1 Introduction

Synthetic dyes have found large-scale use in industries such as textile, leather, food production, and paper industries [1]. Classic blue, orange II, methylene blue, and malachite green are potential dyes used in industries and are primarily used for dyeing cotton silk, paper leather, etc. [1,2,3,4,5,6,7,8]. When released into the water bodies, these dyes affect and pollute the aquatic environment, which has significant impacts on the kidney, liver, gills, and pituitary glands of aquatic organisms [9]. The above mentioned dyes are potential carcinogens and can confer toxicity in plant and animal growth [10, 11]. Many developments in removing such organic pollutants have been made, and advances in auto-oxidation using ozone, titanium dioxide, ultraviolet (UV) [7], and Fenton’s reagent have scanned the attention in the removal of organic pollutants treating water quality. The reports suggest that Fenton’s reaction is the most effective method for degrading organic pollutants [12,13,14]. The use of Fe2+ in nanocomposite for the treatment of water is already known; here, we try to find an alternative to Fe2+ for the degradation of dyes. The major role in degradation is always played by the alteration in the pH of the degradation medium [15,16,17,18,19]. The degradation of such dyes lies in the catalyst's efficiency, which is related to the nanoparticle stability and surface area of the nanoparticles. However, in large-scale treatment of wastewater, major regulation without altering the pH can be a challenging task for the researchers.

The present-day focus on the green synthesis of metal oxide nanoparticles rather than the conventional methods has been preferred in endorsing the degradation of more toxic compounds to fewer toxic compounds or directly to O2, CO2, and H2O as by-products along with secondary products. The individual contribution of metal oxide nanoparticles, viz., SrO, CuO, or MnO, are known [20,21,22]. However, the synthesis of in situ triple-mixed nanoparticles has been a turnabout factor in catalytic application in bioremediation.

The present work includes the synthesis of mixed metal nano-oxide composite of strontium, copper, and manganese using Carica papaya fruit extract. The work aims to exploit the efficiency of the nanocomposite in the degradation of both aniline blue (AB) and malachite green (MG) under sunlight as the source of UV in the presence of H2O2. The photocatalysts were characterized using scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), and energy dispersive spectra (EDS). The degradation of dyes at regular time intervals is studied using a UV spectrometer. The particle size was measured using Debye–Scherrer equation, and Willamson–Hall analysis is performed with XRD data to explore the lattice strain of the material. Lattice strain is present due to imperfection in crystals, which includes lattice dislocation, grain boundary triple junction, contact or sinter stress, coherency stress, etc. Mechanical alloying also contributes to the introduction of strain in powdered samples. X-ray profile analysis is a convenient tool to estimate the crystal strain. [23,24,25,26] The statistical analysis on degradation of AB- and MG- data is done. We observed the normality criteria for each variable which is present in AB- and MG- data. To match the requirements of normality, two nonparametric tests, viz., Kolmogorov–Smirnov and Shapiro–Wilk tests, are employed. Kolmogorov–Smirnov test is used to find whether any data has been drawn from a particular probability distribution. Similarly, the Shapiro–Wilk test is also used to check whether any data comes from a normal distribution or not. The objective of the work is to get the degradation time of both aniline blue and malachite green. Multiple linear regression is implemented for getting the degradation time when absorption becomes zero.

2 Experimental

2.1 Materials and method

Strontium nitrate (Sr(NO3)2) was purchased from Qualigens and cupric sulfate (CuSO4) and potassium permanganate (KMnO4) was purchased from Fisher Scientific, and the chemicals were used without any purification.

2.2 Synthesis of Sr/Cu/MnO composite

SrO/CuO/MnO nanocomposites were prepared via previously reported synthetic procedures reported earlier [11]. Stock solutions of desired concentrations of strontium nitrate, cupric sulfate, and potassium permanganate were prepared. Fresh papaya (Carica papaya) was obtained from the local market, and the skin and seeds were removed and boiled for 3 h with the addition of batches of distilled water. The content is then filtered, and the extract is used to prepare the nanocomposite. Fifty milliliters of each stock solution was mixed in a beaker and stirred vigorously with a magnetic stirrer, followed by adding papaya extract in drops. A color change in the solution is noted, and the system is kept in motion for the next 2 h. The solution mixture is then allowed to settle, and a layer of the precipitate is obtained, which is then washed thoroughly with distilled water, followed by drying and then calcination at 520 °C. On removal, the fine powder is crushed with a mortar and pestle.

2.3 Experimental procedures

A 250 ml Erlenmeyer flask was used for the batch experiments. Fifty milliliters of each 30 ppm MG and AB was taken in four separate flasks. During the first set of experiments, in two flasks containing MG and AB, 1 ml of 10% H2O2 was added, followed by 30 mg Sr/Cu/MnO composite, and kept in sunlight for degradation. The initial concentration of both MG and AB were recorded, and the samples were taken out from the conical flask periodically and were analyzed immediately. During the experimental proceedings, no alteration in pH was made and performed at room temperature.

2.4 Analytical methods

The efficiency of the experimental processes was evaluated by monitoring the degradation of MG and AB using a double-beam UV/Vis spectrophotometer (Shimadzu, Model UV Japan). The decrease in the absorbance values of MG and AB after irradiation at a particular time shows the efficiency of the nanocomposite photocatalysts and the activity of the material. The degradation efficiency (D%) was calculated as

$$D\left(\%\right)=\left(\left({C}_{0}-{C}_{t}\right)\times 100\%\right)\%/{C}_{0}$$
(1)

where C0 and Ct are the concentrations of MG and AB at time 0 (min) and t (min), respectively, and t(min) is the irradiation time.

2.5 Statistical analysis of degradation

Two hypotheses viz., null hypothesis, which considers degradation time is normally distributed, and alternative hypothesis, considering degradation time is not normally distributed. To find the degradation time of the absorption in the case of both AB and MG, multiple linear regression method is used. Multiple regression is a statistical technique and one of the machine learning tools employed to analyze the interrelation between a single dependent variable and several independent variables. The primary need for multiple regression analysis is to predict the value of a single dependent variable using independent variables whose values are known. In both cases, degradation time in a minute is taken as dependent variable, while considering absorption data of AB and MG is usually distributed. First quartile (x1), median (x2), and third quartile (x3) are selected as three independent variables. The multiple regression model for aniline blue (AB) and malachite green (MG) is provided by Eq. (2) below:

$$y=a+b{x}_{1}+c{x}_{2}+d{x}_{3}$$
(2)

y = degradation time in minute;

\({x}_{1}\)= first quartile value of absorption;

\({x}_{2}\)= median value of absorption;

\({x}_{3}\)= third quartile value of absorption.

3 Results and discussion

3.1 Textural characterization of the materials

3.1.1 XRD analysis

The XRD pattern of the nanocomposite is shown in Fig. 1. The polycrystalline nature of the particles has been revealed, and the presence of strontium oxide (SrO) has been observed at 28.6 and 45.23, having planes (101) and (112), complying with JCPDS data no. 820915. Major peak position at 30.1 having plane (311) is due to copper manganese oxide (CuMnO). Other peaks at 32.69, 33.5, 37.7, 54.38, and 62.84 having planes of (110), (200), (005), (020), and (113) is due to the presence of CuO in the sample, complying with JCPDS card no. 481548. The shift in the major peak position may be due to the presence of sulfur and other free metals as an impurity. The intense peaks at 27.0, 42.07, and 44.29 is due to the formation of composite. The major constituent of the composite mixture is SrO, as the intensity of SrO peak is higher as compared to CuO and MnO present in the sample. The other peaks in the spectrum is due to the formation SrSO4 formed due to the sulphate ions from CuSO4 solution. The EDS spectra discussed later are in agreement with the fact that SrO-SrSO4 is the major constituent in the sample. The sharp peaks in the spectra confirm the crystalline nature of the material. The average particle was calculated using Debye–Scherrer’s formula:

$$D=0.89\lambda /\left(\beta \mathrm{cos}\theta \right)$$
(3)

where D is the crystallite size in nanometer, λ is the wavelength (1.5418 Å), and B is the full width at half maximum. The crystallite size is found to be 20.56 nm.

Fig. 1
figure 1

XRD diffractogram of Sr/Cu/MnO composite

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The total broadening is given by

$${B}_{\mathrm{T}}={\beta }_{\mathrm{D}}+{\beta }_{\varepsilon }$$
(4)

where βD is the broadening due to crystallite size and βε is the broadening due to strain.

Peak broadening due to micro-strain is given by

$${\beta }_{\varepsilon }=4\varepsilon \mathrm{tan}\theta$$
(5)

Now rearranging the above equation, we get, and putting the values of Eqs. (3) and (5) in Eq. 4, we get

$${B}_{\mathrm{T}}\mathrm{cos}\theta =4\varepsilon \mathrm{sin}\theta +\left(K\lambda \right)/D$$
(6)

where K = 0.89.

The above equation represents a straight line.

$$y=mx+c$$
(7)

where slope m is equal to ε, and from the Willamson–Hall plot, the slope will provide the strain of the material (Fig. 2). For plotting the Willamson–Hall plot, we employ data enlisted in Table 1.

Fig. 2
figure 2

Willamson–Hall plot indicating the line broadening due to strain

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Table 1 Peak indexing and values of FWHM to plot Willamson–Hall plot
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From the above Willamson–Hall plots, the slope ε is found to be 0.42711, which is the strain of the material.

3.1.2 SEM analysis

The Scanning electronic microscopic (SEM) image of Sr/Cu/MnO (Fig. 3a–d) composite as synthesized represents a clear oval texture, and the primary occupancy of SrO-SrSO4 decorated with the presence of MnO and CuO can be visualized easily from the images supported by EDS data. The SEM images in Fig. 3 reveal the fine particle nature of Sr/Cu/MnO in a mixture. All the particles maintained an oval shape, as is worth noting from the overall image of the composite. The particles are fine and aggregated, and the surface of the oval oxides is decorated with other ornamental oxides (Fig. 3b and c) validated from EDS spectra. The fractures in the SEM images are due to surface modification due to the presence of other oxides together forming the composite material of Sr/Cu/MnO mixed oxides. Figure 3(d) represents the oval surface, which turns out to be rough rather than polished due to the presence of other oxides on the surface of the nano-oxide.

Fig. 3
figure 3

SEM image of the synthesized nanocomposite representing the distinct spherical structure (a–d)

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3.1.3 TEM-EDS analysis

The morphology and particle size of Sr/Cu/MnO are studied using TEM (Fig. 4(a–d)). The TEM images of the prepared Sr/Cu/MnO nanocomposite and Fig. 4(e), representing the histogram, reveals the average particle size is 83 nm. The particles are agglomerated, and the surface of the corresponding material reveals the surface decoration with spherical agglomerates. Similarities in the spherical structure can be easily observed from SEM and TEM images. The particle size calculated by the Debye–Scherrer equation finds relevance from the histogram, where the highest bar is observed nearly at 25 nm length.

Fig. 4
figure 4

TEM images of the Sr/Cu/MnO nanocomposite (a–d) and histogram of average particle size (e) calculated from TEM

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The EDS reveals the elemental composition of the sample (Fig. 5). The spectral data clearly represents the presence of Sr, Cu, Mn, and O as the constituent. The appearance of sharp peak near strontium is due to the sulfur from CuSO4 solution resulting to formation of SrSO4 with the composite using Carica papaya fruit extract. The major constituent of the material is oxygen, present in the form of oxides with other elements. The spectral data is in agreement with the fact that the nanocomposite contains Sr/Cu/MnO as its primary constituent.

Fig. 5
figure 5

EDS spectrum of the nanocomposite

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3.2 Particle crystallinity index

Peak breath and specific phases are proportional to the crystallinity index of the material. The sharper the XRD, the larger the crystalline peaks. The particle size calculated from the Debye–Scherrer equation is 20.56 nm. The particle’s crystallinity is evaluated by comparing the particle size obtained from the Scherrer equation and those calculated from the TEM image. The crystallinity equation is represented as

$${I}_{cry}={D}_{\mathrm{p}}\left(\mathrm{TEM\;or\;SEM}\right)/D\left(\mathrm{XRD}\right)$$
(8)

where Icry is the crystallinity index, Dp is the particle size from TEM images, and D is the particle size calculated from XRD data using Debye–Scherrer equation. [27] The particle crystallinity is summarized in Table 2.

Table 2 Crystallinity index of the nanocomposite
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3.3 Photocatalytic degradation

Representation for the photocatalytic degradation of two commercial dyes, viz., aniline blue (AB) and malachite green (MG), has been represented above. The uniform decrease in the absorbance of both aniline blue (AB) and malachite green (MG) has been achieved without altering the pH of the medium. Aniline blue (AB) and malachite green (MG) absorb at wavelengths 599 and 617 nm, respectively. The degradation efficiency of the photocatalyst was calculated using Eq. (1), as mentioned earlier. The percentage of degradation of AB turns out to be 74.21% and that of MG is 91.07% in the span of 150 min (Fig. 6).

Fig. 6
figure 6

a Photocatalytic degradation of aniline blue; b photocatalytic degradation of malachite green

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A statistical tool has been used to calculate the probable time for the complete degradation of both dyes. To check the normality at different degradation times of aniline blue and malachite green, two nonparametric tests were used, namely Kolmogorov–Smirnov and Shapiro–Wilk. Both Kolmogorov–Smirnov and Shapiro–Wilk tests reject the null hypothesis that the data is normally distributed since the p-value is less than 0.05 at a 5% significance level. The same is summarized in Tables 3 and 4. It is observed that data is not uniform in nature. Thus, transforming data into a normal one by using the df (data transformation), or normal function under inverse df (data transformation) in SPSS. The data transformation is a tool used for changing non-normal data into normal one. After transforming aniline blue and malachite green for different degradation times, again normality test is performed on transformed data. It is found that data is normally distributed since the p-value is greater than 0.05 at a 5% significance level (Tables 5 and 6). Descriptive analysis of both aniline blue and malachite green is provided in Tables 7 and 8. The number of responses recorded in each degradation time with absorption is 803. The degradation time is provided in minutes, and it starts from 0, 10, 20, and lastly, it goes up to 150 with their absorption value. The value of the first quartile, median, and third quartile were provided for each degradation time since the first quartile contains 25% of the entire dataset. Similarly, the median and third quartiles contain 50 and 75% of the whole dataset. Using this information and applying machine learning algorithm we computed absorption time for both aniline blue and malachite green.

Table 3 Test of normality on raw aniline blue (AB)
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Table 4 Test of normality on raw malachite green (MG)
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Table 5 Test of normality on transformed aniline blue (AB)
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Table 6 Test of normality on modified malachite green (MG)
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Table 7 Descriptive analysis on modified aniline blue (AB)
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Table 8 Descriptive statistics on modified malachite green (MG)
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To find the exact time when the concentration of aniline blue (AB) becomes zero, the entire data is transformed into a normal distribution. The equidistant values first quartile is computed with median and third quartile. Using these three independent variables and degradation time in a minute as a dependent variable, multiple regression model is fitted, which is represented in Eq. (2). The multiple regression model is a good fit with a R2 value of 98.42 and adjusted R2 97.63. The regression analysis result of aniline blue are summarized in Table 9. The independent variables turned out to be significant, with a p-value of more than 0.05. Thus, to get the degradation time in minutes when the absorption will become zero (0), all the independent variables is assumed to be 0, which indicates a flat line of the absorption around the x-axis. After executing the regression models, finally, the degradation time around 184.2 min is observed, which can be approximated to 180 min. Thus, after 3 h, the absorption will become zero (0) in the case of aniline blue (AB). However, Table 10 represents the multiple regression model for malachite green (MG), which fits well with a R2 value of 97.01 and adjusted to R2 of 96.01. On parallel execution, after calculating the degradation time it is found to be 152.2 min, which is approximated as 152 min, thus, after 152 min, the absorption will become zero (0) in the case of malachite green (MG).

Table 9 Regression analysis table of aniline blue (AB)
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Table 10 Regression analysis table of malachite green (MG)
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4 Possible mechanism of degradation

Heterogeneous photocatalysis consists of a sequence of reaction events co-occurring. Some reported mechanism includes five-step processes that contains (1) diffusion of reactant to the surface of the material, (2) adsorption on the surface, (3) reaction occurring on the surface, and (4) diffusion of products formed on the surface. [8, 10] The reaction medium includes H2O2, which generates OH free radicals. The proposed mechanism can be summarized as

$$\mathrm{Sr}/\mathrm{Cu}/\mathrm{MnO}+hv\to \mathrm{Sr}/\mathrm{Cu}/\mathrm{MnO}\left({{e}_{\mathrm{CB}}}^{-}\right)+\mathrm{Sr}/\mathrm{Cu}/\mathrm{MnO}\left({{h}_{\mathrm{VB}}}^{+}\right)$$
$$\mathrm{Sr}/\mathrm{Cu}/\mathrm{MnO}\left({{h}_{\mathrm{VB}}}^{+}\right)+{\mathrm{H}}_{2}\mathrm{O}\to \mathrm{Sr}/\mathrm{Cu}/\mathrm{MnO}+\mathrm{OH}+{\mathrm{H}}^{+}$$
$$\mathrm{Sr}/\mathrm{Cu}/\mathrm{MnO}\left({{h}_{\mathrm{VB}}}^{+}\right)+{\mathrm{OH}}^{-}\to \mathrm{Sr}/\mathrm{Cu}/\mathrm{MnO}+\mathrm{OH}$$
$$\mathrm{Sr}/\mathrm{Cu}/\mathrm{MnO}\left({{e}_{\mathrm{CB}}}^{-}\right)+{\mathrm{O}}_{2}+{\mathrm{H}}^{+}\to \mathrm{Sr}/\mathrm{Cu}/\mathrm{MnO}+{\mathrm{HO}}_{2}\to {{\mathrm{O}}_{2}}^{-}+{\mathrm{H}}^{+}$$
$$\mathrm{Sr}/\mathrm{Cu}/\mathrm{MnO}\left({{h}_{\mathrm{VB}}}^{+}\right)+\mathrm{dye}\to \mathrm{oxidation\;of\;dye}$$
$$\mathrm{OH}+\mathrm{dye}\to \mathrm{degradation\;of\;dye}$$

The catalytic efficiency of individual MnO, CuO, or SrO nanoparticles is known. The surface modification with the presence of Sr/CuO/MnO seems to enhance the photocatalytic activity. The surface decoration can result in enhanced effect in photocatalytic activity.

5 Comparison with other works

The present work reported includes mixed metal oxide composite of Sr/Cu/MnO synthesized via co precipitation method. The efficiency of the photocatalyst is seen to be comparable with the other reported catalysts. The data has been summarized in Table 11. 

Table 11 Comparison of photocatalyst with other reported catalysts
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6 Conclusion

Mixed Sr/Cu/MnO nano-oxide has been obtained via co-precipitation method using Carica papaya extract. The composite has the efficiency of degrading both malachite green (MG) and aniline blue (AB) in short period of time without acid. The mixed nano-oxide composite has been analyzed using XRD, SEM, TEM, and EDS techniques. The particle size lies in close agreement with the one calculated from the XRD data and TEM histogram diagrams. The Willamson–Hall plot constructed reveals the strain of the material to be 0.42711 and particle crystallinity index is calculated to be 4.036. The degradation of dyes has followed the photo-Fenton-like mechanism with H2O2 as an oxidant. It is observed that the catalyst has degraded 74.2% of aniline blue (AB) and 91.07% of malachite green (MG) dye, which are used on an industrial scale. The statistical approach has revealed that the complete degradation of both aniline blue (AB) and malachite green (MG) can be achieved at 180 and 152 min, respectively. From the results, it can be concluded that material is promising and can be categorized as one of the efficient nanocatalysts reported.