Development of Micro-Structural Mitigation Strategies for PEM Fuel Cells:
Morphological Simulations and Experimental Approaches
Silvia Wessel (PI)
David Harvey
Ballard Materials Products
16 May 2012 Project ID# FC049
This presentation does not contain any proprietary, confidential, or otherwise restricted information
Smarter Solutions for a Clean Energy Future 2 16 May 2012
Overview
Project Partners Georgia Institute of Technology
Los Alamos National Laboratory
Michigan Technological University
Queen’s University
University of New Mexico
Timeline
Start Date: January 2010
End Date: March 2013
Percent Complete: 69%
Budget Total Project: $6,010,181
• $ 4,672,851 DOE + FFDRC
• $ 1,337,330 Ballard
DOE FY11 Funding: $1385K
Planned FY12 Funding: $1200K
Barriers A. Durability
• Pt/carbon-supports/catalyst layer
B. Performance
C. Cost (indirect)
Smarter Solutions for a Clean Energy Future 3 16 May 2012
Relevance and Objective
Objective • Identify/Verify Catalyst Degradation Mechanisms Pt dissolution, transport/ plating, carbon-support oxidation and
corrosion, and ionomeric thinning and conductivity loss Mechanism coupling, feedback, and acceleration
• Correlate Catalyst Performance & Structural Changes Catalyst layer morphology and composition; operational conditions Gas diffusion layer properties
• Develop Kinetic and Material Models for Aging Macro-level unit cell degradation model, micro-scale catalyst layer
degradation model, molecular dynamics degradation model of the platinum/carbon/ionomer interface
• Develop Durability Windows Operational conditions, component structural morphologies and
compositions Impact • Increasing catalyst durability Based on understanding of the effect of structure and operating
conditions
Smarter Solutions for a Clean Energy Future 4 16 May 2012
Technical Targets/Barriers
2020 Durability Targets • Automotive Drive Cycle: 5000 hours • CHP and Distributed Generation 1 – 10kWe: 60,000 hours 100 kW – 3MW: 80,000 hours
Ref: http://www1.eere.energy.gov/hydrogenandfuelcells/mypp/pdfs/fuel_cells.pdf
c Mass activity loss after triangle sweep cycles at 50 mV/s between 0.6 V and 1.0 V at 80°C, 100% RH
d Mass activity loss after 1.2V hold in H2/O2 at 80°C, 100% RH
e MEA test at 80°C, 100% RH in H2/O2
Smarter Solutions for a Clean Energy Future 5 16 May 2012
Model Development • 3 scale modeling approach
Molecular dynamics model of the Pt/ carbon/ionomer interface, Pt dissolution and transport process
Microstructural catalyst layer model to simulate the effect of local operational conditions and effective properties on performance and degradation
Unit cell model predicting BOL performance and voltage degradation
Experimental Investigations/Characterization • Systematic evaluation of performance loss, catalyst layer structural and
compositional changes of different catalyst layer structures/compositions under a variety of operational conditions Carbon support type, Pt/C ratio, ionomer content, ionomer EW, catalyst loading Potential, RH, O2 partial pressure, temperature Accelerated stress tests (ASTs) combined with in-situ/ex-situ techniques Performance loss breakdown to determine component contribution In-situ/ex-situ characterization to quantify effect of electrode structure and
composition on performance and durability
Develop Durability Windows • Operational conditions, component structural morphologies and compositions
DOE Working Groups (Durability and Modeling) • Interaction and data exchange with other projects
Approach
Smarter Solutions for a Clean Energy Future 6 16 May 2012
Approach Schematic
Design Curves
Properties
MD Model Pt/C/Ionomer
3-phase interface structure Pt dissolution/transport
mechanism/rates Effective properties Mechanism rates Catalyst structure
Catalyst Powder /Ink Characterization MEA/ Components Characterization
GDL
Experimental Investigations 0
20
40
60
80
100
0 2000 4000 6000
Cycles
EPSA
Los
s (%
)
0
Kin
etic
Los
s (%
)
Microstructural Catalyst Layer Model
1D-MEA degradation model Performance/degradation design curves
Deliverable
Mechanism Understanding Degradation Design Curves Mitigation Windows for Catalyst Degradation
1D-Unit Cell Model
Vali
dati
on
Boundary conditions Effective properties
Boundary conditions
Micro-structural GDL Model
Milestones & Timeline FY 2011 to 2013
Go/No-Go Decision Point (completed 30 June 2011) Validation of statistically generated BOL UC-Model
performance curves against experimental results • Model predictions are within the 95% statistical variability of
the experimental data for the baseline MEA at standard conditions
Q42010 Q4
Q52011 Q1
Q62011 Q2
Q72011 Q3
Q82011 Q4
Q92012 Q1
Q102012 Q2
Q112012 Q3
Q122012 Q4
Q132013 Q1
Go/No-Go Decision Point Modeling MilestonesCorrelations Development MilestonesTools/Methodology Development Milestones
Improved BOL Catalyst Micro-structure Model
Catalyst Layer Capillary
Pressure Tool
Coupled Op. & Struct.
Effects
Structural Design Curves
Operational Design Curves
Integrated Unit Cell
Degradation Model
Transient CatalystMicro-structure
Degradation Model
+Methodology for Quantification of
C Corrosion
++
Unit Cell Degradation
Model
Unit Cell Performance
Model
Molec.-Dyn. Model of Pt / C / Ionomer
Interface
Mitigation Windows
Smarter Solutions for a Clean Energy Future 8 16 May 2012
2011/2012 Milestones
Experimental Investigations • Carbon Types
Investigate lower upper voltage limits
Correlate degradation with material properties
• Ionomer equivalent weight • Pt/C ratio study • Carbon corrosion (potential
hold) study Material Characterization • GDL wettability and capillary
pressure • Interface characterization • Property changes of aged
GDLs and catalyst layers
Molecular Dynamics Model • Completion of Pt/C/ionomer
interface • Molecular modeling of Pt
dissolution Micro-structural Model • Completion of two-phase flow
implementation • Simulation of effective properties
and performance with liquid water 1D-MEA Model • Pt Dissolution, agglomeration • Validation of statistical 1D-MEA
model with experiment Go/No-Go decision June 30, 2011
• Integration of electrical contact resistance model
• Implementation of Multi-step ORR
= Completed = In progress/on target
Smarter Solutions for a Clean Energy Future 9 16 May 2012
Accomplishments
Modeling Status
Smarter Solutions for a Clean Energy Future 10 16 May 2012
Surface Area Analysis of O-covered Pt MD Simulation: Nafion®117 with 10 wt % H2O @, 353 K, 1 atm
Molecular Dynamics Model Three Phase Interface Model
water
H3O+ (160)
Sulfonate (160)
O2 (~ 30 out of 180)
Ionomer
Pt
Graphite
O on Pt
Calculated species coverage of bare and oxide covered platinum • Determined active and
inactive surface moieties (H2O, H3O+, O2, SO3, and polymer)
O2 prefers polymer phase over H2O SO3 interacts strongly
with Pt/PtO • SO3 is well solvated by
the water phase despite being connected to the hydrophobic chain
Improved understanding of three-phase interface (coverages vs. ECSA) • Correction factor for ECSA estimation in micro-structural model
Interaction between PtO, SO3, and H2O is important to understand dissolution
Smarter Solutions for a Clean Energy Future 11 16 May 2012
Geometry Mesh Generation
Material Transport Properties
Solver Modules
Parametric Setup
Post Processing Performance User
Inputs
Model was separated into modular parts • User inputs, transport properties, and physics • Statistical variation User inputs (material constants or operational conditions) Transport properties (effective properties vs. composition of porous media)
Effective transport properties from micro-structural models • Catalyst layer (gas diffusivity, thermal conductivity) • Gas diffusion layer (gas diffusivity, permeability, thermal conductivity)
Unit Cell Model Development Scripting and Statistical Input Options
Electrochemistry
Degradation Physics Transport
Physics
Smarter Solutions for a Clean Energy Future 12 16 May 2012
Vo
ltag
e (
V)
Current density (mA/cm2)
Vo
ltag
e (
V)
Current density (mA/cm2)
Sample to sample variation created using a normally distributed, random population
Initial model validation, single phase • Predictions were within 1 standard deviation up
to 1.0 A/cm2 Two-phase model validation
• Accurately captures effect of increasing water content
• Experimental and model variation both increase with current density due to “noise” factors having increased effects on transport processes
Experimental dataset of 20 MEAs
Statistical Model Inputs Component Properties % Deviation (1 Std Dev)Catalyst/Catalyst Layer
Thickness (microns) +/- 8%Weight Ratios (%)
Pt:C +/- 1%(Pt:C):Ionomer +/- 1%
Pt Loading [mg/cm^2] +/- 1.25 %Pt size +/- 10%Tafel Slope [mV/dec] fixedJo [A/cm^2 pt] +/- 10%
GDLPorosity fixedTortuosity +/- 3%Thickness (microns) +/- 4%
MembraneThickness (microns) +/- 2%
Unit Cell BOL Model Validation (Baseline MEA, Standard Conditions)
Single Phase Two-Phase
Added Liq. Water model
Smarter Solutions for a Clean Energy Future 13 16 May 2012
Accomplishments Modelling/Experimental Results
Effect of Cathode Catalyst Structure / Composition on Performance and
Degradation
Pt Loading Study (Pt50-LSAC)
Carbon Ratio Study (PtX-LSAC)
Reference MEA: 50:50 Pt/C, Nafion® ionomer, 0.4/0.1 mg/cm2 (Cathode/anode), Ballard CCM, Nafion® NR211, BMP GDLs
Ballard Test Cell: 1D, 45cm2 active area Reference AST: Air/H2, 100% RH, 5 psig, 80oC, 0.6 V (30 sec) 1.2V (60 sec), 4700 cycles
Smarter Solutions for a Clean Energy Future 14 16 May 2012
Effect of Pt Loading Catalyst Layer Structure (Experiment)
0
200
400
600
800
1000
1200
0 0.5 1 1.5 2 2.5
Current Density (A/cm2)
Perfo
rman
ce (m
V)
0.055 mg/cm2 Pt0.10 mg/cm2 Pt0.19 mg/cm2 Pt0.31 mg/cm2 Pt0.40 mg/cm2 Pt0.41mg/cm2 Pt0.50 mg/cm2 Pt
02468
101214161820
0 0.1 0.2 0.3 0.4 0.5 0.6
Pt Loading (mg/cm2)
BOT
CC
L Th
ickn
ess
(mic
ron)
0
50
100
150
200
250
300
0 0.1 0.2 0.3 0.4 0.5 0.6
Pt Loading (mg/cm2)
BOT
ECSA
ECSA/Thickness vs. loading • Relationships for macro-model • Validation data for micro-structural model
Performance loss increases with low loaded structures • Below ECSA ~75 • Loss increases with increasing current • Higher sensitivity to low oxygen
concentration
0
200
400
600
800
1000
0 100 200 300
ECSA
Air P
erfo
rman
ce (m
V)
0.1A/cm20.5A/cm21.0A/cm2BOL data shown in
Smarter Solutions for a Clean Energy Future 15 16 May 2012
Platinum Loading Study BOT Performance (Experiment & Predicted)
Effect of Partial Pressure at 0.05 [mg/cm^2]
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 500 1000 1500 2000 2500
Current Density [mA/cm^2]
Cel
l Vol
tage
[V]
x_O2=100% x_O2=21% x_O2=10.5% Model-21% Model-10.5% Model-100%
Effect of Partial Pressure at 0.408 [mg/cm^2]
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 500 1000 1500 2000 2500
Current Density [mA/cm^2]
Cel
l Vol
tage
[V]
Exp.-100% Exp.-21% Exp.-10.5% Model-21% Model-10.5% Model-100%
0.000.020.04
0.060.080.100.12
0.140.160.18
0 0.2 0.4 0.6
Pt Loading (mg/cm2)
Iono
mer
Vol
ume
Frac
tion
65
70
75
80
85
90
95
100
CL P
oros
ity, S
EM (%
)
Ionomer Vol. Frac. Porosity
Model captures behaviour at low Pt loading and oxygen sensitivity • Permeability is fitted at 21% O2
Sensitivity to oxygen fraction • Saturation vs. diffusivity relationship • Ionomer film behaviour?
Volume fraction variation with loading and thickness • Important in capturing behaviour
Smarter Solutions for a Clean Energy Future 17 16 May 2012
Effect of Pt Loading Degradation - Pt Dissolution
Performance correlates to ECSA for BOT and degraded samples
Degradation rate increases for <0.3 mg/cm2 Pt loading
Pt dissolution changes structure of catalyst layer • Depletion of Pt at membrane interface, PITM,
increased Pt size, lower surface area • No significant change in catalyst layer thickness
0
100
200
300
400
500
600
700
0 100 200 300ECSA
Perf
orm
ance
, 1A
/cm
2 (mV)
BOT
EOT
BOT
EOT
BOT
ECSA 75
ECSA 195
0
20
40
60
80
100
0 0.1 0.2 0.3 0.4 0.5 0.6
Pt Loading @ BOT (mg/cm2)
ECSA
Los
s at
210
0 C
ycle
s (%
)
0.00
0.02
0.04
0.06
0.08
0.10
Deg
rada
tion
Rat
e,
1 A
/cm
2 (mV/
cycl
e)
0.4 mg/cm2 Loading
16 May 2012
Carbon Corrosion Degradation Impact of Dwell time
1
10
100
1000
10000
100000
1000000
10000000
1.1 1.2 1.3 1.4 1.5 1.6 1.7
Upper Potential Limit
Tim
e at
UPL
(sec
) Prio
r to
Car
bon
C
orro
sion
Per
form
ance
Los
s
80C, 100%RH
MSAC50
LSAC50
1.4V UPL AVG Voltage @ 1.0 A/cm2
0
200
400
600
800
0 200 400 600
Time at UPL (min)
Volta
ge (m
V)
5s dwell 1.4V UPL20s dwell 1.4V UPL60s dwell 1.4V UPL300s dwell 1.4V UPL600s dwell 1.4V UPL
Pt50-LSAC
Onset of observable performance loss due to corrosion is dependent on time spent at UPL (total) • Critical carbon oxidation threshold dependent
on the carbon type • Pt dissolution is affected by oxide build-up
with increased particle size with shorter dwell times
• PITM formation impacted by amount of dissolved Pt, also increases with shorter dwell times
Time to corrosion onset is dominated by the UPL and graphitisation level of the support
Dissolution versus 1.4V UPL Dwell Time
0
4
8
12
16
20
0 200 400 600 800UPL Dwell Time / Cycle (s)
Pt C
ryst
allit
e Si
ze (n
m)
PITM
(ppm
* 1,
000)
0
20
40
60
80
100
EPSA
Los
s (%
)
Pt Crystallite SizePITM% EPSA Loss
Smarter Solutions for a Clean Energy Future 20 16 May 2012
30% & 60% Pt:C
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 500 1000 1500 2000 2500Current Density [mA/cm^2]
Cel
l Vol
tage
[V]
60% C:Pt (Run #1)60% C:Pt (Run #2)30% C:Pt (Run #1)30% C:Pt (Run #2)2-phase Model, 60% Pt:C2-phase Model, 30% Pt:C
80% Pt:C
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 500 1000 1500 2000 2500Current Density [mA/cm^2]
Cel
l Vol
tage
[V]
80% Pt:C (Run#1)80% Pt:C (Run#2)2-phase Model, Pt:C 80%
Effect of Pt/C Ratio BOT Performance (Experiment & Predicted)
ECSA vs. Performance • Similar behavior in kinetic region with Pt
loading study • Pt dispersion effect at high ratios
80% Pt/C has lower performance • Increased CL ionic resistance and
reduced porosity Model predictions
• Similar move in kinetics, liquid water effects with layer thickness changes
• Able to capture effect of higher I/C ratio
0
200
400
600
800
1000
0 50 100 150 200 250 300
ECSA
Air
Perf
orm
ance
(mV)
Carbon Ratio Study 0.1 A/cm2Carbon Ratio Study 1.0 A/cm2Pt Loading Study 0.1A/cm2Pt Loading Study 1.0 A/cm2BOL data shown in black 100% RH, 75'C
0.1 A/cm2
1.0 A/cm2
Smarter Solutions for a Clean Energy Future 21 16 May 2012
0
50
100
150
200
250
20 40 60 80 100% Pt/C Ratio
ECSA
BOTEOT
0
50
100
150
200
250
20 40 60 80 100% Pt/C Ratio
ECSA
BOTEOT
75'C, 5psig, 100%RH
0
200
400
600
800
1000
0 1000 2000 3000 4000 5000
Cycles
Volta
ge (m
V)
30%Pt/C
40% Pt/C
50% Pt/C
60% Pt/C
30%Pt/C
1.3 A/cm2
0.1 A/cm2
NOTE: 80% Pt/C had much worse performance and is not
0
5
10
15
20
25
30
35
30 40 50 60Pt/C Ratio %
CC
L Th
ickn
ess
(um
)
BOTEOT
0
2
4
6
8
10
12
30 40 50 60 %Pt/C
Pt C
ryst
allit
e Si
ze (n
m)
BOL EOT
57%
40%
57% 63%
Effect of Pt/C Ratio Degradation
Voltage Degradation decreases with increasing Pt/C Ratio • Improved performance at higher current densities
after degradation cycling % ECSA loss at EOT is similar for all Pt
ratios • Each sample losing ~ 50% of the initial EPSA
• BOT crystallite sizes increase with Pt/C ratio
• No electrode thickness changes (change is within variation at BOL)
Smarter Solutions for a Clean Energy Future 22 16 May 2012
Plan Forward
Model Development 1-D MEA Model
• Pt dissolution Linking platinum dissolution to multi-
step ORR (underway) Pt-dissolution, agglomeration,
formation of PITM (underway) • Carbon support oxidation/ corrosion 2-stage pathway
• Validation with AST cycling • Correlations and development of
design windows Micro-structural Catalyst Model
• Mass transport limitations and low loaded catalysts
• Platinum dissolution, Carbon corrosion
Molecular Dynamics Model • Platinum dissolution within 3-phase
interface • Transport of Ptn+ within membrane
phase
Experimental Investigations Complete operational studies for
carbon corrosion and platinum dissolution • Selected experimental studies for
model development support Correlations and development of
design windows
Collaborators Complete chemical structural
analysis of degraded catalyst layers/MEAs Capillary pressure measurements
on catalyst layer Quantify interface changes in
degraded MEAs
Smarter Solutions for a Clean Energy Future 23 16 May 2012
Organizations /Partners
Prime: Ballard Material Products/Ballard Power Systems S. Wessel, D. Harvey, V. Colbow
• Lead: Micro-structural/MEA/Unit Cell modeling, AST correlations, characterization, durability windows
Queen’s University – Fuel Cell Research Center K.Karan, J. Pharoah
• Micro-structural Catalyst Layer/Unit Cell modeling, catalyst characterization
Georgia Institute of Technology S.S. Jang
• Molecular modeling of 3-phase interface & Pt dissolution/transport Los Alamos National Laboratory R. Borup, R. Mukundan
• Characterization of catalyst layer/GDL Michigan Technological University J. Allen, R. S. Yassar
• Capillary pressure and interface characterization, catalyst layer capillary pressure tool development
University of New Mexico P. Atanassov
• Carbon corrosion mechanism, characterization of catalyst powder/layers
Relevance • Improve understanding of durability for fuel cell materials and components • Provide recommendations for the mitigation of MEA degradation that
facilitates achieving the stationary and automotive fuel cell targets Approach
• Develop forward predictive MEA degradation model using a multi-scale approach
• Investigate degradation mechanisms and correlate degradation rates with catalyst microstructure, material properties, and cell operational conditions
Technical Accomplishments and Progress to date • Completed BOL 1D-MEA model, simulations of composition and operational
effects on BOL performance were validated with experimental results • Quantified Pt/C catalyst performance degradation mechanisms with catalyst
loading, Pt/C ratio, carbon type, ionomer EW , UPL , RH, time at UPL Collaborations
• Project team partners GIT, LANL, MTU, Queen’s, UNM • Participation in DOE Durability and Modeling Working Group
Proposed Future Research • Extend micro-structural model to include degradation and validate
Complete MD model of Pt dissolution and transport mechanisms • Complete experimental investigation and correlations • Develop durability design windows using experimental results and the 1-D
MEA model Smarter Solutions for a Clean Energy Future 24 16 May 2012
Summary
Smarter Solutions for a Clean Energy Future 25 16 May 2012
Acknowledgement
Thank you: • Financial support from the U.S. DOE-EERE Fuel Cells
Technology Program • Support from project managers/advisor Kathi Epping Martin,
David Peterson, and John Kopasz • Project Collaborators
Technical Backup Slides
Smarter Solutions for a Clean Energy Future 27 16 May 2012
Project Applicability to Industry
Model Predictions of Performance & Degradation based on MEA Components, Composition, and Processing (Structure)
Operating Conditions
0
2
4
6
8
10
12
14
16
0 500 1000 1500 2000 2500 3000 3500
Cycles
Per
form
ance
Los
s (%
)
30% RH 50%RH 80%RH 100%RH 120%RH
0
10
20
30
40
50
60
70
80
90
100
0 1000 2000 3000 4000
Cycles
EC
SA
Los
s (%
)
30% RH 50%RH 80%RH 100%RH 120%RH
1D Unit Cell Model
Predicted ECSA Loss
Catalyst Layer
Membrane
GDL MEA
Catalyst Ink
Catalyst Powder Plates
Component Properties and Structure
Cat. Powder BET SA Mass activity ECA
Catalyst Layer Mass activity ECSA Utilization Thickness Conductivity (H+, e-,T) Capillary pressure Porosity.
Membrane EW Thickness
GDL Thickness Tortuosity Diffusivity Porosity Capillary Press. Cond. (e-,T)
Cat. Ink Pt/C/Ionomer Vol. fractions
Plate Cond. (e-,T) Geometry
BOL Performance
ECSA Exchange current density Tafel slope Mass activity HFR
Predicted Voltage Degradation
Parametric Performance Study
Smarter Solutions for a Clean Energy Future 28 16 May 2012
State-of-the-Art Unit Cell
Reference MEA • Pt Catalyst Graphitized carbon-support 50:50 Pt/C ratio Nafion® ionomer
• Catalyst Loading Cathode/anode 0.4/0.1 mg/cm2
• Catalyst Coated Membrane • Ballard manufactured CCM
• Nafion® NR211 • Gas diffusion layer BMP Product Continuous Process
1D Test Hardware • Bladder compression • High flow rates
• Temperature control Liquid cooling
• Carbon Composite Plates Low pressure Parallel flow fields Designed for uniform flow
• Framed MEA 45 cm2 active area
Smarter Solutions for a Clean Energy Future 29 16 May 2012
Experimental Approach
MEA In-situ diagnostics* H2/Air Polarization
Performance Limiting current
H2/O2 polarization V-loss break-down: Kinetic, Ohmic, Mass Transport
Cyclic Voltametry CO stripping ECSA Double layer charging current H2 cross-over Pt surface understanding
Electrochemical Impedance Spectroscopy (EIS) Cell resistance Ionomer resistance Double layer charging current
Mass and specific activity
Ex-situ Diagnostics* SEM: Catalyst/membrane thickness SEM/EDX: Pt content in membrane
and catalyst layer XRD: Pt crystallite size and orientation BPS Diagnostic Tool Voltage Loss Breakdown (Kinetic Loss) Limiting Current
Selected BOT/EOT
Samples for Collaborators
* Ongoing evaluation, i.e. list of diagnostics may change
Reference AST: Air/H2, 100% RH, 5 psig, 80oC, 0.6 V (30 sec) 1.2V (60 sec), 4700 cycles Reference MEA:50:50 Pt/C, Nafion® ionomer, 0.4/0.1 mg/cm2 (Cathode/anode), Ballard CCM, Nafion® NR211, BMP GDLs Ballard 1D Test Cell, 45cm2 active area
BOT
AST Testing
Conditioning
MOT x
MOT 1
EOT
Selected MEA Components for Collaborators
BOT/MOT/EOT = Beginning/Mid/End of Test
29
Smarter Solutions for a Clean Energy Future 30 16 May 2012
Ex-situ Characterization Component Structure/Property Changes
Technique
• SEM/EDX (BPS)
• Pseudo Hele-Shaw (MTU) • Sessile Drop • FTIR, X-ray Fluores. (LANL) • MIP(BPS)
• XRD (BPS) • SEM/EDX (BPS) • MIP/BET (BPS/LANL) • SEM/FESEM (BPS/MTU) • XPS (UNM) • Laser Profiliometry (MTU) • Hele-Shaw (MTU) • cAFM (MTU) • AFM (MTU))
Technique • HRTEM (UNM) • BET (LANL/BPS) • XPS (UNM) • XRD (BPS) • HRTEM (UNM) • HRTEM (UNM)
• BET/MIP (LANL/BPS)
• XPS (MTU)
• AFM (MTU) • Raman/FTIR (MTU)
Purpose
Purpose
MEA GDL
Cathode Cat Layer
Membrane
Catalyst Powder
Carbon Support
CL/Membrane Interface
Not Run Conditioned Degraded Membrane Changes
• Thickness • PTIM
Water Management Changes • Capillary pressure • Contact angle • Surface energy/species • PSD
Structure/ Property Changes • Pt crystallite size • Pt content, Thickness • Porosity • Crack density, depth and width • Surface species • Surface roughness • Capillary pressure • Electrical conductivity • Cohesive strength
Properties
• Pt crystallite size • Pt size distribution • Pt agglomerate size
• Porosity • Pore size distribution • Surface species
Structure/Property Changes • Cohesive strength/adhesion • Chemical bond
• Structure/morphology • Pore size distribution • Surface species
• Model input • Correlation dev. • Model input • Dev. of
correlations
• Determine if memb. degrades
• Model validation
• Model input • Determine if
GDL degrades
• Mechanism understanding
• Model input • Model validation • Structure/material
properties - BOL/ EOL performance correlations
• Model input • Correlation dev.
