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Research Article
Optimization, Characterization, and Antibacterial Activity of
Copper Nanoparticles Synthesized Using Senna didymobotrya
Root Extract
Bernard Otieno Sadia ,
1
,
2
Jackson Kiplagat Cherutoi,
1
and Cleophas Mecha Achisa
3
1
Department of Chemistry and Biochemistry, School of Sciences and Aerospace Studies, Moi University, P.O. Box 3900-30100,
Eldoret, Kenya
2
Africa Centre of Excellence II in Phytochemicals,Textile and Renewable Energy (ACE II PTRE), Moi University,
P.O. Box 3900-30100, Eldoret, Kenya
3
Department of Chemical and Process Engineering, School of Engineering, Moi University, P.O. Box 3900-30100, Eldoret, Kenya
Correspondence should be addressed to Bernard Otieno Sadia; benardsadia@gmail.com
Received 11 August 2021; Revised 3 October 2021; Accepted 8 October 2021; Published 15 October 2021
Academic Editor: Brajesh Kumar
Copyright ©2021 Bernard Otieno Sadia et al. is is an open access article distributed under the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is
properly cited.
e economic burden and high mortality associated with multidrug-resistant bacteria is a major public health concern. Bio-
synthesized copper nanoparticles (CuNPs) could be a potential alternative to combat bacterial resistance to conventional
medicine. is study for the first time aimed at optimizing the synthesis conditions (concentration of copper ions, temperature,
and pH) to obtain the smallest size of CuNPs, characterizing and testing the antibacterial efficacy of CuNPs prepared from Senna
didymobotrya (S. didymobotrya) roots. Extraction was done by the Soxhlet method using methanol as the solvent. Gas chro-
matography-mass spectrometry (GC-MS) analysis was performed to identify compounds in S. didymobotrya root extracts.
Box–Behnken design was used to obtain optimal synthesis conditions as determined using a particle analyzer. Characterization
was done using ultraviolet-visible (UV-Vis), particle size analyzer, X-ray diffraction, zeta potentiometer, and Fourier transform
infrared (FT-IR). Bioassay was conducted using the Kirby–Bauer disk diffusion susceptibility test. e major compounds
identified by GC-MS in reference to the NIST library were benzoic acid, thymol, N-benzyl-2-phenethylamine, benzaldehyde,
vanillin, phenylacetic acid, and benzothiazole. UV-Vis spectrum showed a characteristic peak at 570 nm indicating the formation
of CuNPs. e optimum synthesis conditions were temperature of 80°C, pH 3.0, and copper ion concentration of 0.0125 M. e
FT-IR spectrum showed absorptions in the range 3500–3400 cm
−1
(N-H stretch), 3400–2400 cm
−1
(O-H stretch), and
988–830 cm
−1
(C-H bend) and peak at 1612 cm
−1
(C�C stretch), and 1271 cm
−1
(C-O bend). Cu nanoparticle sizes were
5.55–63.60 nm. e zeta potential value was −69.4 mV indicating that they were stable. e biosynthesized nanoparticles exhibited
significant antimicrobial activity on Escherichia coli and Staphylococcus aureus with the zone of inhibition diameters of
26.00 ±0.58 mm and 30.00 ±0.58 mm compared to amoxicillin clavulanate (standard) with inhibition diameters of 20 ±0.58 mm
and 28.00 ±0.58 mm, respectively.
1. Introduction
Nanotechnology is of great scientific interest due to its wide
application in pharmaceutical products, electronics, bio-
technology, and medicine [1, 2]. Nanoparticles are solid
particles with sizes approximately extending from 1 nm to
100 nm in length in at least one dimension [3]. eir
application in the field of biotechnology has grown because
of their comparable size range scale to biomolecules and
their versatile properties that can be controlled using the
method used for their biosynthesis [4]. Copper nanoparticle
(CuNP) is one of the most common nanoparticles utilized in
medicine. ey have been synthesized using both physical
and chemical methods [4]. Physical methods experience low
Hindawi
Journal of Nanotechnology
Volume 2021, Article ID 5611434, 15 pages
https://doi.org/10.1155/2021/5611434
production of nanoparticles and high energy consumption
to maintain high temperature and pressure utilized during
the synthesis process. Chemical methods are known to use
noxious precursor chemicals, harmful by-products, and uses
toxic solvents [5, 6].
Due to the limitations of physical and chemical methods
of CuNPs synthesis, biological methods have been devel-
oped. ese use bacteria, algae, fungi, plants, and plant
products. e biological method of synthesis of the copper
nanoparticle is considered a bottom-up technique, where
oxidation or reduction is the main reaction that occurs
during the production of nanoparticles [7]. Currently, the
use of phytochemicals in the synthesis of nanoparticles is
being explored as such nanoparticles are friendly both to the
environment and humans [8]. Biosynthesized inorganic
nanoparticles can offer solutions to the emergence of
multidrug-resistant microbes. is can act as substitutes to
the traditional organic agents that have limited application
due to the high rate of decomposition and low heat resis-
tance. e unique chemical and physical properties, low-cost
preparation, surface-to-volume ratio, and low toxicity make
CuNPs command a superior position as gas sensors, pho-
tocatalysts, dye absorbents, antioxidant, antimicrobial, an-
timalarial, and antitumor agents in comparison to
nanoparticles prepared from gold, zinc, iron, and silver
compounds [2, 9–13].
Senna didymobotrya (Fresen) Irwin & Barneby (Syno-
nym: Cassia didymobotrya Fresen.), a plant from the genus
Senna and family Fabaceae has been used by different ethnic
communities worldwide [14–16]. In Kenya, it is used to treat
malaria, fungal and bacterial infections, hypertension,
haemorrhoids, sickle cell anaemia, a range of diseases af-
fecting women such as inflammation of fallopian tubes,
fibroids, and backache, stimulate lactation, and induce
uterine contraction and abortion [17–26]. Preceding authors
reported that aqueous and organic extracts and fractions of
different parts (leaves, flowers, twigs, roots, stem bark,
immature pods, and root bark) of S. didymobotrya elicited
antipyretic activity [27], hypolipidemic activity [28], anti-
microbial activity against bacteria (such as Bacillus cereus,
Bacillus subtilis,Escherichia coli,Enterobacter aerogenes,
Lactobacillus acidophilus,Klebsiella pneumoniae,Proteus
vulgaris,Ralstonia solanacearum, Salmonella typhi,Serratia
liquefaciens, and Streptococcus mitis) [29–40] and fungi
(such as Aspergillus niger,Candida albicans,Candida
glabrata,Candida krusei,Candida parapsilosis,Candida
tropicalis,Candida duobushaemulonii,Candida haemulonii,
Candida auris,Candida famata,Candida orientalis, Cryp-
tococcus neoformans,Trichophyton mentagrophyte, and
Microsporum gypseum) [15, 34, 35, 40–42]. Insecticidal
activity (against fleas and Acanthoscelides obtectus) and
anthelmintic and antiamoebic activities as well as toxicity of
the extracts have also been reported [34–36, 43, 44].
Classical phytochemical screening of various extracts of
S. didymobotrya has indicated that anthraquinones, tannins,
saponins, naphthoquinones, terpenes, steroids, alkaloids,
flavonoids, phenols, and terpenoids are the major secondary
therapeutic secondary metabolites [14, 30, 34, 36, 45, 46].
Alemayehu et al. [45] isolated and characterized for the first
time 2,6,4′-trihydroxy-trans-stilbene (a stilbenoid deriva-
tive) and 4-(2′-oxymethylene-4′-hydroxyphenyl) chrys-
ophanol (a phenyl anthraquinone) from chloroform/
methanol extract of S. didymobotrya roots. Later, chro-
matographic separation of the hexane and dichloromethane
extracts of S. didymobotrya roots led to the identification of
terpenoids (3β-sitosterol and stigmasterol) and anthraqui-
nones (chrysophanol and physcion) [35]. Recently, terpi-
nolene and alpha-pinene were reported as the main
antipyretic compounds in dichloromethane extract of
S. didymobotrya leaves [27].
ough some pharmacological activities and toxicity of
different extracts of S. didymobotrya parts have been re-
ported, there is no report on the synthesis of CuNPs and
antimicrobial activity of nanoparticles synthesized from this
plant. e current study therefore for the first time inves-
tigated the synthesis of CuNPs using S. didymobotrya roots
extracts and their antimicrobial efficacy against E. coli and
Staphylococcus aureus. Since the synthesis of nanoparticles
of smaller and uniformly distributed size, crystalline, and
good stability requires control of experimental conditions
[47, 48], synthesis conditions (concentration of copper ions,
temperature, and pH) for the CuNPs were optimized.
2. Materials and Methods
2.1. Chemicals and Reagents. Copper (II) sulphate penta-
hydrate (CuSO
4
·5H
2
O), anhydrous sodium sulphate, silica
gel, and methanol were purchased from Merck Ltd., USA.
All the chemicals and reagents were of analytical grade and
were used without further purification. E. coli (ATCC
25922), S. aureus (ATCC 25923), Kirby–Bauer disks,
amoxicillin clavulanate, and 0.5 McFarland standards were
obtained from Cypress Diagnostics, Belgium.
2.2. Sample Collection and Preparation. S. didymobotrya
roots were harvested from plants growing in their natural
habitat in West Uyoma sublocation, Siaya County, Kenya
(0°15′8S 34°16′02.8E). ey were identified and authenti-
cated at the Department of Biological Sciences, Moi Uni-
versity (Kenya), where a voucher specimen (SD 2018/03) was
deposited for future reference.
e collected roots were washed several times with
distilled water to remove dust. ey were dried at room
temperature under shade for three weeks. After, they were
chopped into small pieces and pulverized using a laboratory
mill. e extraction was carried out according to the method
described by Kigondu et al. [49] with slight modifications.
Weighed 50 g of the root powder was transferred into the
Soxhlet apparatus and extracted with 250 mL of methanol
for 48 hours. Methanol was used as the solvent of extraction
because it was the best solvent of extraction according to trial
extractions done using diethyl ether, methanol, and distilled
water. e crude extract was concentrated by rotary evap-
oration at 40°C and transferred to a desiccator containing
anhydrous sodium sulphate. e percentage yield of the
crude extract was determined as per the following
equation [50]:
2Journal of Nanotechnology
extractive yield value �weight of concentrated extract
weight of plant dried powder ×100.(1)
2.3. Gas Chromatography-Mass Spectrometry Analyses.
GC-MS analysis was performed using an Agilent 8890A GC
system interfaced with a 5977B mass spectrometer detector
fused with a capillary column (30 ×0.25 mm, 0.25 μm). For
GC-MS detection, an electron ionization system was operated
in electron impact mode with an ionization energy of 70 eV.
Helium gas (99.999%) was used as a carrier gas at a constant
flow mode of 1.2 ml/min, and an injection volume of 2 μL was
employed (a split ratio of 10:1). e injector temperature was
maintained at 250°C; the ion-source temperature was 200°C;
and the oven temperature was programmed from 60°C (for
1.5 min), with an increase of 20°C/min to 220°C, then 5°C/min
to 280°C (4 min), and ending with a 10 min isothermal at
280°C. Mass spectra were taken at 70 eV. e Jet-Clean Ion
Source temperature was at 320°C, and MS Quadrupole was at
180°C with a scan interval of 0.5 s. e solvent delay was 0 to
3 min, and the total GC-MS running time was 36 min.
Identification of the peaks was based on computer matching
of the mass spectra with the National Institute of Standards
and Technology (NIST 08) library; direct comparison with the
published data was also utilized.
2.4. Synthesis, Optimization, and Characterization of CuNPs
from S. didymobotrya Root Extracts
2.4.1. Synthesis of CuNPs. Synthesis of CuNPs was carried
out by adding 10 mL of S. didymobotrya root extracts to
90 mL of 0.0125, 0.03125, and 0.05 M of CuSO
4
·5H
2
O so-
lution. e reaction mixture was kept on a magnetic stirrer
at 200 rpm and varying temperatures (40, 60, and 80°C) and
pH (3, 6.5, and 10 pH). e reaction mixture was centrifuged
at 5,000 rpm for 5 min to remove any free biomass residue.
e supernatant was again centrifuged at 12,000 rpm for
40 min to obtain pellets. e pellets of CuNPs were resus-
pended using distilled water. e reduction of Cu ions was
measured by UV-Vis spectrophotometer (Beckham Coulter
DU 720, Beckham Coulter Inc., USA) after 4 hours.
2.4.2. Optimization of Synthesis of CuNPs. A three-level
Box–Behnken experimental design was used for the opti-
mization of analytical parameters affecting the synthesis of
CuNPs [51] using the methanolic root extract of
S. didymobotrya. Minitab statistical software (v17, Minitab
Inc., USA) was used for the experimental design. e se-
lected design matrix from Box–Behnken consisted of 15
trials. e parameters optimized were concentration of
copper ions (0.0125–0.05 M), pH of the mixture (3.0–10.0),
and temperature of the mixture (40°C–80°C) on the particle
size of CuNPs. Response variables as a function of the
synthesized parameters followed a second-order polynomial
as follows:
average size � −85.2+2.570 Temp −174 Conc +16.97 pH −0.02691 Temp ∗Temp
−5813 Conc ∗Conc −0.9391 pH ∗pH +8.41 Temp ∗Conc +0.0278 Temp −23.1 Conc ∗pH.
(2)
where Conc �concentration and Temp �temperature.
2.4.3. Ultraviolet-Visible Spectroscopy. Synthesized CuNPs
(300 μL) were diluted with 3 mL of distilled water and
scanned on a UV-Vis spectrophotometer (Beckham Coulter
DU 720, Beckham Coulter Inc., USA) from 300 to 700 nm at
a resolution of 1 nm using distilled water as the blank [52].
2.4.4. Particle Size Analysis. e sizes of synthesized CuNPs
were measured using a particle size analyzer (Microtrac
Nanotrac Wave II, SL-PS-25 Rev. H) with a laser diode
detector.
2.4.5. X-Ray Diffraction Analysis. e synthesized CuNPs
were subjected to an X-ray diffraction (XRD) analyzer op-
erated at the voltage of 40 kV and 20 mA with copper Kα
radiation in the range of θ–2θconfiguration with a scanning
rate of 0.030°C/s. e crystallite size (CS) was calculated
using Debye–Scherrer equation as follows [52, 53]:
CS �Kλ
cos θ,(3)
where constant (K)�0.94, λ�1.5406 ×10
−10
, cos θ�Bragg
angle, and βis the full width at half maximum (FWHM). Full
width at half maximum in radius (β)�FWHM ×π/180.
2.4.6. FT-IR Analysis. FT-IR analysis was performed to
identify functional groups bound on the surface of the
CuNPs. e specimen and potassium bromide granules were
powdered together in a ratio of 1:100 (w/w) and then
compressed into pellets. Subsequently, the analysis was
performed and measured using FT-IR spectrophotometer in
the range of 400–4,000 cm
−1
and with a resolution of 4 cm
−1
[52, 53].
2.5. Antibacterial Activity of the Synthesized CuNPs from the
S. didymobotrya Root Extract. e antimicrobial efficacy of
biosynthesized 4 cm
−1
CuNPs was assessed using Kir-
by–Bauer disk diffusion susceptibility test protocol [54]. e
test microorganisms were chosen according to the National
Journal of Nanotechnology 3
Committee for Clinical Laboratory Standards 2010 protocols
[55]. Gram-negative E. coli and Gram-positive S. aureus
were tested. Amoxicillin clavulanate impregnated antimi-
crobial susceptibility testing discs were used as a positive
control. All bioassay was done with 30 μL of solution of
CuNPs resuspended in distilled water, S. didymobotrya root
extract, and copper sulphate solution as per the specification
of the positive control (amoxicillin clavulanate). After 18
hours of incubation, the zone of inhibition diameter (ZOI)
was measured to the nearest millimetre using a ruler and
recorded. e susceptibility or resistance of the test or-
ganism to each drug tested was determined using the
published Clinical Laboratory Standards Institute (CLSI).
e ZOI was classified as susceptible (S), intermediate (I), or
resistant (R) based on the CLSI interpretive criteria [50].
3. Results and Discussion
e percentage yield of S. didymobotrya root powder was
9.94% as calculated using equation (1).
3.1.GC-MS Results. e GC-MS analysis on S. didymobotrya
methanolic root extract was conducted to identify the active
phytochemicals that might take part in the fabrication of
CuNPs. e results indicated that the extract contained
mainly fatty acids and some volatile organic compounds.
e compounds along with their retention times, abun-
dances, molecular formulae, and molecular weights are
presented in Table 1. e major compounds identified were
benzoic acid, thymol, n-benzyl-2-phenethylamine, benzal-
dehyde, vanillin, phenylacetic acid, and benzothiazole.
ere is a paucity of literature on volatile compounds in
S. didymobotrya. is study presented the first compre-
hensive report on the GC-MS analysis of volatile compounds
in S. didymobotrya extract. Previously, Mworia et al. [27]
reported the presence of terpinolene and alpha-pinene as the
main antipyretic compounds in dichloromethane extract of
S. didymobotrya leaves using GC-MS. None of the foregoing
compounds were identified in this study. Interestingly, some
compounds identified in the methanolic extract of
S. didymobotrya roots in this study have a potential to take
part in the formation of nanoparticles. For instance, alizarin
(a dihydroxyanthraquinone with two hydroxyl groups on a
phenyl ring) possesses a structure similar to compounds
proposed to take part in chelation and reduction of copper
ions to CuNPs [2, 56].
3.2. Synthesis and Characterization of CuNPs.
Bioreduction of copper ions to CuNPs on exposure to
methanolic extract of S. didymobotrya roots was monitored
by observing the colour change and using UV–visible
spectroscopy. ere was a gradual colour change from light
orange solution to dark brown, indicating the formation of
CuNPs after 4 hours [57–61]. Pretrial runs indicated that no
significant changes occurred after 3 hours. Usually, small
metal nanoparticles absorb visible electromagnetic waves
through the collective oscillation of conduction electrons at
the surface, a phenomenon known as surface plasmon
resonance (SPR) effect [62]. us, the final dark colour
observed could be ascribed to the excitation of surface
plasmon vibrations, indicating the formation of CuNPs
[10, 52]. Copper oxides are thermodynamically more stable
than copper sulphates, which leads to the aggregation and
oxidation of copper without proper protection [62]. us,
the addition of the S. didymobotrya root extract might have
inhibited the oxidation of copper, thereby acting as a re-
ducing and capping agent for the CuNPs [10].
e UV–Visible spectrum of the methanolic root extract
of S. didymobotrya (Figure 1(a)) showed bands at λ
max
338 nm (band II). e band at 338 nm (band II) can either be
due to n⟶π∗transition or a combination of n⟶π∗and
π⟶π∗transitions of heteroatoms linked in a double bond.
e presence of quercetin, a class of flavonoids, has also been
reported as a major constituent of the crude aqueous root
extract of S. didymobotrya [63]. e observed transitions are
probably related to quercetin involved in the reduction
process and formation of CuNPs via π-electron interactions
[56, 64]. Hence, the extract of S. didymobotrya roots further
acted as a reductant and stabilizer agent.
e UV–Vis spectrum of the CuNPs (Figure 1(b))
showed changes in the absorbance maxima due to surface
SPR, demonstrating the formation of CuNPs [65, 66]. e
SPR peak, which is a signature of the formation of CuNPs,
appears in the visible region [67, 68] at 542, 570, 604, 616,
638, 662, and 694, nm with absorbances of 0.064, 0.153,
0.066, 0.064, 0.065, 0.072, and 0.970, respectively (Figure 1).
According to Mei’s theory, the occurrence of a single UV-
visible peak in the UV-Visible spectrum of synthesized
nanoparticles confirms that they are spherical in shape [58].
3.3. Design of Experiments and Optimization Analysis.
Table 2 contains the list of experimental runs and the
corresponding responses obtained from the experiments
projected by Box–Behnken design. e design optimized
parameters that would yield CuNPs with the least average
particle size. e experiments were done as per the run
order to eliminate experimental bias. e mean particle
size of CuNPs was recorded on particle size analyzer
(Nanotrac).
A regression coefficient (R
2
) of 0.9964 was obtained with
a second-order quadratic equation generated for the opti-
mization process. e adequacy of the model was checked
using ANOVA. e predictor variables, that is, pH, con-
centration of copper ions, and temperature, of the mixture
were all significant [47]. e value of p≤0.05 indicated that
pH (p≤0.001) is the most influencing factor when com-
pared to the concentration of copper ion (p≤0.003) and
temperature of the mixture (p≤0.001). Variance inflation
factors (VIF) value close to 1 indicates that the predictors are
not correlated (Table 3) [69]. e qualities of the fitted
models were evaluated based on the coefficients of deter-
mination (R
2
) that was 0.9964. e model explains 99.64% of
the variation in the average size data. e adjusted R
2
is
99.00%. R
2
(pred) is 94.31%, which indicates that the model
explains 94.31% of the variation in the average size of CuNPs
when used for prediction.
4Journal of Nanotechnology
Figure 2 presents the main effects plot for the average
size of CuNPs. e temperature of the reaction mixture, the
concentration of copper ion, and pH of the medium affect
the average size of CuNPs. Comparing the slopes of the lines,
it can be concluded that pH had the greater magnitude of
effects.
Table 1: Compounds identified by GC-MS in S. didymobotrya methanolic root extract.
SN Retention time (mins) Compound Molecular
formula Molecular weight (g/mol)
1 14.4375 Benzoic acid C
7
H
6
O
2
122.12
2 12.4726 Benzyl alcohol C
7
H
8
O 108.14
3 16.7112 ymol C
10
H
14
O 150.22
4 11.0757 N-Benzyl-2-phenethylamine C
15
H
17
N 211.3022
5 17.5703 Benzaldehyde C
7
H
6
O 106.1219
6 18.3040 Vanillin C
8
H
8
O
3
152.15
7 15.7370 Phenylacetic acid C
8
H
8
O
2
136.15
8 15.9515 Nonanoic acid C
9
H
18
O
2
158.24
9 16.0344 Benzothiazole C
7
H
5
NS 135.19
10 14.3651 Tuaminoheptane C
7
H
17
N 115.2166
11 11.5752 Furfurylmethylamphetamine C
15
H
19
NO 229.3175
12 17.8169 Disiloxane H
6
OSi
2
78.22
13 18.6719 Barbital/barbitone C
8
H
12
N
2
O
3
184.195
14 30.7212 6H-Dibenzo (b,d) pyran-1-ol,6a-beta,7,8,10-a-beta-
tetrahydro-3-pentyl-6,6,9-trimethyl-,(+-)-Z- C
21
H
30
O
2
314.5
15 33.5783 Oxymetazoline C
16
H
24
N
2
O 260.381
16 21.5570 1-Methyl-9H-pyrido (3,4-b) indole C
12
H
10
N
2
182.2212
17 10.7265 3-Carene C
10
H
16
136.2340
18 19.1589 5-Hexyldihydro-2(3H)-furanone C
10
H
18
O
2
170.2487
19 19.1900 2,6-bis-(1,1-Dimethylethyl)-2,5-cyclohexadien-1,4-dione C
14
H
20
O
2
220.3074
20 9,12-Hexadecadienoic acid, methyl esther C
19
H
34
O
2
294.4721
21 12.0521 3-Amino-s-triazole C
2
H
4
N
4
84.0800
22 18.4926 Diphenylether C
12
H
10
O 170.2072
23 7.4527 Formamide CH
3
NO 45.0406
24 14.7857 Glycine C
2
H
5
NO
2
75.0666
25 17.205 iocyanic acid, 4-(dimethylamino) phenyl ester C
9
H
10
N
2
S 178.26
26 9.4063 2-(p-Tolyl) ethylamine C
9
H
13
N
27 4.3626 Methyl vinylketone C
4
H
6
O 70.0898
28 28.5117 Pyrene C
16
H
10
202.2506
29 22.3363 4H-1-Benzopyran-4-one C
9
H
6
O
2
146.1427
30 16.8355 Methane, isocyanato-/isocyanic acid/methyl isocyanate C
2
H
3
NO 57.0513
31 23.6700 Phenanthrene C
14
H
10
178.2292
32 26.7448 Menthol C
10
H
20
O 156.269
33 32.1937 Alizarin C
14
H
8
O
4
240.21
34 14.7857 N-Benzylglycine C
9
H
9
NO
3
169.19
35 13.0157 4-(2-Aminoethyl) phenol C
8
H
13
NO
2
155.19
36 14.6250 Benzeneethanamine, N,alpha-dimethyl-N-(phenylmethyl)-,
hydrochloride C
17
H
22
ClN 275.82
37 14.7857 Acetophenone C
8
H
8
O 120.15
38 21.5570 2,4,6-Trimethoxyamphetamine C
12
H
19
NO
3
.HCl 261.70
39 32.8342 (2-Chlorophenyl)-bis[4-(dimethylamino)phenyl]methanol C
23
H
25
ClN
2
O 380.9
40 7.4527 Formamide CH
3
NO 45.04
41 8.2517 Aniline C
6
H
7
N 93.13
42 8.6932 4-Methyl-4-hydroxy-2-pentanone C
6
H
12
O
2
116.1583
43 10.1989 Hexylene glycol C
6
H
14
O
2
118.17
44 11.0757 Propylbenzene C9H12 120.2
45 11.6747 2-(2-Ethoxyethoxy)ethanol C
6
H
14
O
3
134.17
46 11.8208 1,3,5-Trimethylbenzene C
9
H
12
164.7
47 12.1959 2-Ethylhexan-1-ol C
8
H
18
O 130.2279
48 12.2944 1,3-Dichlorobenzene C
6
H
4
Cl
2
147.002
49 14.0562 1,2,3,5-Tetramethylbenzene C
10
H
14
134.22
50 14.1173 2-Hydroxy-3,5,5-trimethyl-2-cyclohexen-1-one C
9
H
14
O
2
154.21
51 22.0834 Methyl tetradecanoate C
15
H
30
O
2
242.2
52 22.3954 1-(4-Hydroxy-3,5-dimethoxyphenyl)ethanone C
10
H
12
O
4
196.1999
53 23.7934 1,2-Benzenedicarboxylic acid, bis(2-methylpropyl) ester C
16
H
24
O
4
278.3435
54 15.1598 4-Tert-butylphenol C
10
H
14
O 150.22
Journal of Nanotechnology 5
338
Absorbance
S. didymobotrya root extracts
0.0
0.2
0.4
0.6
0.8
350 400 450 500 550 600 650 700 750300
Wavelength (nm)
(a)
336
542
570
604
616
638
662
668
694
Absorbance
UV-Vis spectrum:Biosynthesized Cu NPs
0.0
0.1
0.2
0.3
0.4
0.5
0.6
350 400 450 500 550 600 650 700 750300
Wavelength (nm)
(b)
Figure 1: UV-visible spectra of (a) S. didymobotrya methanolic root extract and (b) CuNPs synthesized from S. didymobotrya methanolic
root extract.
Table 2: Box–Behnken design and response variables.
Std order Run order PtType Blocks Temp (°C) Conc (M) pH Size (nm)
15 1 0 1 60 0.03125 6.5 53.59
1 2 2 1 40 0.0125 6.5 53.5
9 3 2 1 60 0.0125 3 21.63
5 4 2 1 40 0.03125 3 16.11
11 5 2 1 60 0.0125 10 63.6
14 6 0 1 60 0.03125 6.5 53.58
3 7 2 1 40 0.05 6.5 38.65
2 8 2 1 80 0.0125 6.5 36.59
8 9 2 1 80 0.03125 10 50.41
4 10 2 1 80 0.05 6.5 34.35
10 11 2 1 60 0.05 3 19.5
13 12 0 1 60 0.03125 6.5 53.57
12 13 2 1 60 0.05 10 55.4
6 14 2 1 80 0.03125 3 5.55
7 15 2 1 40 0.03125 10 53.18
Table 3: Calculated values of the coefficients of the model.
Term Effect Coeff SE coeff T-value pvalue VIF
Constant 53.580 1.020 52.65 0.001
Temp −8.635 −4.317 0.623 −6.93 0.001 1.00
Conc −6.855 −3.427 0.623 −5.50 0.003 1.00
pH 39.950 19.975 0.623 32.05 0.001 1.00
Temp ∗Temp −21.528 −10.764 0.917 −11.73 0.001 1.01
Conc ∗Conc −4.088 −2.044 0.917 −2.23 0.076 1.01
pH ∗pH 23.008 −11.504 0.917 −12.54 0.001 1.01
Temp ∗Conc 6.305 3.153 0.881 3.58 0.016 1.00
Temp ∗pH 3.895 1.948 0.881 2.21 0.078 1.00
Conc ∗pH −3.035 −1.518 0.881 −1.72 0.146 1.00
Conc �concentration and Temp �temperature.
6Journal of Nanotechnology
Figure 3 presents an interaction effects plot for mean size
for Cu NPs. From the plot, it is seen that there was the
interaction of temperature and concentration and the in-
teraction of concentration and pH as shown by lines
intersecting at a point, but there was no possible interaction
of temperature and pH as indicated by lines being ap-
proximately parallel from each other.
3.3.1. Effect of pH. e pH of range 3–10 was varied during
CuNPs average size optimization process. e study revealed
that pH as a parameter strongly influenced the size of CuNPs
as shown by Figure 3 of the interaction effects plot for mean
particle size. e least average size of the nanoparticles was
recorded at a lower pH of 3.0. It was observed that increasing
the pH increased the mean size of the nanoparticles. Similar
observations have been reported by Honary et al. [70] and
Dang et al. [62]. A possible explanation for this observation
is that at a pH of 3.0, nanoparticles were experiencing high
electrostatic repulsion, hence reducing agglomeration.
erefore, at alkaline pH, the nanoparticles were exhibiting
lower electrostatic forces hence allowing particle growth.
3.3.2. Effect of Copper Ion Concentration. Copper ion
concentration (0.0125–0.05 M) was varied for CuNPs av-
erage size optimization. e least mean size of nanoparticles
was recorded at lower concentrations of copper salt as
revealed in Figure 3. is finding agrees with previous
findings [70, 71] that reported that high salt ion concen-
trations led to large particle sizes and broad size distribution
of synthesized nanoparticles. is could be because a low
concentration of salt reduced the probability of copper-
copper interactions, hence reducing agglomeration.
3.3.3. Effect of Temperature. A temperature of range
40–80°C was controlled for CuNPs mean size optimization.
e study showed that an increase in temperature from
40–80°C led to a reduction in the mean size of CuNPs. A
previous research has reported similar findings [71]. is
could be due to possible agglomeration at lower tempera-
tures. (Figure 4).
According to Figure 5, the predicted average particle size
is 1.7862 nm. Increasing temperature yields small particle
size nanoparticles. Decrease in salt concentration and pH
favours synthesis of CuNPs of the least mean size. ese
observations agree with those of Dang et al. [62]. Previous
studies [72, 73] indicated that the pH of aqueous media
influences copper reduction reaction in CuNPs synthesis.
Probable kinetic enhancement is thus conducive for the
reduction of crystallite size because of the enhancement of
the nucleation rate [62].
3.4. Characterization Results for the CuNPs
3.4.1. Particle Size Analysis. Particle size analysis was con-
ducted for thirteen (13) samples of CuNPs prepared at varied
conditions of pH of the reaction medium, copper ion
concentration, and temperature of the solution. e smallest
particle was for CuNPs prepared at 80°C, pH 3.0, and copper
ion concentration of 0.03125 M (Figure 6).
3.4.2. X-Ray Diffraction Results. e XRD peaks were
assigned in comparison with the standard powder diffrac-
tion card of the Joint Committee on Powder Diffraction
Standards (JCPDS card no. 89-2838). e peak positions
were consistent with metallic copper of a crystalline nature.
X-ray diffraction spectrum (Figure 7) revealed diffraction
peaks at 2θvalues of 43.30°, 50.02°, and 73.41°corresponding
to the Miller indices (111), (200), and (220), respectively,
which represent face-centred cubic structure of copper [66].
Further, the peak at 30.0°showed that a small amount of
copper is oxidized to copper (II) oxide. e average size of
CuNPs as determined using Debye–Scherrer’s formula was
6 nm, which is close to 5.55 nm as established by XRD
analysis. e size of the crystal under 100 nm suggested that
the nanocrystalline nature of the biosynthesized CuNPs was
Temp (°C) Conc (M) pH
10
15
20
25
30
35
40
45
50
55
Mean
6.5 10.03.00.03125 0.050000.0125060 8040
Data Means
Figure 2: Main effects plot for the average size of Cu NPs.
Journal of Nanotechnology 7
6.5 10.03.060 8040
0
25
50
0
25
50
0
25
50
0.01250 0.03125 0.05000
Temp (°C)
Conc (M)
pH
Data Means
Temp (°C)
60
80
40
Conc (M)
0.01250
0.03125
0.05000
pH
6.5
10.0
3.0
Figure 3: Interaction effects plot for mean particle size of CuNPs synthesized using S. didymobotrya root extract.
60
48
36
24
12
0
0.008 0.016 0.024 0.032 0.040 0.048
10.5
9.0
7.5
6.0
4.5
3.0
Size (nm)
pH
Conc (M)
(a)
60
48
36
24
12
0
Size (nm)
0.048
0.040
0.032
0.024
0.016
0.008
40 48 56 64 72 80
Temp (°C)
Conc (M)
(b)
10.5
9.0
7.5
6.0
4.5
3.0
60
48
36
24
12
0
Size (nm)
40 48 56 64 72 80
pH
Temp (°C)
(c)
Figure 4: 3 D response surface curves: (a) mean particle size versus concentration and pH, (b) mean particle size versus temperature and
concentration, and (c) mean particle size versus temperature and pH.
8Journal of Nanotechnology
below 15 nm [57]. Similar results were reported by other
researchers from the structure analysis of XRD for bio-
synthesized CuNPs [57, 58, 60].
3.4.3. Zeta Potential of the CuNPs. e zeta potential value
of biosynthesized CuNPs was −69.4 mV (Figure 8). is
indicated that the biosynthesized CuNPs surfaces possessed
Optimal
D: 1.000 High
Cur
Low
Temp (°C)
80.0
[80.0]
40.0
Conc (M)
0.050
[0.0125]
0.0125
pH
10.0
[3.0]
3.0
Predict
Average
Minimum
y = 1.7862
d = 1.0000
Figure 5: Response optimization for average particle size of CuNPs from S. didymobotrya root extract.
100
90
80
70
60
50
40
30
20
10
0
10
9
8
7
6
5
4
3
2
1
0
%Passing
%Channel
Particle Size Distribution
0.01 0.1 1 10 100 1,000 10,000
Size (nanometer)
Figure 6: Particle size of CuNPs prepared at 80°C, pH 3.0, and copper ion concentration of 0.03125 M.
80
70
60
50
40
30
20
10
908070605040302010
Intensity (Counts/Second)
2-eta (degree)
110
111
200 220 311
Figure 7: X-ray diffraction pattern of CuNPs synthesized from S. didymobotrya root extract.
Journal of Nanotechnology 9
strong electrostatic repulsion hence good stability. A recent
study [61] indicated that CuNPs of size 82.32 nm had a
negative zeta potential of −11.9 mV. Such negative zeta
potentials suggest that charge distribution of the nano-
particles as well as their sizes could play a role in promoting
or enhancing their biological properties [74]. In other words,
high negative zeta potential translates into strong repulsion
between the particles causing amplification or enhancement
of their stabilities [75].
3.4.4. FT-IR Analysis. FT-IR analysis was done to identify
the functional groups of the phytochemicals that partici-
pated in synthesizing CuNPs and their stabilization. e
spectrum shown in Figure 9 revealed a broadband in the
range 3,400–3,500 cm
−1
characteristic of N-H stretch of
amines and amides, and a band of the range 3400–2400 cm
−1
indicating the presence of O-H of carboxylic acids, alcohols,
and phenols. e peak at 1,612.25cm
−1
is assigned to C�C of
alkenes and aromatic compounds. e presence of aromatic
compounds was confirmed by the two peaks at 988.30 cm
−1
and 830.60 cm
−1
known for C-H out-of-plane bend for
aromatic compounds. A peak at 1,271.13 cm
−1
is attributed
to C-O bond of alcohols, carboxylic acids, and esters.
e presence of these functional groups indicated the
possible involvement of reductive groups on the surfaces of the
CuNPs [76]. ey are also involved in the capping of the
CuNPs, as observed in previous studies that synthesized CuNPs
from plant extracts [10, 77]. e spectrum indicated new
chemical linkages on the surface of CuNPs, suggesting that
S. didymobotrya root extract can bind to CuNPs through
hydroxyl and carbonyl groups of the amino acid residues in the
protein of the extracts, therefore acting as reducing, stabilizing,
and dispersing agents for synthesized copper oxide nano-
particles and preventing agglomeration of the CuNPs [60, 61].
3.5. Antibacterial Activity of S. didymobotrya Root Extract and
Synthesized CuNPs. Figure 10 shows that the CuNPs had an
inhibitory effect against E. coli and S. aureus. Pearson’s
product-moment correlation was performed to evaluate the
association between the size of CuNPs and ZOI of CuNPs
against E. coli and S. aureus (n�13). e analysis showed
that there was a negative correlation between the size of
CuNPs and the zone of inhibition of E. coli (r� −0.74;
p≥0.01). Similarly, a negative correlation was observed
between the size of CuNPs and the zone of inhibition of
S. aureus by the CuNPs (r�0.74; p≥0.05).
0
50000
100000
150000
200000
Total Counts
-100 100 2000
Apparent Zeta Potential (mV)
Figure 8: Zeta potential distribution of CuNPs synthesized using S. didymobotrya root extract.
0.14
0.12
0.10
0.08
0.06
0.04
0.02
3500 3000 2500 2000 1500 1000 500
Wavenumber cm-1
Absorbance Units
1612.25
1271.13
988.30
830.60
683.43
Figure 9: FT-IR spectrum of CuNPs synthesized from S. didymobotrya root extract.
10 Journal of Nanotechnology
e highest zone of inhibition was 30.00 ±0.58 mm for
S. aureus and 26.00 ±0.58 mm for E. coli was achieved for
CuNPs with the least mean particle size that was synthesized
at optimum conditions of 80°C, copper ion concentration of
0.03125 M, and pH 3.0. is indicated that CuNPs of least
mean particle size had a high surface area to volume ratio,
hence effectively binding to the microbial membrane and
probably altered its permeability that could have caused
growth inhibition. Sathiyavimal et al. [10] reported similar
results in which 100 μL of CuNPs prepared from Sida acuta
extract highly inhibited E. coli with a zone of inhibition
maximum of 15 mm, showed a lower antibacterial activity
against S. aureus while the lowest inhibition diameter was
11 mm against P. vulgaris. Previous authors [66, 78, 79] have
reported similar results, in which E. coli was the most
inhibited bacteria when compared with S. aureus and other
Gram-positive bacteria.
e higher inhibition of Gram-negative bacteria by CuNPs
could be partially explained by the facilitated influx of smaller-
sized nanoparticles into the cell wall of Gram-negative bacteria
that consists of a unique outer membrane layer and a single
peptidoglycan layer as compared to the cell wall of Gram-
positive bacteria with several peptidoglycan layers [80, 81].
Furthermore, CuNPs have been speculated to adhere to Gram-
negative bacterial cell walls due to electrostatic interaction, or
the copper ions facilitate rapid DNA degradation and reduc-
tion of bacterial respiration [82]. In some Gram-negative
strains, copper ions alter the conformation and electron
transferase of the associated reductases, culminating in the
inhibition of cytochromes in the membrane [83].
4. Conclusion
Synthesis of CuNPs from S. didymobotrya methanolic root
extract had the following optimum synthesis conditions:
temperature 80°C, pH 3.0, and copper ion concentration of
0.0125 M. e mean particle size of CuNPs predicted by the
design at the optimum conditions was 1.7862 nm. UV-Vis
analysis showed a characteristic surface plasmon resonance
peak at 571 nm indicating the formation of CuNPs. FT-IR
analysis revealed that the nanoparticles were bound by
carboxylic acids, amines, and amides, phenols, and esters.
Particle size analysis conducted using Nanotrac particle
analyzer showed that synthesized CuNPs were of the range
of 5.55–63.60 nm particle size. X-ray diffraction measure-
ment confirmed the presence of cubic face centred CuNPs.
e measured zeta potential value of CuNPs was −69.4 mV
indicating that they were stable. In conclusion, the bio-
synthesized Cu nanoparticles are stable and displayed better
antimicrobial activity against E. coli and S. aureus compared
to amoxicillin clavulanate (standard). e study recom-
mends the testing of biosynthesized CuNPs against other
potential multidrug resistant microbes to enable their de-
velopment into antimicrobial agents.
Abbreviations
CuNPs: Copper nanoparticles
E. coli:Escherichia coli
S. didymobotrya:Senna didymobotrya
SPR: Surface plasmon resonance.
18 19
16
18 18
15
17
15
26
18
15 16
23
20
13
11
16
21
19 20 19
16 15 14
30
19
16 17
22
28
14
10
CuNPs.T60.C0.03125.pH6.5
CuNPs.T60.C0.0125.pH3.0
CuNPs.T40.C0.03125.pH10
CuNPs.T80.C0.05.pH6.5
CuNPs.T40.C0.05.pH6.5
CuNPs.T60.C0.05.pH10.0
CuNPs.T60.C0.05.pH3.0
Ammoxillin calvnalate (Standard)
Senna root extract
Copper sulphate solution
CuNPs.T60.C0.0125.pH10.0
CuNPs.T80.C0.03125.pH10.0
CuNPs.T80.C0.0125.pH6.5
CuNPs.T40.C0.0125.pH6.5
CuNPs.T40.C0.03125.pH3.0
CuNPs.T80.C0.03125.pH3.0
ZOI E coli
ZOI S. aureus
0
5
10
15
20
25
30
35
Zone of Inhibition
Figure 10: Antibacterial activity of CuNPs, amoxicillin clavulanate, copper sulphate solution, and S. didymobotrya methanolic root extract.
Journal of Nanotechnology 11
Data Availability
e datasets supporting the conclusions of this study are
available from the corresponding author upon request.
Conflicts of Interest
e authors declare that there are no conflicts of interest
regarding the publication of this paper.
Acknowledgments
e authors are grateful to the World Bank and the Inter-
University Council of East Africa for the fellowship awarded
to Bernard Otieno Sadia through the Africa Center of Ex-
cellence II in Phytochemicals, Textile and Renewable Energy
at Moi University, Kenya. is study was financially sup-
ported by the Africa Center of Excellence II in Phyto-
chemicals, Textile and Renewable Energy (ACE II PTRE)
hosted at Moi University, Kenya (Credit No. 5798-KE).
Timothy Omara (Department of Chemistry and Biochem-
istry, Moi University) is acknowledged for his tireless
guidance in preparing and English proofreading of this
article.
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