EXPERIMENTAL STUDIES IN HYDROGEN GENERATION FOR FUEL CELL
APPLICATIONS USING ALUMINUM POWDER
Thesis
Submitted to
The School of Engineering of the
UNIVERSITY OF DAYTON
In Partial Fulfillment of the Requirements for
The Degree Of
Master of Science in Renewable and Clean Energy
By
Faizan Ahmad
UNIVERSITY OF DAYTON
Dayton, OH
December, 2010
EXPERIMENTAL STUDIES IN HYDROGEN GENERATION FOR FUEL CELL
APPLICATIONS USING ALUMINUM POWDER
APPROVED BY:
_______________________________
Sukh S. Sidhu, Ph.D.
Committee Chair
Distinguished Research Scientist
Sustainable Environmental Technologies
Group
_________________________________
Kelly Kissock, Ph.D, P.E.
Committee Member
Professor
Department of Mechanical and Aerospace
Engineering
_______________________________
Moshan Kahandawala, Ph.D.
Committee Member
Research Engineer
Sustainable Environmental Technologies Group
_________________________________
John G. Weber, Ph.D.
Assistant Dean
School of Engineering
_________________________________
Tony E. Saliba, Ph.D.
Wilke Distinguished Professor and Dean
School of Engineering
ii
ABSTRACT
EXPERIMENTAL STUDIES IN HYDROGEN GENERATION FOR FUEL CELL
APPLICATIONS USING ALUMINUM POWDER
Name: Ahmad, Faizan
University of Dayton
Advisor: Dr. Sukh S. Sidhu
One method of producing on-demand hydrogen for fuel cells is through the use of
aluminum which reacts with water under certain conditions to produce hydrogen. This
process can be used for applications as small as portable handheld devices, onboard
generation for vehicles, or as large as a hydrogen refueling center. However, the
utilization of aluminum for generating on-demand hydrogen is critically dependent on the
control of the rate of hydrogen generation from the reaction. Experiments with micron
and nano-sized aluminum powder are described in this work and the effects of particle
size, reagent quantities, temperature and solution concentration on the hydrogen
generation rate and total yield are analyzed and quantified. Regression models are
developed and yield and rate predictions are confirmed. In general, aluminum
nanoparticles are found to have poorer hydrogen yields, but marginally faster reaction
rates as compared to micron particles.
iii
ACKNOWLEDGEMENTS
First and foremost I would like to thank God for sustaining me as I completed this
work, and for giving me the strength to overcome seemingly insurmountable obstacles. In
the non-divine arena, I would like to express my deepest gratitude for Dr. Moshan
Kahandawala for his mentorship and support throughout the project. We burnt the
midnight oil together on numerous occasions while troubleshooting the experimental
systems - the only deadline being my wish to graduate on time. I have learnt much about
scientific experimentation from his vast experience and knowledge, and his persistence
and attention to detail. Special thanks are also due to Anupriya Krishnan for her advice
and input, help in sensor interfacing and conducting the experiments, and in patiently and
painstakingly editing this manuscript. Giacomo Flora was also particularly obliging
during the gas analysis process. Also, Dr. John Doty willingly provided his expert input
on experimental design and analysis both inside and outside of his class.
I have looked at the list of names of all twenty or so members of the Sustainable
Environmental Technologies Group (SETG), and have realized that I have sought
assistance from each one of them at some point in time. For their companionship,
readiness to help, and good humor, I am grateful. Last but not least, I would like to thank
my advisor Dr. Sukh Sidhu for his guidance and direction during the project, and for
expressing his confidence in my abilities to complete the task at hand.
iv
TABLE OF CONTENTS
ABSTRACT ........................................................................................................................................... III
ACKNOWLEDGEMENTS ........................................................................................................................ IV
TABLE OF CONTENTS............................................................................................................................. V
LIST OF ILLUSTRATIONS...................................................................................................................... VIII
LIST OF TABLES ..................................................................................................................................... X
LIST OF ABBREVIATIONS AND ANNOTATIONS ...................................................................................... XI
INTRODUCTION .................................................................................................................................... 1
1.1
MOTIVATION FOR STUDY .........................................................................................................................1
1.2
SYNOPSIS OF HYDROGEN PRODUCTION METHODS ........................................................................................2
1.3
WATER-DISPLACEMENT REACTIONS FOR HYDROGEN GENERATION ..................................................................2
1.4
ALUMINUM-WATER REACTIONS WITH THE ASSISTANCE OF ALKALIS .................................................................3
LITERATURE REVIEW ............................................................................................................................. 6
2.1
OVERVIEW OF SELECTED PAPERS ...............................................................................................................6
2.2
HYDROGEN GENERATION USING ALUMINUM NANOPARTICLES ......................................................................10
SAMPLE FUEL CELL DESIGN CALCULATIONS ..........................................................................................12
3.1
HYDROGEN REQUIREMENTS ...................................................................................................................12
3.2
ALUMINUM REQUIREMENTS ..................................................................................................................13
EXPERIMENTAL SETUP AND PROCEDURES ............................................................................................15
4.1
PRELIMINARY EXPERIMENTAL SETUP AND PROCEDURES ...............................................................................15
v
4.2
MAIN EXPERIMENTAL SETUP AND PROCEDURES .........................................................................................17
4.2.1
MAIN EXPERIMENTAL SETUP .............................................................................................................17
4.2.2
REAGENT PREPARATION ...................................................................................................................20
4.2.3
EXPERIMENTAL PROCEDURES .............................................................................................................21
4.2.4
EVOLUTION OF THE EXPERIMENTAL SYSTEM DESIGN ..............................................................................22
RESULTS AND ANALYSES FOR PRELIMINARY EXPERIMENTS ..................................................................24
5.1
RESULTS AND ANALYSES FROM PRELIMINARY EXPERIMENTS .........................................................................24
5.2
CONCLUDING REMARKS ON PRELIMINARY EXPERIMENTS .............................................................................28
RESULTS AND ANALYSES FOR MAIN EXPERIMENTS ..............................................................................31
6.1
CHOICE OF FACTOR LEVELS ....................................................................................................................31
6.2
DETERMINATION OF SYSTEM VOLUME .....................................................................................................34
6.3
EXAMPLE OF DATA ANALYSIS METHODOLOGY ...........................................................................................35
6.4
SUMMARY OF RESULTS .........................................................................................................................39
6.5
DISCUSSION AND ANALYSIS OF YIELD RESULTS ...........................................................................................41
6.6
DISCUSSION AND ANALYSIS OF RATE RESULTS ............................................................................................48
6.7
FURTHER DISCUSSION OF RESULTS ..........................................................................................................56
6.8
CONFIRMATION TESTS ..........................................................................................................................61
ADDITIONAL EXPERIMENTATION .........................................................................................................62
7.1
REPRODUCIBILITY TEST ..........................................................................................................................62
7.2
FLOW-METER COMPARISON RUNS ..........................................................................................................62
7.3
EFFECT OF SOLUTION VOLUME CHANGE ...................................................................................................65
7.4
COMPARISON BETWEEN FIVE PARTICLE SIZES.............................................................................................66
vi
7.5
GAS ANALYSIS .....................................................................................................................................69
7.6
ALUMINUM PARTICLE ANALYSES WITH TRANSMISSION ELECTRONIC MICROSCOPY (TEM)..................................70
7.7
ENHANCED REGRESSION MODELS ...........................................................................................................76
SUMMARY AND CONCLUSIONS............................................................................................................78
RECOMMENDATIONS FOR FUTURE WORK ...........................................................................................80
APPENDICES ........................................................................................................................................83
APPENDIX A - DERIVATION OF 3 WATT-HR / LITER OF H2 RULE-OF-THUMB ...............................................................83
APPENDIX B – PYTHON 2.6 SCRIPT FOR HYDROGEN RATE AND YIELD MEASUREMENTS ...............................................85
APPENDIX C– LIST OF REAGENTS AND EQUIPMENT...............................................................................................86
APPENDIX D – ANOVA RESULTS FOR YIELD .......................................................................................................87
APPENDIX E – ANOVA RESULTS FOR RATE ........................................................................................................88
APPENDIX F – ANOVA RESULTS FOR ENHANCED REGRESSION MODELS ..................................................................89
APPENDIX G – RAW DATA ..............................................................................................................................94
REFERENCES ........................................................................................................................................95
vii
LIST OF ILLUSTRATIONS
FIGURE 1. SCHEMATIC OF PRELIMINARY EXPERIMENTAL SETUP ...................................................................................16
FIGURE 2. PICTURE OF MAIN EXPERIMENTAL SETUP .................................................................................................18
FIGURE 3. SCHEMATIC OF MAIN EXPERIMENTAL SETUP .............................................................................................19
FIGURE 4. COMPARISION BETWEEN NAOH AND KOH ...............................................................................................25
FIGURE 5. EFFECT OF REDUCING SOLUTION QUANTITY ON REACTION RATE .....................................................................26
FIGURE 6. EFFECT OF USING INSUFFICIENT NAOH ON REACTION RATE ..........................................................................27
FIGURE 7. EFFECT OF INCREASING ALUMINUM QUANTITY ON THE RATE AND YIELD OF REACTION ........................................28
FIGURE 8. RAW TEMPERATURE AND PRESSURE DATA FOR EXPERIMENT # 1 ..................................................................35
FIGURE 9. NONE-BASELINE ADJUSTED HYDROGEN VOLUME PROFILE FOR EXPERIMENT #1 .................................................38
FIGURE 10. BASELINE-ADJUSTED HYDROGEN VOLUME PROFILE FOR EXPERIMENT # 1 ......................................................38
FIGURE 11. YIELD AS A FUNCTION OF RATE ..............................................................................................................41
FIGURE 12. YIELD AS A FUNCTION OF PARTICLE QUANTITY ..........................................................................................42
FIGURE 13. YIELD AS A FUNCTION OF TEMPERATURE .................................................................................................43
FIGURE 14. YIELD AS A FUNCTION OF CONCENTRATION ..............................................................................................43
FIGURE 15. ANOVA RESULTS FOR YIELD ................................................................................................................44
FIGURE 16. PREDICTED YIELD VS. ACTUAL YIELD ........................................................................................................46
FIGURE 17. NORMAL PLOT OF RESIDUALS FOR YIELD..................................................................................................47
FIGURE 18. RESIDUALS VS. PREDICTED FOR YIELD ......................................................................................................47
FIGURE 19. RATE AS A FUNCTION OF PARTICLE QUANTITY ...........................................................................................48
FIGURE 20. RATE AS A FUNCTION OF PARTICLE SIZE ...................................................................................................49
FIGURE 21. RATE AS A FUNCTION OF TEMPERATURE ..................................................................................................50
viii
FIGURE 22. RATE AS A FUNCTION OF CONCENTRATION ..............................................................................................51
FIGURE 23. ANOVA TABLE FOR REACTION RATE ......................................................................................................52
FIGURE 24. PREDICTED RATE VS. ACTUAL RATE .........................................................................................................53
FIGURE 25. NORMAL PLOT OF RESIDUALS FOR RATE .................................................................................................54
FIGURE 26. RESIDUALS VS. PREDICTED FOR RATE .....................................................................................................55
FIGURE 27. RATE COMPARISON WITH “FREE ALUMINUM” ADJUSTMENT........................................................................60
FIGURE 28. PRESSURE AND TEMPERATURE PROFILE FOR EXPERIMENT # 15...................................................................64
FIGURE 29. HYDROGEN VOLUME PROFILE FOR EXPERIMENT # 15 ...............................................................................64
FIGURE 30. YIELD PERFORMANCE COMPARISON AS A FUNCTION OF PARTICLE SIZE ...........................................................67
FIGURE 31. RATE PERFORMANCE COMPARISON AS A FUNCTION OF PARTICLE SIZE ...........................................................68
FIGURE 32. 40-60 NM NANOPARTICLES .................................................................................................................71
FIGURE 33. < 150 NM NANOPARTICLES ..................................................................................................................72
FIGURE 34. 1-3 MICRON PARTICLES .......................................................................................................................73
FIGURE 35. < 75 MICRON PARTICLES .....................................................................................................................74
FIGURE 36. 1MM PARTICLES.................................................................................................................................75
ix
LIST OF TABLES
TABLE 1. FACTOR LEVELS FOR SCREENING EXPERIMENT .............................................................................................32
TABLE 2. EXPERIMENTAL TEST MATRIX ...................................................................................................................32
TABLE 3. SYSTEM VOLUME DETERMINATION ...........................................................................................................34
TABLE 4. EXAMPLE OF DATA ANALYSIS ...................................................................................................................37
TABLE 5. YIELD AND RATE RESULTS FOR TEST MATRIX ...............................................................................................40
TABLE 6. ADDITIONAL INFORMATION ON EXPERIMENTAL RUNS ...................................................................................40
TABLE 7. CONFIRMATION TESTS ............................................................................................................................61
TABLE 8. REPRODUCIBILITY TESTS ..........................................................................................................................62
TABLE 9. EFFECTS OF SOLUTION VOLUME CHANGE ...................................................................................................66
TABLE 10. MEASURED PARTICLE SIZES ...................................................................................................................76
x
LIST OF ABBREVIATIONS AND ANNOTATIONS
Al
Al2O3
ANOVA
Aq.
C
eg.
g
g/mol
H2
KOH
Aluminum
Aluminum Oxide
Analyses of Variance
Aqueous
degrees Celsius
for example
gram(s)
grams per mole
Hydrogen
Potassium Hydroxide
M
Molar
ml
milliliter
NaOH
vs.
Sodium Hydroxide
versus
xi
CHAPTER 1
INTRODUCTION
1.1
Motivation for Study
The current fossil-fuel based economy is generally considered unsustainable due
to resource as well as environmental constraints. One possible alternative is the
development of a hydrogen-based economy, as hydrogen is an abundant and
environmentally friendly fuel. However, it should be noted that free hydrogen does not
occur naturally, and needs to be generated by various means. Hydrogen should therefore
not be considered a primary energy source (eg. coal), but rather, an energy carrier.
The need for high pressure storage systems is one impediment to the large-scale
utilization of hydrogen as a fuel. The production of on-demand hydrogen, thereby
bypassing the storage system requirement, could greatly aid in making the hydrogen
economy a reality.
One method of producing on-demand hydrogen for fuel cells is through the use of
aluminum which reacts with water under certain conditions to produce hydrogen. This
can be used for applications as small as portable handheld devices, onboard generation
for vehicles, or as large as a hydrogen refueling center. However, the utilization of
aluminum for generating on-demand hydrogen is critically dependent on the control of
the rate of hydrogen generation from the reaction. Decreasing the aluminum particle size
1
can result in increased reaction rates due to higher reactant surface area. It should be
noted that in general, aluminum-water reactions for hydrogen generation have been
extensively studied and reported in literature. However, there is a dearth of literature on
the use of aluminum particles at the nano-scale in particular. Moreover, controlling the
rate of hydrogen generation from the aluminum-water reaction has not been well-studied.
1.2
Synopsis of Hydrogen Production Methods
Hydrogen is currently produced through biological processes (reforming
biomass), electrolysis or other various chemical methods. The problems associated with
biomass reformation include low yield and energy content, along with carbon-neutrality
disputes. Hydrogen production from electrolysis does not emit CO2, but is too expensive
to be feasible. Steam reformation of natural gas is currently the most well-developed and
widely used method for hydrogen production, but is not CO2-free. Other chemical
methods include reactions of chemical hydrides with aqueous solutions. Although the use
of hydrides aids in the reduction of hydrogen storage issues, hydrides are sensitive to
moisture, unstable and expensive [1].
1.3
Water-Displacement Reactions for Hydrogen Generation
Water-displacement reactions of metals are another possible method for on-
demand hydrogen generation. Zinc, magnesium and aluminum have been used for this
purpose, but Aluminum is most commonly-used given its high availability, recyclability
and energy content. Also, water-displacement reactions are of particular interest given
that the hydrogen content per unit volume of water is higher than in pure hydrogen [1].
2
In practice, aluminum will not react with water at room temperature because of a
thin layer of aluminum oxide (Al2O3) on its surface which prevents the reaction. Hence
the key to inducing and maintaining the reaction of aluminum with water at room
temperature is the removal of the oxide layer, which can be accomplished in different
ways. The metal can be continuously cut, drilled or ground to expose the non-oxidized
surface to water and hence allowing the reaction to proceed. Also, the metal can be
chemically activated using alloys such as Gallium and Zinc. However, some of the alloys
required are not easily available and are unstable. Also, at high temperatures (using
steam), the reaction proceeds spontaneously. However, the use of steam may not be
viable or safe. Hydroxide ions in alkaline solutions are also able to destroy the protective
oxide layer, resulting in hydrogen production [1].
1.4
Aluminum-Water Reactions with the Assistance of Alkalis
Hydroxide ions (OH-) in alkaline solutions are able to destroy the protective oxide
layer on the aluminum surface, forming AlO2-. As a result, aluminum and its alloys
readily dissolve in the alkaline environment even at room temperature, resulting in
hydrogen production. Among different alkalis, sodium hydroxide (NaOH) is the most
commonly encountered and has been found to have the fastest aluminum consumption
time, with the following series of reactions:
2Al + 6H2O + 2NaOH  2NaAl(OH)4 + 3H2
(Rxn 1)
NaAl(OH)4  NaOH + Al(OH)3
(Rxn 2)
2Al + 6H2O  2 Al(OH)3 + 3H2
(Rxn 3)
3
NaOH depleted for the hydrogen evolution in Reaction (1) will be regenerated
through the NaAl(OH)4 decomposition in Reaction (2). Therefore, essentially, only water
is consumed during the whole process if the reaction is properly controlled. Adding steps
(1) and (2) together yields the overall reaction as expressed by Reaction (3). It should be
noted that highly concentrated solutions of NaOH are extremely corrosive and are
generally not considered suitable for H2 production in vehicles or household power
systems [1].
The molar masses of aluminum, water and NaOH are 27 g/mol, 18 g/mol and 40
g/mol respectively. Hence, in terms of mass, the stoichiometric ratio is:
Aluminum : Water : NaOH
2:4:3
The activation energy for the Aluminum - Aq. NaOH reaction has been reported
in the range of 42.5 kJ/mol to 68.4 kJ/mol [1] and the heat of reaction as 15.4 kJ/ g-Al
[2]. The byproduct of the reaction, Al(OH)3 can be used for water purification, as well as
for recovering the aluminum for reuse [3].
As reported in literature, the optimum temperature and NaOH concentration in
order to achieve a high rate of hydrogen generation was 70-90 º C and 5.75 mol/dm3
respectively. At these temperatures and concentrations, the reaction proceeded in a
controllable manner and the mass of NaOH and water required was minimized. Other
factors affecting the rate of reaction include the morphology of aluminum, initial
quantities of reactants, concentration of aluminate ions in solution, metal pretreatments,
mixing conditions, alloys, and base solution used [1].
4
Since this is a surface-based reaction, larger reactant surface area would be
expected to result in higher reaction rates. Hence, the use of aluminum nanoparticles is of
great interest [4].
5
CHAPTER 2
LITERATURE REVIEW
The aluminum-water reaction for hydrogen generation with the assistance of
alkalis has been well-studied and reported in articles in numerous technical journals.
2.1
Overview of Selected Papers
Belitskus reported on experiments conducted on the Aluminum - Aq. NaOH
reaction as far back as 1970 [2]. This paper is an excellent resource for both qualitative
and quantitative information about the factors which affect the rate of reaction, including
the question of how the relative rates of Reaction (1) and (2) (see section 1.4) affect
overall hydrogen production. The author used large “ingots” of Al. powder, as well as
compacted pelletized powder for his study. Standard quantities were 0.2 g of aluminum
and 200 ml of NaOH. The author reports that 0.2 g of high surface area powder in 1M
NaOH proceeded to completion (275 ml) in 10 minutes. The rate of hydrogen generation
was directly proportional to the sample size used, and the delay in evolution increased
with the reduction in surface area of the powders. When aluminum and solid sodium
hydroxide were added to the water without mixing, the generation of hydrogen was as
rapid as when NaOH was pre-dissolved. The author notes that gas evolution rates
decreased with increasing density of the pellets and that pellet density was more
important than surface area in determining the rate of reaction. The author also conducted
6
experiments with low solution volume to observe the effect of reaction heat. Reducing
the solution down to 25 ml and using 2M or 3M NaOH solutions resulted in localized
boiling of water, while the bulk temperature rose to above 70 ºC. Also, the reaction delay
time decreased with increased concentration. The author notes that if the stoichiometric
amount of NAOH is not present, the relative rates of reaction (1) and (2) play a part in
determining the rate of hydrogen evolution (See Section 1.4 for reactions). According to
the author’s study, reaction (2) is not sufficiently rapid to sustain initial gas generation
rates, and hence (2) is the rate-limiting step. However, slow generation can continue even
with a lower sodium hydroxide to aluminum ratio [2].
Yu A. Aleksandrov et al. studied the kinetic characteristics and mechanism of the
reaction of aluminum powder and foil with dilute NaOH solutions [5]. While this work is
extremely useful for qualitatively understanding many of the factors affecting the rate of
the reaction, it should be noted that the authors used extremely dilute concentrations of
NaOH solutions. This paper reports results and analyses, but unfortunately makes very
little mention of the experimental setup used, which could have been instructive for the
present study. As reported by the authors, the reaction stoichiometry is strictly constant
according to the experimental data. Hence, the progress of the reaction can be monitored
by the liberated hydrogen and side reactions can be ignored. The kinetic curves of the
reaction are S-shaped, and the reaction rate is maximal at 20% conversion. The rate
decreases to a steady state level (rate of the developed process) after the completion of
the induction period. The induction period can be shortened by mechanically polishing
the metal. The products of the reaction also affect the hydrogen liberation rate: Aluminate
ions accumulated in solution inhibit hydrogen liberation, which explains the kinetics at
7
high conversions. The maximal reaction rate is a linear function of the initial aluminum
weight, and hence the reaction is first order with respect to aluminum. Stirring the
reagents does not have any effect on the rate of hydrogen generation. The authors also
derive temperature-dependence and rate equations for the reaction and attempt to provide
a graphical description of the reaction mechanism. In summary, all conclusions drawn by
the authors in this paper are supported by well-presented data.
C.R Jung et al. reported experimental results for a micro-fuel processor with
aluminum and water as reactants, developed in a flow-reactor [6]. Two types of reactors
used by the authors were discussed: One reactor permits the direct feeding of liquid water
in channels containing aluminum pellets, whereas the other utilizes the heat produced
from the reaction to vaporize liquid water before entry into the reactor. The authors use
aluminum powder “pelletized” under pressure, and also use CaO alongside NAOH as a
catalyst. The system developed was fully automated with a flow meter, gas analyzer etc.
interfaced with a computer for data collection and monitoring. Data is provided for the
total volume evolved as well as the rate of evolution using different concentrations and
amounts of NaOH, CaO, as well as different pressures for the pelletization. The authors
note that using high concentrations of NAOH makes it difficult to control the reaction
and reduces the aluminum into powder form which blocks the channels of the reactor.
They used a constant liquid flow rate of 12 ml/hr and used a cold trap to condense out
liquid from the hydrogen produced. The aluminum was pelletized using a hydraulic press
and the applied pressure affected the rate and amount of hydrogen evolved. With
vaporized NaOH, the reactants were more uniformly distributed over pellets and this
increased the penetration capability and hence the rate of reaction. One useful fact noted
8
in the paper is that the CO2 emissions of hydrocarbon cracking to obtain hydrogen are
about 7 tonnes of CO2 per ton of H2.
The United States Department of Energy (US-DOE) released a study in 2008 on
the Aluminum-Water reaction for hydrogen generation [7]. The purpose of this paper is
to describe and evaluate the potential of aluminum-water reactions for the production of
hydrogen for on-board hydrogen-powered vehicle applications. While the direction and
all conclusions drawn by the authors are geared towards the specific application of onboard vehicle power generation, the report is nonetheless very useful for the present
study. This is one of the few papers that discusses the various design criteria and
parameters required for a workable aluminum hydrogen generation system in detail.
The authors note that the 2010 DOE targets for gravimetric and volumetric
hydrogen capacity of H2 generation systems are 6 wt.% hydrogen and 45 grams of
hydrogen per liter respectively. The corresponding parameters for the aluminum-water
hydrogen generation system with a hydroxide promoter are 2.5 wt. % of hydrogen and 35
grams of hydrogen per liter respectively. This paper also contains a detailed section on
“System Considerations” which outlines various factors that need to be considered for
any engineering work based on this reaction. The authors note that further investigations
need to be made in the issues of storing fresh reactants as well as the separation, storage,
loading and unloading of reagents and byproducts. Moreover, they make mention of the
need for developing mechanisms for generating hydrogen in response to variable demand
profiles, as well as employing thermal management systems. The authors also remark that
the most straightforward way to control the reaction would be to control the rate of liquid
9
flow to the metal reactant, while still retaining a buffer storage system for highly variable
loads.
2.2
Hydrogen Generation using Aluminum Nanoparticles
The use of aluminum nanoparticles for the aluminum-water reaction is of
particular interest as the larger reactant surface area could be expected to result in higher
reaction rates [4]. However, one drawback for using aluminum nanoparticles is that at the
nanoscale, the oxide layer makes up a significant proportion of the particle’s mass,
thereby resulting in less “free” aluminum for hydrogen generation. For particles of 50 nm
or less in diameter, the oxide layer could account for up to 60% of the particle’s mass [8].
Bunker et al. have reported results on using aluminum nanoparticles for hydrogen
generation [4]. Instead of using NaOH to remove the aluminum oxide layer, the authors
modified the nature of the protective shell using sonochemistry and created organically
capped particles capable of directly reacting with water. According to the authors, the
percentage of actual aluminum in their particles was about 40% by mass, with the
remainder being made up by the modified shell [4].
The paper reports a tunable hydrogen generation rate from 6.4 × 10-4 to 0.01 g of
hydrogen per second per gram of aluminum. The rate was tunable by controlling the
amount of water in contact with the aluminum particles, thereby controlling the
temperature and heat release of the reaction. As reported by the authors, the hydrogen
evolved by reacting 0.1 g of aluminum and 2 ml of water achieved a pressure of about
300 psi in a 25 ml stainless steel pressure vessel [4].
10
It should be noted that controlling the rate of reaction by varying the volume of
water is less complex in the case described above, as compared to the aluminum-water
reaction assisted by alkalis. This is because in the latter case, the quantity of NaOH
dissolved in the water is also critical for the hydrogen generation rate.
11
CHAPTER 3
SAMPLE FUEL CELL DESIGN CALCULATIONS
For the purpose of illustrating aluminum quantity and hydrogen requirements for
a fuel cell, a 3-Watt Global Positioning System (GPS) unit that requires continuous
power for 72 hours is considered. This chapter presents calculations estimating the
required amount of power for a GPS unit using a Proton Exchange Membrane (PEM) fuel
cell with hydrogen generated from the aluminum-water displacement reaction using
aluminum nanoparticles, and assisted by NaOH.
3.1
Hydrogen Requirements
The total energy input required for the GPS unit over a period of 72 hours is:
3 Watts x 72 hrs = 216 Watt-hrs
Assuming a 90% efficient inverter to provide the appropriate voltage, the energy required
from the fuel cell is about
216 Watt-hrs / 0.9 = 240 Watt-hrs
From the results derived in the Appendix A, 1 liter of H2 can generate about 2.6 Watt-hrs
of electricity at RTP (Pressure = 1 atm, Temperature = 298 K).
Assuming the fuel cell is 50% efficient, the required volume of H2 for the fuel cell at RTP
is about:
12
240 Watt-hrs / (2.6 Watt-hrs / liter-H2 x 0.5) = 185 liters-H2
Including a 20% safety factor:
185 liters-H2 + (20% x 185 liters-H2) ≈ 225 liters-H2
Hence, about 225 liters of hydrogen at RTP are required by the GPS system.
For an on-demand system, the required rate of hydrogen generation would be about:
225 liters / 72 hrs = 3.125 liters/hr
Converting to ml/min:
3.125 liters/hr x 1000 ml /liter / 60 min/hr = 52 ml/min ~ 50 ml/min
Hence, a hydrogen generation rate of about 50 ml/min is required to power a 3-Watt GPS
system.
3.2
Aluminum Requirements
The NaOH-assisted aluminum-water reaction is:
2Al + 2NaOH + 6H2O → 2NaAl(OH)4 + 3H2
Hence, 3 moles of H2 are produced for every 2 moles of aluminum.
At RTP (p = 1 atm, T = 298 K), the number of moles, n, in 225 liters of H2 is given by
the ideal gas law:
n = (p x V) / (R x T)
13
where pressure, p = 1 atm, volume, V = 225 L, temperature, T = 298 K, and R = 0.0821
L-atm/mol-K,
Hence:
n = (1 atm x 225 L) / (0.0821 L-atm/mol-K x 298 K) = 9.2 mols-H2
Hence, the number of aluminum moles required is:
2/3 x 9.2 mols-H2 = 6.1 mols-Al
Given that the molar mass of aluminum is 27 g/mol, the mass of aluminum required is:
6.1 mols x 27 g/ mol = 166 g
At the nano-scale, the naturally occurring passivation layer on the surface of aluminum is
a significant portion of the particle's mass. As mentioned earlier, the passivation layer for
aluminum nanoparticles under 50 nm can make up about 60% of the mass.
Since pure aluminum only makes up 40% of aluminum nanoparticles’ mass, the mass of
aluminum nanoparticles required to generate 225 liters of H2 is about:
166 g x 100 % / 40% = 414 g ≈ 400 g
14
CHAPTER 4
EXPERIMENTAL SETUP AND PROCEDURES
Two different experimental setups were employed for the study of hydrogen
generation from the aluminum-water reaction. A preliminary setup involving rudimentary
apparatus was first used to gain familiarity with the reaction and foreshadow any
potential issues before further experimentation with a more sophisticated system.
Initial experiments were conducted mainly with 1 mm aluminum flakes. Different
alkaline solutions (NaOH vs. KOH), particle quantities (less than 1 g) and solution
quantities (up to 100 ml) were tested.
Subsequent experiments were conducted using two different types of particles:
40-60 nm and 1-3 micron aluminum powder. A constant 15 ml solution of NaOH was
used and the effects of varying particle quantity (0.1 g vs. 0.2 g), NaOH solution
temperature (~25 ºC vs. 35 ºC) and solution concentration (0.5 M, vs. 1 M) were
examined for both kinds of particles.
4.1
Preliminary Experimental Setup and Procedures
The preliminary setup was based on a similar arrangement described by Soler et
al [9]. A schematic of the setup is shown in Figure 1 below.
15
Figure 1. Schematic of Preliminary Experimental Setup
The reactor was a triple-neck 200 ml round-bottomed glass vessel. The reaction
was initiated by introducing aluminum particles through the central vessel neck into the
alkaline solution poured in the vessel from beforehand. After particle introduction, the
neck was immediately corked to prevent any gas leakage. Tubing inserted in one of the
adjacent neck corks routed the evolving hydrogen gas through water into an inverted 250
ml burette. The evolving hydrogen displaced the water in the burette, and the changing
water level in the burette was measured as a function of time. The rate of change of the
water level provided an indication of the rate of hydrogen generation from the reaction,
and the difference between the initial and final water levels in the burette indicated the
total hydrogen yield. For experiments using less than 5 ml of solution, the aluminum
particles were introduced into the empty glass vessel first, and the alkaline solution was
injected into the vessel subsequently.
16
The setup described above was useful for gaining familiarity with the reaction
process, developing preliminary results and providing direction for future avenues of
investigation. However, some of the shortcomings of the system included difficulties in
preventing hydrogen leaks as well as the inherent inaccuracy of the manual process of
recording the changing water level in the burette. To facilitate the recording process, a
computer script was implemented to automatically record the elapsed time interval when
the user entered a volume measurement (See Appendix B). In addition to these issues,
there were no means to purge the air space above the liquid in the reaction vessel.
4.2
Main Experimental Setup and Procedures
4.2.1
Main Experimental Setup
As a result of the inadequacies of the original setup, a new experimental
arrangement was designed and assembled to investigate the reaction. A picture and
schematic of the setup are shown respectively in Figure 2 and Figure 3 below. Appendix
C comprises a list of all critical equipment and reagents used in the experiments, along
with manufacturer name and part numbers.
17
Syringe with NaOH
Flow-meter
Temperature
Controller
Temperature
Logger
Pressure Vessel
Figure 2. Picture of Main Experimental Setup
18
Pressure
Readout
Figure 3. Schematic of Main Experimental Setup
This setup centered on a 40 ml Swagelok pressure vessel. Using 1/8 inch diameter tubing,
a 50 ml stainless steel syringe was used to inject 15 ml of NaOH into the vessel, in which
aluminum powder had been introduced beforehand. An industrial-grade hydrogen
cylinder was connected to the system in order to purge air out before the initiation of an
experiment, ensuring a hydrogen-only environment. A shutoff valve (V1) and a check
valve (CV1) allowed for control of the flow of hydrogen from the cylinder, and ensured
that there was no back flow from the vessel to the cylinder. Using an assortment of
Swagelok fittings, a pressure transducer and thermocouple were positioned inside the
system to measure the pressure and temperature of the evolving gas. An additional
thermocouple was also inserted in the bottom of the vessel to measure solution
temperature, after injection of NaOH. Another shutoff valve (V2) was placed on the right
side of the system, just before an electronic flow-meter. If V2 was closed, no hydrogen
would enter the flow meter and the build-up of gas from the reaction would increase the
19
pressure inside the vessel. If V2 was open, the evolving hydrogen would flow through the
flow-meter, allowing for direct measurements of flow-rates and yields. A check valve
with a nominal rating of 1 psig (CV2) prevented any back flow of air into the system
through the flow meter after purging. An additional shutoff valve (V3) allowed the flow
of NaOH from the syringe, and when closed, ensured that the system was isolated from
the syringe plunger. The syringe was wrapped in heating tape regulated by a bench-top
temperature controller for experiments where initial solution temperature was varied. A
relief valve was also added to the system to manually reduce pressure build-up if
required.
Data from the sensors and flow-meter were automatically logged during the
reaction at one second intervals, using a data acquisition system located next to the
system. The precision and scale of the pressure sensor were 0.01 psia and 1000 psia
respectively, with a reproducibility of 0.5 psia. The precision of the flow-meter was 1
ml/min, with a 0.2% full scale error (full scale = 500 ml/min).
4.2.2
Reagent Preparation
NaOH solutions were prepared using distilled water and standard laboratory
NaOH pellets. Fresh solutions were made up every day experiments were conducted. Due
to safety concerns, required quantities of the aluminum particles were measured inside a
glove-box. The required quantities of powder were then placed inside non-stick gas
chromatography (GC) vials in order to facilitate their introduction into the reactor vessel.
20
4.2.3
Experimental Procedures
After detaching the vessel from the system, the required quantity and type of
particles were introduced into the vessel via the non-stick GC vials. The vials were
measured before and after the introduction of particles to ensure that no residual particles
remained. Next, 15 ml of NaOH solution was drawn into the stainless steel syringe, and
the valve V3 was closed to prevent any liquid from dripping through the tubing
prematurely. The tubing from the syringe extending into the vessel area was wiped dry
before reattaching the vessel to the system, in order to prevent a premature reaction
initiation. After securing the vessel, hydrogen from the cylinder was allowed to flow into
the system. The flow valve V2 was kept closed in order to allow for the pressure inside
the system to build up to about 30 psia. V1 was then closed, and the system was deemed
leak-proof if the pressure remained constant for a whole minute. After ensuring the
system was leak-proof, the hydrogen gas was released through the relief valve. The
process was repeated three times to thoroughly purge the system of air. After ensuring the
logging and proper operation of the sensors, the reaction was initiated by opening V3,
injecting NaOH into the vessel, and then immediately closing V3.
As mentioned earlier, the experimental system was designed to allow for two
different methodologies for investigating the yield and rate of hydrogen generation: (a)
With V2 closed, the evolving hydrogen gas would remain in the system, but would result
in increasing the system pressure during its evolution. Given the validity of ideal gas law,
the pressure and temperature data could be used to calculate corresponding yields and
hydrogen generation rates. (b) With V2 open, the second method would allow the
21
evolving gas to pass directly through an electronic flow-meter (which operated based on
thermal conductivity measurements of the gas flow).
Most of the experiments conducted in this work utilized the first method, though
additional runs were conducted using the flow-meter method for corroboration purposes.
The reaction was deemed complete (typically within ten minutes) after the system
pressure remained constant or the flow-meter indicated zero flow. The vessel was then
detached from the system, rinsed and dried in an air stream before the introduction of
aluminum particles for the next experiment.
4.2.4
Evolution of the Experimental System Design
The system and procedures described above went through a number of
evolutionary steps before a final working design was established. Initially, a separate port
had been machined into the vessel to facilitate the aluminum powder introduction.
However, due to great difficulties in ensuring that the area around the additional
machined port was leak-proof, this idea was abandoned in favor of the current setup.
Also, a syringe pump was initially employed to introduce NaOH into the system.
However, due to the presence of high system pressures which would have required costly
and high-end syringe pumps to inject the NaOH at a reasonable rate into the system, the
manual method of injection was finally decided upon. Also, in order to facilitate the
manual injection, the syringe tubing size was changed from 1/16th to 1/8th inch diameter.
The “pressure” method as opposed to the “flow-meter” method was also decided upon, as
the expected rates of hydrogen generation during the experimentation phase were
uncertain. Consequently, costly and non-robust instruments such as electronic flow-
22
meters could run the risk of being damaged upon experiencing flow-rates beyond their
range of operation.
23
CHAPTER 5
RESULTS AND ANALYSES FOR PRELIMINARY EXPERIMENTS
Using the triple-neck glass vessel reactor setup described in Section 4.1, multiple
experiments were conducted in order to gain familiarity with the reaction under
consideration, confirm basic trends described in literature, and draw qualitative
conclusions about certain factors affecting the rate and yield of the reaction.
5.1
Results and Analyses from Preliminary Experiments
Figure 4 below shows a comparison between the evolution curves of the hydrogen
volume as a function of time when using NaOH and KOH. Both runs were conducted
using 0.1 g of 1 mm aluminum flakes in 100 ml of 5 M alkaline solution.
24
Figure 4. Comparision between NaOH and KOH
The rate of the reaction can be gauged from the slope of the evolution curve,
where steeper slopes indicate faster reactions, and vice versa. As is evident from the
graph above, using NaOH as opposed to KOH results in a better rate profile. This is in
accordance with the literature pertaining to the subject.
Figure 5 below illustrates the differences in reaction rate as a function of solution
quantity. All runs were conducted using 0.1 g of 1 mm aluminum flakes in a 5 M NaOH
solution.
25
Figure 5. Effect of reducing solution quantity on reaction rate
When reducing the solution volume from 100 ml to 50 ml, the rate of reaction
decreases (as indicated by the slope of the curves). However, on further reduction to 10
ml and 1 ml solutions, the reaction rate increases, with the 1 ml solution run resulting in
the highest rate. This can possibly be explained by two factors: temperature and reagent
quantity. When the solution quantity is reduced, there is less water and NaOH to react
with a given quantity of aluminum. However, with the reduction in solution quantity, the
heat produced by the reaction results in increasing solution temperature (the same amount
of heat transferred to a smaller volume will cause a greater rise in temperature), which
increases the reaction rate. As is evident from the graph, the reduction in reagent
availability is a larger factor than the temperature increase when the solution volume is
reduced from 100 ml to 50 ml, and hence the rate decreases. However, on further
reduction of solution volume to 10 ml and 1 ml, the rate of reaction increases as the
26
increase in temperature is a larger driving factor compared to the reduction in reagent
quantities.
Figure 6 below shows the results of further decreasing the solution quantity, while
keeping other factors constant.
Figure 6. Effect of using insufficient NaOH on reaction rate
In order to maintain stoichiometric proportions, 0.1 g of aluminum requires 0.2 g
of water and 0.15 g of NaOH. However, 0.5 ml of 5 M NaOH solution only contains 0.1g
of NaOH, which is below the stoichiometric requirements. As was reported by Belitskus
[2] and noted in the Literature Review section, in the three-sequence aluminum-water
reaction, the regeneration of NaOH from NaAl(OH)4 is the rate-limiting step. This is
clearly evident from the graph above, which shows the non-optimum rate profile when
the stoichiometric NaOH proportion is not maintained.
27
Figure 7 below shows the effect of doubling the aluminum quantity on the rate
and yield of the reaction. Both runs were conducted with a 5 M NaOH solution.
Figure 7. Effect of increasing aluminum quantity on the rate and yield of reaction
As indicated by the figure above, increasing the aluminum quantity results in both
increased rates and yields. As reported by Aleksandrov et al [5] and noted in the
literature review, the reaction rate is first-order with respect to aluminum quantity.
5.2
Concluding Remarks on Preliminary Experiments
The discussion and analysis of the preliminary results is qualitative in nature and
was more focused on the rate of reaction as opposed to total yields. Nonetheless, the
experiments were useful in providing guidance for future avenues of investigation.
However, it should be noted that in some of the preliminary experiments, the total yield
28
of hydrogen measured was more than the theoretical maximum for the given amount of
aluminum, as shown below:
The reaction is noted below again for the sake of convenience:
2Al + 6H2O  2 Al(OH)3 + 3H2
The number of moles in 0.1 g of aluminum is given by:
0.1g-Al / 27 g /mol-Al = 0.00371 mols-Al
The corresponding number of moles of hydrogen generated is:
0.00371 mols-Al x 3 mols-H2 / 2mols-Al = 0.00556 mols-H2
The resulting mass of hydrogen is:
0.00556 mols-H2 x 2 g /mol- H2 = 0.0112 g
At RTP (T = 298 K, P = 1 atm), using ideal gas law, the resulting volume is given by:
V = nRT/p = 0.00556 mol x 0.0821 L-atm/mol-K x 298 K / 1 atm = 136 ml
Given the precision of the weighing apparatus (to the nearest 0.01 g), used to
measure the aluminum, a measured quantity of 0.1 g could lie between 0.095 g and
0.0105 g. The corresponding uncertainty in the theoretical volume calculation would
result in a volume range of 136 ± 7 ml.
For the case of using a measured quantity of 0.2 g of aluminum, the
corresponding volume range is 272 ± 7 ml.
29
However, as indicated in the graphs above, volumes in excess of 150 ml were
measured when 0.1 g of aluminum was used. It was surmised that the increase in volume
could be due to impurities in the reagents, which resulted in the evolution of additional
gases. Moreover, a pressure equilibration process with the atmosphere (air could have
leaked in from the burette knob) may have also contributed to a lower water level in the
burette, and hence a higher hydrogen volume measurement. In either case, the issue was
not explored further with the current experimental setup. However, while the experiments
provided good qualitative indications of trends, using the data for quantitative purposes
would be inappropriate without addressing the excess volume issue.
30
CHAPTER 6
RESULTS AND ANALYSES FOR MAIN EXPERIMENTS
Based on research goals and the results of the preliminary experiments, the effects
of aluminum quantity, particle size, initial solution temperature and solution
concentration on the rate and total yield of the aluminum-water reaction were deemed of
interest.
With the objective of developing an empirical model of the effects of the four
factors on the response variables, a single replicate two-level full factorial experimental
design (all possible combinations of two levels of the different factors are tested)
consisting of 16 experiments was proposed. In addition to model development for
prediction purposes, the “factor-screening” experimental results provided quantitative
information about the relative importance of the different factors and their effects on the
yield and rate of reaction. A trial version of the Design Expert 8.0 software was used for
the analysis of the results.
6.1
Choice of Factor Levels
Table 1 below shows the different factor levels chosen for the experiments and
Table 2 shows the resulting test matrix, with low levels represented by (-1) and high
levels represented by (1) for ease of reading.
31
Table 1. Factor Levels for Screening Experiment
Factor
A_Aluminum Quantity
B_Particle Size
C_Starting Solution Temperature
D_Concentration
Low Level (-1)
0.1 g
40-60 nm
~25 °C
0.5 mol/dm3
High Level (+1)
0.2 g
1000-3000 nm
35 °C
1 mol/dm3
Table 2. Experimental Test Matrix
Experiment # A_Quantity (g) B_Size (nm) C_Temperature ( °C ) D_Concentration (mol/dm3)
1
-1
-1
1
1
2
1
-1
1
1
3
-1
1
1
1
4
1
-1
1
-1
5
-1
1
1
-1
6
-1
-1
1
-1
7
1
1
1
1
8
1
1
1
-1
9
-1
-1
-1
-1
10
-1
-1
-1
1
11
1
-1
-1
-1
12
-1
1
-1
-1
13
1
-1
-1
1
14
1
1
-1
1
15
1
1
-1
-1
16
-1
1
-1
1
All experiments were conducted using a 15 ml solution volume of NaOH. Initially
the solution volume was also noted as a factor of interest. However, for the two reasons
outlined below, varying the solution volume was not implemented in the final test matrix:
1) Successfully injecting more than 15 ml of NaOH in the reactor was extremely difficult,
given the immediate pressure build-up in the reactor system. On the other hand, injecting
32
less than 15 ml would have resulted in insufficient NaOH for certain combinations of the
factors, which was not a region of interest for the experimentation.
2) The solution volume can be expected to impact the yield and rate due to either the
temperature effect, or the reagent quantity effect as outlined earlier in Section 5.1.
However, information about both possible solution effects can be derived from the
current matrix by varying the starting solution temperature and concentration.
Nonetheless, the results and conclusions from the experiments can only be said to
hold for the constant volume case.
The choice of the factor levels was inspired by both research goals and
experimental limitations. Micron-sized powder was chosen as the standard to compare
the nanopowder against because the aluminum flakes used earlier have relatively low
reaction rates for the given solution concentrations (See Section 7.4). The higher starting
solution temperature level of 35 ºC was chosen as larger temperature values resulted in
uncontrollable reactions during trial runs. The approximate ten degree difference between
35 ºC and room temperature was considered significant enough to evaluate the
temperature effect, and this supposition was supported by the experimental results. The
particular combinations of solution concentration and aluminum quantity were selected
given the size of the 40 ml reactor and the solution volume injected. For example, using a
lower concentration than 0.5 M would have resulted in the requirement for higher
solution volume in order to maintain the minimum stoichiometric ratios, which was not
favorable. As most reactions achieved completion within ten minutes, using higher
concentrations was also not viewed as favorable or necessary.
33
6.2
Determination of System Volume
As mentioned in Section 4.2.3, the rate and yield of hydrogen generated was
calculated using the ideal gas law and temperature and pressure measurements made on
the system. However, the total system volume (40 ml reactor vessel and additional
fittings and tubing) needs to be known accurately to employ this method.
In order to calculate the system volume, selected volumes of air were injected into
the system using a syringe. Next, using the fundamental gas relation, P1V1 = P2V2, the
volume of the system was calculated by the pressure rise after the injection of air.
For example, when 20 ml of air at atmospheric pressure (14.3 psia) was injected
into the system, the pressure rose from 15.8 psia to 21.4 psia. The system volume is
hence given by:
V = 20 ml x 14.3 psia (21.4 psia – 15.8 psia) = 51 ml
The process was repeated with two more injection volumes. Table 3 below shows the
results of the three experiments.
Table 3. System Volume Determination
Vol. Air Injected (ml) Air Pressure (psia) Orig. Sys. Pressure (psia) New Sys. Pressure (psia) Sys.Vol. (ml)
20
14.3
15.8
21.4
51
30
14.3
15.5
23.9
51
40
14.3
15.5
26.7
51
Hence, the system fittings and tubing added 11 ml of volume, for a total system
volume of 51 ml.
34
6.3
Example of Data Analysis Methodology
To illustrate the data analysis methodology for calculating the total yield and rate
from temperature and pressure measurements, Experiment 1 is considered as an example.
Figure 8 below shows raw temperature and pressure data from reacting 15 ml of 1M
NaOH at 35 ºC with 0.1 g of nanopowder.
Figure 8. Raw Temperature and Pressure Data for Experiment # 1
T1 represents the solution temperature, T2 represents the measured gas
temperature, and T3 represents the room temperature during the run time. As is evident
from the graph, and as was noted in Chapter 2, the kinetic curves for the reaction (as
represented by the pressure profile) are S-shaped. There is a brief induction period,
before the initiation of steady state period, during which the pressure rose to about 60
psia. For the above case, the reaction was completed within two minutes.
As can be seen in the graph, the initial solution temperature was between 30 ºC
and 35 ºC. While the syringe was maintained at 35 ºC for the elevated temperature runs
35
using a controller, the solution may have lost heat in the tubing section from the syringe
to the reactor, resulting in a slightly lower temperature. The solution temperature rose to
just under 40 ºC, before gradually decreasing. The rise in temperature coincided with the
high pressure-rise period of the reaction. The gas temperature loosely followed the
solution temperature profile, but with relatively milder temperature gradients. This is to
be expected as the thermal conductivity of gases is relatively low compared to liquids.
The room temperature remained relatively constant at around 23 ºC.
The reaction profile for Run #1 described here is typical of most of the
experimental runs, albeit with different values.
Using the temperature and pressure data, and the system volume of 51 ml, the
ideal gas law was used to determine the number of moles of hydrogen gas evolved from
the reaction. It should be noted that three additional adjustments were made to the data:
1) The system volume was adjusted down to 36 ml in order to account for the 15 ml of
NaOH solution injected from the syringe. The solution volume was validated postexperiment by measuring the volume of liquid remaining in the reactor.
2) The initial number of moles of hydrogen present in the system (due to the purging
process) was subtracted from the final count.
3) The initial pressure rise (due to the injection of NaOH) moved the baseline higher
from the pre-injection pressure, before the evolution of hydrogen began. This was simply
accounted by subtracting the new baseline from the calculations.
Table 4 below shows a small sample of the spreadsheet calculations described above.
36
Table 4. Example of Data Analysis
Time
Pressure (atm) T2_gas (K) Mols
Mols Adj V at RTP (ml) Vol Adj (ml)
18
1.44
298.9 0.002106 0.000647
15.83
0.83
19
1.48
298.9 0.002168 0.000709
17.34
2.34
20
1.54
298.9 0.00226 0.000801
19.59
4.59
21
1.58
299.1 0.00232 0.000861
21.07
6.07
To illustrate the process further, the first row of the calculations in the table above
is considered:
At a pressure of 1.44 atm and a temperature of 298.9 K, the number of moles of
hydrogen as given by the ideal gas law is:
n = pV/RT = 1.44 x (51 -36) / (0.0821 x 298.9) = 0.002106 mols (Units omitted)
The initial 0.001459 moles of hydrogen present in the system after the purging
process and before the initiation of the reaction are subtracted, leaving 0.000647 moles of
hydrogen generated by the reaction up to this point.
Next, the adjusted number of moles is converted to volume values at RTP (T =
298 K, P = 1 atm):
V = nRT/p = 0.00647 x 0.0821 x 298 / 1 = 0.01583 liters = 15.83 ml
(Units omitted)
The graph of the nome-baseline-adjusted cumulative volume for Run 1 is shown
in Figure 9 below.
37
Figure 9. None-baseline adjusted hydrogen volume profile for Experiment #1
From the spreadsheet calculations, and as is depicted in the graph above, the
initial 15 ml of the volume rise shown coincides with the injection of 15 ml from the
syringe, and should not be attributed to hydrogen generation from the reaction.
Subtracting the baseline of 15 ml from 15.83 ml results in 0.83 ml, as indicated in
Table 4 above. Figure 10 below shows the final baseline-adjusted volume profile for
Experiment # 1.
Figure 10. Baseline-adjusted hydrogen volume profile for Experiment # 1
38
It should be noted that the last adjustment of subtracting the new baseline value is
also required when using the flow-meter method described earlier, instead of the
pressure-method.
After the development of volume profile, the total yield was taken as the
maximum volume generated (94 ml for Experiment # 1). The rate was calculated by
determining the volume at the 25th and 75th percentiles of the final volume, and
calculating the gradient with respect to time.
For example, for Experiment #1, the rate calculation was as follows:
Rate (ml/s) = (71 ml – 22.5 ml) / (48 s – 29 s) x 60 s/min = 153 ml/min
6.4
Summary of Results
Using the methodology outlined in the previous section, values for total yield and
reaction rate were calculated for all sixteen experiments. Table 5 below summarizes the
results for the experiments, whereas Table 6 on the next page provides further
information on the maximum solution and gas temperatures, initial room temperature,
average room temperature and maximum system pressure for each experiment. In
addition, two columns also highlight the difference between the maximum solution and
gas temperatures and the average room temperature.
39
Table 5. Yield and Rate Results for Test Matrix
Experiment # A_Quantity (g) B_Size (nm) C_Temperature ( °C ) D_Concentration (mol/dm3)
1
-1
-1
1
1
2
1
-1
1
1
3
-1
1
1
1
4
1
-1
1
-1
5
-1
1
1
-1
6
-1
-1
1
-1
7
1
1
1
1
8
1
1
1
-1
9
-1
-1
-1
-1
10
-1
-1
-1
1
11
1
-1
-1
-1
12
-1
1
-1
-1
13
1
-1
-1
1
14
1
1
-1
1
15
1
1
-1
-1
16
-1
1
-1
1
Yield Rate
(ml) (ml/min)
94
153
181
435
147
133
178
252
121
67
82
79
278
388
260
217
73
44
89
81
178
162
132
50
183
279
270
286
254
144
145
72
Table 6. Additional Information on Experimental Runs
Experiment # Max Sol. Temp
( °C )
1
36.9
2
43.3
3
41.1
4
44.4
5
38.7
6
35.9
7
48.9
8
48.2
9
31.1
10
33.0
11
39.5
12
34.1
13
42.2
14
45.8
15
42.4
16
35.8
Max Gas
Temp ( °C )
27.6
30.3
29.6
31.6
30.2
28.1
31.2
32.0
26.4
27.8
29.6
27.8
30.5
31.0
30.2
27.5
Initial RT Avg. RT Max Pressure Max Sol. Delta T Max Gas Delta T
( °C )
( °C )
(psia)
( °C )
( °C )
23.7
24.1
59.3
12.8
3.5
24.1
24.1
95.5
19.2
6.2
25.6
24.4
81.4
16.7
5.2
25.7
24.6
94.5
19.8
7.0
25.6
25.1
71.3
13.6
5.1
24.5
24.2
54.6
11.7
3.9
23.9
24.0
136.6
24.9
7.2
25.6
25.4
128.6
22.8
6.6
25.7
25.5
50.6
5.6
0.9
25.8
25.8
57.8
7.2
2.0
24.7
24.1
94.2
15.4
5.5
25.9
26.0
75.4
8.1
1.8
24.7
24.3
97.1
18.0
6.2
24.2
24.2
133.7
21.6
6.8
25.5
26.6
125.3
15.8
3.6
23.9
23.8
81.4
12.0
3.7
40
6.5
Discussion and Analysis of Yield Results
Figure 11 below shows the calculated yield values as a function of the calculated
rate values. The diamonds and crosses are the experiments which used 0.1 g and 0.2 g of
aluminum respectively.
Figure 11. Yield as a function of rate
As can be seen from the spread of data in the graph above, lower yields are
correlated with lower reaction rates, and vice-versa. Usage of a larger quantity of
aluminum results in higher yields as well as higher reaction rates. This is to be expected
because employing a greater quantity of aluminum particles allows for proportionally
greater displacement of hydrogen from water, assuming the water is in excess (as was the
case for all experiments).
Figure 12 below shows the yield values as a function of particle quantity, with the
cross and diamond points indicating runs with micron-sized and nano-sized particles
41
respectively. Other than the already-mentioned trend of higher yields for higher particle
quantities, the graph below also shows that micron particles perform consistently better
than the nanoparticles in terms of yield, given the same aluminum quantity.
This is an extremely important finding and as reported in Chapter 2, the results
can most probably be attributed to the fact that the percentage of “free” aluminum in a
given mass of nano-sized particles is lower due to the oxide layer making up a larger
proportion of the mass.
Figure 12. Yield as a function of particle quantity
Figure 13 and 14 below show the yield values as a function of temperature and
concentration respectively, with the cross and diamond points signifying runs with 0.2 g
and 0.1 g of aluminum particles respectively.
42
Figure 13. Yield as a function of temperature
Figure 14. Yield as a function of concentration
As is evident from Figure 13, the yield does not appear to be affected by changes
in temperature for the experiments performed. However, a very slight correlation
between increased concentrations and increased yields can be evinced from Figure 14.
One possible explanation for this is that higher concentration levels of NaOH reduce the
build-up of aluminate ions in the solution, by ensuring that Reaction (1) is dominant in
the sequence as opposed to the rate-limiting Reaction (2). As reported by Aleksandrov [5]
43
and noted in the Literature Review, aluminate ions in the solution have an adverse effect
on the yield. Hence, at higher concentration levels, the reaction proceeds extremely
swiftly, and the yield-inhibiting aluminate ion build-up is relatively low.
Using Design Expert 8.0, a model was developed for the yield data with respect to
the different factors investigated (See Appendix D for ANOVA details). Coded factors (1 for low and 1 for high) were used for developing the regression model as they are nondimensional and provide a better indication of the relative magnitudes of the factor
effects.
Figure 15 below is a screenshot of the results of the ANOVA table used to
develop a mathematical model of yield as a function of the four factors considered.
Figure 15. ANOVA Results for Yield
The developed regression model is:
44
Yield = 166.56 + 56.19A + 34.31B + 6.81D + 8.44AB
where A is the particle quantity level, B is the particle size level and D is the
solution concentration level. The Pred-R-square value for this model is 0.99.
According to the model, the particle quantity, A, has the largest effect on the total
yield, which was expected for reasons described earlier. The particle size, B, also has a
significant effect on the total yield: the larger sized particles performed better. It is
pertinent to mention that two-level factor screening experiments do not provide any
indication of non-linearity, and physical knowledge of the process along with subjectmatter expertise is absolutely necessary before the interpretation of the statistical results.
From knowledge of the physical process, it was deduced that the reason behind the
relatively poorer performance of the nanoparticles in terms of yield is due to the oxide
layer effect. However, when comparing larger particle sizes with each other, we would
not expect the size level to significantly affect the total yield. Moreover, it is extremely
unlikely that the yield increases linearly with the particle size level, even in the region
tested. The results of the regression model are only applicable within the boundaries of
the factor levels tested, and also, additional experimentation is required to determine nonlinearity in factor effects.
As discussed earlier, the solution concentration level, D, is also noted to have an
effect on the total yield and the model also indicates a minor positive interaction effect
between the particle size A and quantity B.
Figure 16 below shows how the yield regression model matches with the actual
data points.
45
Figure 16. Predicted yield vs. actual yield
The developed regression model is predicated on the assumptions that the
residuals are normally distributed and the observation variances are relatively constant.
Figure 17and 18 below indicate that these assumptions are justified.
46
Figure 17. Normal plot of residuals for yield
Figure 18. Residuals vs. predicted for yield
47
6.6
Discussion and Analysis of Rate Results
Figure 19 below shows the rate values as a function of particle quantity, with the
cross and diamond points indicating runs with high and low solution concentrations
respectively.
Figure 19. Rate as a function of particle quantity
Two trends can be evinced from the graph above. Larger particle quantities and
larger solution concentrations both have a favorable effect on the rate. As mentioned
earlier, the physical explanation for the results is that larger quantities of aluminum and
NaOH allow for more reaction sites, given that water is already present in sufficient
quantity.
Figure 20 below shows the rate values as a function of particle size with the cross
and diamond points signifying runs with high and low concentrations respectively.
48
Figure 20. Rate as a function of particle size
The graph above indicates a slightly negative correlation between particle size
and rate. That is, the larger micron-sized particles have a less favorable rate profile as
compared to the smaller nano-sized particles.
Further insight can be developed about this trend from physical knowledge
of the reaction process. As indicated in an earlier section, one of the main reasons for
investigating aluminum powder on the nano-scale was the expectation that the greater
surface area resulting from smaller sized particles would lead to more favorable reaction
rates. However, given that the area of the nanopowder is on the order of 2000 times more
than the area of the micron particles, the only marginally better rate profile for the nanoparticles does not appear to justify the extra cost and safety hazards associated with
nanopowder.
However, one extremely pertinent caveat to be noted is that “similar to similar” is
not being compared in the above graph, due to the nanopowder oxide layer effects. As
already noted, a nominal 0.1 g quantity of aluminum nanopowder does not actually
49
comprise 0.1 g of aluminum, as the oxide layer is known to make up to 60% of the mass.
Hence, given that lower aluminum quantities result in lower reaction rates, the favorable
effect of smaller particle sizes on the rate is greatly underestimated by the data, unless
oxide layer effects are accounted for. However, despite the lower actual aluminum
quantity in the nanopowder, the rate values are still more favorable as compared to the
micron-powder.
Figure 21 below shows the rate values as a function of the temperature levels,
with the cross and diamond points symbolizing runs with higher and lower concentrations
respectively. As expected, elevated solution temperatures result in higher rate values.
Figure 21. Rate as a function of temperature
Figure 22 below shows the rate values as a function of the concentration levels, with the
cross and diamond points symbolizing runs with higher and lower particle quantities
respectively. For reasons described earlier, and as expected, elevated concentrations
result in higher rate values.
50
Figure 22. Rate as a function of concentration
Using Design Expert 8.0, a regression model was developed for the rate data with
respect to the different factors investigated (See Appendix E for ANOVA details). Coded
factors (-1 for low and 1 for high) were used for developing the regression model as they
are non-dimensional and provide a better indication of the relative magnitudes of the
factor effects.
Figure 23 below is a screenshot of the results of the ANOVA table used to
develop a mathematical model of the reaction rate as a function of the four factors
considered.
51
Figure 23. ANOVA table for reaction rate
The developed regression model is:
Rate = 177.63 + 92.75A -8.00B + 37.88C + 50.75D + 14.75AC + 25.88AD +
11.00CD
where A is the particle quantity level, B is the particle size level, C is the starting
solution temperature and D is the solution concentration level. The Pred-R-square value
for this model is 0.98.
According to the model, the particle quantity, A, has the largest effect on the rate,
followed by the concentration, D, and the temperature, C. As noted earlier in the
discussion, the particle size level, B, has a relatively smaller, but still significant effect on
the rate, with the use of the nanopowder resulting in higher rates.
The rate model is decidedly more complex than the yield model, with a number of
interactions between the factors also playing an important role in the determination of the
52
reaction rate. However, the main effects are generally more important and larger in
magnitude than the interaction effects. The size effect is the smallest in magnitude among
the main effects. However, as mentioned earlier, this is misleading due to the lower
percentage of “free” aluminum in the nanopowder, and other things being equal, the
actual size factor effect is probably significantly larger, as discussed in the next section.
The solution concentration effect is the most significant factor after the quantity level.
This indicates that for a given quantity of aluminum, varying the solution concentration is
one possible way of controlling the reaction rate.
Figure 24 below shows how the rate regression model matches with the actual
data points.
Figure 24. Predicted rate vs. actual rate
53
As was the case with the yield model, the developed rate regression model is
predicated on the assumptions that the residuals are normally distributed and the
observation variances are relatively constant. Figure 25 and 26 below provide a check on
these assumptions.
Figure 25. Normal Plot of Residuals for Rate
54
Figure 26. Residuals vs. Predicted for Rate
The above graph shows that the magnitude of the residuals increases as the
observation magnitude increases. This is due to the fact that at higher rate values, the
time interval over which the rate is calculated is relatively smaller, hence resulting in
larger variations and uncertainties. However, as the ANOVA F-test is robust to the
constant variance assumption when a balanced experimental matrix is employed, the
resulting regression model is still deemed adequate.
55
6.7
Further Discussion of Results
The regression models developed from the experimental data can provide
extremely useful information with regards to the design of on-demand hydrogen
generation systems for fuel cell applications. While the effect of the different factors
investigated on the reaction rate and yield may have already been qualitatively
understood, the mathematical model provides greater insight by quantifying the relative
magnitudes of the different effects. For example, a design constraint on a system
employing the reaction under study may involve the minimization of the use of high
concentrations of NaOH to prevent corrosion issues. Using the regression model, the
effect of reducing solution concentrations can now be quantitatively predicted.
Nonetheless, it should be noted that a factor screening experiment is just the first step in
the process of sequential experimentation. Moreover, the regression model can only be
considered valid within the considered factor ranges. The next logical step would be to
augment the test matrix with center points and design points outside the initial factor
ranges in order to test for non-linearity of factor effects, hence enhancing the accuracy
and prediction power of the developed model.
A minor point of concern is that the calculated yields for Experiment # 3 and
Experiment #16 were 147 ml and 145 ml respectively (both runs used 0.1 g of micron
particles), whereas as noted earlier in Section 5.2, the theoretical maximum yield for
hydrogen for both experiments is 143 ml (given the precision uncertainty of the weighing
apparatus). However, given that the errors are under 3%, and that the volume calculations
56
are sensitive to the uncertainties in the solution volume, temperature and pressure
measurements, the differences can be safely attributed to experimental uncertainty.
As mentioned in Chapter 2, a tunable hydrogen generation rate from 6.4 × 10-4 to
0.01 g of hydrogen per second per gram of aluminum was reported by Bunker et al in
their study of organic-capped aluminum particles [4]. The paper noted that the reaction
rate was controlled by adjusting the volume of water reacting with the particles.
For the nanoparticle experiments described in this work, the hydrogen generation
rates ranged from 44 ml/min to 435 ml/min, depending on the levels of the particle
quantity, solution temperature and concentration. After normalizing by grams of
aluminum and converting units, the resulting rate range is from 6.0 x 10-4 to 4.0 x 10-3
grams of hydrogen per second per gram of aluminum. While the lower ends of the two
ranges are comparable, the higher end of the range reported by Bunker is greater than the
results reported in this work by a factor of three.
No strong inferences can be drawn from the comparison in ranges as different
methodologies were employed to achieve control over the hydrogen generation rate.
While this work did not rigorously study the effects of changing solution volume on the
reaction rate or yield, results are nonetheless reported for an experiment with 10 ml, as
opposed to 15 ml of NaOH (See Section 7.3).
As noted earlier, a nominal quantity of 0.1 g of aluminum nanopowder does not
actually have 0.1 g of “free” aluminum, due to the oxide layer effect. This is further
supported by the fact that unlike the micron particles, the calculated yields for the
nanopowder do not approach the 100% yield limit (136 ml). However, employing the
57
assumption that 0.1 g of “free” aluminum in the nanopowder would approach a total yield
of 100%, a rough estimate of the mass proportion of the oxide layer in the nanopowder
may be obtained: The average yield of the four experimental runs using 0.1 g of
nanopowder was 85 ml. Assuming 0.1 g of “free” aluminum would have resulted in a
100% yield of 136 ml, the percentage of free aluminum within the nanoparticles is about:
85 ml / 136 ml x 100 = 62.5 % ~ 60%
Hence the oxide layer can be assumed to make up about 40% of the mass of the
aluminum nanopowder used for the experiments.
One of the objectives of the current study was to evaluate the possibility of using
aluminum particles at the nano-scale for hydrogen generation, given the expectation of a
more favorable rate profile due to larger reactant surface areas. However, the results of
the initial factor screening experiments lead to the conclusion that while nanopowder may
offer a slightly better performance in terms of hydrogen rate, the disadvantages due to the
decreased yields (due to the lower percentage of “free” aluminum, which also results in
relatively lower reaction rates), exponentially increased cost and safety and handling
concerns appear to greatly outweigh the advantages.
Nonetheless, it would be instructive to obtain an example of a true comparison of
the nanoparticles vs. micron powder reaction rate, by normalization with respect to “free”
aluminum. Given that the percentage of free aluminum within the nanoparticles is about
60%, the quantity of nanoparticles required to obtain 0.1 g of “free” aluminum is:
100% / 60% x 0.1g = 0.17 g
58
Hence, 0.17 g of nanopowder can be compared with 0.1 g of micron powder, as
both contain 0.1 g of “free aluminum”.
The rate regression model is given again below for ease of reference.
Rate = 177.63 + 92.75A -8.00B + 37.88C + 50.75D + 14.75AC + 25.88AD +
11.00CD
where A is the particle quantity level, B is the particle size level, C is the starting
solution temperature and D is the solution concentration level.
Using the coding scheme where 0.1 g and 0.2 g are indicated by - 1 and 1
respectively, 0.17 g corresponds to a code value of 0.4 for particle quantity, A. For the
sake of convenience, the variables C and D are set to zero for the following analysis.
When equal nominal quantities (0.1 g of nanoparticles and 0.1 g of micron
particles) are compared, the resulting rates as per the regression model are 93 ml/min and
77 ml/min for the nano and micron particles respectively.
However, when equal “free” aluminum quantities (0.17 g of nanoparticles and 0.1
g of micron particles) are compared, the resulting rates are 222 ml/min and 77 ml/min for
the nano and micron particles respectively.
Figure 27 below indicates the difference in rates graphically.
59
Figure 27. Rate comparison with “free aluminum” adjustment
The latter comparison is a true indication of the effect of the smaller particle size
(and hence larger reactant surface area) on the rate of reaction. The calculations indicate
that rate values for nanoparticles are underestimated by about 60% when equal nominal
quantities, as opposed to equal “free aluminum” quantities, of nano and micron particles
are compared.
Anyhow, additional particle size levels in between the defined range should also
be tested to determine whether an optimally sized particle can provide a better rate profile
than the micron particles, while still obtaining yields approaching 100%. The
experiments described in Section 7.4 are a first step towards this goal.
60
6.8
Confirmation Tests
Two additional experiments were conducted in order to confirm the integrity of
the developed regression models for yield and rate.
0.15 g of aluminum nanopowder and micron powder were reacted with 15 ml of
0.75 M NaOH at room temperature respectively. Table 7 below shows the resulting
temperature and pressure parameters for the experiments. In addition, calculated and
model-predicted yields and rates are given as well.
Table 7. Confirmation Tests
Description
Confirmation Test A Confirmation Test B
A_Quantity (g)
0.15
0.15
B_Size
40-60 nm
1-3 microns
C_Temperature ( °C )
~ 25
~ 25
D_Concentration (mol/dm3)
0.75
0.75
Yield (ml)
121
204
Predicted Yield (ml)
132
201
Rate (ml/min)
136
153
Predicted Rate (ml/min)
148
170
The calculated values are within 10% of the predicted values, indicating that the model
predictions agree very well with the calculated values.
61
CHAPTER 7
ADDITIONAL EXPERIMENTATION
7.1
Reproducibility Test
Experiment #2 (0.2 g nanoparticles reacted with 1 M solution at 35 ºC) was
replicated three times in order to gauge the level of experimental uncertainty and
reproducibility in yield and rate calculations. Table 8 below shows the relevant
parameters.
Table 8. Reproducibility Tests
Experiment # Max Sol. Temp ( C ) Max Gas Temp ( C ) Avg. RT ( C ) Max Pressure (psia) Yield (ml) Rate (ml/min)
2
43.3
30.3
24.1
95.5
181
435
Replicate 1
45.3
31.1
25.3
95.5
181
468
Replicate 2
43.9
30.8
25.2
93.2
175
484
As the table shows, while the three yield values are relatively similar, the
hydrogen generation rate range is 459 ± 25 ml. Hence, as discussed earlier, the reaction
rate values appear to have a larger variance as compared to the yield calculations.
7.2
Flow-meter Comparison Runs
In order to corroborate and validate the results of the experiments conducted using
the “pressure” method rather than the “flow-meter” method described in Section 4.2,
Experiments # 14 and 16 of the test matrix were repeated using an electronic flow-meter
to determine the hydrogen generation rate and yield.
62
The flow-meter yield and rate values for Experiment #14 and 16 were 290 ml @
270 ml/min and 162 ml @ 89 ml/min respectively. As noted in Table 5, the
corresponding “pressure” method results for Experiment #14 and 16 were 270 ml @ 286
ml/min and 145 ml @ 72 ml/min.
While yield and rate values for both experiments conducted with the two different
methods agree fairly well, the higher total yield values from the flow-rate measurements
were still a point of concern. Apart from the fact that both flow-meter yield values were
higher than the theoretical maximum hydrogen volumes (143 ml and 279 ml), there
appeared to be a possible constant offset of about 20 ml.
It was hypothesized that unpurged air in the tubing leading to the flow-meter may
have been confounding the results. As the electronic flow-meter was calibrated for use
with hydrogen gas only, the flow of air through the meter would affect the accuracy of
the measurements. Experiment # 16 was repeated with the flow meter, after removing the
tubing and attaching the meter directly to the system to prevent the supposed influence of
air.
The repeated Experiment # 16 gave yield and rate values of 151 ml and 92
ml/min. The 10 ml reduction in the yield value lends credence to the hypothesis that air in
the tubing may be a confounding factor.
It was also surmised that the discrepancy could result from premature truncation
of the “pressure” method experiments, while hydrogen was still being generated (albeit at
a very slow rate). In order to evaluate this supposition, Experiment # 15, in which 0.2 g
of micron powder were reacted with 15 ml of 0.5 M NaOH at room temperature was
63
analyzed. The measured temperature and pressure, and final calculated volume profiles
for Experiment # 15 are shown below in Figure 28 and 29 respectively.
Figure 28. Pressure and Temperature Profile for Experiment # 15
Figure 29. Hydrogen Volume Profile for Experiment # 15
Experiment # 15 was chosen for this analysis as the particular combination of
factor levels (low solution concentration and high particle quantity) has the maximum
likelihood of all the experiments for the continued evolution of hydrogen after the end of
64
the initial swift phase. This supposition is supported by the extremely gentle upward
gradient in the volume curve.
In order to estimate the possible error in the volume calculation due to early
truncation, the gas temperature, T2, in Figure 23 was extrapolated down to the average
room temperature, in order to estimate the time taken for the gas to reach room
temperature (1960 seconds).
Next, the equation of the volume curve (towards the end of the run) was
determined, and was extrapolated for 1960 seconds, to determine the estimated volume at
the time when the gas achieves room temperature. It was determined that the new volume
determination was 258 ml, 4 ml above the original 254 ml.
The worst-case scenario for an under-estimated volume calculation due to early
truncation resulted in only a 4 ml error. Hence it can be concluded that early truncation
does not explain the discrepancy between the flow-meter and pressure method volume
calculations. Moreover, if the early truncation error had indeed explained the
discrepancy, additional insight would be required to determine why the measured yield
values were above the theoretical maximum limits noted in Section 5.2.
7.3
Effect of Solution Volume Change
While the NaOH solution volume was not one of the factors in the experimental
matrix, one experiment with a reduced solution volume of 10 ml was nonetheless
conducted to observe the effects.
65
Table 9 below shows the resulting temperature and pressure parameters along
with the yield and rate values for the experiments with two different solution volumes,
using a 1 M solution reacted with 0.1 g of micron particles at room temperature.
Table 9. Effects of Solution Volume Change
Volume (ml)
Max Sol. Temp ( °C )
Max Gas Temp ( °C )
Avg. RT ( °C )
Max Pressure (psia)
Max Soln Delta T ( °C )
Max Gas Delta T ( °C )
Yield (ml)
Rate (ml/min)
15
35.8
27.5
23.8
81.4
12.0
3.7
145
72
10
42.4
29.7
24.2
80.5
18.2
5.5
141
129
As is evident from the table, the reduction in solution volume resulted in a reaction rate
increase of about 80%, from 72 ml/min to 129 ml/min. As explained earlier, this can be
attributed to the larger solution temperature rise (also evident from the table) due to the
lower solution volume. No conclusions can be drawn about the effect of solution volume
on the yield for these two experiments, as the slight reduction in yield in the 10 ml as
opposed to the 15 ml experiment is within experimental uncertainty.
7.4
Comparison between Five Particle Sizes
As noted in Section 6.7, results with different particle sizes from those used in the
main experiments would be of great interest, and may provide an indication of the range
in which the optimal particle size may lie for improving the reaction rate and yield
profile.
66
Using 15 ml of 1 M NaOH at room temperature and 0.1 g of Al, three additional
particle sizes (~1 mm, ~75 microns, ~150 nm) were tested. Figure 30 and Figure 31
below respectively indicate the yield and rate performance of the three new particles
along with that of the former two particle sizes, reacted under the same conditions. The
particle sizes are from low to high, from left to right.
Figure 30. Yield performance comparison as a function of particle size
67
Rate (ml/min)
Rate vs. Particle Size
180
160
140
120
100
80
60
40
20
0
Rate (ml/min)
40-60 nm < 150 nm
1-3
microns
< 75
microns
1mm
Particle Size
Figure 31. Rate performance comparison as a function of particle size
As is evident from the figures above, the ~150 nm particle has the fastest reaction
rate amongst the five sizes selected. Hence, there is indeed an optimum size between the
nanopowder and micron particles used in the main experiments, with respect to reaction
rate.
With respect to total yield, the original 1-3 micron particles used in the main
experiments appear to have the best performance, as none of the other particles have total
yields approaching 100%.
The 1 mm particles have an extremely unfavorable reaction rate profile of under 5
ml/min. Surprisingly, only a marginal improvement is seen when the particle sizes is
reduced to ~75 microns, but a much greater improvement is seen when the particle size is
reduced further to the 1-3 micron level.
From the graphs, it appears that the optimum particle size lies between the ~150
nm and 1-3 micron particles. Somewhere in this range, particles of a particular size will
68
have excellent reaction rates without any deficiencies in total yield. However, as noted in
Section 7.6, the nominal sizes of the particles are not necessarily an accurate reflection of
the true size ranges, and hence no conclusions can be drawn with certainty.
7.5
Gas Analysis
Gas samples were taken from Experimental Run # 13 (0.2 g of nanoparticles, reacted
with 1 M NaOH solution at room temperature) for analysis with a Varian CP 3800 Gas
Chromatography-Thermal Conductivity Detector (GC-TCD). The system conditions are
outlined below:
Column: A 15ft column containing 60/80 mesh sizes, 0.5 g/ft packing density of
Carboxen 1000
Injector Temperature: 225 °C
Oven Temperature 40 °C maintained for 5 minutes and then raised to 225 °C at
20 °C/min
Carrier Gas: Helium
Carrier Gas flow rate: 30 ml/min
Detector Temperature: 230 °C
Filament Temperature: 300 °C
The spectrum showed that the sample contained trace amounts of air, along with
hydrogen. However, given that the industrial-grade hydrogen cylinder used for purging
69
also contained air as an impurity, this was not a matter of concern. Analysis of a sample
taken from the hydrogen cylinder indicated that H2 was ~ 98.7 % by volume, with the
balance comprising of oxygen (~ 0.3 %) and nitrogen (~ 1 %). Also, the yield estimate
from the GC-TCD analysis was corroborated with the calculated hydrogen yield and was
within 4 %.
7.6
Aluminum Particle Analyses with Transmission Electronic Microscopy
(TEM)
The five particles employed for the experiments in Section 7.4 were analyzed
using a TEM system in order to characterize the nature and size of the aluminum oxide
shell surrounding the particles, if any. The particles were prepared for the microscopy by
sonication in an iso-propanol solution, and were placed on a 400-mesh grid. Figure 32
through Figure 36 show selected pictures from the TEM of the five particles in the order
of smallest to largest.
70
Figure 32. 40-60 nm nanoparticles
71
Figure 33. < 150 nm nanoparticles
72
Figure 34. 1-3 micron particles
73
Figure 35. < 75 micron particles
74
R the
Figure 36. 1mm particles
As can be seen from the above five pictures, the oxide shell is clearly visible in
the two nanoparticle varieties examined. However, no oxide layer is evident for the 1-3
75
micron particles and larger. Moreover, the < 75 micron and 1 mm particles are notable
for their irregular shapes.
According to the estimated sizes of the 40-60 nm particles and their oxide layer
noted in the pictures, the percentage of “free” aluminum in the particles is on the order of
50-60%, which is in good agreement with the 60% figure arrived at in Section 6.7.
Table 10 below shows the maximum and minimum diameters of the four smaller
particles surveyed using TEM. The values indicate that the nominal size designations of
the particles are not necessarily accurate, and these discrepancies should be taken into
account before drawing any conclusions.
Table 10. Measured Particle Sizes
Aluminum Particle Size
40-60nm
< 150 nm
1- 3 microns
< 75 microns
7.7
Large particle size
142.6 nm
166.3 nm
2783 nm
30.81 µm
Small particle size
32.28 nm
49.58 nm
140.94 nm
7819 nm
Enhanced Regression Models
The results of the confirmation tests described in Section 6.8 were added to the
data- set used to develop the regression models for yield and rate. Details of the ANOVA
analysis are given in Appendix F, but the resulting equations in terms of coded factors for
are given below:
Yield = 166.11 + 56.19A + 35.11B + 6.81D + 8.44AB
Rate = 178.10 + 92.75*A - 6.98B + 37.40C + 50.75D + 14.75AC + 25.87AD - 7.28BC
+ 11.00CD
76
where A is the particle quantity level, B is the particle size level, C is the starting solution
temperature and D is the solution concentration level. The Pred-R-square value for both
yield and rate models are 0.99.
The enhanced yield model is fairly similar to the original yield model. However,
the enhanced rate model contains a new BC interaction term.
The regression models were used to predict the yield and rate profiles of the < 75
nm particles (see Section 7.4). For modeling, the size of the particles was input as 75 nm,
which resulted in a coded value of -0.9 (on a scale where 40-60 nm is -1 and 1000-3000
nm is 1)
Compared to an actual yield and rate of 95 ml and 167 ml/min, the models
predicted 93 ml and 76 ml/min.
Hence, while the yield prediction is in good agreement with the actual
observation, the same cannot be said for the rate prediction and observation. However, as
noted earlier in Section 7.6, the nominal size designations of the particles are not
necessarily accurate, and therefore no certain conclusions can be derived about the
adequacy of the regression models at different particle size levels.
77
CHAPTER 8
SUMMARY AND CONCLUSIONS
This work has presented results from experimental investigations in the alkaliassisted aluminum-water reaction for hydrogen generation. The motivation for study was
the critical requirement for controlling the reaction rate to produce on-demand hydrogen
for fuel cell applications. Moreover, the reaction performance of aluminum particles at
the nano and micron-scale were examined and the expectation of smaller particle sizes
resulting in higher reaction rates due to larger exposed reactant surface area was critically
evaluated.
After a review of recent literature on the subject to determine the current state of
knowledge on the subject, preliminary experiments were conducted and the effects of
particle quantity, alkali concentration and solution size were investigated qualitatively,
confirming trends described in the literature. Next, a more comprehensive and
sophisticated series of factor screening experiments were conducted and the effects of
particle quantity, size, solution temperature and solution concentration on the total yield
and reaction rate were analyzed. Regression models for both total yield and rate were
developed. The model for yield indicated that the yield was largely determined by the
particle quantity and size. However, the reaction rate was significantly dependent on all
factors evaluated, with the particle quantity having the largest effect, followed by the
solution concentration and temperature.
78
The micron sized particles were found to achieve higher hydrogen yields when
compared to the same quantity of nano-sized particles. It was hypothesized that at the
nano-scale, the protective oxide layer present on aluminum makes up a larger proportion
of the particle’s mass, hence resulting in less “free” aluminum per unit mass. The
reduction in “free” aluminum adversely affects both the yield and reaction rate.
Confirmation tests were successfully conducted to check the validity of the
developed mathematic models. Also, the performances of three other particle sizes were
evaluated, providing direction for future experimentation.
79
CHAPTER 9
RECOMMENDATIONS FOR FUTURE WORK
The work presented here is the first known comparative study between aluminum
particles at the nano-scale level vs. particles at the micron-level and larger, for use in the
alkali-assisted aluminum-water reaction for hydrogen generation. However, sequential
experimentation and further analysis are required in order to develop a feasible and
workable on-demand hydrogen generation system.
The regression models developed using the factor-screening experiments
described in this work can be improved on and enhanced by the addition of data points in
the middle of the factor ranges considered, thereby accounting for any non-linearity in
response levels.
However, for applications requiring long-term uninterrupted power, a continuous
flow-reactor system as opposed to an enclosed pressure vessel design (as was adopted in
this study) would appear to be a more elegant as well as practical solution. Such a system
would allow for the continuous removal of waste products, and the reaction rate could be
controlled by varying the liquid flow-rate over the solid particles. Moreover, the
aluminum powder could be pelletized to facilitate easier handling and manipulation,
while still retaining surface area advantages. First steps towards realizing such a system
have already been described by Jung et al [6]. However, a comprehensive statistical study
80
on controlling the hydrogen generation rate was not performed. The development and
testing of an aluminum flow-reactor system using the methodology outlined in this work
would provide great insight into meeting the requirements for controlling the hydrogen
generation rate from the reaction.
At current aluminum prices, using the aluminum-water reaction to generate
electricity via a fuel cell is unfortunately not cost-competitive. Using the 3 Wh / liter-H2
rule of thumb, it can quickly be determined that about 0.25 kg of aluminum are required
to generate 1 kWh of energy. As of December 2010, scrap aluminum can be purchased
for about $2 /kg [10]. Hence, even the use of scrap aluminum material results in a
relatively high cost of about $0.5/kWh. Given that the costs associated with aluminum on
the micron and nanoscale are many orders of magnitude higher, the economics become
extremely unfavorable.
However, there are many factors which can be taken into consideration in order to
make the system more viable and competitive. Aluminum is particularly well-known for
its ease of recyclability. If much of the aluminum from the reaction can be recovered and
regenerated at a low cost, the economics will improve greatly. Hence a comprehensive
life-cycle analysis of the system in question would be very instructive. In fact, the waste
product of the reaction, aluminum hydroxide, is already useful in its original form for
many applications such as water purification, paper manufacturing and sewage treatment.
The reaction process can also be made more efficient in many ways: The water given
off as waste by the attached fuel cell can be reused to react with aluminum. Also, as the
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reaction is exothermic, the heat given off can be used to preheat the reactant solution,
thereby improving the reaction rate profile.
In conclusion, while the aluminum water-displacement reaction for hydrogen
generation offers great promise, considerable efforts and resources need to be expended
before a viable and practical product can be realized.
82
APPENDICES
Appendix A - Derivation of 3 Watt-hr / liter of H2 rule-of-thumb
The following is a derivation of the 3 Watt-hr / liter of H2 rule-of-thumb typically used
for fuel cell calculations:
The Faraday Constant (F) is the magnitude of electric charge per mole of electrons, and is
given by:
F = NA x e = 96,485 C/mol
where NA = 6.02 x 1023 mol-1 is the Avogadro constant and e = 1.602 x 10-19 C is the
magnitude of the charge of an electron. This relation is true because the amount of
charge of a mole of electrons is equal to the number of electrons in a mole multiplied by
the amount of charge per electron.
At the anode of a fuel cell, hydrogen and its electrons are separated, allowing hydrogen
ions to pass through the electrolyte while the electrons pass through an external electrical
circuit to power useful devices.
The reaction at the fuel cell anode is:
H2  2H+ + 2eHence 2 moles of electrons are available for useful work per 1 mole of H2 consumed.
Now, the quantity of charge, Q, available for useful work from a fuel cell is given by:
Q=axFxn
where a is the number of moles of electrons per mole of H2, F is the Faraday Constant,
and n is the number of moles of H2.
At p = 1 atm and T = 273 K, the number of moles, n, in 1 liter of H2 is given by the ideal
gas law:
n = (p x V) / (R x T)
where pressure, p = 1 atm, volume, V = 1 L, temperature, T = 273 K, and R = 0.0821 Latm/mol-K,
Hence:
n = (1 atm x 1 L) / (0.0821 L-atm/mol-K x 273 K) = 0.045 mols
83
Hence, the quantity of charge available for work from 1 liter of H2 is:
Q = 2 mols /mol-H2 x 96,485 C/mol x 0.045 mol-H2 = 8,684 C
Now, electrical power, P in Watts, is given by:
P=IxV
where I is the current measured in Amperes and V is voltage measured in Volts.
I is given by:
3,600 x Q / t
where Q is the charge measured in Coulombs and t is the time measured in hours.
Hence,
P = 3600 x Q x V/t
Energy, in Watt-hrs is given by:
Energy (Watt-hrs) = P (Watts) x t (hrs)
Hence Energy is given by:
Energy (Watt-hrs) = 3600 x Q x V
Theoretically, the maximum voltage that can be generated by a single fuel cell is 1.2
Volts.
Therefore, the useful energy obtainable from 1 liter of H2 is:
Energy (Watt-hrs) = 3,600 x 8,684 C x 1.2 V = 2.9 Watt-hrs ≈ 3 Watt-hrs
However, at RTP (T = 298 K, p = 1 atm), there are less moles of hydrogen per unit
volume, due to the higher temperature. Using the same procedure as outlined above, the
useful energy obtainable from 1 liter of H2 at RTP is about 2.6 Watt-hrs.
84
Appendix B – Python 2.6 Script for Hydrogen Rate and Yield Measurements
#!/usr/bin/python
#Program to facilitate data collection for hydrogen generation
import time
f = open('rate.xls', 'w')
tElapse = []
volGen = []
volume = 0 # just initializing it to anything
dataCount = 0 # variable for initializing time
i = 0 #variable for appending time correctly
while volume != "s":
volume = raw_input("Enter volume level ('s' to stop data collection) ")
volGen.append(volume)
x = time.time()
if dataCount == 0 :
dataCount = 1
startTime = time.time()
tElapse.append(str(0))
print 0, volume
else :
i=i+1
tElapse.append(round(x))
tElapse[i] = str(tElapse[i] - startTime )
print tElapse[i],volume
for item in tElapse:
f.write(item)
f.write("\n")
f.write("\n")
for item in volGen:
f.write(item)
f.write("\n")
f.close()
#End Script
85
Appendix C– List of Reagents and Equipment
#
Type
Chemical Inventory
Part #
Manufacturer
1 Sens or
Tempera ture Da ta Logger a nd
Thermocoupl es
HX309A
Omega
2 Sens or
DC Power Meter
-
Wa tts vi ew
3 Sens or
Pres s ure Tra ns ducer a nd Logger
DP41-S-S2 & PX01C1-1KA5T
Omega
4 Sens or
6 Rea gent
Fl ow Meter
FMA 6707
Al umi num Na nopa rticl es (40-60
nm)
Product # 0220XH
Spheri ca l Al umi num Powder,
Si ze 1 -3 mi cro meters
AL-104
Omega
Rea de Adva nced
Ma t.
Rea de Adva nced
Ma t.
7 Rea gent
Al umi num fl a kes (1 mm)
518573
Al dri ch
8 Rea gent/Other
Hydrogen Cyl i nder
HY 20
Ai rGa s Grea t La kes
9 Equi pment
Syri nge Pump
KDS 100
KDSci entifi c
10 Equi pment
Hydrogen Lea k Detector
22839
RESTEK
11 Equi pment
40 ml Pres s ure Ves s el
304L-HDF2-40-T
Swa gel ok
12 Equi pment
10-cel l Fuel Cel l
TDM-10
TDM Fuel Cel l Store
13 Equi pment
M-10058
La b Depot
14 Rea gent
Hot Pl a te Stirrer
Al umi num Powder (<75
mi crometers )
202584
Al dri ch
15 Rea gent
Al umi num Na nopowder(<150 nm) 653608
Al dri ch
16 Rea gent
Na O Pel l ets
CAS # 1310-73-2
TRInterna tiona l
17 Equi pment
Wei gh Sca l e
PI-214
Denver Ins truments
5 Rea gent
86
Appendix D – ANOVA Results for Yield
87
Appendix E – ANOVA Results for Rate
88
Appendix F – ANOVA Results for Enhanced Regression Models
Yield Results
89
90
91
Rate Results
92
93
Appendix G – Raw Data
See contents of associated zip file.
94
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