Introduction

In the field of nanoparticle synthesis from different materials, notable improvements have recently been accomplished and lots of effort have been done to control their size, composition, and uniformity [1]. Nanoscales’ materials have raised as novel antibacterial agents comprising a great ratio of surface area to volume and the unique physical and chemical properties [2, 3]. Nanoparticles display exclusive physicochemical attributes contrasted with their bulk materials. There is a considerable keen on obtaining well-diffused, ultrafine, and monotonous nanoscales to delineate and take their distinct distinguished [4]. Metallic nanoscales, like nanomaterials, have attracted much interest in academia and engineering because of their physicochemical properties [5]. Mn oxides can be employed in molecular sieves, solar cells, optoelectronics, drug delivery ion sieves, as well as other fields such as imaging contrast agents, magnetic storage devices, and water treatment and purification, due to their privileged physical and chemical properties [4, 6,7,8,9,10,11].

Various methods including chemical and physical means, chemical reduction, sol–gel, solvothermal or hydrothermal, and electrochemical reduction techniques are widely employed for the synthesis of the nanomaterials [12, 13]. Their available synthetic processes include either oxidation of Mn(II) in basic solution or oxidation by oxygen, potassium persulfate, and hydrogen peroxide, or by reduction of permanganate using different routes [14, 15]. Eventually, synthesize of nanoscales has been done by bacteria, fungi, and other microorganisms [12, 16, 17]. The menace of growing contamination causes a great request for green chemistry and biological processes for preparation, recycling, and degrading chemical materials [18]. The synthesis of nanomaterials using plants extracts can be preferable than other biological methods like microbial procedure [18, 19]. Antioxidant activity of the plant’s extracts is responsible for synthesizing of metallic nanomaterials. The usage of the extract of Parthenium [20], Euphorbia hirta, Polyalthia longifolia [21], Coriandrum sativum, Dittrichia graveolens (L.) [10, 22] Azadirachta indica, Jatropha curcas [23], Ocimum sanctum, and several other plants supply the principles of green chemistry that is environmentally friendly. This reaction is safe, quick, and easily done at the ambient temperature and pressure, and can be scaled-up easily [21]. Early researchers of Yucca gloriosa bark yielded two Yucca species of tropical or subtropical plants with a tree-like habit, which grow mainly in the arid or semi-arid regions. They contain large quantities of steroidal glycosides. They thus have potential in biological, pharmaceutical, and industrial applications and several steroidal glycosides exhibit fungistatic or fungicidal property [24]. In addition, they contain several very uncommon phenolic constituents named gloriosaols A, B, C, D, and E [25]. The Trolox equivalent antioxidant capacity (TEAC) assay confirmed the remarkable antioxidant activity of the Y. gloriosa extract [25], which have made it useful for the synthesis of the nanoparticles [14].

In this study, manganese nanoscales are prepared via the Y. gloriosa leaves extract, optimized, and evaluated by the design expert software‏. RSM as a cost-effective and time-saving method [26] was used for optimization. MnO2 NPs characterized via XRD and FESEM, and TEM analysis methods.

Experimental

Materials

Manganese acetate [(CH3COO)2Mn·6H2O] the analytical grade was purchased from Sigma-Aldrich company (USA). Fresh leaves of Y. gloriosa were cut from University of Tehran campus (Tehran, Iran); leaves thoroughly washed thrice with distilled water and air-dried in the shade. All chemicals and solvents were used as received without further purification and distilled water was used in all experiments.

Optimization of green synthesis

Green synthesis of the MnO2 NPs

8 g dried powder of Y. gloriosa was boiled for 5 min in an Erlenmeyer flask comprising 200 mL of distilled water. The combination was chilled and centrifuged at 3500 rpm for 15 min. The supernatant was collect in a colored bottle and stored at 4 °C. To synthesize the MnO2 NPs, different ratios (10, 25, and 50%) of Y. gloriosa leaf extract and the aqueous solution of 0.01 mM manganese acetate [(CH3COO)2Mn·6H2O] at different pH (4, 6, and 8) were mixed and stirred at room temperature for various times (40, 80, and 120 min). The precipitates were obtained by centrifuging of each sample, washed using distilled water and ethanol several times, and suspended in 7 mL distilled water for UV–Vis spectra analysis. 9 runs were designed using Design Expert 10 to survey the effect of pH, the metal aqueous solution-to-extract ratio (v/v), and time (Table 1), the formation of MnO2 NPs was monitored via recording UV–Vis spectroscopy. The UV–Vis spectrum of run 1 is shown in Fig. 1.

Table 1 Experimental planning
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Fig. 1
figure 1

UV–Vis spectroscopy of synthesized MnO2 NPs at Run 1

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Statistical analysis

RSM is a statistical method that uses quantitative data from suitable experiments to define regression model equations and operating conditions [27]. This is generally accomplished by performing a prior screening design to define which of the experimental variables and their interactions present more significant effects. Certainly, there are numerous variables that may affect the response of a system, and it is practically inconceivable to identify and control all of them [28]. In this research, the statistical design of the response surface was chosen to study the main effects of the factors and their interactions [22].

In the RSM, for each dependent variable, one model is defined which states the main and mutual effects of the factors on each variable singly. In this research, the design with three variables including the time (40, 60, and 120 min), plant extract ratio (25, 50 and 75% v/v), and pH (4, 6, and 8) was used to optimize the synthesis of the MnO2 NPs to obtain the higher yield.

Characterization of the MnO2 NPs

16 g powdered turmeric was placed in a flask containing 400 mL of ethanol and boiled for 5 min. The cooled mixture was centrifuged at 3500 rpm for 15 min. The clear supernatant was stored at 4 °C. 20 mL 0.01 mM manganese acetate [(CH3COO)2Mn·6H2O], and the aqueous solution at pH 8 was mixed with 180 mL leaf extract (extract ratio 90%) for 60 min and stirred at room temperature. In this step, 20 mL turmeric which contains bio-active curcumin added to the solution. This curcumin extract was employed as a stabilizer for MnO2 NPs [9]. The obtained solution was centrifuged and the precipitate was collected and washed with deionized water and ethanol several times, and the precipitate was collected, washed, and dried for XRD, TEM, and FESEM analyses.

Results and discussion

Statistical analysis

The reduction of Mn ions to manganese dioxide nanoparticles (MnO2 NPs) for run 1 was spectrometrically identified by double beam UV–Vis spectrophotometer (Perkin Elmer, Lambda 850) at a different wavelength (200–700 nm). The absorption spectra of the synthesized sample are shown in Fig. 1. The samples show two sharp absorption peaks at 284 and 354 nm each of which is related to the bandgap absorption of the MnO2 NPs. It should be noted that the absorbance peak of MnO2 NPs sol also changed [29]. The absorbance peak at 284 and 254 nm shows the absorption and transmission spectra of the MnO2 NPs sols with various impurities [29]. The MnO2 NPs showed absorption maxima at 284 nm. Based on the above discussions at the second section of an experiment a stabilizing agent, curcumin extracted from turmeric was used for preventing the MnO2 NPs from the accumulation [9]. The absorbance peaks at 284 nm are reported in Table 1.

Evaluation of the fitted model

For fitting the model, different statistical analysis methods are engaged to advise the experimental error, the compatibility of the model, and statistical significance of the qualifications in the model. This is generally done with the aid of an RSM program [30]. Critical evaluation of the quality of the fitted model is by the application of analysis of variance (ANOVA). The principle thought ANOVA is to contrast the variation owing to the behavior with the variation due to random errors innate to the mensuration of the generated responses [31]. The ultimate model can be employed to make a graphical display of parameter dependency.

Experimental design

To study the effect of the parameters: time, pH, and extract ratio of the synthesis progress, experiments were carried out using I-optimal Coordinate Exchange Design. The effect of the three variables studied by means of accomplishing nine different experiments. The responses obtained by the measuring adsorption of the MnO2 NPs at 353 nm and the polynomial second-degree equation for each factor are as follows:

Final equation in terms of coded factors:

$${\text{Absorbance }} = \, + (0.59 \, + 0.11) \times A \, + (9.825{\text{E}} - 003) \times B \, + 0.14 \times C.$$
(1)

Final equation in terms of actual factors:

$${\text{Absorbance }} = \, - 0.13444 \, + \, (2.73150{\text{E}} - 003) \times {\text{time }} + \, (4.91231{\text{E}} - 003) \times {\text{pH }} + \, (6.86504{\text{E}} - 003) \times {\text{extract,}}$$
(2)

where A, B, and C represent the initial time, pH, and extract ratio, respectively. Multiple interactions are seen between the two factors. Equations (1) and (2) demonstrate that the extract ratio was the most influential parameter with a positive effect on absorbance, and then, time also pH did not have many positive effects.

The results of each experience carried out by the software are shown in Table 1.

Variance analysis

The ANOVA (Tables 2, 3) showed that the equation is very indicative of the real communication between the response (the adsorption at 284 nm) and the significant variables. There is communication between the observed and predicted values as displayed by closeness between R2 and adjusted R2 value which is one (Table 2). The result demonstrates that the regression model caters a description of the communication between the independent factors and adsorption. The model is considered to be statistically significant, since the associated Prob. > F value for the model is lower than 0.05 (Table 3) [32].

Table 2 Model summary statistics
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Table 3 Analysis of variance table [partial sum of squares—type III]
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Effect parameters

UV–Vis experiences were carried out by the chosen model with a selected range of pH and time to check the composed effect of the pH and time values on the system. RSM was used and results were given in the form of 3D and contours plots. Figure 2a, b displays that if time increases from 40 to 120 min and extract ratio remains at 70%, absorbance will increase from about 0.2 to about 0.45. The optimum value of both the factors including time and pH can be analyzed by checking the maximum formed by X and Y coordinates. Time has a specific positive effect on absorbance.

Fig. 2
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Contour plot (a) and 3D plot (b) displaying the effect of time and pH on absorbance

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Figure 3a, b shows the effect of extract ratio and pH on the absorbance value under the pre-defined status given by the model. This chart shows that the maximum absorbance (0.58) happens at the extract ratio of 90%, which means that it is in agreement with the model. Increasing the extract ratio to the metal solution to 90% rises the absorbance, which clearly means that the number of effective materials of the plant has the greatest effect on MnO2 NPs’ synthesis.

Fig. 3
figure 3

Contour plot (a) and 3D plot (b) displaying the effect of extract ratio and pH on absorbance

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The combined effect of the time and extract ratio has been analyzed (Fig. 4a, b) and it has been computed that as the time augments from 40 to 120 min, maintaining pH at 6.0 and increasing the extract ratio to 90%, absorbance increases to 0.65. This clearly shows that the ratio of extract and time is the most important factors for the synthesis of nanomaterials.

Fig. 4
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Contour plot (a) and 3D plot (b) displaying the effect of extract ratio and time on absorbance

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Characterization of MnO2 NPs

XRD analysis

X-ray diffraction (XRD) studies of synthesized NCs were carried out at room temperature with an X-ray diffract meter (PANalytical, X’ Pert Pro) using Cu Kα radiation. XRD pattern of MnO2 NPs (Fig. 5) displays a broad pattern which has been associated with bio-capped and amorphous materials in MnO2 NPs [33]. Diffraction peaks appeared at 2θ values of 20.9965°, 26.8411°, 36.5673°, 39.7091°, 41.4953°, 42.4683°, and 68.0813° reflections can be indexed to the known orthorhombic structure of MnO2 with lattice constants of a = 9.5160 Å, b = 2.8640 Å, c = 4.7060 Å, and α = β = γ = 90.0000° (COO-213 card, no. 96-900-3477). The sharp XRD peaks clearly show that MnO2 NPs were synthesized with suitable purity. The XRD pattern display extra peak of low importance, marked with (o). This may be due to the formation of crystalline compounds that are present in the plant extracts [34]. The average size of the MnO2 nanoparticles was determined via Debye–Scherrer equation d = (kλ/βcosθ), where k is the Debye–Scherrer constant (0.89), λ is the X-ray wavelength (0.154 nm), β is the width of the peak with the maximum intensity in half height, d is the thickness of the crystal, and θ is the diffraction angle [35,36,37]. The results showed a size of 35 nm for MnO2 nanoparticles. For comparative, size of green synthesized Mn NPs via different plants is provided in Table 4.

Fig. 5
figure 5

XRD pattern of synthesized MnO2 NPs

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Table 4 Comparison of size of Mn NP in different works
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FESEM and TEM analyses

FESEM (HITACHI, S-4160) images were carried out based on the morphology surface study. The synthesized MnO2 NPs were clean and spherical in shape [40, 41]. The FESEM micrographs in Fig. 6 clearly illustrate well dispersed and spherical MnO2 NPs developed with Y. gloriosa aqueous extract. The MnO2 NPs instead of having a compressed packed structure display the much open and semi-linear structure [42].

Fig. 6
figure 6

FESEM images of synthesized MnO2 NPs

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The structure and morphology of the MnO2 NPs at higher resolution are shown in the TEM images (Fig. 7). The images clearly show the attendance of secondary material around MnO2 which indicated to bioorganic compounds that synthesized and stabilized the spherical MnO2 NPs.

Fig. 7
figure 7

TEM images of synthesized MnO2 NPs

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Conclusions

Yucca gloriosa leaf extract was a suitable reducing agent for the synthesis of the MnO2 nanoparticles. The effects of three factors that are pH of the metallic solution, time, and the extract ratio were studied and optimized using RSM. The concentration of the extract was the most effective parameter and then time, and also pH did not have much effect on absorbance. The MnO2 NPs synthesized using Y. gloriosa leaf extract and turmeric extract were used as a reducing and stabilizing agent, respectively. The MnO2 NPs were characterized using XRD, FESEM, and TEM analyses. XRD study confirms the synthesized of the MnO2 NPs with around size of 32 nm. The synthesis using plant extract is feasible by an easy reaction at ambient temperature and pressure, without the need of using catalysts, cast, or costly material. The degradation ability of the Y. gloriosa was demonstrated by MnO2 NPs synthesis. As a suggestion, Mn oxides can be employed in imaging contrast agents, magnetic storage devices, water treatment, and purification, due to their privileged physical and chemical properties.