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Physicochemical characterization of microwave assisted synthesis of silver nanoparticles using Aloe Vera (Aloe barbadensis)

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PHYSICOCHEMICAL CHARACTERIZATION OF MICROWAVE ASSISTED
SYNTHESIS OF SILVER NANOPARTICLES USING ALOE VERA (Aloe
barbadensis)
by
ABIOLA JOHN KUPONIYI
A THESIS
Submitted in partial fulfillment of the requirements
for the degree of Master of Science
in the Department of Food and Animal Sciences
in the School of Graduate Studies
Alabama Agricultural &Mechanical University
Normal, Alabama 35762
May 2016
ProQuest Number: 10189851
All rights reserved
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ProQuest 10189851
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Copyright by
ABIOLA JOHN KUPONIYI
2016
iii
This thesis is dedicated to my loving wife, Bukky, and to my wonderful children,
for their support, kindness and patience throughout the course of this research.
iv
PHYSIOCHEMICAL CHARACTERIZATION OF MICROWAVE ASSISTED OF
SILVER NANOPARTICLES SYNTHESIZE USING ALOE VERA (Aloe barbadensis)
Abiola, Kuponiyi, M.S., Alabama A&M University, 2016. 104 pp.
Thesis Advisor: Dr. Lamin S. Kassama
Biosynthesis of silver nanoparticles (AgNP) using different biological extracts is gaining
recognition for its numerous applications in different disciplines. Although different
approaches (physical and chemical) have been used for the synthesis of AgNP, the green
chemistry method is most preferable because of its high efficacy, cost effectiveness, and
environmental
benignity.
Aloe
Vera
(AV)
contains
chemical
compounds
(anthraquinones) that are known to possess antibacterial, antivirus and anticancer
properties and the extract is a good chemical reduction agent for AgNP. Hence, it was
hypothesized that a microwave assisted synthesis will produce highly concentrated,
homogeneous, stable and biologically active AgNP. Thus, the main objective of the study
was to evaluate the effect of microwave assisted synthesis of AgNP, the effect of pulse
laser treatment on size reduction of a microwave synthesized AgNP, and the
physicochemical characterization of AgNP synthesized with Aloe Vera water and ethanol
extract. The experiment was conducted in two phases. Phase 1 was first conducted to
optimize the experimental variables, thus establishing the optimum variables to apply in
the second phase. The experiment in Phase 1 was conducted using three-factor factorial
experimental design comprised of the following factors: 1) Extraction Solvent, 2) Heating
Methods, 3) pH; and their corresponding levels were water and ethanol, conventional and
microwave, pH (7, 8, 10 and 12), respectively. All synthesis was conducted at constant
temperature of 80°C. Phase II experimental treatments were Laser ablation (0, 5, and 10
v
min) and Storage time (Week 1, 2 & 3). The Phase I of the results showed that that
increased AgNP concentrations were significantly (p < 0.05) influenced by synthesis
time, hence, (15 min) gave the highest concentration. The solvent type, heating methods
and pH had a significant effect (p < 0.05) on the concentration AgNP. Hence, ethanol
extract (99.2 ppm), microwave method (77 ppm), and pH 10 (125 ppm) are variables that
exhibited the maximum contribution to the formation of AgNP. The phase II ANOVA
results indicated that laser treatment has a significant effect (p < 0.01) on the
concentration of AgNP during synthesis. The intensity of the absorption peak
significantly (p < 0.01) increases with laser exposure time. While 214 ppm was observed
at laser exposures time 0 min, 224 and 229 ppm at 5 and 10 min and at the following
rates of formation 0.384, 0.408 and 0.4288 min-1 respectively.
Particle sizes
(hydrodynamic diameter) were approximately 37.84 nm with no laser treatment in
contrast (p < 0.01) with laser treated samples at 5 and 10 min at week 1 were 10.1 and
8.72 nm, respectively. However, storability up to the maximum storage period of six
weeks of the AgNP solutions does not significantly (p > 0.05) impact the particle size
distribution. Hence, the Zeta potential of the particles has values typically ranging
between +100 mV to -100 mV, hence indicative of colloidal stability matrix.
Furthermore, the Polydispersity indexes of Week 1, 2, & 3 treatments were 0.312, 0.591
and 0.768 respectfully, indicating that the control is monodispersed while treatments
week 2 & 3 indicating the laser ablation effect in further reduction of sizes to a different
level of aggregation. Microwave synthesis showed significantly (p < 0.05) higher
concentration of biological compounds such as aliphatic amines, alkenes (=C-H), alkanes
(C-H), alcohol (O-H) and unsaturated esters(C-O).
vi
KEY WORDS: Microwave, FTIR, Aloe Vera, Nanoparticles, Dynamic Light scattering
vii
TABLE OF CONTENTS
CERTIFICATE OF APPROVAL …...................................................................................ii
ABSTRACT AND KEYWORDS.......................................................................................v
LIST OF TABLES…………………………………………..............................................xi
LIST OF FIGURES………………………………………………………….…….........xiii
LIST OF ABBREVIATIONS…………………………….……………………...........xviii
CHAPTER
1- INTRODUCTION…………………………………………………...……...….....1
Statement of problem/Justification of the research……………........................3
Objectives..........................................................................................................4
2- LITERATURE REVIEW……………………….……………………...................6
History of Aloe Vera………………………………….....................................6
Plant Morphology..............................................................................................8
Nutrient Content...............................................................................................10
Aloin................................................................................................................13
Extraction of Bioactive Compound.................................................................14
Silver Nitrate ......................................……………………………….............16
General Overview about Nanoparticles...........................................................17
Silver Nanoparticles (AgNP)...........................................................................18
Biosynthesis….................................................................................................20
Conventional Heat Assisted Synthesis………………………….....................22
viii
Microwave Heat Assisted Synthesis................................................................23
Kinetics of Reaction………………………………………………………….24
Size and Physical Characterization..................................................................27
UV-Vis Spectrophotometer.............................................................................27
Fourier Transform Infra Red............................................................................30
Dynamic Light Scattering................................................................................33
Particle Size Distribution.................................................................................33
Zeta Potential......................................................….........................................35
Polydispersity Index.........................................................................................36
Laser Illumination............................................................................................37
3- MATERIALS AND METHODS………………………………………...............41
Experimental Design and Statistical Analysis.................................................42
Sample Preparation..........................................................................................43
Extraction Method of Biological Components................................................43
Biosynthesis and characterization of AgNP....................................................44
Determination of the Parameters that Gives the Optimum
Concentration and Sizes...................................................................................45
New Experimental Design and Statistical Analysis.........................................47
Laser Illumination (laser treatments)...............................................................48
Reaction Kinetics UV-Visible Spectrophotometer..........................................48
FTIR Spectra Determination of Functional Groups.........................................48
Particle Size Distribution and Stability Measurements...................................49
4- RESULTS AND DISCUSSION……………………………………………........50
ix
Experimental results of Phase 1…………………………………......................50
Transmission Electron Microscopy (TEM) Studies...........................................59
Experimental Results of Phase 2……………………………...…....……..........62
Kinetics of Reaction………………………...……………………….................65
Particle Size Distribution and Stability Measurements………….…….............69
Zeta Potential Analysis………………………………………………...............75
Fourier Transform Infrared (FTIR) Determination
of Functional Group………………………..……………………...…...............83
5- CONCLUSION AND RECOMMENDATIONS……………………………………………………..…….88
REFERENCES…………………………………………………………………..............91
APPENDICES…………………………………………………………….....................101
VITA……………………………………………………….………….…….............…104
x
LIST OF TABLES
Table
Page
4.1. The Analysis of Variance of AgNP concentration synthesized with
microwave assisted and conventional heating using water and
ethanol extract………………………………………………………………………58
4.2. Duncan mean comparison of concentration (ppm) at different times
(T), solvent type (ST), heating methods (HM), and pH during the
synthesis of AgNP…………………………………………………………………..59
4.3. The Analysis of Variance of the effect of laser exposure and storage
period on the concentration (ppm) of AgNP………………………………………..64
4.4. Duncan mean comparison combined table of concentration,
absorption, particle size distribution and polydispersity index of the
three treatments at phase 2 of the experiment……………………………………….65
4.5. The Analysis of Variance of the effect of laser exposure on
the particle size distribution (PSD) of AgNP………………………………………..75
4.6. The Analysis of Variance of the effect of laser exposure on the
Zeta Potential (ZP) of AgNP………………………………………………………...82
4.7. The Analysis of Variance of the Statistical level of significance for the
PI coefficient of the three treatments…………………………………………….…82
4.8. Infrared absorption bands and functional groups of the three
treatments…………………………………………………………………………....85
4.9. The Analysis of Variance of FTIR spectra of aliphatic with no laser
treatment (T82), 5 min laser treatment (T83), and 10 min
xi
laser treatment (T84)……………………………………………….…………..…...86
4.10. Duncan mean comparison combined table of Chemical substituent
of the three treatments at phase 2 of the experiment at
different concentrations…………………………………………………………....87
xii
LIST OF FIGURES
Figure
Page
2.1.
Structure of Aloe Vera….........................................................................................7
2.2.
Chemical structure of Aloe Vera............................................................…….......10
2.3.
Structure of Aloin isolated from Aloe barbadensis Miller leaves…………….....14
2.4
UV-Visible Spectrophotometer………………………………………….............28
2.5
Fourier Transform Infra-Red Spectrometer………………………………...........31
2.6
Fourier Transform Infra-Red Spectrometer using Michelson Interferometer
Principle.................................................................................................................32
2.7
Zetasizer Nano ZSP………………………………………………………...……34
2.8.
Discrete energy level................................................................................……......38
2.9.
Mean diameters of AgNP as a function of laser fluence…...................................39
3.1.
Experimental design for the synthesis of AgNP using water and ethanol
extract of Aloe Vera........……………………………………….……..................42
3.2.
Synthesis process of AgNP using Microwave assisted method.............................44
3.3.
Synthesis process of AgNP using Conventional heat method...............................45
3.4.
Experimental design for the application of laser ablation on the produced
AgNP and their characterization............................................................................47
4.1abcd Surface Plasmon Resonance spectral profile monitored during
the MWM synthesis of AgNP using parenchyma leaf layer of
Aloe Vera EE as reduction agent at various pH……………………………….....52
4.2abcd Surface Plasmon Resonance spectral profile monitored during the
CHM synthesis of AgNP using parenchyma leaf layer of Aloe Vera
xiii
EE as reduction agent at various pH………………………………..…………….54
4.3abcd Surface Plasmon Resonance spectral profile monitored during
the MWM synthesis of AgNP using parenchyma leaf layer of Aloe
Vera WE as reduction agent at various pH…………………………………….....55
4.4abcd Surface Plasmon Resonance spectral profile monitored during
the CHM synthesis of AgNP using parenchyma leaf layer of Aloe
Vera WE as reduction agent at various pH…………….……………….………...56
4.5.
Microgram of TEM image for AgNP synthesized with microwave
assisted synthesis using Aloe Vera ethanol extract EE
at pH of 10……………………………………………………………………......60
4.6.
Microgram of TEM image for AgNP synthesized with conventional
heat method of synthesis using Aloe Vera ethanol extract EE at
pH of 10……………………………………………………………………..…...61
4.7.
Surface Plasmon resonance spectral profile during laser exposure
of the treatments: the control with no laser (T82), laser exposure
for 5 min (T83), and laser exposure for 10 min (T84)……………….…………..63
4.8a.
Kinetic of reaction curve of concentration against reaction time
process during laser exposure to treatments (A) T82
with no laser………………………………………………………………...…...66
4.8b.
Kinetic of reaction curve of concentration against reaction time
process during laser exposure to treatments (B) T83 at
laser exposure time of 5 min……………………………………..........................67
xiv
4.8c.
Kinetic of reaction curve of concentration against reaction time
process during laser exposure to treatments (C) T84 at laser exposure
time of 10 min………………………………………………………………....…68
4.9
PSD measurements by volume for the control with no
laser treatment………………………………………………………………...….69
4.10
PSD measurements by volume for treatment 2 exposed to
laser for 5 min……………………………………………………………..…..…70
4.11
PSD measurements by volume for treatment 3 exposed to
laser for 10 min………………………………………………………………..…71
4.12a. PSD measurements by volume for treatment T82 with no laser at
week three of storage………………………………………………………..……72
4.12b. PSD measurements by volume for treatment T83 at laser exposure
time of 5 min at week three of storage………………………………………...….72
4.12c. PSD measurements by volume for treatment T84 at laser exposure
time of 10 min at week three of storage……………………………………......…73
4.13a. PSD measurements by volume for treatment T82 with no laser
at week six of storage…………………………………………………….…….....73
4.13b. PSD measurements by volume for treatment T83 at laser exposure
time of 5 min at week six of storage……………………………………………...74
xv
4.13c. PSD measurements by volume for treatment T84 at laser exposure of
10 mins at week six of storage……………………………………………………74
4.14. Zeta potential profile of the control T82 with no laser at week
one of storage……………………………………………………………………...76
4.15. Zeta potential profile for treatment T83 at laser exposure time of 5
min at week one of storage………………………………………………...........…77
4.16. Zeta potential profile for treatment T84 at laser exposure time
of 10 min at week one of storage…………………………………………………..78
4.17a. Zeta potential profile of the control T82 with no laser at week three
of storage…………………………………………………………………………..79
4.17b. Zeta potential profile for treatment T83 at laser exposure time of 5 min
at week three of storage…………………………………………………………...79
4.17c. Zeta potential profile for treatment T84 at laser exposure time of
10 min at week three of storage………………………………………………...…79
4.18a. Zeta potential profile of the control T82 with no laser at
week six of storage……………………………………………………………..…80
4.18b. Zeta potential profile for treatment T83 at laser exposure time
of 5 min at week six of storage……………………………………….…………..80
4.18c. Zeta potential profile for treatment T84 at laser exposure time
xvi
of 10 min at week six of storage……………………………………….……........81
4.19. FTIR spectra of 1. Aloe Vera ethanol extracts (AVEE), 2 the
control, AgNP produced by microwave assisted method
with no laser (T82), 3. AgNP produced by microwave assisted
method with laser treatment of 5 min (T83), 4. AgNP
produced by microwave assisted method with laser treatment
of 10 min (T84)……………………………………………………………..……...84
xvii
LIST OF ABBREVIATIONS
AgNO3 – Silver Nitrate
AgNP – Silver Nanoparticles
Au – Absorption unit
AuNP – Gold Nanoparticles
AV- Aloe Vera
CHM- Conventional Heat Method
DLS – Dynamic Light Scattering
EE- Ethanol Extract
EM- Electromagnetic
FTIR – Fourier Transform Infra-Red Spectroscope
HPLC – High Performance Liquid Chromatography
Hrs. – Hours
IR – InfraRed
LSPR- Localized Surface Plasmon Resonance
MWM- Microwave Method
Min - Minutes
MPa – Mega Pascal
mV – Milli Volt
NAD – Nicotine amide Adenine Dinucleotide
nm – Nano Meter
ppm – Parts per Million
xviii
PSD- Particle Size Distribution
RPM – Revolution per Minute
SAS - Statistic Analysis System
SEM – Scanning Electron Microscopy
SPR – Surface Plasmon Resonance
STD - Standard Deviation
UV-Vis - Ultra Violet Visible Spectroscopy
WE- Water Extract
µL–Micro Liter
LI– Laser Illumination
ZP – Zeta Potential
xix
ACKNOWLEDGMENTS
My profound gratitude goes to the Almighty for his mercies and grace for giving
me the wisdom, knowledge and understanding to start and finish my research project.
This work was supported by the USDA National Institute of Food and Agriculture,
[USDA-NIFA Capacity Building Grant Project Title: Nanotechnology Application in the
Food Engineering Curriculum Accession number 230755]. I would like to thank my
supervisor and Chairman of my committee, Dr. Lamin S. Kassama, for his support,
suggestions, inspiration, encouragement, and good wishes for the success of my research.
I also want to extend my thanks to Dr. Verghese for her support, educational drive and
encouragement during the course of my research. I am extremely thankful to my mentor,
Mrs. Tanja Kukhtareva, for her encouragement, counseling, guidance and personal
interest during my work. I would also like to extend my gratitude to my advisory
committee members: Dr. Martha Verghese, Dr. Jorge Vizcarra, Dr. Vanessa Edwards, Dr.
Armitra Davies - Jackson and Dr. Judith Boateng, for their advice during my research.
My gratitude goes to my Food Engineering and Processing laboratory mates and friends
during the time of my research. Special thanks to my parents, Mr. and Mrs. Kuponiyi, Dr.
Jacob Oluwoye and my entire family, for their showers of love and affection as well as
inspiration that have made come to completion.
xx
CHAPTER 1
INTRODUCTION
Nanotechnology is a relatively new field that deals with the manipulation of
particle structures within the range of 1-100 nm. Hence, it is a novel technology used for
the miniaturization of biological components, providing an impetus for research
strategies for technological advancement leading to broad innovation in the fields of
science and engineering (Groves et al., 2010). Over the last decade, research in this field
has increased dramatically resulting in the fabrication of numerous forms of nano-sized
matters (Duncan, 2011).
The potential applications of the use of Nanotechnology in every segment of the
food chain has been suggested from preharvest agricultural process such as: pesticides,
fertilizers, animal and plant pathogen detectors and targeted genetic engineering; to
postharvest food processing such as: encapsulation of flavor or odor enhancers, food
textural or quality improvement; in food packaging such as: pathogen gas, UVprotection, more impermeable polymer films, antimicrobial impregnation; and for
nutritional supplements such as nutraceutical with higher stable
bioactive and
bioavailable components (Duncan, 2011).
Biosynthesized AgNP based on the combination of Aloe Vera and Silver nitrate
has medicinal properties with broader application in the use for bio-detection of
1
Pathogens, gene delivery, detection of proteins, tumor destruction via heating
(hyperthermia), anti-cancer, anti-bacterial and anti-viral treatments and etc. (Sahayaraj &
Rajesh, 2011).
In recent studies, the antibacterial activity of AgNP was investigated at different
concentrations between 2 and 15 ppm on gram positive and gram negative bacteria.
Okafor, Janen, Kukhtareva, Edwards and Curley, (2013) found that AgNP inhibited the
growth of Staphylococcus aureus, Kocuria rhizophila, Bacillus thuringiensis (Grampositive organisms); Escherichia coli, Pseudomonas aeruginosa, and Salmonella
typhimurium (Gram-negative organisms) at concentration of 2 and 4 ppm. Also,
preliminary studies were done on the cytotoxicity of the synthesized AgNP using lnQTM
Cell Research System instrument with HEK 293 cells. It was reported that AgNP with a
concentration of 2 ppm and 4 ppm although inhibited bacterial growth, but were not toxic
to human healthy cells. (Okafor et al., 2013)
Various physical and chemical methods have been used for the synthesis of stable
AgNP. Thus, the chemical methods involve chemical reduction using organic and
inorganic reducing agents, electrochemical techniques, radiolysis and physicochemical
reduction (Wiley, Sun, Mayers, & Xi, 2005; Evanoff & Chumanov, 2004; Merga,
Wilson, Lynn, Milosavijeric, & Meisel, 2007).
Recently, the use of medicinal plant extract with solvent (water or ethanol) as
opposed to other organic solvents as a reduction agent is referred to as green chemistry;
and it is gaining importance among researchers because of its cost effectiveness, nontoxicity and eco-friendliness (Vigneshwaranm, Ashtaputre, Varadarajan, Nachane,
Paralikar & Balasubramanya, 2007). Further size reduction can be achieved with the use
2
of pulsed laser which induces cyclic heating-melting-evaporation, thus generating
sequential energy level to break molecular bonds of the AgNP. This novel application of
pulsed laser that reduces the nanoparticles sizes and enhance their stability was first
proposed by Takami, Kurita and Koda, (1999) and was further developed by Pyatenko,
Wang, Koshizaki and Tsuji (2009).
Conventional method of synthesizing AgNP is achieved via slow heating. The
generation of long temperature gradient is one of the main constraints, thus causing
localized overheating leading to heterogeneous heat distribution and hence the
decomposition of the substrate and reagent (Lidstrom, Tierney, Wathey, & Westman,
2001). In contrast, microwave assisted synthesis provides a more rapid and homogeneous
heating hence a more efficient synthesis is achieved due to selective absorption of
microwave energy by polar molecules (Kappe, 2004).
Statement of the problem/Justification of the research
AgNP exhibit unique properties which are quite different from those of larger
particles due to their exclusive properties that arise from their small sizes and high
surface/volume ratio (Gurunathan, Kalishwaralal, Vaidyanathan, Deepak, Pandian,
Muniyandi, 2009) which is responsible for its myriad applications. Various factors
govern the size and shape of AgNP, the rate of chemical reaction and reaction
temperature play a major role in biosynthesis of nanoparticles (Rai, Singh, Ahmad &
Sastry, 2006). Song and Kim (2009) reported the stability and uniformity of particles
sizes is a function of temperature, rate of reaction, even distribution of energy during
synthesis of AgNP.
3
One of the limitations of conventional method of biosynthesis of nanoparticles is
the lack of providing even distribution of heat. Hence the conductive mode of heat
transfer through the heating vessel walls limits the activation of reactants is due to the
delay of the activation energy to drive the reaction between the solvent and reactants.
Thus, impedes the formation of nanoparticles, control sizes and reproducibility. In
contrast, microwave dielectric heating provides instantaneous and uniform heating, hence
reaction rate is increased, and both particle size and stability are enhanced (Lidstrom et
al., 2001). However, based on literature search, no information was found on microwave
biosynthesis of AgNP, likewise the application of laser ablation to reduce the sizes and
stability of AgNP.
Therefore, it is hypothesized that microwave method of synthesizing AgNP will
produce a more stable, homogeneous nanoparticles; and pulsed laser treatment will
produce much smaller AgNP.
Objectives of the study
The main objective of the study was to evaluate the effect of microwave assisted
synthesis of AgNP, the effect of pulse laser treatment on size reduction of microwave
synthesized AgNP, and the physicochemical characterization of AgNP synthesized with
Aloe Vera water and ethanol extract. The specific objectives were as follows:

To evaluate the reaction kinetics and concentration of AgNP using a UV –Visible
Spectroscopy.

To evaluate the effect of laser ablation on particle size reduction and stability of
the produced AgNP.
4

To characterize the size distribution of AgNP using the Dynamic Light Scattering
(DLS) methods.

To characterize the chemical constituent of the AgNP with Fourier Transform
Infrared Spectroscopy (FTIR).
5
CHAPTER 2
LITERATURE REVIEW
History of Aloe Vera
The word “aloe” is believed to be derived from an old Arabic word “alloeh,”
meaning “shinning bitter substance,” while “Vera” is a Latin word meaning true
(Barcroft & Alasdair, 1999). Aloe Vera belongs to the lily family called Liliaceae. It is
believed to originate from Africa and its usage dated back 6000 years B.C., it is an
overgreen with over 240 species (Sharrif & Sandeep, 2011). It was first known to the
people of Egypt and later to the Greeks. The clay tablets of ancient Egyptian papyrus and
tablet in Mesopotamian described aloe as being useful in curing infections, skin problems
and as a laxative (Shelton, 1991).
Around 6000 BC, Arab traders traveled with the aloe also known as the ‘Desert
Lily’, because of its inner gel and external fibrous part of the leaves that were considered
valuable commodities in Persia and India. During this ancient period the inner gel and the
sap were separated from the outer rind with bare feet to crush the leaves, and pulps were
stored in the goatskin bags and sun dried to powder (Barcroft & Alasdair, 1999).
According to legends a physician to the Roman emperor used Aloe Vera as a healing
agent (Galen, AD 131-201). He wrote over 100 books on herbal and conventional
medicine and followed after the work of Hippocrates and Aristotle (Barcroft & Alasdair,
6
1999). In the 15th century, there was a massive explosion in exploration by the leading
maritime powers like Britain, France, Holland, Spain and Portugal. During that period,
Jesuit priests from Spain were instrumentals in bringing Aloe Vera back to their so called
New World (Barcroft & Alasdair, 1999). The Spanish were also credited for passing on
Aloe Vera to Central America, West Indies, California, Florida and Texas (Barcroft &
Alasdair, 1999).
Several researchers have reported Aloe Vera to contain over 150 nutritional
ingredients which have ranges of mechanism of actions and may act synergistically or
individually. They also have ten major chemical constituents: amino acids,
anthraquinones, enzymes, minerals, vitamins, lignin, monosaccharide, polysaccharides,
salicylic acid, saponins, and sterols (Barcroft & Alasdair, 1999; Shelton, 1991; Safran,
1975).
Figure 2.1. Structure of Aloe Vera plant (Moghaddasi & Verma, 2011).
7
In addition, Aloe Vera contains vitamins A, C, and E and minerals such as zinc,
and selenium which helps in boosting the immune system and combat free radicals in the
body (Barcroft & Alasdair, 1999).
Plant morphology
Aloe Vera plant is a shrubby, perennial, xerophytic, succulent, pea-green color
plant which has a fibrous or woody stem with very short and hardly visible as it is
covered by dense leaves and partially buried in the soil.
The aloe plant is about 20 inches long and 5 inches wide with a triangular shape
cross section fleshy leaves that have spikes along its edges (Baker, 1975). Aloe Vera has
the ability to stop wounded leaf from losing water and nutrients, thus has a self-healing
property due to special chemical constituents. The Aloe Vera leaf consists of four layers:
the rind, sap, mucilage, and parenchyma or gel.
The leaf is grayish green in color with a waxy coating on the surface. The leaf
lining contains different compounds in which the major constituent is the laxative
anthraquinones (Schulz, Hänsel, Blumenthal, & Tyler, 1997). The sticky bitter latex
liquid (gel) is derived from the pericyclic tubules of the leaf. The gel consists of 99%
water with a pH of 4.5; it is sometimes dried to form Aloe Vera concentrate or diluted
with water to make Aloe juice products (Moghaddasi & Verma, 2011).
Aloe Vera has a trumpet-shaped flower or small tube that is 2-3 cm long. The
flower colors vary from yellow to orange and it also has medicinal use (Moghaddasi &
Verma, 2011). Aloe Vera has a very short and fibrous root system and it takes
8
approximately four years to reach maturity and the life span of about 12 years
(Moghaddasi & Verma, 2011).
The whole leaf extract contains both the gel from the inner parenchyma leaf pulp
and the latex. Due to restricted distribution of the bitter latex within the margin of the
leaves which suggest that this thin layer is the primary site of secondary metabolites
biosynthesized compounds do not function directly in plant growth and development and
serve as a plant defense strategy (Boudreau, Beland, Nicholas & Pogribna, 2013).
Aloe Vera is a good candidate for the synthesis of Nanoparticles because it
contains fat soluble photochemical such as flavonoids, organic acids and quinines. These
chemical compounds are similar to those found in edible plants; they are known to
prevent chronic and degenerative diseases by modulating human metabolism (Tripoli,
2007). They are good reducing agents which neutralize reactive oxygen species leading
to the formation of electrons which reduces the Ag+ ion to Ag0 (Kavanagh et al., 1972;
Zhang, Jiang, Ding, Povey & York, 2007) during the synthesis of AgNP.
Figure 2.2 shows the four major C- glycosyl constituents of Aloe Vera latex:
Aloin A, Aloin B, aloesin, aloesin A. Aloin A and its epimer, aloin B which is known
also as isobarbaloin have a 9-anthrone skeleton and a β-D-glucopyranosyl substituent.
Aloesin, also known as aloesin B is a 5-methyl chromone with an 8-β-D-glucopyranosyl
substituent and aloesin A is 5-methyl chromone with an 8-β-D-glucopyranosyl-2-Otrams-p-coumarol substituent (Boudreau et al., 2013).
9
Figure 2.2. Chemical Structure of Aloe Vera whole leaf and gel (Boudreau, Beland,
Nicholas, & Pogribna, 2013).
.
Nutrient constituents
Several researchers have reported Aloe Vera to have over 150 nutrients with wide ranges
of mechanism of actions which react individually and or synergistically. It consists of ten
major chemical constituents which are amino acids, anthraquinones, enzymes, minerals,
10
vitamins, lignin, monosaccharide, polysaccharides, salicylic acid, saponins, and sterols
(Barcroft &Alasdair, 1999).
The amino acids are the building blocks of protein which influence brain
functions in humans, they are also found in Aloe Vera. Humans require about 22 amino
acids. The body makes all of them except eight essential amino acids which it can only
obtain from the food/drinks it consumes. All the essential amino acids are available in
Aloe Vera. They are: isoleucine, leucine, lysine, methionine, phenylalanine, threonine,
valine, and tryptophan. Also, it contains some of the non-essential amino acids such as
alanine, arginine, asparagine, cysteine, glutamic acid, glycine, histidine, proline, serine,
tyrosine, glutamine Enzymes which act as biochemical catalysts and break down the
proteins into amino acids, enabling the cells in our body to function and work efficiently.
Some of the enzymes found in Aloe Vera include Amylase (breaks down sugars and
starches), Bradykinase (stimulates immune system, analgesic, anti-inflammatory),
Catalase (prevents accumulation of water in the body), cellulase (aids digestion cellulose), Lipase (aids digestion - fats), Oxidase, Alkaline Phosphatase, Proteolytiase
(hydrolyses proteins into their constituent elements) and Creatine Phosphokinase which
aids metabolism (Baker, 1975), and aspartic acid (Moghaddasi & Verma, 2011).
In addition, Aloe Vera contains vitamins A, C, and E and minerals such as zinc,
and selenium which helps in boosting the immune system and combat free radicals in the
body. It also contains vitamins B1, B2, B3, B5, B6, and B12 along with choline which is
not really an essential vitamin for humans unless the diet consumed is devoid of
methionine and folate (Barcroft & Alasdair, 1999).
11
Aloe Vera contains minerals such as calcium which is responsible for muscle
contractions and teeth and bone formation; magnesium, which strengthens teeth and
bones and also maintains healthy muscles and nervous system; zinc, which speeds up
wound healing, mental quickness and also assists with healthy teeth, bones, skin, immune
system, and digestive aid, manganese (activates enzymes, builds healthy bones, nerves
and tissues), chromium (assists with protein metabolism and balancing of blood sugars),
and selenium, which influence our brain performance (Barcroft &Alasdair, 1999).
Additional minerals found in Aloe Vera include copper, which is responsible for
the formation of red blood cells, skin and hair pigment; iron, which is responsible for the
transportation of oxygen; potassium, which helps in fluid balancing; sodium, which
regulates bodily liquids and helps in the delivery of nutrients into body cells. Also, it
contains trace minerals such as rhodium and iridium which are used in cancer and tumor
treatment research experiments (Colman, Carol & Robert, 2000).
Aloe Vera also
contains carbohydrates such as monosaccharide and
polysaccharide which are beneficial for human consumption. Monosaccharides are
simple sugars which include glucose. Polysaccharides are the more complex long-chain
sugars such as glucose and mannose or the gluco-mannans. These sugars, when ingested,
are not broken down like other sugars and are present in the bloodstream in exactly the
same form. This process is known as “Pinocytosis”. Once in the blood stream, these
polysaccharides are not absorbed but rather stick to some cell linings of the gut forming a
barrier and preventing absorption of unwanted materials whereby helping to prevent a
leaking gut syndrome. They also exert a healing and immuno-regulating effect (Balch &
James, 2000).
12
Aloin
Aloin, also known as Barbaloin, is a bitter, yellow-brown colored compound
found in the exudates of at least 68 Aloe species at levels ranging from 0.1 to 6.6% of dry
leaf weight (Groom & Reynolds, 2004). It is used as a laxative stimulant which is used in
treating constipation by inducing bowel movements. The compound is present in what is
commonly referred to as the aloe latex that exudes from cells adjacent to the vascular
bundles, found under the rind of the leaf and in between it and the gel. When dried, it has
been used as a bittering agent in commercial alcoholic beverages (Teske, 2006).
Aloin occurs naturally as a mixture of two diastereomers, aloin A (barbaloin) and
aloin B (isobarbaloin), which have similar chemical properties. Aloin is the main
anthraquinone in aloe leaf. Anthraquinones are aromatic organic compounds of the
family of naturally occurring yellow, orange, and red pigments.
In addition, aloin has other compounds such as aloenin, aloenin B, and isoaloesin.
These compounds have been related to the biological properties of Aloe Vera extracts
and have cathartic properties, attributes shared by aloin (Saccu, Bogoni & Procida, 2001).
Their anthraquinone skeletons have been modified by the addition of a sugar
molecule as shown in Fig. 2.3 and are therefore referred to as anthraquinone glycoside.
Aloin is related to aloe emodin, which lacks a sugar group but shares aloin's biological
properties (Grun & Franz, 1981).
13
Figure 2.3. Structure of Aloin A and B isolated from Aloe barbadensis
Miller leaves (Boudreau, Beland, Nicholas, & Pogribna, 2013).
Esmat, Tomasetto and Rio (2006) studied aloin as a chemopreventive factor and
antineoplastic agent and found that aloin inhibits angiogenesis, enhances melanogenesis
and regulates transglutaminase activity and therefore reported the effect of aloin
derivatives against some human breast cancer cell lines. Other activities of aloin
compounds include antimicrobial and antioxidant properties on free radical-induced
DNA breaks (Kambizi, Sultana & Afolayan, 2004; Tian & Hua, 2005).
Extraction of bioactive compounds
Phenolics of plant derived antioxidants are gaining important recognition due to
their potential health benefits. Arabshahi-Delouee & Urooj (2007) in an epidemiological
study reported that consumption of plant foods containing antioxidants is beneficial to
14
health and can effectively lower the incidence of cancer and cardio-vascular diseases by
down regulating many degenerative processes.
Antioxidant compounds recovery from plant materials is typically accomplished
by using different extraction techniques by taking into consideration their chemistry and
uneven distribution in the plant matrix. Soluble phenolics are present in higher
concentrations in the outer tissues mainly epidermal and sub-epidermal layers of fruits
and grains than in the inner tissues comprising of mesocarp and pulp (Antolovic et al.,
2000).
The most frequently used technique for isolation of plant antioxidant compounds
is solvent extraction. Due to the different antioxidant compounds of varied chemical
characteristics, solubility and polarities, they may not be soluble in a particular solvent,
the extraction yields and resultant antioxidant activities of the plant materials are strongly
dependent on the nature of extracting solvent (Sultana, Anwar & Ashraf, 2009).
Polar solvents are the most common solvents used to recover polyphenols from
plant matrix. The most suitable of these solvents are ethanol, methanol, acetone, and
ethyl acetate or their aqueous mixtures containing ethanol, methanol, acetone, and ethyl
acetate (Peschel, Sánchez-Rabaneda, Diekmann, Plescher, Gartzía, Jiménez, Codina,
2006).
Methanol and ethanol have been extensively used to extract antioxidant
compounds from various plants and plant-based foods (fruits, vegetables etc.) such as
Aloe Vera, plum, garlic, ginger, strawberry, pomegranate, broccoli, rosemary, sage,
sumac, rice bran, wheat grain and bran, mango seed kernel, citrus peel, and many other
fruit peels (Sultanaa et al., 2009).
15
Silver Nitrate
Silver Nitrate is an inorganic compound which is antiseptic and is used in the
industrial preparation of other silver salts (Alidaee, Taheri, Mansoori & Ghodsi, 2005). In
order to produce silver nanoparticles, silver salt is needed. Silver is one of the basic
elements that make up our planet and is a rare naturally occurring element that is slightly
harder than gold and very ductile and malleable. Metallic silver itself is insoluble in
water, but metallic salts such as AgNO3 and NaCl are soluble in water (Giampaoli &
Spica, 2014). Silver metals dissolve readily in nitric acid to produce silver nitrate which
is a transparent crystalline solid that is readily soluble in water and is photosensitive
(Giampaoli & Spica, 2014). Many researchers have reported the use of silver nitrate in
the biosynthesis of AgNP due to its colloidal yield of particle diameters in nanometers
after the reduction of silver ions (Kapoor, Lawless, Kennepohl, Meisel, & Serpone,
1994). Moreover, before the advent of nanotechnology, metallic silver was used for
surgical prosthesis and splints, fungicides and coinage while soluble silver compounds
were used for treating epilepsy, nicotine addiction, gastro enteritis, stomatitis and
sexually transmitted diseases such as syphilis and gonorrhea (Alidaee et al., 2005;
Tanweer & Hanif, 2008).
The major disadvantage of this is that silver ions form complexes in the body and
the effect of the ions remained for a short while (Sahayaraj & Rajesh, 2011). Modern
research in nanotechnology has overcome this by the use of pure silver which is inert and
exhibits antimicrobial properties inducing reactive oxygen species produced such as
hydrogen peroxide (Sahayaraj & Rajesh, 2011).
16
General overview of Nanoparticles
The term “Nanoparticles” is used to describe a particle with size in the range of
1nm-100 nm. Nanoparticles can be made of materials of diverse chemical nature such as
metals, metal oxides, silicates, non-oxide ceramics, polymers, organics, carbon and
biomolecules (Tamasa & Suman, 2013).
Nanoparticles can be broadly grouped into two categories namely: organic and
inorganic. The organic nanoparticles are carbon based nanoparticles in the form of
fullerenes, while inorganic nanoparticles are magnetic based nanoparticles, for example,
noble metal nanoparticles (gold and silver) and semi-conductor nanoparticles (titanium
oxide and zinc oxide). Inorganic nanoparticles synthesized using noble metals of gold
and silver have attracted lots of interest because they possess superior material properties
and have multiple functionalities (Tamasa & Suman, 2013).
Inorganic nanoparticles have been examined as potential tools for medical
imaging, cellular delivery and controlled release of targeted drug due to their rich
functionality and good compatibility (Xu, Zeng, Lu & Yu, 2006). Compared to other
metals, AgNP have antimicrobial properties which have led to their use in different fields
of medicine, animal husbandry, food packaging, cosmetics, health and military (Cho,
Park, Osaka, & Park, 2005; Durán, Marcato, Souza, Alves, & Esposito, 2007).
Nanoparticles exist in several different morphologies such as spheres, cylinders,
platelets and tubes which are designed with surface modifications to meet the needs of
specific applications. Various chemical, physical, and biological approaches can be used
to synthesize nanoparticles. The physical method includes evaporation-condensation and
laser ablation offers greater advantage of produce more homogeneous nanoparticles
17
without the use of organic solvents, hence it is more cost effective (Kruis, Fissan &
Rellinghaus, 2000; Magnusson, Malm, Bovin, & Samuelson, 1999). Although chemical
method of synthesis requires a short period of processing time with a large quantity of
nanoparticles produced, yet, this method requires chemical agents for stabilization and
capping, thus leads to the production of non-ecofriendly toxic byproducts (Gericke &
Pinches, 2006; Ravindran, Arora, Balamurugan, & Mehta, 1999; Lin, Li, Song & Wu,
2000).
Therefore, there is a need for a clean, nontoxic and environmental friendly ‘green
chemistry’ procedure using microorganisms including bacteria, fungi and plants
(Mukherjee, Ahmad, Mandal, Senapati, Sainkar, Khan, Sastry, 2001; Spring & Schleifer,
1995). The use of plants provides a better platform for nanoparticles synthesis as they are
free from toxic chemicals as well as provide natural capping agents. Also, the use of plant
extracts reduces the cost of microbial isolation and culture media used, therefore,
eliminating the very complex procedures of maintaining microbial cultures (Garima et
al., 2011).
Silver Nanoparticles (AgNP)
Silver nanoparticles have unique physical and chemical properties and they are
known for their antimicrobial and anti-inflammatory properties, hence an excellent
candidate for medical applications. Syntheses of AgNP involve the use of medicinal plant
extract with concentration of phytochemical and are used as reducing agents of silver
nitrate. Thus, the methods is referred to as green chemical synthesis and has offered
numerous benefits for eco friendliness and compatibility for pharmaceutical, biomedical
18
and agricultural applications since it does not involve the use of toxic chemicals (Jain,
Kumar, Kachhwaha, Kothari, 2009).
Studies have shown that the reduction process may be due to a mechanism called
glycolysis, which is a metabolic pathway that converts glucose into pyruvate and
hydrogen ion (Jain et al., 2009). Nicotiamide Adenine Dinucleotide (NAD) a coenzyme
found in all living cells are present in two forms in the cells, play a vital role in the redox
reaction by donating and accepting electrons hence results in the conversion of AgNO3 to
Ag° as shown in chemical equation 1, 2, 3, and 4:
AgNO3→ Ag+ +NO-3,
(1)
NAD+ + e → NAD,
(2)
NAD + H+→ NADH + e−,
(3)
e−+Ag+→Ag0
(4)
However, studies and reports suggested that AgNP can allegedly cause adverse
effects on humans as well as the environment. Also, there have been reports that the
AgNP may have indiscriminate effects on different strains of bacteria, hence may destroy
microbes beneficial to the ecology (Allsopp, Walters, & Santillo, 2007). Also, few
studies were conducted to assess the toxicity of AgNP. One in vitro toxicity assay of
AgNP in rat liver cells has shown that even with low-level exposure to AgNP resulted in
oxidative stress and impaired mitochondrial function (Hussain, Hess, Gearhart, Geiss, &
Schlager, 2005). Studies have also suggested the release of silver when the nanoparticles
are stored over a period of time. Therefore, aged nanosilver tends to be more toxic than
fresh nanosilver (Kittler, Greulich, Diendorf, Köller, & Epple, 2010).
19
Biosynthesis
A different approach has been applied in the synthesis of AgNP using physical
and chemical methods which requires the use of both strong and weak chemical reducing
agents and protective agents such as sodium citrate, sodium borohydride and alcohols
(Sahayaraj & Rajesh, 2011). These agents show low production rate, flammability and
toxicity and cannot be easily disposed of due to environment issues (Mohanpuria, Rana,
& Yadav, 2008; Rai, Yadav & Gade, 2008; Sharma, Yngard & Lin, 2009; Bar, Bhui,
Sahoo, Sarkar, De, & Misra, 2009ab).
Research is being sought for environmental benign alternatives that are safe to the
health of humans and animals. Biomolecule extracts of certain organisms such as
enzymes/proteins, amino acids, polysaccharides, and vitamins are responsible for the
bioreduction of metal ions are environmentally benign (Korbekandi & Iravani, 2012).
Kalishwaralal, Deepak, Ramkumarpandian, Nellaiah, and Sangiliyandi (2008)
reported successful synthesis of highly stable AgNP of 40 nm in size using bioreduction
of aqueous silver ions with a nonpathogenic bacterium, Bacillus licheniformis culture.
Nair and Pradeep (2002) reported the use of Lactobacillus strains in the biosynthesis of
nanoparticles within the bacterial cells when exposed to silver ions. The lactic acid
bacteria in the whey of buttermilk were exposed to the mixtures of silver ion resulting in
the nucleation of AgNP on the cell surface through the sugars and enzymes in the cell
wall.
Ingle, Gade, Pierrat, Sonnichsen, and Rai (2008) reported the use of fungi,
Fusarium acuminatum Ell. and Ev. (USM-3793) cell extracts in the biosynthesis of
AgNP with particle sizes of 5-40 nm with an average diameter of 13 nm with a spherical
20
shape in 15-20 min. Sanghi et al. (2009) also reported the ability of Coriolus versicolor in
the formation of monodispersed spherical AgNP. Under alkaline conditions (pH 10) the
time of synthesis was reduced from 72 hr to 1 hr. It was indicated that alkaline conditions
might contribute to the bioreduction of silver ions, water hydrolysis and interaction with
protein functionalities. The results of their findings showed that glucose was necessary
for the reduction of AgNP, and S-H of the protein played an important role in the
bioreduction process.
Among all the living organisms, plants are most suitable to accumulate metals
unlike bacteria and algae which are sensitive to metal ions. Their ability to accumulate
and withstand higher concentration of metal ions and the presence of polyphenols and
flavonoids enhances more production of AgNP (McIntyre, McCutcheon & Schnoor,
2003). Also, AgNP produced by plants vary more in shapes are faster in synthesis, and
are more stable as compared with other living organisms (Iravani, 2011; Korbekandi,
Iravani & Abbasi, 2009).
There are several reports on the synthesis of AgNP using medicinal plants
(Kassama, Kuponiyi, Kukhtareva, 2015; Kuponiyi, Kassama & Kukhtareva., 2014;
Okafor et al., 2013). Plant extracts are the most adopted method of green, eco-friendly
production of nanoparticles because they are readily available, are much safer to handle
and act as a source of several metabolites (Ankamwar, Damle, Ahmad, & Sastry, 2005).
Several experiments have been performed on the synthesis of AgNP using medicinal
plants such as Oryza sativa, Helianthus annus, Saccharum officinarum, Sorghum
bicolour, Zea mays, Basella alba, Aloe vera Capsicum annuum, Magnolia kobus,
21
Medicago sativa (Alfalfa), Cinamomum camphora and Geranium sp. (Kasthuri,
Kathiravan & Rajendran, 2008).
Kuponiyi et al. (2014) successfully biosynthesized AgNP using Aloe Vera plant
as a reduction agent and making comparison on the physicochemical characterization of
the produced AgNP using water and ethanol extract. It was found that biological
compounds such as aliphatic amines, alkenes (=C-H), alkanes (C-H), alcohol (O-H) and
unsaturated esters(C-O) with an average particle size of 109 and 215.8 nm and
polydispersity index of 0.451 and 0.375 for ethanol and water extract, respectively. The
results also suggested that ethanol derived AgNP contained higher yield of organic
compounds, thus has better solubility power than water.
Conventional Heat Assisted Synthesis
One of the most important parameters in the synthesis of AgNP is temperature; it
influences the reaction time by changing the stabilization of the AgNP formed and their
surface modifiers (photochemical) (Schmid, 1994). With this method, the reactants are
slowly activated due to the slow conductive heat transfer from external source through
the walls of the vessel to the solvent, thus resulting in low product yield, and uneven
particle formation and distribution (Madhvi, Smith & Desai, 2012). Many researchers
have synthesized AgNP using conventional heat method and they have reported uneven
particle size distribution and larger particles (Elizondo, Segovia, Coello, Arriaga,
Belmares, Alcorta, & Paraguay, 2012; Kuponiyi et al., 2014).
22
Microwave Assisted Synthesis
Microwave heating is well known in the food industry and has various
applications in the synthesis of different materials such as the hydrolysis of benzyl
chloride to yield benzyl alcohol, 1, 3-Dipolar cycloadditions of organic azides to ester or
benzotriazolylcarbonyl activated acetylenic amides (Patel, Kapoor, Dave, & Mukherjee,
2006). Microwave heating has gained popularity due to its ability to achieve significant
reduction of heating times, high heating rates, more uniform heating, safe handling, easy
to operate and low maintenance (Salazar-Gonzalez, San Martin-Gonzalez, Lopez-Malo,
& Sosa-Morales,, 2006).
The acceleration of chemical reactions when a product is exposed to microwave
results from the interaction between the material and electromagnetic field leading to the
thermal and non-thermal effects. In the electromagnetic spectrum, microwave irradiation
commonly used irradiation frequency (2450 MHz) which oscillates at (2.45 x 109 cycles
per second) (Galema & Halstead, 1998).
The underlying principle behind microwave heating is that the substance must
possess a molecular polarization; such characteristic induces dipole rotation and friction
of the molecules which generates internal homogenous heating. Also, the conductive
mechanism results in stronger interactions of ions with electric field to heat generation
(Madhvi et al., 2012). These ions move under the influence of electric field which results
in energy expenditure due to increased collision rate and conversion of kinetic energy
into heat.
Dielectric properties such as the relative dielectric constant and relative dielectric
loss factors are important electrical properties for microwave heating. Polar compounds
23
with high dielectric constants such as water, ethanol, ethylene and acetone tends to heat
rapidly while less polar solvents such as aromatic and aliphatic hydrocarbons are poorly
absorbed due to no net dipole (Madhvi et al., 2012).
In microwave assisted, ethanol and water are polar solvents and have high
relative dielectric constant and dielectric loss factors (24.6, 80.4) and (0.054, 0.123),
respectfully. These properties enhance rapid and efficient synthesis due to the selective
absorption of microwave energy by polar molecules (Kappe, 2004).
The introduction of microwave in organic synthesis in 1986 has led to the
question of what actually alters the outcome of the synthesis (Madhvi et al., 2012).
Hence, the “Specific microwave effect” was claimed to be responsible for this when the
outcome of a synthesis performed using microwave heating differs from its thermally
heated counterpart (Berlan, Giboreau, Lefeuvre & Marchand, 1991).
Microwave heating is a new technique for the preparation of controlled size
metallic nanoparticles due to rapid heating and penetration. Compared to conventional
heating method, microwave method shortens the reaction time; spread uniformly over the
volume of the reaction and therefore enhances the particle size distribution (Patel et al.,
2006).
Kinetics of Reaction
Kinetics is a science which deals with the study of chemical reaction rates and
mechanisms of reaction. Chemical reaction involves the collision of sufficient energy to
break the necessary bonds. This reaction is affected by the concentration of the reacting
24
species (substrate), temperature and finally, the presence or absence of a catalyst
(Castellan, 1964).
Chemical reactions occur in foods during processing and storage in which some
reactions result in quality loss and must be minimized, whereas others result in the
formation of a desired flavor or color and must be optimized in order to achieve a high
quality food products, therefore, knowledge of the mechanism of reactions coupled with
quantification of rate constants will help in facilitating the selection of the best processing
or storage conditions in order to achieve the desired characteristics (Labuza & Baisier,
1992).
The use of kinetics is therefore necessary in food processing to study the different
types (enzymatic, chemical, physical or microbial) of reactions in foods during
processing and storage. The order-of-reactions coincide with the molecularity of the
elementary process; therefore, a true order with respect to the species involved in the
reaction could be determined theoretically by the decomposition of the process into their
elementary reactions (Toledo, 1991).
In order for a reaction to occur, a collision of proper orientation must take place
which must be of sufficient energy to break the necessary bonds. During this collision,
existing bonds are broken and new bonds are formed. It takes energy to break bonds and
energy is released when new bonds are formed (Castellan, 1964).
This energy source which is temperature dependent comes from the kinetic
energy of the compound due to the velocity at which it is zipping around. The
relationship of this energy as a function of kinetic energy and temperature is called the
energy of activation. The kinetic energy is temperature dependent, the higher the
25
temperature, the faster the molecules motion and the greater the kinetic energy (Smith,
1981). The combination of all these factors are related to the rate of the reaction which
can be represented by a mathematical expression referred as the Arrhenius equation show
in Equation 5:

  = 2.303 +  
(5)
Where, K = rate constant at temperature (T), E = energy of activation, R = gas constant
(8.314 J/mol K), T = Temperature (Kelvin) and A = collision factor.
The rate and order of the reaction are determined using the rate law Eq. 8, with
stipulation that the rate of disappearance of reactant is proportional to the concentrations
of product formed shown in Equation 6:
−


 = −


=  =
−


= 
(6)
The exponents associated with each concentration term are referred to as the
order-of-reaction. Thorough literature search reveals that few reports on reaction kinetic
and the determination of the order of reaction and activation energy for the synthesis of
AgNP. Nair and Panda (2012) used kinetics of reaction to determine the exact location of
the formation of AgNP intracellularly or extracellularly in the growing cell and whole
cell systems of Fusarium oxysporum by varying the concentrations of silver ions. It was
reported that the order of reactions followed a Michaelis Menten type of mechanism
26
wherein it initially exhibited a pseudo-zero-order kinetics and then followed higher order
kinetics with respect to the concentration of the reactants.
Size and Physical Characteristic
The physical characteristics and size is a significant factor in monitoring the
synthesis of AgNP. Various techniques such as UV-Vis Spectrophotometer, Fourier
Transform Infra-Red, Dynamic Light Scattering, Zeta Analysis, X-Ray Diffraction, and
Scanned Electron Microscope have been used by researchers to characterize AgNP
(White, Kerscher, Brown, Morella, Mcallister, Dean & Kitchens,, 2012; Pandey, Thakur,
Mewada, Shah, Oza & Sharon, 2013; Iravani & Zolfaghari, 2013). There is need to
monitor the synthesis of nanoparticles using plants or their extracts before
characterization with the instrumentations mentioned above. For example, spectral
absorption peak with increase is used to estimate the reaction time and concentration of
plant extracts and with salt ions as an indicator of nanoparticle formation (Sahayaraj &
Rajesh, 2011).
UV- Spectrophotometer
Ultraviolet -Visible spectroscopy, also referred to as electronic spectroscopy, is an
important tool in analytical chemistry. The instrumentation works on the basis of
promoting electrons from the ground state to the higher energy or excited state (Thakur,
2011), hence referred to as the absorption, transmission, spectroscopy or reflectance
spectroscopy in the UV-Visible spectral region (Sooväli, Rõõm & Kütt, 2006).
27
When an atom or molecule absorbs energy, electrons are promoted from their
ground state to an excited state. The absorption of UV or visible radiation corresponds to
the excitation of outer electrons. The energy of the ultra-violet radiation that is absorbed
is equal to the energy difference between the ground state and higher energy states
(Skoog, Holler, Crouch & Stanley, 2007).
UV spectroscopy obeys the Beer-Lambert law, which states that when a beam of
monochromatic light passes through a solution of an absorbing substance, the rate of
decrease of intensity of radiation with thickness of the absorbing solution is proportional
to the incident radiation as well as the concentration of the solution (Akul, 2012).
The expression of Beer-Lambert law is by Equation 7:

 = 10 (  ) =  ∗  ∗ 
Figure 2.4. Ultraviolet-Visible Spectrophotometer used for the characterization
of AgNP
28
(7)
Where, A = absorbance, I0 = intensity of light incident upon sample cell, I = intensity of
light leaving sample cell, C = molar concentration of solute, L = length of sample cell
(cm.) and  = molar absorptivity.
The Beer-Lambert law stipulates that the greater the number of molecules capable of
absorbing light of a given wavelength, the greater the extent of light absorption. This is
the basic principle of UV spectroscopy. UV spectroscopy is used to detect the functional
groups present in a molecule by confirming the presence or absence of chromophore
which is part of a molecule responsible for its color (Skoog et al., 2007).The absence of a
band at a particular band can be seen as an evidence for the absence of a particular group.
If the spectrum of a compound transparency is above 200 nm, then it confirms the
absence of conjugation, a carbonyl group, benzene or aromatic compound and bromo or
iodo atoms (Skoog et al., 2007).. Also, it can be used to detect the extent of conjugation
of polyenes with increase double bonds causing the absorption shifts towards longer
wavelength. Increasing polyenes double bond causes absorption shift by 8 to the visible
spectral region (Ansell, Tromp, & Neilson, 2015). An unknown compound can be
identified with the help of UV spectroscopy by comparing the spectrum to a reference
compound, and if both the spectrums coincide, then it confirms the identification of the
unknown substance (Soovali et al., 2006).
Absorption of many molecules occurs in the ultraviolet or visible light range.
Noble metal nanoparticles have a Surface Plasmon Resonance (SPR) absorption peak in
the UV–Visible region (Korbekandi et al., 2009). Various researchers have used UVVisible spectroscopy to monitor the optical absorption of colloidal silver which is an
indicator for the formation of AgNP (Korbekandi et al., 2009; Kothaus et al., 1997;
29
Kassama et al., 2015; Kuponiyi et al., 2014). Formation of various nanoparticles from
their different salts gives characteristics peaks at different absorption (Sahayaraj &
Rajesh, 2011). Kuponiyi et al. (2014); Kassama et al. (2015) reported the absorption
peak of between 420-430 nm for AgNP, while Mewada, Pandey & Oza, (2013), reported
the absorption peak of around 420-440 nm for AgNP and 540-580 nm for AuNP.
Fourier Transform Infra-Red (FTIR)
Fourier Transform Infrared is used to study of interactions between matter and
electromagnetic fields in the Infrared (IR) region based on the working principle of
Michelson Interferometer. In this spectral region, molecules can be excited to a higher
vibrational state by absorbing IR radiation and the probability of a particular IR
frequency being absorbed depends on the actual interaction between this frequency and
the molecule. In general, a frequency will be strongly absorbed if its photon energy
coincides with the vibrational energy levels of the molecule. FTIR spectroscopy is
therefore a very powerful technique which provides fingerprint information on the
chemical composition of the sample that can be used to identify chemical compounds and
substituent groups.
Fourier Transform Infrared has been used to determine the nature of associated
molecules of plants or their extracts with AgNP (Saharayah & Rajesh, 2011). This
technique has also been used by various researchers in the characterization of AgNP and
AuNP and their associated biomolecules from plant extracts in various studies (Shankar,
Ahmad, & Sastry, 2003; Chandran, Chaudhary, Pasricha, Ahmad, Sastry, 2006; Sharma
et al., 2007).
30
Figure 2.5. Fourier Transform Infra-Red Spectrometer.
(Source: http://www.ch.ic.ac.uk/klug/Research/Instruments/Instruments.html)
Figure 2.6 shows the working principle of (FTIR) using the principle of
Michelson interferometer. Light from the light source is directed to the beam-splitter.
Absorption occurs when a quanta of infrared is directed to the beam-splitter. Half of the
light is reflected and half is transmitted. The reflected light goes to the fixed mirror
where it is reflected back to the beam-splitter. The transmitted light is sent to the moving
mirror and is also reflected back towards the mirror. The two beams reaching the detector
come from the same source and have an optical path difference determined by the
positions of the two mirrors, i.e. they have a fixed phase difference. Therefore, the two
beams interfere. The two beams may be made to interfere constructively or destructively
for a particular frequency by positioning the moving mirror. If the moving mirror is
scanned over a range, a sinusoidal signal is detected for a particular frequency with its
maximum corresponding to constructive interference and the minimum corresponding to
31
destructive interference. This sinusoidal signal is referred to as the interferogram –
detector signal (intensity) against optical path difference. (Doyle, 1991).
Figure 2.6. Fourier Transform Infra-Red Spectrometer using Michelson Interferometer
Principle.
(Source: http://www.physics.nus.edu.sg/~L3000/Level3manuals/FTIR.pdf)
The mathematical expression for Fourier transform is expressed as shown in equation 8:
(8)
Where ω is angular frequency, x is the optical path difference, F (ω) is the
spectrum and f(x) is the interferogram.
Rajendram et al. (2010) identified the functional compounds in Aloe Vera skin
water extract identified at the following wave number 611.4; 717.5; 1051.1; 1398.3;
1623.9; 1730.0; 2912.3; 3155.3 and 3398.3 cm-1. Kassama et al. (2015) used this
32
technique in a comparative study of AgNP synthesized using water and ethanol extracts
of Aloe Vera to identify that the biomolecules are responsible for the capping and
stabilizing the AgNP synthesized using both extracts.
Although the FTIR biomolecular profiles of the AgNP synthesized using both
extracts showed similar peaks as the reference standard, thus, indicating consistent
biological compounds such as aliphatic amines, alkenes (=C-H), alkanes (C-H), alcohol
(O-H) and unsaturated esters(C-O), yet, a higher concentration in AgNP synthesized
using ethanol extract was observed. Gregory et al. (2012) synthesized robust, compatible
AgNP using garlic extract and used FTIR technique to identify the active chemical
species in the garlic extract, which showed large –OH and –CH stretches obtained for the
dried garlic extract at 3300 and 2930 cm-1 and garlic extract prepared AgNP at 3270 and
2930 cm-1 which are characteristic of sugars present in the garlic extract solution and
AgNP dispersion.
Dynamic Light Scattering (DLS)
Dynamic Light Scattering is also referred to as Photon Correlation Spectroscopy
or Quasi-Elastic Light Scattering system. It is a system used to develop techniques for
measuring the size of particles, Particle Size Distribution (PSD) in the sub-micron region
and also for determining the surface charge of AgNP, Zeta potential (ZP) in solution
(colloids).
33
Particle Size Distribution (PSD)
In the sub- micron region, DLS measures Brownian motion and relate it to the
sizes of the AgNP. Brownian motion is the random movement of particles induced by the
bombardment of the particle in the solvent as a result of excitation energy (Pecora, 1985).
Figure 2.7. Zetasizer Nano ZSP
(Source: http://www.malvern.com/en/products/productrange/zetasizer-range/zetasizerhelix/default.aspx)
Typically, molecules in suspension or solution undergo Brownian motion, the
larger the particle, the slower the Brownian motion. If the particles or molecules are
illuminated with a laser, the intensity of the scattered light fluctuates at a rate that is
dependent upon the size of the particles as smaller particles are “kicked” further by the
solvent molecules and move more rapidly (Dahneke, 1983).
Analysis of these intensity fluctuations yields the velocity of the Brownian motion
of the analyte or particle in a particular solvent. Knowledge of the viscosity is also
required; therefore, a known temperature is necessary since the viscosity of a liquid is
influenced by temperature. Steady state temperature is required, otherwise, convection
currents in the sample will cause non-random movement leading to a wrong
interpretation of particle sizes (Cumming, 1992). The velocity of the Brownian motion is
34
defined by a property known as the translational diffusion coefficient (D). The size of
AgNP is calculated from the translational diffusion coefficient d (H) using the StokesEinstein equation shown by Equation 9:
(9)
Where d (H) is Hydrodynamic parameter, D is Translational diffusion coefficient, K is
Stephan Bolzman constant, T is absolute temperature, and ŋ is viscosity. The translational
diffusion coefficient is not only dependent on size of the particle “core” but also on any
surface structure, as well as the concentration and the type of ions in the medium.
Dynamic Light Scattering (DLS) technique has been used by various researchers
to determine the PSD of AgNP. Hebeish, El-Rafie, El-Sheikh, and El-Naggar (2013)
used this technique to measure the particle size of AgNP powder synthesized through
concurrent formation of the nanosized particles of both starch and silver and reported an
average particle size between 5 & 50 nm. Kuponiyi et al. (2014) also used this technique
to determine the particle size of AgNP synthesized with the ethanol extracts and water
extracts of Aloe Vera using conventional method and reported a PSD of between 20 to
100 nm for ethanol extract while 100 to 1000 nm for water extracts.
35
Zeta Potential (ZP).
Zeta Potential analysis is a technique for determining the surface charge of
nanoparticles in solution (colloids). It is also an important tool for understanding the state
of the nanoparticle surface whereby predicting the stability of the nanoparticle (Malvern,
2012). AgNP have a surface charge which attracts ions of opposite charge to the
nanoparticle surface, creating a double layer. This double layer of ions travels with the
nanoparticle as it diffuses throughout the solution. The electric potential at the boundary
of the double layers is the Zeta potential of the particles and has values that typically
range from +100 mV to -100 mV. Nanoparticles with ZP values greater than +25 mV or
less than -25 mV typically have high degrees of stability while solutions with a low ZP
values will aggregate much quicker due to the Van Der Waal particle-particle attractions.
Therefore, the magnitude of the zeta potential is prerequisite to colloidal stability
(Pandley et al., 2013)
Surface charge and particle sizes have been determined using Zetasizer to
comprehend the stability of AgNP in a solution (Mewada et al., 2013). AgNP are very
small in size, which makes them energetically very unstable, therefore, the particles
undergo constant tendency to agglomerate/aggregate due to the potential charges on the
surface of the AgNP.
Kuponiyi et al. (2014) used this technique to determine ZP of AgNP synthesized
with Aloe Vera ethanol and water extracts using conventional method and reported a ZP
of between +15 and -40 mV for both extracts. Hebeish et al. (2013) reported a ZP of -28
36
mV for AgNP powder synthesized through concurrent formation of the nanosized
particles of both starch and silver.
Polydispersity Index (PI)
Polydispersity Index is a parameter calculated from a Cumulants analysis of the
DLS-measured intensity autocorrelation function. In the Cumulants analysis, a single
particle size mode is assumed and a single exponential fit is applied to the autocorrelation
function which describes the width of the assumed Gaussian distribution (Malvern,
2012). The Polydispersity Index is dimensionless which is scaled such that values smaller
than 0.05 are rarely seen other than with highly monodispersed standards and values
greater than 0.7 indicate that the sample has a very broad size distribution which cannot
be read and therefore not suitable for DLS technique (Malvern, 2012).
This index is a number calculated from a simple two parameter (Z- value and
Gaussian distribution) fit to the correlation data (the Cumulants analysis) which is
performed automatically by a modern day dynamic light scattering instruments. The
quality of the result however depends significantly on the quality of the data and the
constraint settings of the fitting procedure (Malvern, 2012).
Laser Illumination
Laser is a device which emits light through a process of optical amplification
based on the stimulated emission of electromagnetic radiation. The term “laser” is an
37
acronym of ‘Light Amplification by Stimulated Emission of Radiation” (Gould &
Gordon, 1959). In 1917, Albert Einstein established the theoretical foundations for laser
and maser in the paper “Zur Quantentheorie der Strahlung” (On the Quantum Theory of
Radiation) through a re-derivation of Max Planck’s law of radiation, while in 1928,
Rudolf W. Ladenburg confirmed the existences of the phenomena of stimulated
emission and negative absorption (Steen & Mazumba, 2010). In 1939, Valentin A.
Fabrikant predicted the use of stimulated emission to amplify "short" waves while in
1947, Willis E. Lamb and R. C. Retherford found apparent stimulated emission in
hydrogen spectra and effected the first demonstration of stimulated emission (Steen &
Mazumba, 2010).
When an electron absorbs energy either from light (photons) or heat (phonons), it
receives that incident quantum of energy. Transitions are only allowed in between
discrete energy levels as shown in Fig 2.8. This leads to emission lines and absorption
lines. When an electron is excited from a lower to a higher energy level, it will not
remain in that state forever. An electron in an excited state may decay to a lower energy
state which is not occupied, according to a particular time constant characterizing that
transition. When such an electron decays without external influence, it emits a photon,
which is called "spontaneous emission".
38
Figure 2.8. Discrete energy levels. (Source: //www.wikimedia.org)
The phase associated with the photon that is emitted is random. A material with
many atoms in such an excited state may thus result in radiation which is very spectrally
limited (Pyantheko et al., 2013). Link & El-Sayed (2000), Bunda et al. (2005), Bauer,
Abid, Ferman & Giault (2004), reported that the mechanism in which nanoparticles sizes
are reduced is by ultrafast excitation with a femtosecond laser which generates an
instantaneous relaxation of hot electrons (electron−electron relaxation), lattice heating by
thermalized electrons (electron−lattice relaxation, and heat transfer to the surrounding
medium (lattice−lattice relaxation). Picosecond and nanosecond laser excitation of the
Localized Surface Plasmon Resonance (LSPR) band resulted in the melting and sizereduction of AgNP in solution as shown in Fig. 2.9.
39
Figure 2.9. Mean diameters of Ag NPs as a function of laser fluence at
60 MPa, after excitation at two wavelengths: 355 nm (blue solid curve)
and 532 nm (red dotted curve), starting from 100 nm diameter.
(Source: pubs.acs.org/Langmuir)
The successful use of laser for nanoparticle size reduction has been reported in the
literature by only few researchers. Werner and Hashimoto (2013) reported to have
successfully used laser to reduce 100 nm diameter highly monodispersed spheres of
AuNP in colloidal solution to various diameters ranging from 90 to 30 nm with laser
excitation intensity level of 532 nm. Further size reduction of the diameter to 20 nm was
achieved by reducing the excitation wavelength to 355 nm (Werner & Hashimoto, 2013).
40
CHAPTER 3
MATERIALS AND METHODS
Experimental design and statistical analysis
The experiment was conducted in two phases. Phase 1 was first conducted to
optimize the experimental variables, thus established the optimum variables which to
apply in the second phase. The experiment in Phase 1 was conducted using four-factor
factorial experimental design as shown in Figure 2. The design comprised of the
following factors: 1) Extraction Solvent, 2) Heating Methods, 3) pH; 4) Time and their
corresponding levels were water and ethanol, conventional and microwave, pH (7, 8, 10
and 12), time (0, 5, 10 and 15) respectively. All synthesis was conducted at a constant
temperature of 80°C.
The data obtained from the experiment was analyzed using analysis of variance
(ANOVA) with using the SAS 9.0 statistical programs, and Duncan’s group mean
comparison test was used for the mean comparisons of significant treatments. All
experiments were carried out in triplicates and statistical tests were performed at 5% level
of significance.
41
Aloe Vera leaves
Eth Ext R1
Eth Ext R2
H2O Ext R1
Eth Ext R3
H2O Ext R2
H2O Ext R3
42
CHM
MWM
CHM
MWM
(P H)
0, 8,
10, 12
(P H)
0, 8,
10, 12
(P H)
0, 8,
10, 12
(P H)
0, 8,
10, 12
T(min)
0, 8,
10, 12
T(min)
0, 8,
10, 12
T(min)
0, 8,
10, 12
T(min)
0, 8,
10, 12
CHM
(P H)
0, 8,
10, 12
T(min)
0, 5,
10, 15
MWM
CHM
MWM
(P H)
0, 8,
10, 12
(P H)
0, 8,
10, 12
(P H)
0, 8,
10, 12
(P H)
0, 8,
10, 12
(P H)
0, 8,
10, 12
T(min)
0, 5,
10, 15
T(min)
0, 5,
10, 15
T(min)
0, 5,
10, 15
T(min)
0, 5,
10, 15
T(min)
0, 5,
10, 15
CHM
MWM
CHM
(P H)
0, 8,
10, 12
T(min)
0, 5,
10, 15
MWM
(P H)
0, 8,
10, 12
T(min)
0, 5,
10, 15
Figure 3.1. Phase 1: Experimental design for the synthesis of AgNP using water and ethanol extracts of
Aloe Vera
1
Sample Preparation
Aloe Vera leaves used for this study were bought from a local horticultural
entrepreneur (Bennett Nurseries) North West, Huntsville, Alabama. The leaves were
sanitized by wiping them thoroughly with ethanol to remove traces of soil, dirt, and other
debris. The parenchymatous (skin) of the leaves were separated from the gel of the plant
by using an ethanol- sterilized surgical blade. Afterwards, 480 grams each of skin were
weighed on a scale ground to increase the surface area using a conventional grinder
according to the method described by Okafor (2013).
Extraction method of biological components
Approximately 400 mL of ethanol was added into a 1000 mL of Erlenmeyer flask
for preparation of ethanol extract and another 400 mL of W5-4 HPLC water grade was
added to another 1000 ml of Erlenmeyer for the preparation of the water extract. Each
extraction flask 80 g of ground Aloe Vera leaves was weighed and added to the flask
containing water or ethanol.
The flask with water and ground leaves was boiled for 5 minutes. The extraction
was done in three replicates for both ethanol and water. All the six flasks were allowed to
sit overnight for extraction according to the method described by Hashoosh, Fadhil and
Nabeel, (2014). The supernatant collected was used for the reduction of silver ions. To
complete the extraction process, the extracts were filtered using the-Whatman filter paper
125 mm under vacuum according to the method described by Prathap (2006).
43
Biosynthesis and characterization of AgNP
The extracts were used as a reducing agent for the synthesis of the AgNP. The
AgNP synthesis protocol was followed by stirring a mixture of 0.011 grams of silver
nitrate, 50 mL of W5-4 HPLC water grade and 3 mL of ethanol extract and heated at
80˚C. The same procedure was applied to the water extract. The syntheses were
conducted using a Microwave Work Station-240 with FISO Commander Workstation
software for sensors and result management (FISO Technologies Inc. Quebec, Canada)
and Conventional hot plate (Fischer Scientific, U.S.A.) shown in Figure 3.2 and 3.3. All
procedures were conducted in a dark room to avoid Ag from absorbing light
Figure 3.2. Synthesis process of AgNP using Microwave assisted method
44
Figure 3.3. Synthesis process of AgNP using conventional
heat method
Determination of the parameters that gives the optimum concentration and sizes.
Reaction Kinetics UV-Visible Spectrophotometer
The resultants AgNP were subsequently characterized with a UV-Visible
spectroscopic (Cary 3E UV-Vis, Varian PTY Ltd. Australia). Deionized water was used
first for baseline correction of the spectra. Two mL of the AgNP synthesized were placed
in a quartz cuvette to measure the absorption of colloidal suspension (hydrosol) of AgNP
and detection of surface Plasmon resonance absorption according to the method
described by Gregory (2012).
Phase 2: Experimental design and statistical analysis
The following parameters Extraction solvent (Ethanol), heating method
(Microwave), pH (10), and synthesis time (15 min) were the optimum factors obtained
45
from the ANOVA and subsequent Duncan mean comparison analysis of Phase 1 data.
Hence, the experimental factors were adopted to establish the experimental design for
Phase 2 of the study as shown in Figure 3.4.
Phase two experimental treatments is a three-factor factorial which consist of two
factors at three levels each: 1) Laser ablation (0, 5, and 10 min) and 2) Storage time
(Week 1, 3 & 6). Reaction Kinetics using UV-Visible Spectrophotometer and FTIR
Spectra determination of functional groups were taken once and only in week one. All
treatments were further characterized as stipulated in Figure 3.4. Hence, the data obtained
from the experiment were analyzed using Analysis of Variance (ANOVA) using SAS
statistical programs. Duncan’s mean comparison test was used for the mean comparisons
of significant treatments. All experiments were carried out in triplicates and statistical
tests were performed at 5% level of significance. The effect of laser ablation on particle
size distribution on the manufactured AgNP with optimum concentration and sizes were
further studied by exposing the solution at different times under Laser (Continuum
Electro-optics Inc. USA).
46
Figure 3.4. Phase 2. Experimental design for the application of laser ablation on the
produced AgNP and their characterization
*(FTIR – Fourier Transform Infra-Red Spectroscopy), (UV-Vis - Ultra Violet Visible Spectroscopy),
(PSD- Particle Size Distribution), (ZP – Zeta Potential).
47
Laser Illumination (laser treatments)
Particle size distribution was modified by exposing treatments at different times
(5 and 10 min) under Laser illumination (Continuum Electro – optics Inc. USA) to
produce a sharper absorption peak and uniformity of particle size distribution within the
desired particle size. The laser ablation of 2 mL aliquots of aqueous colloidal solutions
contained in a quartz cuvette (optical path length 1.0 cm, width 1.0 cm, height 2.0 cm)
were conducted using the second and third harmonics of an Nd:YAG laser (Continuum,
Surelite I-10) according to the method described by Werner & Hashimoto (2013).
Samples were collected and stored in the freezer until further analysis.
Reaction Kinetics UV-Visible Spectrophotometer
The AgNP samples were characterized with conventional instrument based
analysis. The samples were subjected to UV-Visible spectroscopic (Cary 3E UV-Vis,
Varian PTY Ltd. Australia) studies; two milliliter of the AgNP synthesized was placed in
a quartz cuvette to measure the absorption of colloidal suspension (hydrosol) of AgNP
and detection of surface Plasmon resonance absorption.
FTIR Spectra determination of functional groups
Approximately 0.0016 grams of the treatments were dropped on FTIR card (Real
Crystal IR Card, - 9.5MM Aperture, International Crystal Labs, New Jersey, USA)
according to the method described by Chandran (2006). The cards were placed in the
card slot section where infrared light passed through samples, and its continuing wave
was captured by the detector connected to a computer (Thermo Fisher Scientific Smart
48
Omni transmission, Madison, Wisconsin, USA) gives a sample spectral profile. The
result of analysis consisted of molecular binding form and certain functional groups.
Particle size distribution and stability measurements
Dynamic Light Scattering technique was used to analyze and quantify the particle
size distribution of the AgNP. The Zetasizer Nano Series (ZEN 3690, MAL 1079362,
Worcestershire, UK) is the premium system in the Zetasizer range. AgNP synthesized
were centrifuged to remove excess reducing agents before performing particle size and
stability test. Three milliliter of the AgNP synthesized was placed in a quartz cuvette, and
measurements were taken by intensity and by volume according to the method used by
Gregory (2012). Surface charge of AgNP was measured to determine the stability of the
produced AgNP using Zetasizer.
49
CHAPTER 4
RESULTS AND DISCUSSIONS
The study was conducted in two phases. The first phase consisted of the following
factors: extraction solvent (water & ethanol), heating methods (microwave &
conventional heat), pH (7, 8, 9, 10) and time of synthesis (0, 5, 10, 15 min). The
optimization of the experimental variables were established in Phase 1 using the U-Vis
spectrophotometer to measure the Surface Plasmon Resonance and determining the
concentration of AgNP prior to conducting phase 2 of the experiment. The optimum
values obtained from the statistical analysis were used to study the effect of Laser on
particle size reduction.
Experimental results of Phase 1
Surface Plasmon Resonance (SPR)
The Surface Plasmon Resonance during the formation of AgNP was monitored
with a UV-Vis spectroscopy. The optical absorption of colloidal silver is known to occur
at ~430 nm wavelength and was used as an indicator for the formation of AgNP in the
nanosolution. Hence, 2.45 absorption unit (AU) is equivalent to 125 parts per million
(PPM). Likewise, many researchers have used the same procedure to verify the
synthesis of AgNP (Iravani, 2011; Korbekandi et al., 2009; Kuponiyi et al., 2014;
Kassama et al., 2015).
50
The optical density obtained of the spectral data was used to compute the AgNP
concentrations in the nanosolution. The spectral profile and results of the statistical
analysis of the concentration data are presented below. Figure 4.1abcd shows the
absorption spectra of the different AgNP synthesized using microwave assisted method
MWM with ethanol extract EE at different levels of pH and time T. Figure 4.1a shows
that at pH 7 no formation of AgNP was observed while at pH 8 a distinct peak was
observed at ~430 nm thus reflects formation of AgNP, and the corresponding
concentration of 204 ppm was computed.
51
Figure 4.1abcd. Surface Plasmon Resonance spectral profile monitored during
the microwave assisted synthesis of AgNP using Aloe Vera ethanol extract EE of
leaf parenchyma as reduction agent at various pH
Surface Plasmon Resonance reveals the best relative absorption peak at pH 10 and
15 min synthesis (Fig. 4.1c). A higher concentrated AgNP (214 ppm) was produced at the
highest SPR absorption peak. During the reaction process, an increase absorbance was
observed at a wavelength of ~430 nm, and the apparent concentration of AgNP increased
52
to 214 ppm. Pandley et al. (2013) reported similar observations that optimum alkalinity
(pH 10) had profound influence on the formation of AgNP. Therefore, increase in pH of
the solution gives a better size distribution of AgNP. This is probably due to the presence
of capping proteins in their thermodynamically efficient state when the pH approaches
alkalinity (Gardea-Torresdey, Tiemann, Gamez, Dokken, Tehuacanero, & Jos´eYacam´an, 1999b; Mock, Barbic, Smith, Schultz, & Schultz, 2012). The Role of these
capping proteins is to navigate the growth of the crystal in the solution based on their
surface energies (Mewada et al., 2013; L´evy, Thanh, Christopher Doty., 2004). At pH 12
(Fig. 4.1d), a peak offset to the left of the absorption peak was observed while and the
variation of concentration was indicative of the disappearance of the AgNP (Fig. 4.1d).
Figure 4.2abcd shows the SPR profile of the AgNP synthesized using
conventional heat method CHM with ethanol extract EE at different levels of pH and
time T. The results obtained were similar to the MWM except that the concentration of
the produced AgNP at pH 10 and time of 15 min were lower concentration (203 ppm) for
the CHM synthesized.
53
Figure 4.2abcd. Surface Plasmon Resonance spectral profile monitored during the
conventional heat method synthesis of AgNP using parenchyma leaf layer of Aloe Vera
ethanol extract as reduction agent at different pH and temperature (T).
Figure 4.3abcd and 4.4abcd shows SPR profile of the MWM and CHM using
Aloe Vera water extract at four levels of pH and time. Although, absorption peaks were
observed at different concentrations (82 and 55 ppm) for MWM and CHM, respectively
at pH 10.
54
Figure 4.3abcd. Surface Plasmon Resonance spectral profile monitored during
the microwave method synthesis of AgNP using parenchyma leaf layer of Aloe
Vera water extract as reduction agent at different pH and temperature (T).
55
Figure 4.4abcd. Surface Plasmon Resonance spectral profile monitored during
the conventional heat method synthesis of AgNP using parenchyma leaf layer of
Aloe Vera water extract as reduction agent at different pH and temperature (T).
However, in the case of water extract in comparison with ethanol extract in the
synthesis of AgNP by CHM showed the reverse as observed with the EE, thus showed a
56
decreased reaction and absorption rate with time. This is an indication that Aloe Vera
water extract may not be an efficient reducing agent in synthesizing silver nitrate into
high concentration of AgNP. Organic solvents with polarity are the most common solvent
used to recover polyphenols from plant matrix which are responsible for the reduction
process; and, moreover, organic compounds dissolve readily in organic solvents (Peschel
et al., 2006).
The formation of AgNP within the 400 ~ 430 nm range was verified against the
SPR absorption peak of silver. The raw SPR spectral data was used to compute the
concentration of AgNP in the nanosolutions of each treatment and the Analysis of
Variance (ANOVA) of the data is shown in Table 4.1. The ANOVA showed that the
extraction solvent EE & WE, heating methods MWM & CHM, pH (7, 8, 10, 12) and time
(0, 5, 10 15 min) have significant effect (p < 0.01) on the synthesis and the formation of
AgNP concentration (Table 4.1). The results also show the synergy between the different
experimental variables as reflective of their significant (p < 0.01) interactions.
Estimated means and pair wise comparisons also revealed significant differences
(p < 0.001) between the different experimental variables (EE, pH 10, time 15 min and
MWM of synthesis) gave the highest confidence interval indicating that there is a 0.95
probability that these combination factors will always produce the AgNP with the highest
concentration.
57
Table 4.1. The Analysis of Variance of AgNP concentration synthesized with Microwave
assisted and conventional heating using water and ethanol extract.
Source
Df
SS
Mean Square
F
Sig.
Solvent
1
320,140.0
320,140.000
5,532.84
0.0001
Method
1
71,598.1
71,598.1
1,237.40
0.0001
Time
3
4,335.5
1,445.1
24.97
0.0001
pH
3
333,649.0
111,216.3
1,922.10
0.0001
Solvent * Method
1
40,273.3
40,273.3
696.02
0.0001
Solvent * Time
3
3,453.5
1,151.1
19.89
0.0001
Method * Time
3
854.3
284.7
4.92
0.003
Solvent * Method *
Time
3
1,646.4
548.8
9.485
0.0001
Solvent * pH
3
66,129.4
22,043.1
380.96
0.0001
Method * pH
3
49,206.2
16,402.0
283.47
0.0001
Solvent * Method * pH
3
56086.2
18695.4
Time * pH
9
6,121.3
680.1
11.75
0.0001
Solvent * Time * pH
9
2281.4
253.5
4.38
0.0001
Method * Time * pH
9
3717.9
413.1
7.14
0.0001
Solvent * Method *
Time * pH
9
7457.4
828.6
14.3
0.0001
Model*
63
966950.5
15,348.4
265.2
0.0001
Error
128
7,406.3
57.8
Total
192
1,628,747.8
Corrected Total
191
974356.9
*R Squared = .992 (Adjusted R Squared = .989)
Hence, the effect of time, solvent extraction, heating method and pH were
evaluated by Duncan’s means comparison test shown in Tables 4.2. The results showed
that concentrations increased significantly (p < 0.05) with synthesis time (15 min) which
gave the highest concentration of AgNP among the different times applied in the
58
experiment. The comparison of the means within the different variable i.e., (solvent
extraction type, heating methods and pH) were significantly different (p < 0.05). Thus,
ethanol extract (99.2 ppm), MWM (77 ppm), and pH 10 (125 ppm) are variable which
exhibited maximum contribution to the formation of AgNP.
Table 4.2. Duncan mean comparison of concentration (ppm) at different times (T),
Solvent type (ST), Heating methods (HM), and pH during the synthesis of AgNP
Time Concentration
(min) (ppm)
Solvent
Type
Concentratin
(ppm)
Heating
Method
Concentratin
(ppm)
pH
Concentration
(ppm)
0
52.3593a
Ethanol
99.214a
MWM
77.691a
7
14.1465a
5
56.4371b
Water
17.547b
CHM
39.07b
8
57.9120c
10
59.315c
10
125.4252d
15
65.4103d
12
36.0385b
Means with the letter in the same column are not significantly different (p > 0.05).
Transmission Electron Microscopy (TEM) Studies
Transmission Electron Microscopy (TEM) provided further insight into the
morphology and size variation of the AgNP as shown in Figure 4.5 and 4.6. Microgram
comparison showed that the diameters of the AgNP synthesized using extraction time of
15 min, ethanol extraction solvent, microwave method, and pH 10 and AgNP synthesized
using extraction time of 15 min, ethanol extraction solvent, conventional heat method,
and pH 10 which gave the best formation of AgNP out of the total treatment varies in
aggregation of clusters (28, 29, 30 and 37 nm) and (78, 80 and 82 nm). Kassama et al.
(2015) reported similar particle size for AgNP synthesized using conventional heat
59
method of Aloe Vera ethanol extract. The smallest sizes of AgNP were observed in the EE
synthesized by MWM at pH of 10 at 10 min of synthesis compared to EE synthesized by
CHM at pH of 10 at 10 min of synthesis. Kuponiyi et al. (2014) reported similar size
variation for AgNP synthesized using CHM EE at pH of 10 and 10 min of synthesis with
a particle diameter sizes in the range of 80 – 100 nm.
Figure 4.5. Microgram of TEM image for AgNP synthesized with microwave assisted
synthesis using Aloe Vera ethanol extract EE at pH of 10.
60
Figure 4.6. Microgram of TEM image for AgNP synthesized with conventional heat
method of synthesis using Aloe Vera ethanol extract EE at pH of 10.
As a result, the optimum experimental parameters selected for the phase 2 of this
study was the extraction time of 15 min, ethanol extraction solvent, microwave method,
and pH 10. These parameters based on the statistical analysis contribute to the highest
concentration and formation of AgNP.
61
Experimental results of Phase 2
Monitoring the Surface Plasmon Resonance after Laser Ablation
The AgNP solution selected for phase 2 of the study was synthesized at time 15
min, with ethanol as the extraction solvent, microwave assisted method, and pH of 10.
The decision emanated from the statistical analysis of the data obtained in the phase 1 of
the study.
The silver nanosolutions were treated with laser for 0, 5, 10 min, and storage time
(week 1, 3, and 6). The SPR spectral profile was monitored after each laser treatment and
the results are presented in Figure 4.7. The SPR spectral absorption peaks showed
variation of absorbance while both treatments showed adequate formation at 430 nm. The
ANOVA results indicate that laser treatment has a significant effect (p < 0.001) on the
concentration of AgNP during synthesis. The intensity of the absorption peak
significantly (p < 0.01) increases with laser exposure time (Werner & Hashimoto, 2013).
62
Figure 4.7. Surface Plasmon resonance spectral profile during laser exposure of
the treatments: the control with no laser (T82), laser exposure for 5 min (T83),
and laser exposure for 10 min (T84).
The intensity of the absorption peak significantly (p < 0.01) increases with laser
exposure time. Interestingly, a color variation was also observed during the laser
treatment of the nanosolutions and the color change is believed to be due to the excitation
of the SPR at higher energy levels of the laser. Moreover, the color intensity is due to the
optical properties of AgNP which depend strongly upon the particle size and shape. These
63
optical properties are dominated by the collective oscillation of conduction electrons
resulting from the interaction with electromagnetic radiation (Amal et al., 2011). Table
4.3 shows the summary of the ANOVA of the SPR data of the treatments.
Table 4.3. The Analysis of Variance of the effect of laser exposure and storage period on
the concentration (ppm) of AgNP.
Source
DF
SS
Mean Square
F Value
Pr > F
LI Time
2
1101.2
550.60
3307.38
<.0001
Week
2
0.0579
0.0289
0.17
0.8417
LI Time*Week
4
0.2313
0.0578
0.35
0.8424
Model
8
1101.4
137.68
827.06
<.0001
Error
18
2.9965
0.1664
Corrected Total
26
1104.4
*R Squared = .992 (Adjusted R Squared = .989)
It was observed that the concentration and absorption increase with laser exposure
time, thus the control (T82) had a concentration of 214 ppm while laser exposures time of
5 and 10 min produced higher concentrations of 224 and 229 ppm respectively. However,
it must be noted that storage of the AgNP solutions does not significantly (p > 0.05)
affect the concentration with time, up to the maximum storage period of six weeks.
Hence, no significant (p > 0.05) synergy was observed between the laser illumination
time and storage time. This is a unique physical attribute that denotes storage stability of
laser treated AgNP.
Summary of the Duncan mean comparison for the three treatments at different
laser exposure times shown in Table 4.4 indicated that the effect of laser at different
64
exposure times are significantly (p < 0.01) impacted the absorption unit (AU) and
concentration (PPM) and the polydispersity index (PI).
Table 4.4. Duncan mean comparison combined table of concentration, absorption,
particle size distribution and polydispersity index of the three treatments at phase 2 of the
experiment.
Time (min)
Mean (AU)
Mean (PPM)
Mean (P.I)
Mean (PSD)
229.3084a
0.49333a
6.708c
5 4.396667b
224.32b
0.50256a
9.663b
0 4.193889c
213.974c
0.35689b
41.242a
10 4.494444a
Means with the letter in the same column are not significantly different (p > 0.05).
Kinetics of Reaction
The rate constant in the synthesis of AgNP is a zero-order reaction; hence there is
a direct proportionality between AgNP concentrations against the reaction time during the
synthesis of AgNP as shown in Figure 4.8abc. Although few people reported the order of
reaction in the biosynthesis of AgNP in the literature, yet, Nair & Panda, (2012) reported
the same order of reaction using Fusarium oxisporum to synthesize AgNP. The rate
constants were calculated using the rate law, whereby the rate of disappearance of
reactant is proportional to the concentrations of product formed (Eq. 8).
The rate constants for the control treatment without laser (T82), treatment with
laser exposure of 5min (T83) and treatment with laser exposure of 10min (T84) were
65
determined from the slope of the concentration vs. time curve and the results were 0.384,
0.408 and 0.4288 min-1, respectively.
Also, the reaction followed a zero-order reaction based on the supposition of
direct proportionality of concentration and reaction time, which is true in this case.
Furthermore, a linear correlation was established between concentration and time (Figure
4.8abc). The coefficient of determination (R²=0.9943, 0.9999 and 0.9995) hence shows
Goodness of fit to the linear model for T82, T83 and T84, respectively. Thus, it implies
that the method used in this analysis is adequate and is zero-order reaction kinetic as
described by Nair, & Pander, (2012).
66
Figure 4.8a. Kinetic of reaction curve of concentration against reaction time process with
treatments with no laser exposure (T82)
Figure 4.8b. Kinetic of reaction curve of concentration against reaction time process
during laser exposure to treatments at laser exposure time of 5 min (T83)
67
Figure 4.8c. Kinetic of reaction curve of concentration against reaction time process
during laser exposure to treatments at laser exposure time of 10 min (T84)
68
Particle size distribution and stability measurements
Dynamic Light Scattering Analysis
The particle size distributions (PSD) of the laser treated AgNP solutions stored for weeks
1, 3 and 6 were used for this analysis. The results are presented in Figure 4.9, which
shows that about 90% of the volume of the measured colloidal AgNP in the solution with
no laser treatment at week 1 contains particle sizes of approximately 37.84 nm. In
contrast with laser treated samples at 5 and 10 min at week 1 were 10.1 and 8.72 nm,
respectively, as shown in Figures 4.10 and 4.11.
Figure 4.9. PSD measurements by volume for the control with no laser treatment.
69
Figure 4.10. PSD measurements by volume for treatment 2 exposed to laser for 5 min.
The AgNP solutions exposed to Laser illumination at 5 and 10 min showed a shift
to the left of PSD curve, thus indicative of the effect of size reduction. The effect of laser
impacted the bigger particles; hence their molecular bonds were broken thereby reducing
the particle size of the AgNP. Size distribution changes very little after 5 min of laser
exposure, however, Takami et al. (1999) reported an optimum period of 5-10 min laser
exposure to achieve a maximum effect.
70
Figure 4.11. PSD measurements by volume for treatment 3 exposed to laser for 10 min.
Figures 4.8abc and 4.9abc show the PSD for weeks 3 and 6 of the three treatments. There
were little or no changes in the PSD of the treatments. Therefore, it is concluded that
storage time does not significantly (p < 0.05) affect the PSD.
71
Figure 4.12a: PSD measurements by volume for treatment T82 with no laser
at week three of storage.
Figure 4.12b: PSD measurements by volume for treatment T83 at laser
exposure time of 5 min at week three of storage.
72
Figure 4.12c: PSD measurements by volume for treatment T84 at laser
exposure of 10 min at week three of storage.
Figure 4.13a: PSD measurements by volume for treatment T82 with no laser
at week six of storage.
73
Figure 4.13b: PSD measurements by volume for treatment T83 at laser
exposure time of 5 min at week six of storage.
Figure 4.13c: PSD measurements by volume for treatment T84 at laser
exposure of 10 min at week six of storage.
74
The result obtained from the Analysis of Variance (ANOVA) is shown in Table
4.5. The ANOVA results showed that the effect of laser exposure times significantly (p <
0.01) impacted the particles size distributions. However, no significant (p > 0.01)
interactions were observed between illumination time and storage time and are
independent of each other.
Table 4.5. The Analysis of Variance of the effect of laser exposure on the particle size
distribution (PSD) of AgNP.
Source
DF
SS
Mean Square
F Value
Pr > F
LI Time
2
6595.6
3297.8
587.04
<.0001
Week
2
4.9
2.4
0.44
0.6484
LI Time*Week
4
60.2
15
2.68
0.0651
Model
8
6660.9
832.6
148.21
<.0001
Error
18
101.1
5.6
Corrected Total
26
6762
*R Squared = .992 (Adjusted R Squared = .989)
Zeta Potential Analysis
The nanoparticles are energetically and very unstable of their sizes; as a result, the
particles undergo agglomeration/aggregation to stabilize themselves. So there are
potential charges on the surfaces of the nanoparticles which provide them to gain
stability. The electric potential at the boundary of the double layer is known as the Zeta
potential of the particles and has values that typically ranging from +100 mV to -100 mV,
hence provides a matrix for colloidal stability.
75
Figure 4.14. Zeta potential profile of the control T82 with no laser at week one
of storage
Nanoparticles with Zeta Potential values greater than +25 mV or less than -25 mV
typically have high degrees of stability (Malvern, 2011). The ZP of the three treatments
were studied for weeks 1, 3 and 6 to determine their stability and polydispersity index.
According to figure 4.15, 4.16 and 4.17, shows the average ZP measurements for weeks
1, 3 and 6 of storage time. It is theoretically very important because it serves as an
indicator for aggregation of particles; the greater the PI, the more polydispersed the
emulsion system is. The closer the value is to zero, the more monodispersed the emulsion
system is. Polydispersed systems have a greater tendency to aggregate than
76
monodispersed systems. Hence, polydispersity index less than 0.5 are much desired
(Pecora, 1985).
Figure 4.15. Zeta potential profile for treatment T83 at laser exposure time of 5 min
at week one of storage.
Polydispersity index of the three treatments was 0.312, 0.591 and 0.768
respectfully, indicating that the control is monodispersed while treatments 2 and 3 are
polydispersed indicating that the two treatments have aggregated particles. This result
was similar to weeks 3 and 6, indicating that laser exposure times had no effect on PDI
with storage time. Prior to laser it gives a low PI indicative of more uniformity of AgNP
in the emulsion, however, exposing the treatments to laser decreases the particle sizes but
77
the PI increment is indicative of non-homogenity of AgNP in the emulsion which might
be due to non-optimization of exposure time to laser. Although the laser ablation resulted
in non-uniformity of AgNP of particle sizes, yet the nano emulsion was stable.
Figure 4.16. Zeta potential profile for treatment T84 at laser exposure time of
10 min at week one of storage.
.
Figures 4.17abc and 4.18abc show the ZP and the PI for weeks 3 and 6 of the three
treatments. There were little or no changes in the ZP of the treatments. Therefore, we can
conclude that laser exposure does not significantly affect the ZP but significantly affected
the PI.
78
Figure 4.17a. Zeta potential profile of the control T82 with no laser at week
three of storage
Figure 4.17b. Zeta potential profile for treatment T83 at laser exposure time
of 5 min at week three of storage.
79
Figure 4.17c. Zeta potential profile for treatment T84 at laser exposure time
of 10 min at week three of storage.
Figure 4.18a. Zeta potential profile of the control T82 with no laser at week six
of storage
80
Figure 4.18b. Zeta potential profile for treatment T83 at laser exposure time of
5 min at week six of storage.
Figure 4.18c. Zeta potential profile for treatment T84 at laser exposure time of
10 min at week six of storage.
81
The results obtained from the ANOVA are shown in Table 4.6 and 4.7, which
showed that laser exposure does not significantly (p > 0.01) impact the zeta potential,
Table 4.6. The Analysis of Variance of the effect of laser exposure on the Zeta Potential
(ZP) of AgNP.
Source
DF
SS
Mean Square
F Value
Pr > F
LI Time
2
205.8
102.9
0.89
0.4299
Week
2
194.9
97.4
0.84
0.4486
LI Time*Week
4
577.2
144.3
1.24
0.3289
Model
8
978
122.2
1.05
0.4364
Error
18
2092.7
116.2
Corrected Total
26
3070.7
*R Squared = .992 (Adjusted R Squared = .989)
Table 4.7. The Analysis of Variance of the Statistical level of significance for the PI
coefficient of the three treatments.
Source
DF
SS
Mean Square
F Value
Pr > F
LI Time
2
0.11
0.05
7.02
0.0056
Week
2
0.04
0.02
2.49
0.1106
LI Time*Week
4
0.07
0.01
2.07
0.1272
Model
8
0.23
0.02
3.41
0.0145
Error
18
0.15
0.008
Corrected Total
26
0.38
*R Squared = .992 (Adjusted R Squared = .989)
82
however significantly (p < 0.01) influenced the polydispersity index. The storage time
does not seem to affect (p > 0.05) ZP values likewise the PI, hence indicative of a stable
nanosolution.
Fourier Transform Infrared (FTIR) determination of functional group
FTIR measurements were carried out to determine the biomolecular profile of the
three treatments. The IR bands were used to characterize IR spectrum peaks that are
associated to different biological compounds. Phytochemicals such as aliphatic amines,
carbonyl, alkenes (=C-H), alkanes (C-H), alcohol (O-H) and unsaturated esters(C-O) are
biological compounds present in most plant leaves. Fourier Transform Infrared spectrum
obtained from the aloe ethanol extract and the three treatments is shown in Figures 4.17
and completed in table 4.8.
The FTIR profile of three treatments showed similar peaks as the ethanol Aloe
Vera extract, thus indicative of consisting common biological compounds. Rajendram et
al, (2010) reported functional compounds in Aloe Vera skin were identified at the
following wave number (cm-1) 611.4; 717.5; 1051.1; 1398.3; 1623.9; 1730.0; 2912.3;
3155.3 and 3398.3 using FTIR. Stretches of AgNP were found in the three treatments
except the ethanol extract of Aloe Vera at around 300-350 cm-1 confirming the presence
of pronounced AgNP. Tamasa and Suman, (2013) also reported the confirmation of the
presence of pronounced AgNP at a lower peak range of 500-550 cm,-1 although, leaf
extract of Azadirachta indica was used to synthesize the AgNP, yet, both bands were
similar.
83
T84
T83
T82
AVEE
Figure 4.19. FTIR spectra of 1. Aloe Vera ethanol extracts (AVEE), 2 the control, AgNP
produced by microwave assisted method with no laser (T82), 3. AgNP produced by
microwave assisted method with laser treatment of 5 min (T83), 4. AgNP produced by
microwave assisted method with laser treatment of 10 min (T84).
The AgNP were surrounded by proteins and metabolites that are constituents of
Aloe Vera extract. The FTIR analysis confirmed that the carbonyl groups from the amino
acid residues and proteins have stronger ability to bind metals, hence proteins may have
served as a capping agent for AgNP formation in stable emulsion and prevent
agglomeration. This suggests that the biological molecules could possibly perform dual
functions and thus could contribute to the formation and stabilization of silver
nanoparticles in the aqueous medium (Tamasa & Suman, 2013). Carbonyl groups proved
that flavonoids or terpenoids are absorbed on the surface of AgNP. These issues can be
84
addressed once the various fractions of the Aloe Vera leaf extract are separated, identified
and individually assayed for reduction of the metal ions.
Although the intensity of the functional groups of treatments 2 and 3 diminishes
with laser exposure times, yet the functional groups were present in higher concentration.
Table 4.8. Infrared absorption bands and functional groups of the three treatments.
Wave number
Functional Groups
Treatment 1
Treatment 2
Treatment 3
535.5
CΞC-H:C-H (alkynes)???
Present
Present
Present
1005.9
C-O stretch (aliphatic esters
Present
Present
Present
1158.5
C-N stretch (aliphatic amines)
Present
Present
Present
1247
C-N stretch (aliphatic amines)
Present
Present
Present
1323.7
N-O symmetric stretch (nitroalkane)
Present
Present
Present
1412.3
O-H bend (carboxylic acid)
Present
Present
Present
1603.6
N-H (amines)
Present
Present
Present
1743.5
C-O stretch (aliphatic esters)
Present
Present
Present
2162.5
-CΞC- stretch (alkynes)
Present
Present
Present
2353
C-N???
Present
Present
Present
2862.1
C-H stretch (alkanes)
Present
Present
Present
2925.4
C-H stretch (alkanes)
Present
Present
Present
3357.8
N-H (amines)
Present
Present
Present
It can be concluded based on the results obtained that the particle starts to
evaporate from the surface as soon as its temperature approaches the boiling point.
Continual evaporation of the particles at the boiling temperature decreases the particle
sizes (Pyatenko et al., 2013). Therefore, the particle concentration increases dramatically
due to the bonds broken to release more concentrated organic compounds as the bigger
particles disappear (Takami et al., 1999).
85
The result obtained from the Analysis of Variance (ANOVA) is shown in Table
4.9. The ANOVA results showed that the effect of laser exposures on the treatments
significantly (p < 0.01) impacted the concentration of the chemical substituent of the
produced AgNP.
Table 4.9. The Analysis of Variance of FTIR spectra of aliphatic with no laser
treatment(T82), 5 min laser treatment (T83), and 10 min laser treatment (T84),
Source
DF
SS
Mean
Square
F Value
Pr > F
LI Time
2
64.8
32.4
4313.2
<.0001
Model
2
64.8
32.4
4313.2
<.0001
Error
6
0.04
0.007
Corrected Total
8
64.9
*R Squared = .992 (Adjusted R Squared = .989)
Duncan mean comparison for the different laser exposure times shown in Table
4.10 revealed that the effect of laser impacted the concentration of the two treatments.
The concentrations increased with laser exposure times, hence are significantly (p < 0.05)
different. Appendix C. (Table C.1 - C.6) shows the Anova table for the other chemical
constituents for the three treatments in phase 2.
86
Table 4.10. Duncan mean comparison combined table of Chemical substituent of the
three treatments at phase 2 of the experiment at different concentrations.
Time
Mean
(AA)
Mean
(AE)
Mean
(Ami)
Mean
(Alky)
Mean
(Ami)
Mean
(CA)
Mean
(NA)
10
7.68a
7.95a
8.07a
6.13a
7.22a
6.37a
7.22a
5
3.01b
3.07b
3.12b
2.61b
2.94b
2.84b
2.94b
0
1.24c
1.32c
1.42c
0.90c
0.76c
0.79c
0.76c
Means with the letter in the same column are not significantly different (p > 0.05).
*(AA – Aliphatic Amines), (AE – Aliphatic Esters), (Ami – Amines), (Alky – Alkynes), (Ami – Amines),
(CA – Carboxylic Acid), (NA – NitroAlkanes).
87
CHAPTER 5
CONCLUSIONS
The Phase I of the results showed that increased AgNP concentrations were
significantly (p < 0.05) influenced by synthesis time, hence, (15 min) gave the highest
concentration. The solvent type, heating methods and pH had significant effect (p < 0.05)
on the concentration AgNP. Hence, ethanol extract (99.2 ppm), microwave method (77
ppm), and pH 10 (125 ppm) are variables that exhibited the maximum contribution to the
formation of AgNP. The phase II ANOVA results indicate that laser treatment has
significant effect (p < 0.01) on the concentration of AgNP during synthesis. The intensity
of the absorption peak significantly (p < 0.01) increases with laser exposure time. While
214 ppm was observed at laser exposures time 0 min, 224 and 229 ppm at 5 and 10 min
and at the following rates of formation 0.384, 0.408 and 0.4288 min-1 respectively.
Particle sizes (hydrodynamic diameter) were approximately 37.84 nm with no laser
treatment in contrast (p < 0.01) with laser treated samples at 5 and 10 min at week 1 were
10.1 and 8.72 nm, respectively. However, storability up to the maximum storage period
of six weeks of the AgNP solutions does not significantly (p > 0.05) impact the particle
size distribution. Hence, the Zeta potential of the particles has values that typically range
between +100 mV to -100 mV, hence indicative of colloidal stability matrix.
Furthermore, the Polydispersity indexes of Week 1, 2, & 3 treatments were 0.312, 0.591
88
and 0.768 respectively, indicating that the control is monodispersed while treatments
week 2 & 3 indicating the laser oblation effect in further reduction of sizes to a different
level of aggregation. By FTIR profile, Microwave synthesis showed significantly (p <
0.05) a higher concentration of biological compounds such as aliphatic amines, alkenes
(=C-H), alkanes (C-H), alcohol (O-H) and unsaturated esters(C-O). Although the
intensity of the functional groups diminishes with laser exposure times, yet higher
concentrations were observed.
Recommendations
The study lacks the opportunity to conduct the physical characterization by
imaging using a transmission electron microscopy (TEM) to quantify the sizes and shapes
of the AgNP, hence further studies are recommended. Likewise, the bioactivity and
antimicrobial potential and toxicity to cell are also recommended. Laser synthesis and
optimization of exposure time are potential research areas to pursue to improve size
distribution and stability.
89
APPENDIX A
Table A.1. The Analysis of Variance of FTIR spectra of aliphatic esters with no laser
treatment (T82), 5 min laser treatment (T83), and 10 min laser treatment (T84),
Source
DF
SS
Mean Square
F Value
Pr > F
LI Time
2
64.87111853
32.43555926
4313.23
<.0001
Model
2
64.87111853
32.43555926
4313.23
<.0001
Error
6
0.04512009
0.00752001
Corrected Total
8
64.91623862
*R Squared = .992 (Adjusted R Squared = .989)
90
Table A.2. The Analysis of Variance of FTIR spectra of amines with no laser treatment
(T82), 5 min laser treatment (T83), and 10 min laser treatment (T84),
Source
DF
SS
Mean Square
F Value
Pr > F
LI Time
2
47.79490026
23.89745013
41312
<.0001
Model
2
47.79490026
23.89745013
41312
<.0001
6
0.00347078
0.00057846
8
47.79837104
Error
Corrected Total
*R Squared = .992 (Adjusted R Squared = .989)
91
Table A.3. The Analysis of Variance of FTIR spectra of alkynes with no laser treatment
(T82), 5 min laser treatment (T83), and 10 min laser treatment (T84),
Source
DF
SS
Mean Square
F Value
Pr > F
LI Time
2
64.87111853
32.43555926
4313.23
<.0001
Model
2
64.87111853
32.43555926
4313.23
<.0001
Error
6
0.04512009
0.00752001
Corrected Total
8
64.91623862
*R Squared = .992 (Adjusted R Squared = .989)
Table A.4. The Analysis of Variance of FTIR spectra of aliphatic amines with no laser
treatment (T82), 5 min laser treatment (T83), and 10 min laser treatment (T84),
Source
DF
SS
Mean Square
F Value
Pr > F
LI Time
2
42.78
21.39
24652.3
<.0001
Model
2
42.78
21.39
24652.3
<.0001
Error
6
0.0052
0.00086
Corrected Total
8
42.78
*R Squared = .992 (Adjusted R Squared = .989)
92
Table A.5. The Analysis of Variance of FTIR spectra of carboxylic acid no laser
treatment (T82), 5 min laser treatment (T83), and 10 min laser treatment (T84),
Source
DF
Sum of Squares
LI Time
2
70.88
Model
2
Error
Corrected Total
Mean Square
F Value
Pr > F
35.44
12253.9
<.0001
70.88
35.44
12253.9
<.0001
6
0.0173
0.0028
8
70.90
*R Squared = .992 (Adjusted R Squared = .989)
Table A.6. The Analysis of Variance of FTIR spectra of nitroalkanes with no laser
treatment (T82), 5 min laser treatment (T83), and 10 min laser treatment (T84),
Source
DF
Sum of Squares
LI Time
2
66.54
Model
2
Error
Corrected Total
F Value
Pr > F
33.27
23008.2
<.0001
66.54
33.27
23008.2
<.0001
6
0.0086
0.0014
8
66.55
*R Squared = .992 (Adjusted R Squared = .989)
93
Mean Square
Table A.7. The Analysis of Variance of AgNP concentration synthesized with
Microwave assisted and conventional heating using water and ethanol extract at different
pH and different time
Source
Corrected Model
Intercept
Type III Sum
of Squares
966950.589(a
)
654390.904
df
Mean Square
F
Sig.
63
15348.422
265.260
.000
1
654390.904
11309.554
.000
Solvent
320140.000
1
320140.000
5532.841
.000
Method
71598.138
1
71598.138
1237.400
.000
4335.564
3
1445.188
24.977
.000
333649.083
3
111216.361
1922.104
.000
40273.362
1
40273.362
696.027
.000
3453.537
3
1151.179
19.895
.000
Time
pH
Solvent * Method
Solvent * Time
Method * Time
854.324
3
284.775
4.922
.003
1646.443
3
548.814
9.485
.000
Solvent * pH
66129.411
3
22043.137
380.962
.000
Method * pH
49206.291
3
16402.097
283.470
.000
Solvent * Method * pH
Solvent * Method * Time
56086.292
3
18695.431
323.105
.000
Time * pH
6121.397
9
680.155
11.755
.000
Solvent * Time * pH
2281.367
9
253.485
4.381
.000
Method * Time * pH
3717.984
9
413.109
7.140
.000
Solvent * Method * Time
* pH
7457.396
9
828.600
14.320
.000
Error
7406.307
128
57.862
Total
1628747.801
192
974356.897
191
Corrected Total
a R Squared = .992 (Adjusted R Squared = .989)
94
Table A.8. Duncan mean comparison of concentration (ppm) at different times (T),
Time
N
Subset
1
Duncan(a,b)
2
1
.00
48
5.00
48
52.3593
56.4371
10.00
48
59.3155
15.00
48
65.4103
Sig.
Waller-Duncan(a,c)
3
1.000
.066
.00
48
5.00
48
56.4371
10.00
48
59.3155
15.00
48
1.000
52.3593
65.4103
*Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares
The error term is Mean Square(Error) = 57.862. a Uses Harmonic Mean Sample Size = 48.000. b Alpha =
.05. c Type 1/Type 2 Error Seriousness Ratio = 100.
Table A.9. Duncan mean comparison of concentration (ppm) at different times (pH),
pH
N
Subset
1
Duncan(a,b)
2
.00
48
12.00
48
8.00
48
10.00
48
Sig.
WallerDuncan(a,c)
3
48
12.00
48
8.00
48
10.00
48
1
36.0385
57.9120
125.4252
1.000
.00
4
14.1465
1.000
1.000
1.000
14.1465
36.0385
57.9120
125.4252
Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares
The error term is Mean Square(Error) = 57.862. a Uses Harmonic Mean Sample Size = 48.000. b Alpha =
.05.c Type 1/Type 2 Error Seriousness Ratio = 100.
95
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VITA
I, John Abiola Kuponiyi, was born and raised in Nigeria. I obtained my Bachelor’s
degree in Food and Animal Science from Alabama Agricultural and Mechanical
University in 2011. I obtained my MS in Food and Animal Sciences at Alabama
Agricultural and Mechanical University at the Food Engineering and Processing
laboratory in 2016. I am happily married and blessed with kids.
104
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