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SN Applied Sciences

, 1:403 | Cite as

Application of central composite design for optimization of biosynthesized gold nanoparticles via sonochemical method

  • Adamu Ibrahim UsmanEmail author
  • Azlan Abdul AzizEmail author
  • Bashiru Kayode Sodipo
Research Article
  • 107 Downloads
Part of the following topical collections:
  1. 1. Chemistry (general)

Abstract

Exploring new techniques for synthesising, characterising, optimising, and correlating the impact of different variables for the production of nanoparticles are key features of contemporary researchers. Gold nanoparticles were synthesized using ultrasound radiation and palm oil frond extracts (POFE) as a stabilising agent. A full factorial design, five levels, and four factors experimental design were employed to optimize the process. Four different independent variables: concentration of HAuCl4·3H2O, concentration of POFE, sonication amplitude, and sonication time were considered in the optimisation process. Central composite design and the surface response methodology were used to evaluating the individual and mutual correlation between the regulating variables and the response leading to the optimisation condition. The “adj. R-square” and the “pred. R-square” together with the regressional equations of the hydrodynamical size and p values (psize = 0.0001) demonstrated that the data are well fitted into the model. The predicted value of the average hydrodynamical size (40 nm) at the optimum level is about 95% in agreement with the observed value.

Keywords

Green Gold Sonochemistry CCD Synthesis POFE 

1 Introduction

Green synthesis of gold nanoparticles (AuNPs) has become a major focus area of the scientific community due to their excellent optical properties, high chemical stability and high bioconformity for numerous applications [1, 2, 3, 4, 5]. AuNPs show a potential application in the various field of studies, which include medical applications and catalytic activities [6, 7]. Recently from our lab, we have demonstrated that sonochemical method can be used to fabricate numerous nanostructures [8, 9, 10, 11, 12, 13]. This can be achieved due to various unique secondary conditions such as high temperature, pressure, microjets and collision rate generated by the acoustic cavitation process. These conditions allow rapid and facile production of different nanomaterials [14]. Several works have reported the sonochemical synthesis of AuNPs using different capping agent [15, 16, 17, 18].

Palm oil tree (Elaeis guineensis) belong to the family of Arecaceae known as an African tree. This tree is grown generally in its innate humid regions such as west and central Africa as well as Malaysia and Indonesia for oil production. Benefits of the tree are numerous including its application in the production of biodiesel, ruminant livestock feed, frying, and food [19, 20, 21]. The palm oil fronds derived during the reaping of oil palm fruit produced huge waste which is either burned to ashes or left on the ground to decompose naturally. The practice of burning has been discouraged due to environmental concern since 1990s [22], and the later is a slow process of managing the waste. This plant contained some vital functional ligands, which can be applied as the source of bioagent to replace the conventional use of chemicals that cause various biotic dangers due to their usual toxicity [23]. Several studies had synthesis AuNPs using different plant extracts and optimised the produced AuNPs by manipulating their morphology, sizes, and polydispersity index (PDI) using one factor at a time (OFAT) [24, 25, 26]. However, this OFAT is usually not the true test for the optimum value, because in some cases the variables under consideration engage in interaction with one another, which were not taken into account while using OFAT [27].

The objective of this work is to synthesised AuNPs using POFE as a stabilising agent and ultrasound radiation as a reducing agent. The biosynthesized AuNPs were optimised using central composite design (CCD) and response surface methodology (RSM) version 10.0 (Stat-Ease, Inc., Minneapolis, MN 55413, USA) by employing five-level and four-variables to account for the cross and quadratic interaction among the variables and the corresponding response (hydrodynamical size) of the synthesised AuNPs.

2 Material and method

2.1 Reagents

Hydrogen tetrachloroaurate (HAuCl4·3H2O) was purchased from Sigma-Andrich Corporate (St. Louis, MO, USA) and used without alteration. Double Distilled Water (DDW) was used throughout the experiment as a solvent.

2.2 Preparation of POFE

The palm oil frond extracts (POFE) was prepared according to [28]. Briefly, a fresh palm oil front (POF) was washed with DDW and oven-dried for 6 hours at 150 °C. The POF was grounded into powder using an electrical blender. The required amount (between 2 and 5 g) was immersed in 100 ml of DDW to make 2–5% (w/w) depending on the required amount needed to make the solution. The mixture was heated for 10 min at 80 °C and left overnight. The extracts were filtered using Wattman no.1 filter paper. The filtrate was stored at 4 °C for further used.

2.3 Synthesis of AuNPs

Colloidal AuNPs were prepared according to [29] with modification. Briefly, 10 ml of 3.5% (w/w) of POFE was added into the beaker containing 100 ml of 0.02% (w/w) of HAuCl4·3H2O. Immediately the mixture was placed under ultrasound radiation generated by the probe sonicator at an amplitude of 45% for 20 min using VCX 750 Sonicator. Few minutes after starting the sonication the solution changed from yellow to purple, wine red or pink often depending on the type of set-up being run. Thirty different experimental set-ups were performed with six centred points as provided by the CCD (Table 1). The procedure above is for one of the six centred points, which was repeated five more times. The same procedure was followed for the other 24 experiments, but with different concentration of HAuCl4·3H2O, concentration of POFE, sonication amplitude and sonication time as provided in Table 1. The hydrodynamical size of the synthesised AuNPs were measured using dynamic light scattering (DLS). Analysis of variance (ANOVA) and three-dimensional graphs (3D) were used in analysing and predicting the significance of the model developed as well as the correlation between the variables with their corresponding response.
Table 1

Experimental matrix

Standardized

Runs

\(x_{1}\)

\(x_{2}\)

\(x_{3}\)

\(x_{4}\)

Y1

S30

14

0.020

3.50

45.00

20.00

46.59

S29

22

0.020

3.50

45.00

20.00

49.00

S28

17

0.020

3.50

45.00

20.00

47.56

S27

6

0.020

3.50

45.00

20.00

47.34

S26

29

0.020

3.50

45.00

20.00

43.72

S25

20

0.020

3.50

45.00

20.00

45.26

S1

10

0.010

2.00

30.00

10.00

33.13

S2

28

0.030

2.00

30.00

10.00

50.07

S3

30

0.010

5.00

30.00

10.00

51.31

S4

9

0.030

5.00

30.00

10.00

50.13

S5

15

0.010

2.00

60.00

10.00

38.43

S6

3

0.030

2.00

60.00

10.00

56.87

S7

11

0.010

5.00

60.00

10.00

72.49

S8

1

0.030

5.00

60.00

10.00

56.76

S9

26

0.010

2.00

30.00

30.00

36.41

S10

7

0.030

2.00

30.00

30.00

83.75

S11

23

0.010

5.00

30.00

30.00

42.54

S12

4

0.030

5.00

30.00

30.00

62.34

S13

16

0.010

2.00

60.00

30.00

53.23

S14

19

0.030

2.00

60.00

30.00

100.20

S15

24

0.010

5.00

60.00

30.00

53.39

S16

13

0.030

5.00

60.00

30.00

69.51

S17

12

0.006

3.50

45.00

20.00

74.00

S18

25

0.034

3.50

45.00

20.00

109.90

S19

27

0.020

1.38

45.00

20.00

33.79

S20

21

0.020

5.62

45.00

20.00

32.11

S21

18

0.020

3.50

23.79

20.00

37.52

S22

5

0.020

3.50

66.21

20.00

58.28

S23

2

0.020

3.50

45.00

5.86

28.66

S24

8

0.020

3.50

45.00

34.14

48.55

2.4 Experimental design

Experimental design is a phenomenon that provides the effects of variables on the response(s) to improve the performance and minimise errors in the experiments with a minimum number of runs and generate an optimum level of the process. Different design were used to optimise various process such as Response Surface Methodology (RSM) which comprises: Central Composite Design (CCD), Box Benhkhan Design (BBD), Miscellaneous Desing (MD), etc., followed by Factorial which includes: 2-Level Factorial Design, Irregular Fraction Design, General Factorial Design., The CCD was selected in this study because it is embedded with some centred (nc) point, 2n factorial point, and 2n axial points. It also gives room for adding and eliminating factorial or axial point during the process of the experiment without restarting the whole experimental set-up.

The centred point estimate experimental errors and ensure reproducibility of the experiments [30]. The factors were coded from low to high as − 1 and +1 respectively. A distance of α-value was set from the centre in the axial point to make the design rotatable. For this experiment \(\alpha = \sqrt 2\). A five-level CCD was performed to estimate the effects of the concentration of HAuCl4·3H2O, the concentration of POFE, sonication amplitude, and sonication time on the hydrodynamical size of the synthesised AuNPs. The four independent variables are related with the following mathematical modelling equation (Eq. 1)
$$y = \beta_{o} + \mathop \sum \limits_{i = 1}^{4} \beta_{i} X_{i} + \mathop \sum \limits_{i = 1}^{4} \mathop \sum \limits_{i = 1}^{4} \beta_{ij} X_{i} X_{j} + \mathop \sum \limits_{i = 1}^{4} \beta_{ii} X_{i}^{2}$$
(1)
where y is the response (hydrodynamical size), \(X_{i} 's\) are the independent variable (\(x_{1}\) = concentration of HAuCl4·3H2O, \(x_{2}\) = concentration of POFE, \(x_{3}\) = sonication amplitude, and \(x_{4}\) = sonication time) while the parameter \(\beta_{o}\) is the model constant, \(\beta_{i}\) is the linear coefficients, \(\beta_{ii}\) is the quadratic coefficients, and \(\beta_{ij}\) is the cross product.

Enhancing and optimising the developed process by RSM are the product of analysing the mathematical modelling equation and statistical method of ANOVA to evaluate the significant effects and correlation of all variables in the event of conceptual interrelation on the response to determine the best optimum condition for the process.

2.5 Characterisation

The UV–Vis spectra of the optimised AuNPs was measured using 3600 spectrophotometers (Shimadzu UV—3600) for surface plasma resonance (SPR) in the range of 400–700 nm. The functional groups present in the POFE, which are responsible for stabilising the synthesised AuNPs was investigated using Fourier Transform Infrared Spectroscopy (FT-IR) (Perkin Elmer System 2000) in the range 600–4000 cm−1 at a resolution of 4 cm−1 before and after the synthesis. The hydrodynamical size of the optimized AuNPs was measured using DLS (zeta sizer nano—series). The optimized AuNPs was centrifuged at 14,500 rpm for 10 min, washed twice with DDW, then dried in an oven and subjected to X-ray diffraction (XRD) analysis. The XRD analysis was carryout using D8 ADVANCE BRUKER with Cu K radiation (λ = 0.154 Å) operated at the potential difference and current of 40 kV and 40 mA respectively to confirmed the crystallinity of the synthesised AuNPs. The morphology of the optimised AuNPs was characterised using high-resolution transmission electron RHTEM Tecnai F20.

3 Results and discussion

3.1 Sonochemistry study

Sonochemical production of nanoparticles from various materials is well known [31]. AuNPs can be produced sonochemically by the reduction of HAuCl4·3H2O to Au(0) in an aqueous solution. The effects of sonication amplitude (\(x_{3}\)), which generates the ultrasonic intensity to produce AuNPs along with the effect of concentration of HAuCl4·3H2O (\(x_{1}\)), concentration POFE (\(x_{2}\)), and sonication time (\(x_{4}\)), were investigated in this study.

3.2 The development of the hydrodynamical size

The hydrodynamical size of the synthesised AuNPs from the 30 experimental sets-ups conducted were measured and recorded using DLS (Table 1). Uncontrollable factors were minimised by randomising the experimental series and provide the results in a standard format in this report for easy referral. The reduction of Au3+ ions to Au0 was successful using POFE as a stabilising agent, and the formation of AuNPs were confirmed by both visual observation and proper UV–vis spectra [32] of the SPR of the 30 experiments (Supplementary data 1).

The maximum hydrodynamical size of the AuNPs was obtained with sample S18 with an average hydrodynamical size of 109.9 nm and corresponding wavelength of 616 nm, while the smallest hydrodynamical size was obtained with sample S23 with an average hydrodynamical size of 28.66 nm and corresponding wavelength of 538.5 nm. The band position shifts from blue (530 nm) to red (616 nm). This shifts may be due to the increase in hydrodynamical size, which results from the increase in sonication time from 5.52 to 20.00 min [33].

3.3 Central composite design (CCD)

In the CCD process, the experimental set-ups were regulated in a random style to reduce the effect of uncontrolled variables as showed (Table 1). Four independent variables were represented as the concentration of HAuCl4·3H2O (\(x_{1}\)), concentration POFE (\(x_{2}\)), sonication amplitude (\(x_{3}\)), and sonication time (\(x_{4}\)). These varibales are distributed and coded as five level \(\left( { - \sqrt 2 , - 1, 0, + 1, + \sqrt 2 } \right)\) with \(\pm \sqrt 2\) represent the star point (\(\pm \alpha\)), while − 1, 0, and +1 represent the low, middle, and high level respectively. These levels were selected, and the outputs of all 30 experiments [hydrodynamical size (Y1)] were analyzed based on the interaction of the individual, quadratic, and cross products of the variables (Table 1). The most significant variable and their cross products as well as their quadratic effects were evaluated via ANOVA.

3.4 Analysis of variance (ANOVA) of the hydrodynamical size

Fom the ANOVA results of hydrodynamical size a significant model with F-value 95.92893and p value < 00001 was obtained. Sundari reported that a model would be sufficient and adequate to explain the correlation between the factors and the corresponding response when the p value < 0.01 [32]. Thus, the model from the current study is adequately and sufficiently explained the correlation between the factors under consideration and the response. The lack of fit is not significant with F-value of 3.874761, which implies that there is 9.42% chance that the lack of fit F-value could be larger. This could occur due to noise. The probability of F-values < 0.0500 indicated that the model terms are significant [34]. In this regard, the concentration of HAuCl4·3H2O (\(x_{1}\)), amplitude (\(x_{3}\)), and time (\(x_{4}\)) are significant in linear relation while the concentration of POFE (\(x_{2}\)) is not signifoicant. Furthermore, the cross product of \(x_{1} x_{2}\), \(x_{1} x_{4}\), and \(x_{2} x_{4}\) together with the quadratic effect of \(x_{1}^{2}\), \(x_{2}^{2}\) and \(x_{4}^{2}\) are all significant with p value < 0.0001. However, the concentration of POFE is not significat but its qudartics term is significant, which shows that the variables have significant quadratic effect on the hydrodynamical size. Consequently, the sonication amplitude is significant while it is quadratic terms is not significant (Table 2). This is expected since the value of sonication amplitude is ristricted between 20 to 100% anything above or beyoung this is not possible.
Table 2

ANOVA results for particles size

Source

Sum of squares

Df

Mean

F

p value Prob > F

Remark

Square

Value

Model

10,359.76

10

1035.976

95.92893

< 0.0001

Significant

A-Conc. of HAuCl4·3H2O

1989.419

1

1989.419

184.2156

< 0.0001

Significant

B-Conc. of POFE

0.801649

1

0.801649

0.074231

0.788212

Not significant

C-amplitude

726.7245

1

726.7245

67.293

< 0.0001

Significant

D-time

723.7093

1

723.7093

67.01379

< 0.0001

Significant

AB

765.6289

1

765.6289

70.89545

< 0.0001

Significant

AD

780.6436

1

780.6436

72.28578

< 0.0001

Significant

BD

600.25

1

600.25

55.58175

< 0.0001

Significant

A^2

4670.896

1

4670.896

432.5141

< 0.0001

Significant

B^2

531.6922

1

531.6922

49.23346

< 0.0001

Significant

D^2

204.426

1

204.426

18.92937

< 0.0001

Significant

Residual

205.1888

19

10.79941

   

Lack of fit

187.8723

14

13.41945

3.874761

0.07143

Not significant

Pure error

17.31648

5

3.463297

   

Cor total

10,564.94

29

    

R-square

0.9806

 

Adj. R2

0.9704

Pred. R2

0.9412

C.V.%

3.29

 

Adeq. Pre.

38.441

  

Df degree of freedom

Adequate precision (Adeq. Prec.) measured the signal to noise ration. A ration greater than four is suitable [35]. The ratio 38.441 illustrates sufficient signals for the model to navigate the required hydrodynamical size. The coefficient of determination (R2) and the adjusted R2 estimate the fitness of the model [36], the “pred R2” of 0.9412 is in good agreement with the “Adj R2” of 0.9704. This confirmed and validated the selected model [37]. Furthermore, the coefficient of variation CV is less than 10%, which indicates the reliability and feasible precision of the model developed (Table 2).

The correlation between the observed and the predicted values of the hydrodynamical size is shown in Fig. 1. In general, the final equations that described the relationship between the variables and the response with the actual effect of the significant terms in the model are expressed in Eqs. (2) and (3). The former is in coded factors while the latter is in actual factors.
Fig. 1

Correlation between predicted and actual observed data from the 30 experimental results for average hydrodynamical size

$$\begin{aligned} Y & = 47.09 + 9.97x_{1} - 0.2x_{2} + 6.03x_{3} + 6.02x_{4} - 6.92x_{1} x_{2} + 6.99x_{1} x_{4} - 6.13x_{2} x_{4} \\ & + \,22.06x_{1}^{2} - 7.44x_{2}^{2} - 4.61x_{4}^{2} \\ \end{aligned}$$
(2)
$$\begin{aligned} Particles\,size & = \, - \,7.10475 - 7608.73200*Conc.\,of\,HAuCl_{4} .3H_{2} O + 40.67662*Conc.\,of\,POFE \\ & \quad +\,0.40186*Apmlitude + 2.47954*Time - 461.16667*Conc.\,of\,HAuCl_{4} .3H_{2} O \\ & \quad *\,Conc.\,of\,POFE + 69.85000*Conc.\,of\,HAuCl_{4} .3H_{2} O*Time - 0.40833*Conc.\,of\,POFE \\ & \quad *\,Time + 2.2059E^{5} \left( {Conc.\,of\,HAuCl_{4} .3H_{2} O} \right)^{2} - 0.046146 \\ & \quad *\,\left( {Time} \right)^{2} \\ \end{aligned}$$
(3)

3.5 Three-dimensional (3D) graphs analysis of the responses

It was observed from 3D response surface analysis that upsurge in hydrodynamical size is due to an increase in the concentration of HAuCl4·3H2O (x1) and concentration of POFE (x2) when sonication amplitude (\(x_{2}\) = 45%) and sonication time (\(x_{4}\) = 20 min.) were kept constant (Fig. 3a). The interaction effect between x1 and x2 is significant with the F-value 70.89545 but the quadratic effect of x1 is more pronouced with F-value 432.5141 than that of x2 with F-value 49.23346. However, initially the hydrodynamical size start increasing when x2 is rising but suddenly starts decreasing rapidly after reaching its saturation point at a point of the x1= 0.015% w/w. It is also clear from the 3D graph that increased in x2 and x1 simiultaneously will reduce the hydrodynamical size at some point and increase it in another point. Based on the contour line, x2 reduced the hydrodynamical size while x1 increased the size (Fig. 2a, b). The contour line in Fig. 2a, c indicates a strong intraction between the variables while that of Fig. 2e represent weak interaction between the variables. Increase in sonication time with variation in concentration of HAuCl4·3H2O increases the hydrodynamical size (Fig. 2c, d). Similarly, an increase in soniaction time with the variation of concentration of POFE increases the hydrodynamical size (Fig. 2e, f) [23].
Fig. 2

The combined effect of the response surface of a, b concentration of HAuCl4·3H2O and sonication time c,d concentration of POFE and sonication time, and e, f sonication amplitude and sonication time on the particles size

3.6 Optimization procedure

The optimization process was carried out using design—expert software version 10. In the process of optimization, a target criterion was set as Y1 = 40 nm for the hydrodynamical size. The optimum synthesis condition was obtained at a concentration of HAuCl4·3H2O = 0.02%, concentration of POFE = 2.00%, sonication amplitude = 42.07%, and sonication time = 21.51 min as shown in the profile of predicted and desirability option from the design—expert software. The desirability of the process selected is 100%, which showed a maximum probability of obtaining the target response (Supplementary data 2).

3.7 Characterization of the optimized AuNPs

The formation of the optimised AuNPs was confirmed via the surface plasmon resonance (SPR) of the particles in the range of 400–700 nm (Fig. 3a) [38]. The average hydrodynamical size was found to be 38.7 nm which is about 96% in agreement with the predicted value, the distribution of the hydrodynamical size is shown in Supplementary data 3.
Fig. 3

Characterization of optimised AuNPs a UV–Vis spectra of the optimized AuNPs b FTIR results before the synthesis (A) and after the synthesis (B), and c XRD characterization of the optimized AuPNs

The functional group present in the POFE, which are responsible for stabilizing the synthesised AuNPs as revealed by the FT-IR spectrum are shown in Fig. 3. The presence of absorption peaks at 3292 cm−1 and 1643 cm−1, can be attributed to –OH (phenol) and CO–NH stretching. The functional ligand, secondary amines (protein) in the spectrum before the synthesis (Fig. 3b (A)) indicated that the extract would be a potential capping agent. The shift of some peaks from lower peak (1633 cm−1) and (2125 cm−1) to a higher peak (1636 cm−1) and (2130 cm−1) respectively; and formations of new peaks at (2946 cm−1), (2846 cm−1) and (1337 cm−1) in Fig. 3b (B) confirmed the reduction of Au3+ to Au0 [39]. The XRD characterization was performed by D8 ADVANCE BRUKER with Cu K radiation (λ = 0.154 Å) in the range of 20–90 regulated at a current of 40 mA and voltage of 40 kV (Fig. 3c) and the features indicated by the results are those for the face-centered cubic (fcc) structures for the gold [40].
Fig. 4

HRTEM results of the AuNPs synthesis using POFE as stabilizing agent at different resolution a 100 nm b 50 nm c 5 nm d 2 nm

The morphologies of the optimised AuNPs are shown in Fig. 4. Majority of the particles displayed were spherical with few triangular and hexagonal. It was observed that the distribution of the NPs is well dispersed, and an average grain sizes of 21. ± 3.42 nm was obtained using ImageJ software, and the lattice fringes corresponding to 0.236 nm, which matches the standard lattice fringes of AuNPs [41].

4 Conclusion

Ultrasound radiation was successfully utilized as the source of energy to break the molecular bond of the HAuCl4·3H2O and POFE to produce AuNPs without the addition of any surfactant. The functional group (\(OH^{*}\) and \(CO - NH^{*}\)) present in the POFE was corfirmed as a potential candidate for reducing and stabilizing AuNPs produced. The high regression coefficient of second order polynomial equation and the model developed by the central composite design of the hydrodynamical size indicated that the data were well fitted. Interaction effect was found to exist between the variables on the response. An average hydrodynamical size of 40 nm was successfully synthesised at the optimum level when concentration of HAuCl4·3H2O = 0.02%, concentration of POFE = 2.00%, sonication amplitude = 42.07%, and sonication time = 21.51 with about − 95% in agrement with the observed value. Highly monodispersed AuNPs without aggreation were obtained as reveveled by the HRTEM analysis.

Notes

Acknowledgements

This work was supported by the University Sains Malaysia [Grant Numbers 203/PFIZIK/6763003], and the authors want to thank the Federal University Kashere and TetFund Nigeria for their support toward the completion of this work.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no competing interests.

Supplementary material

42452_2019_429_MOESM1_ESM.docx (143 kb)
Supplementary material 1 (DOCX 143 kb)
42452_2019_429_MOESM2_ESM.docx (39 kb)
Supplementary material 2 (DOCX 39 kb)
42452_2019_429_MOESM3_ESM.docx (61 kb)
Supplementary material 3 (DOCX 60 kb)

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of PhysicsUniversiti Sains MalaysiaGelugorMalaysia
  2. 2.Institutes for Research in Molecular Medicine, USMGelugorMalaysia
  3. 3.Department of PhysicsFederal University KashereAkkoNigeria
  4. 4.Department of PhysicsKaduna State UniversityKadunaNigeria
  5. 5.Center for Energy and Environmental Strategy ResearchKaduna State UniversityKadunaNigeria

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