OPTIMIZATION OF THE MEMBRANE ELECTRODE ASSEMBLY (MEA) FABRICATION FACTORS BY DESIGN

OF EXPERIMENT (DOE) METHOD

U.A. Hasran1, S.K. Kamarudin1,2, W.R.W. Daud1, B.Y. Majlis3, A.B. Mohamad2, A.A.H. Kadhum2, M.M. Ahmad4

1Fuel Cell Institute, Universiti Kebangsaan Malaysia, Malaysia2Department of Chemical And Process Engineering, Universiti Kebangsaan

Malaysia, Malaysia3Institute of Microengineering and Nanoelectronics, Universiti Kebangsaan

Malaysia, Malaysia4School of Bioprocess Engineering, Universiti Malaysia Perlis, Malaysia

email: cghu@vlsi.eng.ukm.my

INTRODUCTION

MEA

Perspex frame

Silicone rubber

Stainless steel mesh

Methanol

Bolt

Cathode

Anode

Micro Direct Methanol Fuel Cell (DMFC)

Membrane Electrode Assembly (MEA)

Polymer Electrolyte Membrane (PEM)

MEA

Electrode area = 1 cm2

+

Catalyst

+

Gas Diffusion Layer (GDL)

HOT PRESSING PROCESS

MEA COMPONENTS

PROBLEM STATEMENT

The current method typically used to optimize the critical hotpressing process for the fabrication of MEA is time-consuming,costly and only capable of estimating the importance of eachinput parameter/factor but not the interactions between themon the chosen response.

OBJECTIVES

� To investigate the effect each hot pressing factor has on theMEA fabrication by observing the performance� To observe the interactions between the input factors on thechosen response� To optimize the hot pressing process

METHODOLOGY

� Fabrication of the MEA components

� Hot pressing process

� Pre-treatment of the MEA

� Performance testing with the One-Factor-At-a-Time (OFAT)

method to obtain the levels of the hot pressing factors in this study

� Performance testing with the Design of Experiment (DOE)

method to optimize the hot pressing factors

OFAT: Effect of Hot Press Pressure

3.125 kgf/cm2

9.375 kgf/cm2

18.75 kgf/cm2

Power (mW/cm2)

Current (mA/cm2)

@Hot pressing temperature = 120C:

•power density decreases as pressure is

increased

•highest peak power density at lowest

pressure value of 3.125 kgf/cm2

@Hot pressing pressure = 9.375 kgf/cm2:

•power density increases as temperature

is increased

•highest peak power density at highest

temperature value of 140C

92.8C

100C

120C

Power (mW/cm2)

Current (mA/cm2)

140C

OFAT: Effect of Hot Press Temperature

PARAMETER RANGE

Pressure (kgf/cm2)

[ ]

Temperature (°C) Duration (min)

Time/duration: •Value fixed at 3 min

Pressure: •Range chosen = 6 – 16 kgf/cm2

•Temperature: •Range chosen = 100 - 135C

Time/durationPressureTemperature

Factor Units Low Level (-1) High Level (+1)

A: Compression pressure kgf/cm2 6 16B: Hot pressing temperature °C 100 135

DOE METHOD

� Software Design-Expert 8.0.7.1

� Response surface methodology (RSM):

•objective: optimizing the response variable(s)

•regression analysis used for modeling and analysis of problems

� Central Composite Design (CCD):

•to study the correlation between the factors and the response

•designed to estimate the coefficients of a quadratic model

•no need for detailed reaction mechanism

•blocking effect was of no interest in this work

� Normal probability plot of

the studentized residuals

Nor

mal

% P

rob

abil

ity

Internally Studentized Residuals

GRAPHICAL ANALYSIS

� Plot of the residuals

against predicted response

Inte

rnal

ly S

tud

enti

zed

Res

idu

als

Predicted

� Plot of the predicted

against actual response

Pre

dic

ted

Actual

� Perturbation plot for the

micro DMFC performance

Pea

k P

ower

Den

sity

(m

W/c

m2)

Deviation from Reference Point (Coded Units)

ANALYSIS OF VARIANCE (ANOVA)

� The ANOVA output for Response Surface Quadratic Model:

EMPIRICAL MODEL

� Final empirical model:

Y = 5.18 - 1.46*A + 0.35*B - 1.07*AB + 0.048*A2 - 0.95*B2

� The coefficients of the model for the response show that:

•negative effect implies that A should be minimized

•positive effect implies that B should be maximized

•excessive increase is less desirable for temperature compared to pressure

A: Pressure ResidualsB: Temperature

Pea

k P

ower

Den

sity

(m

W/c

m2)

NUMERICAL OPTIMIZATION

� Desired goal for factor A and B is ‘within range’ and the response is ‘maximize’

� 3D response surface:

� By a potential expanded design space, optimum peak power density = 8.69 mW/cm2

� Max power density

= 7.23 mW/cm2

� Porous media:•electrodes - the gas diffusion layer and the catalyst layer.•PEM

� Over-pressure: •considerable decrease in size or collapse•transport of reactants suffers

•therefore, excessive hot press pressure may result in decreasing fuel cell performance

THE EFFECT OF HOT PRESS PRESSURE

� Glass transition temperature (Tg) for Nafion 117:•132C just before hot-pressing•99C when fully hydrated

� @ temperatures below Tg:•rigidity during hot-pressing•an increase in ohmic loss and a decrease in long-term stability

� @ temperatures above Tg:•softened during hot-pressing •however, it will undergo a micro-structural change and an irreversible water uptake loss at temperatures much higher than Tg

THE EFFECT OF HOT PRESS TEMPERATURE

� OFAT method: changes in compression pressure have a bigger effect on

the electrodes whereas varying the compression temperature affects the

PEM more

� DOE method: the optimum hot pressing factors expected to deliver the

maximum response were predicted using the RSM with central composite

design.

� The model chosen from the ANOVA analysis to predict the desired

response is the Quadratic model.

� The predicted net peak of 7.23 mW/cm2 was obtained from the studied

design space and an optimum performance of 8.69 mW/cm2 was obtained

from the potential expanded design space.

CONCLUSIONS

� Apply the optimum hot press settings in an active micro DMFC system

� Study more input factors with more than one response

FUTURE WORK