol concentration Since it is well known in the DMFC community that the fuel cell's performance is strongly correlated with the supplied methanol concentration [48e50], this section is therefore devoted to the investigation of this influence on the presented flow field configurations. The analytical and experimental results for each AFF and CFF configuration are presented in Sections Different anode flow field configurations and Different cathode flow field configurations, respectively. All of these experiments were conducted under the same operating conditions: a cell temperature of 70 C, a methanol and oxygen flow rate of 3.9 ml/min and 1200 ml/min, respectively, and a varied methanol concentration (0.50 M, 0.75 M, or 1.00 M).

Table 2 e Summary of the calibrated values for the fuel cell's contact resistance and cathode mass transfer coefficients. Variable

Value

Cathode mass transfer coefficients 7.178 hleaf1 27.73 hleaf2 hlung 3.549 10.00 hserp Contact resistance 10 Rcontact

Unit mm/s mm/s mm/s mm/s mU cm2


6


Table 3 e Summary of the thicknesses and porous properties of each component within the MEA. Parameter Thickness ABL and CBL Membrane ACL and CCL Porosity ABL and CBL Electrolyte volume fraction ACL and CCL Permeability Membrane

Value

Unit

200 120 20

mm mm mm

0.78

e

0.30

e

1018

m2

Different anode flow field configurations In the anode, carbon dioxide is produced within the anode ERR, and is subsequently removed through the AFF [51]. Whereas, in the cathode, water is produced within the cathode ERR. Any accumulated water within the cathode is removed by the CFF. If the flow fields are not well designed, an accumulation of the dispersed phase (carbon dioxide within the anode, water within the cathode) could take place, which would lead to reduced performance due to the restricted mass transfer from the flow field to the respective ERR. In principle, an ideal DMFC AFF should distribute methanol uniformly over the ERR and remove the by-products (e.g., CO2) quickly from the fuel cell, maintaining a near-single phase condition within the flow fields. In this section, the AFF is varied, and the CFF is held constant with a serpentine flow field. This corresponds to configurations 4e7, shown in Table 1. As can be seen in Fig. 4, when the supplied methanol concentration was increased from 0.50 M to 1.00 M, a distinguishable performance improvement was observed (e.g.: a peak power density increase of 27.3% (S-S), 9.2% (L1-S), 26.2% (L2-S), and 22.6% (LG-S), all relative to the 0.50 M case). This is largely due to the increase in limiting current density, as seen in Eqs. (10) and (11), (e.g.: a predicted increase from 3813 A/m2 (0.50 M) to 7625 A/m2 (1.00 M) for the S-S configuration) which is physically due to the greater availability of reactants. This can also be seen at high current densities, where the higher methanol concentrations provided a delayed concentration polarization. However, this increase in methanol concentration also increased the rate of methanol crossover, which in turn increases the cathode's activation polarization. For example, the greatest amount of methanol crossover was obtained at OCV and 1.00 M with the S-S configuration, where ixover ¼ 3755 A/m2, yielding a maximum hc ¼ 0.3552 V. The lowest rate of methanol crossover at OCV and at 1.00 M was obtained with the LG-S configuration, where ixover ¼ 1297 A/m2, yielding a maximum hc ¼ 0.3219 V. However, in one of our previous studies [39], it was shown that the DMFC's performance degraded when a methanol concentration greater than 1.00 M was supplied, primarily due to the increased rates of methanol crossover. From Fig. 4, it can be seen that, the order of the best performing configurations (from high to low performance, based on peak power densities) are as follows: S-S, L2-S, L1-S, and LG-S. The S-S and L2-S configurations performed very similarly (maximum power density of, S-S: 824 W/m2 and L2-

S: 798 W/m2, both at 1 M), which could be attributed to the fact that the model utilizes very similar mass transfer coefficients for each configuration, as shown in Table 2. This comparison would suggest that the distribution of reactants and the hydrodynamics within the two flow field configurations would be comparable. The deviation between the two mass transfer coefficients could be due to the bulging of the backing layer into the three parent channels (which largely have a greater channel width than the remaining daughter channels) within the L2 flow field of the L2-S configuration, which would induce a higher mass transfer resistance within the channel. For the L1-S configuration, the peak power density of the cell increases from 623 W/m2 to 723 W/m2, from a methanol concentration of 0.50 M to 0.75 M. However, for a further increase in the methanol concentration, from 0.75 M to 1.00 M, the fuel cell's peak power density deteriorates from 723 W/m2 to 680 W/m2. Since the daughter channels at the center of the flow field are detached, this could yield the negative effect of creating a low concentration pocket within the center of the MEA. This may in turn induce a greater degree of methanol crossover due to diffusion, in the inplane direction, as this center zone would have a comparatively lower methanol concentration than the remaining anode ERR. Within the LG-S flow field, this configuration obtained the lower performance than the remaining configurations. It is suspected that this is primarily due to the fact that the LG flow field is interdigitated, whereas the other flow fields are not. This design would have a large mass transfer resistance between the non-connected channels since the flow field is completely reliant on under-rib convection. Also, since the supplied methanol initially travels through the middle channels of this configuration, there is a large nonuniformity in the methanol concentration, which would be indicative of the lower mass transfer coefficient for this channel configuration (3.55 mm/s). However, this flow field may be better suited for more highly concentrated methanol feeds due to its comparatively higher mass transfer resistance. This flow field may also induce a greater degree of thermal non-uniformity due to the non-uniform concentration distribution at the ERR. This thermal non-uniformity could reduce the longevity of the MEA and induce thermoosmotic transport, which could cause a water flooding condition within the CFF, reducing the performance of the fuel cell [52]. Lastly, the total surface of the channels in the flow field is another aspect that must be considered in the performance evaluation of the flow field configurations, as this area directly impacts the electrical resistance at the flow field e backing layer interface [53]. For each flow field, the ratio between the channel surface area and entire flow field area was calculated as 47.76% (L1), 47.86% (L2), 52.84% (LG), and 53.14% (S). Although the L1 and L2 flow fields have similar rib area ratios (bU ¼ 1.053 and 1.052 for the L1 and L2 configurations, respectively), the DMFC with the L2 flow field plates exhibits considerably better performance under the same operating conditions, as seen from Fig. 4(b) and (c) (e.g.: a peak power density of 798 W/m2 and 680 W/m2 at 1 M for the L2-S and L1-S configurations, respectively). This could be a clear indicator of



7

Fig. 4 e Power and polarization curves at the methanol concentrations of 0.50 M, 0.75 M, and 1.00 M for the DMFCs having (a) 7th flow field combination, (b) 4th flow field combination, (c) 5th flow field combination, (d) 6th flow field combination at 70 C.

advanced mass transport capability of second bio-inspired leaf flow field configuration. The performance difference between the bio-inspired lung flow field plate and the serpentine flow field plate may be attributed to the same reason.

Different cathode flow field configurations In this section, the CFF is varied, and the AFF is held constant with a serpentine flow field. This corresponds to configurations 1e3 and 7, shown in Table 1. For a well-designed CFF, the following requirements must be fulfilled [17,54]: i) Provide sufficient open channel area to offer a welldispersed oxygen gas over the cathode ERR; ii) Have sufficient channel rib area to provide effective electronic conductivity; iii) Ensure efficient transportation of the oxygen gas with minimal pressure drop between the CFF inlet and outlet; iv) Provide effective liquid water removal within the cathode, to prevent water flooding; v) Supply oxygen gas to the cathode ERR at a high enough rate to compensate the loss of oxygen due to the methanol oxidation reaction (from methanol crossover) within the cathode ERR [55]. Although, it is suspected that these effects will not be as significant as it will be for the anode (since oxygen has ~3000

times higher molecular diffusivity to that of methanol), if oxygen gas is not uniformly distributed over the ERR, this could cause areas having locally higher current density. This in turn would yield a non-uniform temperature distribution across the MEA, causing the cathode to be susceptible to water flooding due mainly to the heat pipe effect [52]. The nonuniform temperature distribution could also induce performance degradation and reduced cell lifetime, due to effects, such as: MEA delamination and pin hole formation within the membrane [56]. Another critical problem at the cathode is the oxygen concentration differences between the channel and under-land areas, and this problem is markedly depended on the configuration of the flow fields [57]. In this context, it is possible to assess the performances of the DMFCs having different flow field configurations considering these effects. The results of the conducted studies are shown in Fig. 5. As can be seen, there is an overall increase in performance, with respect to the previous section, where the peak power densities increased by 9% (L1), 17% (L2), and 25% (LG). Since the S-S configuration provided the greatest performance for the varied AFF configurations (see Section Different anode flow field configurations), it is expected that this configuration's methanol concentration distribution is the most uniform. In this case, the anode configuration is constant and the analytical model provides identical crossover current densities for each of the cathode configurations (ixover ¼ 3755 A/m2 at OCV). However, in the previous section, each of the AFFs provided different methanol concentrations at the anode ERR and thus


8


Fig. 5 e Power and polarization curves at the methanol concentrations of 0.50 M, 0.75 M, and 1.00 M for the DMFCs having (a) 7th flow field combination, (b) 1st flow field combination, (c) 2nd flow field combination, (d) 3rd flow field combination at 70 C.

different crossover current densities. This in turn yielded different anode and cathode activation polarizations. However, in the case of the varied CFF scenario, oxygen is not affected by the CFF's geometry as greatly as the anode is 2 ¼ 130hM (hoCFF AFF , from Eq. (12)), due to oxygen's comparatively higher diffusivity as discussed earlier. This in turn allows for a more uniform oxygen concentration distribution at the cathode ERR and thus improved performance in comparison to the configurations from the previous section. Furthermore, as the methanol concentration increased, so did the maximum current density at 0.2 V. For example, from 0.50 M to 1.00 M, a 30% (S-S), 12% (L1-S), 16% (L2-S), and 21% (LG-S) increase in maximum current density at 0.2 V were observed. However, for the L1-S configuration in the previous section, this observation was reversed, as the 0.75 M case provided the highest performance. Because the S-L1 configuration uses the S flow field on the anode, this would provide a more uniform methanol concentration distribution on the anode, whereas the oxygen concentration distribution would not be as uniform. However, since oxygen has a higher molecular diffusivity than that of methanol, the low concentration pocket at the center of the MEA on the cathode would not be as significant as it would be for methanol. This can be observed by the comparatively higher performance (~13%) for the S-L1 configuration versus the L1-S configuration (maximum power density of 778 W/m2 (S-L1) versus 680 W/m2 (L1-S), both at 1 M). Furthermore, as seen from Fig. 5, the following peak power densities were obtained: 888 W/m2 (S-L2), 824 W/m2 (S-S),

778 W/m2 (S-L1) and 747 W/m2 (S-LG), each at 1.00 M. In this section, it was observed that the S-L2 configuration obtained the highest performance, whereas the S-S configuration previously obtained the better performance. This could be attributed to the better water management properties of the L2 flow field, as this flow field provides a more direct path for water to flow to the cathode outlet. The serpentine flow field, on the other hand, forces water to follow a more meandering path, causing a greater mass transfer resistance for oxygen. The same principle, as well as differences in their estimated mass transfer coefficient (listed in Table 2), could be attributed to the remaining configurations. Fig. 5 also demonstrates the effects of methanol concentration on the performance of the DMFCs having the previously mentioned configurations. The performance of each configuration demonstrated improvement when the methanol concentration was increased from 0.50 M to 1.00 M. These results are also consistent with those given in Section Different anode flow field configurations. Thereby, the performance trends with the variation of methanol concentration could be attributed to the same reasons provided in Section Different anode flow field configurations.

Effect of anode and cathode flow rates Since the anode and cathode stoichiometric flow rates dictate the uniformity of the reactants' concentration within the MEA, and the fuel cell's capabilities of removing the cell's byproducts [58], a series of experiments were conducted to



understand the fuel cell's behavior under different flow rates. The operating conditions during these experiments were: a cell temperature of 70 C, a methanol concentration of 1.00 M, and a varied methanol (MeOH) and oxygen (O2) flow rate of 1.3 ml/ min (MeOH) and 400 ml/min (O2), 2.6 ml/min (MeOH) and 800 ml/min (O2), and 3.9 ml/min (MeOH) and 1200 ml/min (O2).

Different anode flow field configurations Fig. 6 presents the results of the conducted experiments for each flow field configuration, at different methanol and oxygen flow rates. As can be seen in these figures, increasing the flow rates for both reactants leads to an improvement in the DMFC's performance. For example, there was an increase in peak power density of 28% (S-S), 37% (L1-S), 24% (L2-S), and 27% (LG-S) from the lowest to highest flow rate conditions (i.e.: 1.3 ml/min methanol and 400 ml/min oxygen to 3.9 ml/min methanol and 1200 ml/min oxygen). With an increased methanol concentration, a more uniform concentration distribution [57] and better surface coverage at the channel-BL interface can be attained, which causes an increased anode limiting current density (for example, 5061 A/m2 and 7652 A/ m2, as given by Eq. (10), for an anode flow rate of 1.3 ml/min and 3.9 ml/min, respectively, for the S-S configuration), and decreased anode activation polarization (for example, 0.5492 V and 0.4867 V for an anode flow rate of 1.3 ml/min and 3.9 ml/min, respectively, for the S-S configuration). Both of these were estimated at a current density of 2484 A/m2 which corresponds to the current density at 0.2 V for the 1.3 ml/min case, as given by Eqs. (10) and (5), respectively. However, this also yields an increased crossover current density (for

9

example, 3005 A/m2 and 3755 A/m2 for an anode flow rate of 1.3 ml/min and 3.9 ml/min, respectively, at OCV for the S-S configuration). Furthermore, an increased anode flow rate is expected to increase the removal of accumulated CO2 from the anode channels (as seen from Eq. (15); the analytical concentration of CO2 within the ACL), leading to a flow regime which is closer to the desired single phase condition. This would in turn lead to an enhanced cell performance [6]. 2 CCO g;ACL ¼

" # i tABL A 1 $ CO ;eff þ þ 2 2 6F Dg;ABL 2Q_ AFF dAFF hCO AFF

(15)

For the anode side, it is clear that the S-S configuration demonstrates more promising behavior with respect to performance at each of the corresponding flow rates of methanol and oxygen. It can be clearly seen from Fig. 6(a), (b), and (d) that if the methanol and oxygen flow rates are doubled (from 1.3 ml/min methanol and 400 ml/min oxygen to 2.6 ml/min methanol and 800 ml/min oxygen), the improvements in the peak power density are more observable (e.g.: an increase of 19% (S-S), 25% (L1-S), 12% (L2-S), and 17% (LG-S)). This could be attributed to the fact that these configurations have some difficulties in the removal of accumulated CO2 inside the anode flow channels and homogenous distribution of methanol over the ERR at relatively low flow rates of methanol. As the flow rates of methanol and oxygen are further increased (from 2.6 ml/min methanol and 800 ml/min oxygen to 3.9 ml/ min methanol and 1200 ml/min oxygen), the improvements in peak power density are observable but they are lower compared to the first increments (i.e.: an increase in peak power density of 7% (S-S), 10% (L1-S), 10% (L2-S), and 9% (LG-

Fig. 6 e Power and polarization curves at different oxygen and methanol flow rates for the DMFCs having (a) 7th flow field combination, (b) 4th flow field combination, (c) 5th flow field combination, (d) 6th flow field combination at 70 C and 1.00 M. Please cite this article in press as: Ozden A, et al., Designing, modeling and performance investigation of bio-inspired flow field based DMFCs, International Journal of Hydrogen Energy (2017), http://dx.doi.org/10.1016/j.ijhydene.2017.01.007

10


Fig. 7 e Power and polarization curves at different oxygen and methanol flow rates for the DMFCs having (a) 7th flow field combination, (b) 1st flow field combination, (c) 2nd flow field combination, (d) 3rd flow field combination at 70 C and 1.00 M. S)). Basically, as emphasized in Ge and Liu's study [58], the performance improvements are much more distinguishable up to a certain flow rate value of methanol, while after this flow rate, there is no substantial performance improvement is observed. According to the analytical model, this would be attributed to the inverse proportionality between the volumetric flow rate and limiting current density, as seen in Eqs. (10) and (11).

Different cathode flow field configurations In this section, the same study as in the previous sub-section is performed for the case where the AFF is held constant with a serpentine flow field, whereas the CFF is varied. The results of the conducted experiments are presented in Fig. 7(a)e(d). As can be seen in these figures, when the flow rates of methanol and oxygen are doubled (i.e.: from 1.3 ml/ min methanol and 400 ml/min oxygen to 2.6 ml/min methanol and 800 ml/min oxygen), the performance improvements are much more discernible when compared to those presented in the previous sub-section (e.g.: an increase in peak power density of 19% (S-S), 21% (S-L1), 22% (S-L2), and 25% (S-LG), respectively). An elevated oxygen flow rate, as discussed in previous sections, provided better water management capabilities by enhancing the rate of water droplet detachment from the BL-channel interface and better removal of liquid droplets from the CFF. The higher flow rate also enhances the coverage of oxygen across the cathode ERR [58,59]. In addition to these benefits, an elevated flow rate of oxygen compensates for the unfavorable influences of methanol crossover by

improving the efficiency of the oxidation of crossed over methanol, as seen by Eqs. (8) and (11) [55]. The combination of all of these mentioned effects generates a substantial performance improvement in all of the DMFC configurations. Fig. 7(c) clearly indicates that the S-L2 configuration is very promising as a CFF, as its performance is much better in comparison to its second opponent (S-S configuration), where the maximum power densities for each configuration were 888 W/m2 (S-L2) and 824 W/m2 (S-S) both at 1 M methanol. Thereby, it may be concluded that the S-L2 configuration is superior to the other configurations in regard to all abovementioned desirable properties. These performances were followed by the DMFCs having S-L1 and S-LG configurations under the same operating conditions.

Conclusions In the present study, the effects that different flow field configurations (L1, L2, LG, and S) have on the performances of the DMFCs were investigated both analytically and experimentally. Murray's Law was used in the design of the L1 and L2 flow field designs to determine the channels' geometry. The designed flow field configurations were manufactured and seven different anodeecathode flow field combinations were determined (shown in Table 1). Performance studies were conducted by varying the methanol concentration between 0.50 M and 1.00 M at 70 C. The main conclusions obtained from the conducted experiments are listed as follows.



The highest performance was obtained with the S-L2 flow field configuration. For comparison, the highest peak power density for the S-L2 and S-S configurations were: 888 W/m2 and 824 W/m2, respectively. Relative to the tested configurations, the LG-based flow fields displayed the lowest performance under all tested operating conditions. All of the bio-inspired flow fields demonstrated their highest performance when used on the cathode. The highest tested methanol and oxygen flow rates of 3.9 ml/min methanol and 1200 ml/min oxygen, respectively, provided the best performance for all configurations. Each of the tested flow field configurations achieved their maximum power densities at a methanol concentration of 1.00 M. The exception being the L1-S configuration, which showed its best performance at a methanol concentration of 0.75 M. The results of the conducted studies showed that the bioinspired flow field plates, particularly the L1 and LG bioinspired AFFs, did not demonstrate a significant improvement in performance. In addition, the L2 AFF showed slightly lower performance in comparison to the conventional serpentine AFF. On the other hand, the L2 CFF provided much better performance as compared to the serpentine CFF. Consequently, it is possible to achieve improved performance with a DMFC having the S-L2 flow field configuration. To achieve further improvements, it is suggested that either different bio-inspired flow field configurations should be examined or optimization studies should be conducted.

Acknowledgements The authors gratefully acknowledge the financial support of the Research Fund of Erzincan University with Project FBA2016-318. Also, one of the authors (D.O.) thanks TUBITAK (The Scientific and Technological Research Council of Turkey) for their financial support through the Research Fellowship Programme for International Researchers e 2216.

Nomenclature Abbreviation ABL Anode backing layer ACL Anode catalyst layer AFF Anode flow field CBL Cathode backing layer CL Catalyst layer CCL Cathode catalyst layer CFF Cathode flow field Carbon dioxide CO2 DMFC Direct methanol fuel cell PEMFC Proton exchange membrane fuel cell EOD Electro-osmotic drag ERR Electrochemical reaction region GDL Gas diffusion layer L1 First bio-inspired leaf flow field design

L2 LG MEA MeOH Mem OCV S Sc Pr

Second bio-inspired leaf flow field design Bio-inspired lung flow field design Membrane electrode assembly Methanol Membrane Open circuit voltage Serpentine flow field design Schmidt Number Prandtl Number

Variable A C D F h i K Ka ” N_ nd P Q_ R T t u V W

Active area, m2 Molar concentration, mol/m3 Molecular diffusion coefficient, m2/s Faraday's constant, 96,485 C/mol Mass transfer coefficient, m/s Current density, A m2 Absolute permeability, m2 Methanol oxidation reaction constant, mol/m3 Molar flux, mol/m2/s Coefficient of electro-osmotic drag, e Pressure, Pa; Channel perimeter, m Volume flow rate, m3/s Universal gas constant, 8.31446 J/mol/K Temperature, K Thickness, m Velocity, m/s Voltage, V Channel width, m

11

Greek letters a Charge transfer coefficient b Contact resistance scaling factor d Channel open area ratio, e ε Volume fraction h Overpotential, V m Dynamic viscosity, kg/m/s r Mass density, kg/m3 s Conductivity, S/m Superscripts/Subscripts a Anode act Activation c Cathode d Daughter channel e Electrolyte phase exp Experimental value g Gaseous phase inlet Inlet value l Liquid phase lim Limiting current density M Methanol model Modeled value Oxygen O2 ohm Ohmic p Parent channel ref Reference value rev Value under reversible conditions xover Methanol crossover


12


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