Capability of TiO₂ and Fe₃O₄ nanoparticles loaded onto Algae (Scendesmus sp.) as a novel bio-magnetic photocatalyst to degration of Red195 dye in the sonophotocatalytic treatment process under ultrasonic/UVA irradiation

Abstract

In this study, the magnetic photocatalyst Scendesmus/Fe₃O₄/TiO₂ was synthesized, and its sonophotocatalytic properties in relation to the degradation of the Red195 dye were evaluated. Particles were characterized using a scanning electron microscope (SEM), Fourier's transform infrared spectroscopy (FTIR), X-ray powder diffraction (XRD), and a vibrating-sample magnetometer (VSM). At a pH of 5, a photocatalyst dosage of 100 mg, an initial R195 concentration of 100 mg/l, an ultrasound power of 38W, and an exposure time of 20 min, the maximum Red195 removal efficiency (100%) was achieved. After five cycles of recycling, the composite's sonophotocatalytic degradation stability for R195 remains above 95%. Experiments on scavenging indicate that electrons (h⁺) and hydroxyls (OH^-) are indispensable decomposition agents. The removal of R195 by Scendesmus/Fe₃O₄/TiO₂ is consistent with the pseudo-first-order kinetic, Freundlich, and Henderson's isotherm models, as determined by kinetic and isotherm investigations. The negative activation enthalpy of the standard (ΔH°) illuminates the exothermic adsorption mechanism. The increase in standard Gibbs activation free energy (ΔG°) with increasing temperature reveals the process is not spontaneous. As indicated by the negative value of the standard entropy of activation (ΔS°), activation of the reactants resulted in a loss of freedom.

Introduction

The textile industry's production and disposal of effluent, which frequently contains toxic metals and biodegradation-resistant organic compounds¹. The most widely used dyes in the textile industry are azo dyes with azo (–N=N–), hydroxyl (^•OH), and –SO₃H groups². Due to their resilience and high solubility in aqueous solutions, it is challenging to eliminate these dyes using a microorganism-based remediation method³. Recently, conventional physicochemical processes such as reverse osmosis, coagulation-flocculation, adsorption, and filtration have been utilized to remove persistent pollutants from wastewater⁴. The production of secondary pollutants, high post-treatment costs, and the inability of pollutants to decompose are current issues with technologies⁵. Traditional physicochemical techniques include membrane filtration, adsorption, chemical precipitation, reverse osmosis, ion exchange, electro-dialysis, solvent extraction, chemical oxidation/reduction, and others for removing dye pollutants from contaminated water⁶.

However, current methods frequently have issues, including the production of secondary pollutants, high post-treatment costs, and the inability of pollutants to degrade. In contrast to these removal methods, advanced oxidation processes (AOPs) based on the generation of free radicals such as ^•OH and O₂ can mineralize a wide range of contaminants without generating sediment or hazardous residues^5,6. In recent years, researchers have shown a great deal of interest in the AOP photocatalysis system for the treatment of industrial wastewater due to its demonstrated cost-effectiveness and non-toxic, complete mineralization⁷. By absorbing light, photocatalytic systems generate electron/hole (e^-/h⁺) pairs that degrade contaminants in the aquatic environment by producing reactive oxygen species (such as ^•OH and O₂^•-)⁸. Semiconductors composed of TiO₂ and ZnO are the materials utilized most frequently in this process. In contrast, the disadvantages of semiconductors in real-world applications include high cost, limited affinity for aromatic hydrocarbons, simple deactivation, and rapid e^-/h⁺ pair recombination. To address these limitations, the researchers proposed the development of photocatalysts with a high light absorption potential and suitable electron transport^7,9.

Microalgae have recently emerged as a viable microorganism for removing contaminants from effluent. Microalgae production is not commercially viable, however, due to photosynthesis and high growth and harvesting costs¹⁰. It is simple to obtain and cultivate green algae (Scenedesmus spp.), which are abundant in all aquatic environments. Due to its low cost, ease of recovery and reuse, large contact area, and high efficiency during limited contact periods, the use of algal biomass for the biosorption of pollutants is fascinating. Carbohydrates, intercellular pores, and sulfated polysaccharides observable on the adsorbent cell partition may enhance dye biosorption from effluent¹¹. The recombination of photoproduced carriers limits the photocatalytic effectiveness of Scendesmus/TiO₂ in large-scale treatment¹². Since their abundance, low toxicity, and adequate band opening, it is suggested that magnetic nanoparticles be combined with Scendesmus or TiO₂ to address this issue. Combining iron with Scendesmus/Fe₃O₄/TiO₂ is advantageous because separation by an external magnetic field is easier⁶.

Recent research has combined sonocatalysis and photocatalysis to improve the treatment of resilient wastewater as well as the photocatalyst's activity^13,14. In the sonophotocatalytic process, microbubbles are created by absorbing energy from an Ultrasonic field, which causes high concentrations of •OH¹⁵. Consequently, light and US waves stimulate the photocatalyst to generate more energetic radicals. In addition to enhancing adsorption, mass transfer, and particle dispersion, the resultant cavitation also cleans the active regions of the particles by removing adhesive residues¹⁶.

Sono-photocatalysis based on Scendesmus/Fe₃O₄/TiO₂ is limited due to a lack of information^17–19. In addition, data regarding the efficacy and properties of the synthetic photocatalyst are lacking^13,19,20. Using a variety of diagnostic techniques, Scendesmus/Fe₃O₄/TiO₂ nanoparticles were synthesized and characterized as a novel photocatalyst. In order to determine the viability of a novel photocatalyst for the well-organized degradation of R195, the process efficiencies of sono-photodegradation were compared with those of sonolysis, photolysis, sonocatalysis, and photocatalysis systems.

The main goals of this study are to synthesize a novel structured Scendesmus/Fe₃O₄/TiO₂ magnetic photocatalyst, characterize and evaluate the Scendesmus/Fe₃O₄/TiO₂ potential in R195 removal, and optimize the effects of pH, exposure time, photocatalyst dosage, dye concentration, and US power on R195 removal using response surface methodology. Thus, the findings of this study can serve as a guide for the safe and effective remediation of various textile wastewaters.

Materials and methods

Prepration of algae (Scendesmus sp.)

The Caspian Sea Ecology Research Institute in Mazandaran, Iran, cultivated a sample of Scendesmus sp Algae. The samples were then transferred to the Gorgan University of Agriculture and Natural Resources laboratory. Using a super grinder, the microalgae were then ground as finely as possible²¹.

Synthesis of Fe₃O₄ nanoparticles

For the synthesizing of Fe₃O₄ nanoparticles, the sol–gel method was modified. To produce a golden solution, 65 ml of ethylene glycol and 4.95 g of ferric nitrate nonahydrate were stirred for two hours at 45 °C. After 10 h of increasing the temperature of the mixture to 95 °C, gel formation was obtained²². The emulsion was then centrifuged and desiccated in a 105 °C furnace for twenty hours (Memmert VO 400). The material was annealed for two hours at 450 °C in a vacuum furnace (Nabertherm, R80-750/11, Germany) to produce magnetic Fe₃O₄ nanoparticles⁶.

synthesis of Fe₃O₄/scendesmus

0.49 g of Fe₃O₄ nanoparticles and 3.93 g of Scendesmus were dissolved in 60 ml of ethanol. At 73 °C, one hour was spent agitating the mixture. A solution of 6 ml ethanol and 1.58 ml diethanolamine was added dropwise to the initial mixture, which was stirred with a magnetic stirrer for 10 h at 76 °C until a dark brown solution was obtained. The solid was then isolated with an external magnet and dried in a vacuum furnace (Memmert VO 400) for 24 h at 90 °C^23,24.

Synthesis of scendesmus/Fe₃O₄/TiO₂

For one hour, a mixture of synthesized Scendesmus/Fe₃O₄ and ethanol at a concentration of 99.9% was agitated. During 10 h of heating at 150 °C, the mixture was treated with 6.16 ml of tetrabutylammonium hydroxide (TBOT) and 60 ml of ethanol. After washing the sample with methanol and distilled water, it was calcined at 450 °C for three hours^6,22.

Point of zero charge

The point of zero charge (PZC) of algal biosorbent was determined with minor modifications to the salt addition method. The collection of various containers containing 0.1 M NaNO₃ concentrations. HCl and NaOH (0.1 M) solutions were used to obtain pH values ranging from 2 to 10²⁵. Each vial obtained 1 g of algal biosorbent and was stirred at 160 rpm for 24 h. The pH of each filtrate was noted after its constituents. Calculating the PZC value of algal biosorbent by plotting the initial pH against pH change graph²⁶.

Sonophotocatalytic experiments

Sonophotocatalysis was utilized in a US bath containing a UVA lamp to ascertain the R195 degradation rate. A precise amount of our prepared catalyst (0.25–1 mg/l) was added to a 250 mL Erlenmeyer Pyrex containing R195 at a determined pH (between 3 and 7). Using a pH meter, NaOH, and H₂SO₄, the initial pH adjustment was performed²⁷. To better comprehend the effect of the parameters, the reactor was exposed to US frequencies (20–50 kHz) at UV light intensities (6 W). The concentration of 1 ml samples collected at different times (10–40 min) was determined using UV–vis spectrophotometry at 550 nm. Utilizing Eqs. (1) and (2), the degradation efficiency and reaction kinetics of R195 were determined:²⁸

$$\mathrm{R}(\%)=\frac{(Ci-Ce)}{(C0)}\times 100$$ 1

$${\text{q}}_{\text{e}}=\text{V}\frac{Ci-Ce}{M}$$ 2

q_e in Eq. (1) quantifies the adsorbed ions (sorbate) in milligrams per gram in the biosorbent, where the initial and final metal concentrations C_i and C_e were measured by atomic absorption spectrometry; V represents the volume of the synthetic medium, and M represents the biomass of the biosorbent (g)^27,28.

Desorption and regeneration studies

Using the supplied methodology, the reusability of the adsorbent to desorb the dye ions and regenerate the biomass for reuse was evaluated. To conduct an effective adsorption and desorption experiment, the aforementioned substances were subjected to five cycles of cycle repetition. 0.1 M hydrochloric acid was used to desorb metal ions²⁹. Desorption experiments were carried out by combining a metal-loaded adsorbent with 50 mL of desorption medium (0.1 M HCl) and agitating at 160 rpm³⁰. Each cycle is dominated by sorption, followed by desorption and regeneration. The following equations characterize biosorbent desorption and regeneration performance^29,30:

$$\text{Desorption efficiency}\%=\left(\text{Amount of dye ion desorbed}\right)/\text{Amount of dye ion adsorbed})\times 100$$ 3

$$\text{Photocatalyst efficiency}=\left(\text{Regenerated removal capacity}/\text{Original removal capacity}\right)\times 100$$ 4

Isotherm modeling

Isotherm models help describe the interactions between contaminants and synthetic adsorbents. Langmuir, Freundlich, Temkin, and Harkins–Jura are the adsorption isotherms most frequently used. The Langmuir isotherm model depicts monolayer adsorption on a surface with restricted sites and no intermolecular interaction⁸. For a linear fit of the Langmuir isotherm model to the experimental data, the following equation was used: C_e/q_e versus C_e (Eq. 5).

$$\frac{C_e}{q_e}=\frac{1}{q_{m}b}+\frac{1}{q_m}{C}_e$$ 5

where q_e is the equilibrium adsorbate concentration in the adsorbent phase (mg/g), C_e is the equilibrium adsorbate concentration in the aqueous phase (mg/l), and b is the constant associated with the free adsorption energy and the concentration at which the adsorbent reaches half saturation. q_m also represents the maximum absorption capacity (mg/g)⁵.

The quantity of reversible adsorption on a heterogeneous surface increases with increasing concentration (Eq. 6) according to the Freundlich adsorption isotherm³¹:

$$ln{q}_e=ln{K}_F+\frac{1}{n}ln{C}_e$$ 6

where q_m is the amount of molecules adsorbed to the adsorbent surface at any given time (mg/g), C_e is the equilibrium concentration (mg/l), n and K_F are the Freundlich constant and Freundlich exponent (mg/g (l/g)1/n, respectively), and C_e is the equilibrium concentration (mg/l)⁵.

As demonstrated by the following equations (Eqs. 7 and 8), the Temkin isotherm model is dependent on interactions between the absorbent and the adsorbate and assumes the linearity of the heat of adsorption of all molecules in the layer³²:

$$q_e=\frac{\mathit{RT}}{b_T}ln{A}_T{C}_e$$ 7

$$q_e=\frac{\mathit{RT}}{b_T}ln{A}_T+\frac{\mathit{RT}}{b_T}ln{C}_e$$ 8

b_T is the Temkin isotherm constant (J/mol), R is the universal gas constant (8.314 J/mol K), T is the temperature (K), and A_T is the Temkin isotherm equilibrium binding constant (l/g)³².

The fourth model examined to support the multilayer adsorption of iodine atoms onto the synthesized photocatalyst is the Harkins–Jura model, whose linear form (Eq. 9) is as follows³³:

$$\frac{1}{q_{e}2}=\frac{B}{A}-\frac{1}{A}log{C}_e$$ 9

where A_H and B_H are Harkins constants derived from the slope and intercept of the linear plots of q_e² versus log C_e, respectively³³.

Kinetics modeling

Adsorption kinetics provides data on adsorbent performance and mass transfer modes, such as diffusion, surface adsorption, intramolecular adsorption, and chemical adsorption. Adsorption kinetics are typically consistent with the pseudo-first-order kinetic model when the adsorption control factor is located in the boundary layer⁵. It indicates that a change in adsorption rate is proportional to the accessible sites on the surface of the adsorbent. As demonstrated by Eq. (10) ⁸:

$$\ln \left(q_{e1},{-q}_t\right)=\ln q_{e1}{-k}_{1}t$$ 10

where q_e1 and q_t represent the quantity of adsorbate adsorbed at equilibrium time and time t, respectively (mg/g). K₁ (1/min) is the pseudo-first-order rate constant⁵.

In addition, the pseudo-second-order kinetic model is described as follows (Eq. 11)³⁴:

$$\frac{t}{q_t}=\frac{1}{k_2{q}_{e2}^2}+\frac{1}{q_{e2}}t$$ 11

where t is the time (min) and k₂ is the constant pseudo-second-order rate (g/mg min) ³⁴.

The Elovich model is one of the most commonly employed kinetic models for analyzing the impact of temperature on adsorption systems. The expression for the Elovich model is (Eq. 12)⁸:

$$q_t=\frac{1}{\beta }ln\left(\alpha ,\beta \right)+\frac{1}{\beta }lnt$$ 12

where represents the initial adsorption rate constant (mg/g min) and Elovich's constant is the activation energy and surface coverage associated with chemisorption (g/m²)⁸.

According to the intraparticle diffusion model, the adsorption procedure consists of intraparticle diffusion, film diffusion, and emptying of the infill. This is crucial to the advancement of physical adsorption processes (Eq. 13), as it accounts for the formation of multiple layers based on van der Waals forces^35,36:

$${\text{q}}_{\text{t}}={\text{k}}_{\text{int}}{\text{t}}^{1/2}+\text{C}$$ 13

where k_int represents the intra-particle diffusion rate constant (g/mg min) and the intercept of the plot and C represents the boundary layer effect or surface adsorption^35,36.

Thermodinamics modeling

The Arrhenius equation determines the activation energy, Ea, which is the minimum amount of energy necessary to initiate a chemical reaction⁵.

$$k_{\mathit{app}}=A{e}^{\frac{\mathit{Ea}}{\mathit{RT}}}$$ 14

$${\text{ln k}}_{\text{app}}=\text{lnA}-\frac{\mathit{Ea}}{\mathit{RT}}$$ 15

where kapp represents the apparent rate constant (min^-1), Ea is the activation energy (kJ mol^-1), T is the temperature (K), R is the gas constant (8.314 J K^-1 mol^-1) and A is the Arrhenius constant (min^-1)²². In the transition state theory (TST), the conventional Gibbs free energy, ΔG° (kJ mol^-1), is defined by the following equations⁶:

$$\mathrm{\Delta }{\text{G}}^{{}^{\circ }}=-{\text{RTlnk}}_{\text{app}}$$ 16

$$\mathrm{\Delta }{\text{G}}^{{}^{\circ }}=\mathrm{\Delta }{\text{H}}^{\circ }-\text{T}\mathrm{\Delta }{\text{S}}^{\circ }$$ 17

where ΔH° is the standard enthalpy (kJ mol^-1) and ΔS° is the standard entropy (JK^-1 mol^-1)⁵. TST implies the temperature dependence of the apparent rate constant in the Henry equation³³:

$${\text{k}}_{\text{app}}=\frac{\mathit{KBt}}{h}\text{exp}\left(\frac{\mathrm{\Delta }G}{\mathit{RT}}\right)$$ 18

where K_B is the Boltzmann’s constant (K_B = 1.380510^–23 JK^-1) and h is the Planck’s constant (h = 1.380510^-23Js)³³.

$${\text{k}}_{\text{app}}=\frac{k_B\text{T}}{h}\text{exp}\left(\frac{\mathrm{\Delta }S}{\mathit{RT}}\right)\text{exp}\left(\frac{\mathrm{\Delta }G}{\mathit{RT}}\right)$$ 19

$$\ln \left(\frac{k_{\mathrm{app}}}{k_B\mathrm{T}}\right)=\frac{\mathrm{\Delta }{S}^{\circ }}{R}-\frac{\mathrm{\Delta }{H}^{\circ }}{\mathit{RT}}$$ 20

The ΔH^° and frequency factor constant (A) are analogous to the activation energy quantity (E_a)⁶.

$$\mathrm{A}=\frac{k_B\mathrm{T}}{h}\exp \frac{\mathrm{\Delta }{S}^{\circ }}{R}$$ 21

$${\text{E}}_{\text{a}}=\mathrm{\Delta }{\text{H}}^{\circ }+\text{RT}$$ 22

Experimental design

Four independent variables were selected, including pH (A), photocatalyst dosage (B), exposure time (C), dye concentration (D), and US power (E) at three levels (Table 1). 48 experimental trials were prescribed by the CCD-RSM, and the response of independent variables was fitted to the model using the following regression equation (Table 2):⁵.

$$Y={\beta }_0+\sum _{i=1}^k{\beta }_i{x}_i+\sum _{i=1}^k{\beta }_{\mathit{ii}}{x}_i^2+\sum _{i=1}^{k-1}\sum _{j=2}^k{\beta }_{\mathit{ij}}{x}_i{x}_j+\epsilon$$ 23

where β₀, b_i, b_ii, and b_ij are the intercept, linear, squared, and interaction coefficients, respectively. Y denotes the response. In addition, x_i², x_j²… x_k² are the square effects, and x_ix_j, x_ix_k, and x_jx_k are the interaction effects of variables. k is the number of considered factors, and ε is the random errore⁵.

Table 1.

Range levels of independent variables.

Independent variables	Range and level
	− 1	0	+ 1
pH (A)	3	5	7
Photocatalyst dosage, mg (B)	25	62.5	100
Exposure time, min (C)	5	22.5	40
Concentarion of dye, mg/lit (D)	50	125	200
US power, W (E)	30	65	100

Table 2.

ANOVA used to the designated quadratic model.

Source	Sum of Squares	df	Mean Square	F-value	p-value
Model	4601.64	20	230.08	29.33	< 0.0001	Significant
A-pH	243.56	1	243.56	31.04	< 0.0001
B-Exposure time	24.74	1	24.74	3.15	0.0871
C-Concentraion dye	395.76	1	395.76	50.44	< 0.0001
D-Photocatalyst dosage	59.56	1	59.56	7.59	0.0104
E-US power	105.88	1	105.88	13.50	0.0010
AB	18.00	1	18.00	2.29	0.1415
AC	66.13	1	66.13	8.43	0.0073
AD	45.13	1	45.13	5.75	0.0237
AE	105.13	1	105.13	13.40	0.0011
BC	21.13	1	21.13	2.69	0.1124
BD	153.13	1	153.13	19.52	0.0001
BE	120.13	1	120.13	15.31	0.0006
CD	12.50	1	12.50	1.59	0.2177
CE	2.00	1	2.00	0.2549	0.6177
DE	72.00	1	72.00	9.18	0.0053
A2	165.11	1	165.11	21.04	< 0.0001
B2	207.97	1	207.97	26.51	< 0.0001
C2	33.37	1	33.37	4.25	0.0489
D2	8.22	1	8.22	1.05	0.3150
E2	0.2604	1	0.2604	0.0332	0.8568
Residual	211.84	27	7.85
Lack of fit	168.50	22	7.66	0.8838	0.6268	Not significant
Pure error	43.33	5	8.67
Cor total	4813.48	47

Results and discussion

Characterization

FTIR analysis

As determined by FTIR spectroscopy, Fig. 1 depicts the functional groups of Scendesmus/Fe₃O₄ and Scendesmus/Fe₃O₄/TiO₂. Strong –OH stretching is detected at 3440.55 cm^-1 in Scendesmus/Fe₃O₄/TiO₂ and scendesmus/Fe3O4, which may be related to the presence of water⁶. The bands at 1164.35 and 1367.35 cm^-1 correspond, respectively, to the C=O, C–O, and Fe (C–O–Fe) stretching vibrations²². C=O at 1631.55 cm^-1, however, indicated the presence of acetylacetonate on the photocatalyst surface⁵. The Fe–O content of Scendesmus/Fe₃O₄ and Scendesmus/Fe₃O₄/TiO₂ is also confirmed by bands between 511.06 and 590.14 cm^-137. The observed bands between 550 and 900 cm^-1 verify the presence of Ti–O–Ti and Fe–O⁶. In addition to Fe–O stretching vibrations, symmetric and asymmetric stretching, and COO^-, the bands are also associated with Fe–O stretching vibrations. Anatase Fe–O and TiO₂ are responsible for the peaks at 576 and 593 cm^-1 in the Scendemus/Fe₃O₄/TiO₂ spectrum³⁷.

Figure 1.

FTIR analysis of Scendesmus/Fe₃O₄ and Scendesmus/Fe₃O₄/TiO₂.

SEM,Mapping and VSM analysis

Figure 2a and b depict the surface morphology of Scendesmus/Fe₃O₄/TiO₂, respectively. Figure 2a demonstrates the octagonal shape and flat surface of the Scendesmus.sp³⁷. Scendesmus was uniformly coated with TiO₂ particles for photocatalytic activity, as shown in Fig. 2b ³⁸. This indicates that the titanium particles on the Scendesmus' surface are securely adhered. Therefore, the Scendesmus/Fe₃O₄/TiO₂ synthesis was successful. Carbon, iron, oxygen, and titanium are present in the mapping analysis, confirming the formation of Scendesmus/Fe₃O₄/TiO₂ (Fig. 2c–f)³⁹. Based on VSM analysis, the presence of diamagnetic TiO₂ in the structure of Scendesmus/Fe₃O/TiO₂ was responsible for a minor decrease in magnetic strength⁵. The photocatalyst exhibited robust magnetic activity against a 1.4 Tesla external magnet. In addition, the saturation magnetization (MS) value was approximately 16 emu/g, demonstrating the photocatalyst's high magnetic properties (Fig. 3)²².

Figure 2.

FESEM images Scendesmus (a) and Scendesmus/Fe₃O₄/TiO₂ (b), Map analyses of the Scendesmus/Fe₃O₄/TiO₂, (c) C ka, (d) Fe ka, (e) O ka, (f) Ti ka.

Figure 3.

VSM analysis of (a) Scendesmus/Fe₃O₄ and (b) Scendesmus/Fe₃O₄/TiO₂.

Central composite design

Model and statistical analysis

To design and optimize the interaction effects of five sono-photocatalytic process variables, the CCD model (RSM) was used. Table 2 displays the obtained results (actual and predicted responses) for the R195 degradation by means of the sono-photocatalytic process, after designating the number of trials using the CCD plan. Taking into consideration the coded factors, the proposed model equation (Eq. 24) was fitted to the quadratic model for R195 degradation following statistical analysis.

$$\begin{array}{cc}\hfill \text{Red195 Removal}\left(\%\right)=& +90.57-5.\text{33 A}+1.0\text{6 B}+3.\text{22 C}+2.\text{39D}+0.0\text{6 AB}-0.\text{1875AC}-1.\text{19AD}\hfill \\ \hfill & +1.0\text{6BC}+1.\text{81BD}+1.\text{31CD}-19.{\text{97A}}^2+0.{\text{5263 B}}^2-0.{\text{9737C}}^2-1.{\text{47 D}}^2\hfill \\ \hfill \end{array}$$ 24

Table 3 presents a summary of the F-value, P-value, and R2 values used in the analysis of variance (ANOVA) to determine the significance and degree of fit of the employed model. The F-value and P-value for the degradation of R195 in the constructed model are 29.33 and 0.00001, respectively, indicating that the proposed model is significant⁵. As the factor with the highest F-value, the C-factor (dye concentration) is deemed significant. In addition, the P-value for lack of fit (LOF) reveals an insignificant mode (P-value > 0.05), which indicates a superior action compared to the model described⁴⁰. Three categories of correlation coefficients, including R² (0.9560), adjusted R² (0.9234), and predicted R² (0.8566), were used to evaluate the suitability of the models (Table 4).

Table 3.

ANOVA results for Red195 removals.

Response	Sum of squares	Mean square	F Value	p-valuProb > F	Predicted R2
Red195 removal	4601.64	230.08	29.33	< 0.0001	0.8566
	Std.Dev	C.V	Ad. pre*	R2	Adj.R2
	2.80	3.35	20.63	0.9560	0.9234

Table 4.

Experimental conditions, and the obtained results.

Run	Value
	A	B	C	D	E	R195 removal (%)	Predicted removal(%)
1	7 (+ 1)	40 (+ 1)	50 (− 1)	25 (− 1)	30 (− 1)	71	71.85
2	7 (+ 1)	5 (− 1)	50 (− 1)	100 (+ 1)	100 (+ 1)	86	83.69
3	3 (− 1)	40 (+ 1)	200 (+ 1)	25 (− 1)	100 (+ 1)	82	79.03
4	7 (+ 1)	40 (+ 1)	50 (− 1)	25 (− 1)	100 (+ 1)	81	79.38
5	3 (− 1)	5 (− 1)	50 (− 1)	25 (− 1)	100 (+ 1)	80	81.02
6	3 (− 1)	40 (+ 1)	50 (− 1)	100 (+ 1)	100 (+ 1)	85	88.50
7	5 (0)	22.5 (0)	125 (0)	62.5 (0)	65 (0)	100	97.10
8	7 (+ 1)	40 (+ 1)	50 (− 1)	100 (+ 1)	30 (− 1)	77	77.00
9	3 (− 1)	40 (+ 1)	50 (− 1)	25 (− 1)	30 (− 1)	84	81.83
10	7 (+ 1)	5 (− 1)	200 (+ 1)	100 (+ 1)	100 (+ 1)	70	74.12
11	7 (+ 1)	5 (− 1)	200 (+ 1)	25 (− 1)	30 (− 1)	73	68.44
12	7 (+ 1)	40 (+ 1)	200 (+ 1)	25 (− 1)	100 (+ 1)	70	70.55
13	5 (0)	22.5 (0)	125 (0)	62.5 (0)	30 (− 1)	94	95.66
14	7 (+ 1)	5 (− 1)	200 (+ 1)	100 (+ 1)	30 (− 1)	70	67.34
15	3 (− 1)	5 (− 1)	50 (− 1)	100 (+ 1)	30 (− 1)	80	80.14
16	3 (− 1)	5 (− 1)	200 (+ 1)	25 (− 1)	100 (+ 1)	74	74.70
17	7 (+ 1)	5 (− 1)	50 (− 1)	25 (− 1)	100 (+ 1)	80	81.30
18	5 (0)	22.5 (0)	125 (0)	62.5 (0)	65 (0)	98	97.10
19	7 (+ 1)	40 (+ 1)	200 (+ 1)	100 (+ 1)	30 (− 1)	70	69.67
20	3 (− 1)	5 (− 1)	50 (− 1)	25 (− 1)	30 (− 1)	90	88.50
21	5 (0)	5 (− 1)	125 (0)	62.5 (0)	65 (0)	85	87.07
22	5 (0)	22.5 (0)	125 (0)	25 (− 1)	65 (0)	97	97.60
23	3 (− 1)	40 (+ 1)	200 (+ 1)	100 (+ 1)	100 (+ 1)	87	87.93
24	7 (+ 1)	5 (− 1)	50 (− 1)	100 (+ 1)	30 (− 1)	76	77.91
25	3 (− 1)	40 (+ 1)	200 (+ 1)	25 (− 1)	30 (− 1)	76	77.75
26	5 (0)	40 (+ 1)	125 (0)	62.5 (0)	65 (0)	90	88.78
27	5 (0)	22.5 (0)	125 (0)	62.5 (0)	65 (0)	98	97.10
28	5 (0)	22.5 (0)	125 (0)	62.5 (0)	65 (0)	92	97.10
29	7 (+ 1)	5 (− 1)	50 (− 1)	25 (− 1)	30 (− 1)	80	81.52
30	5 (0)	22.5 (0)	125 (0)	62.5 (0)	65 (0)	98	97.10
31	3 (− 1)	5 (− 1)	200 (+ 1)	100 (+ 1)	30 (− 1)	73	75.32
32	3 (− 1)	40 (+ 1)	50 (− 1)	25 (− 1)	100 (+ 1)	80	82.11
33	3 (− 1)	5 (− 1)	200 (+ 1)	25 (− 1)	30 (− 1)	80	81.17
34	5 (0)	22.5 (0)	200 (+ 1)	62.5(0)	65 (0)	86	90.01
35	3 (− 1)	40 (+ 1)	50 (− 1)	100(+ 1)	30 (− 1)	82	82.22
36	3 (− 1)	5 (− 1)	50 (− 1)	100(+ 1)	100 (+ 1)	80	78.67
37	7 (+ 1)	5 (− 1)	200 (+ 1)	25 (− 1)	100 (+ 1)	70	69.22
38	7 (+ 1)	40 (+ 1)	200 (+ 1)	100(+ 1)	100 (+ 1)	85	84.20
39	3 (− 1)	40 (+ 1)	200 (+ 1)	100(+ 1)	30 (− 1)	83	80.65
40	7 (+ 1)	22.5 (0)	125 (0)	62.5(0)	65 (0)	85	86.25
41	5 (0)	22.5 (0)	125 (0)	62.5(0)	65 (0)	100	97.10
42	3 (− 1)	22.5 (0)	125 (0)	62.5(0)	65 (0)	92	91.60
43	7 (+ 1)	40 (+ 1)	200 (+ 1)	25 (− 1)	30 (− 1)	60	62.02
44	7 (+ 1)	40 (+ 1)	50 (− 1)	100(+ 1)	100 (+ 1)	91	90.52
45	5 (0)	22.5 (0)	50 (− 1)	62.5(0)	65 (0)	100	96.84
46	5 (0)	22.5 (0)	125 (0)	62.5(0)	100 (+ 1)	100	99.19
47	5 (0)	22.5 (0)	125 (0)	100(+ 1)	65 (0)	100	100.25
48	3 (− 1)	5 (− 1)	200 (+ 1)	100(+ 1)	100 (+ 1)	78	74.85

Figure 4a was constructed from a comparison of predicted values against factual values⁴¹. The validity of the model was confirmed by a straight trend line connecting residuals (Fig. 4b). Comparing the residual's plot to the predicted values (Fig. 4c) and run numbers (Fig. 4d) requires a random dispersion. A Box-Cox procedure (Fig. 4e) was used to determine the normality of the data and establish the model significance of the sonophotocatalytic process⁴².

Figure 4.

The diagnostics plots for validation of quadratic model: (a) predicted values vs. factual values, (b) normal probability distribution of residuals, (c) internally studentized residuals vs. predicted values plot, (d) internally studentized residuals vs. run numbers, and (e) Box-Cox plot.

The effect of single factors

The variance analysis (ANOVA) for R195 removal is presented in Table 3. Among pH, exposure time, photocatalyst dosage, R195 concentration, and US power as a single variable, each factor with a high mean square and high F-value exerts the greatest influence on the sono-photodegradation of R195. Thus, the effect of variables on R195's degradation is⁴³:

$$\text{Concentration of Red}195\le \text{pH}\le \text{US Power}\le \text{otocatalyst dosage}\le \text{Exposure time}.$$

The concentration of R195 with a mean square and F-value of 230.08 and 29.33, respectively, was the most crucial factor in R195 removal⁵.

Three dimensional response surface schemes

Three-dimensional (3D) graphical schemes (Fig. 5) were implemented in order to assess the individual and combined effects of operational variables on the sonophotocatalytic degradation of R195. Figure 5a depicts the simultaneous effect of initial pH (three to seven) and dye concentration (fifty to two hundred mg/lit) on optimization under constant conditions (exposure time = 22 min, US power = 65W, and photocatalyst dosage = 62.50 mg). Maximum removal efficacy was observed in a medium with a pH of 5 after 15 min. This trend can be attributed to the following elements: (a) A test apparatus operating under identical conditions will produce analogous results (equal production of hydroxyl radicals at each initial R195 concentration)⁴⁴; (b) the generation of hydroxyl radicals is proportional to the initial concentration of R195⁴⁰. Therefore, an increase in the number of dye molecules can lead to the saturation of active sites on the surface of the photocatalyst and inadequate production of hydroxyl radicals⁴². (c) Produced intermediates of R195 during sonophotocatalytic degradation (at high concentrations of R195) reduce removal efficiency due to a competition reaction between the dye and intermediate with free radicals⁵. Dye molecules and photocatalyst nanorods are brought into favorable contact by increasing the number of accessible active sites. According to the scientific literature, the pka of R195 (3.6) and the pHpzc of TiO₂ (6.8) remind us that electrostatic interaction between the negatively charged facet of R195 (at pH > 3.6) and the positively charged facet of nanorods (at pH 6.8) is the primary reason for the accelerated degradation of R195^6,22. Additionally, by undertaking sonophotocatalytic reactions in an acidic medium and extending the duration of US irradiation, residual R195 in the cavitation bubbles containing more hydroxyl radicals can provide a greater potential for oxidation of the model pollutant⁴⁴. Amri et al.⁴⁵ and Nangia et al.⁴⁶ also reported similar results with our findings^45,46. 5b depicts the reciprocal effect of pH and photocatalyst concentration. By increasing the pH (from 3 to 7) and decreasing the amount of catalyst (from 100 to 25 mg), the removal efficiency was diminished. At a higher photocatalyst dosage, more cavitation bubbles may be produced in the region of ultrasound irradiation, resulting in sufficient free radical generation²².

Figure 5.

The three-dimensional interaction effects of pH and concentration of dye (a), pH and photocatalyst dosage (b), pH and US power (c), exposure time and photocatalyst dosage for (d), photocatalyst dosage and US power (e), exposure time and US power (f).

Figure 5c investigates the effects of pH and US power on the elimination of R195 by varying the US power from 30 to 100 W and the pH from 3 to 7. As the US power increased from 30 to 100 W, the percentage of removal rose from 55 to 85%.The increase in dye degradation can be attributed to a number of factors, including the disintegration of dye molecules, the destruction of dye structures as a result of an increase in energy pressure, and the total decomposition of dye^5,40,47. Figure 5d depicts the interaction effect of contact time and photocatalyst dose. The duration ranged from 5 to 40 min, and the photocatalyst dose ranged from 25 to 100 mg. The removal percentage rose from 65 to 98% as the photocatalyst dosage increased. The optimal dose for reducing photocatalyst consumption was determined to be 62 mg. In relation to the time variable, the photocatalytic removal rate increased from 5 to 83% between 5 and 22 min, and then decreased from 83 to 75% between 22 and 40 min. Increasing the photocatalyst's contact time with US and UVA lamps initially accelerated the oxidation processes. After 22 to 40 min, the removal rate decreased due to increased competition between the dye molecule and the photocatalyst and the saturation of the active sites⁵. Thus, 22 min was considered the optimal duration. Figure 5e examines the effect of the US power parameter in the range of 30 to 100 W and the photocatalyst dose in the range of 25 to 100 mg. Both parameters increased directly in proportion to the amount of dye removed. Figure 5f depicts the interaction effect of photocatalyst dose and US power. Both parameters increased directly in proportion to the amount of dye removed. The dye removal percentage increased from 64 to 95% when the photocatalyst dose was increased from 25 to 100 mg, and when the US power was increased from 30 to 100W. It is due to the high availability of active reaction sites, OH radicals, and electron–hole pairs^8,43,46.

Mechanism of sonophotocatalytic degradation

To identify reactive active species in the degradation of R195 by the Scendesmus/Fe₃O₄/TiO₂ UV/US process, radical trapping experiments with a variety of scavengers were conducted. 100 percent (reactor without scavenger) to 86.9 percent (reaction solution with TiO₂ present). This event demonstrates that O₂ molecules were converted into an O₂^•-reaction solution, decreasing the effectiveness from one hundred percent to 66.7%⁴⁸. These findings indicate that the sonophotocatalytic process generates •OH, h⁺, and O₂^•- in the reaction solution⁴⁹. A potential degradation mechanism for the sonophotocatalytic process has been postulated based on the results of the entrapment test and previous research⁶. Using adsorption and photolysis, certain contaminants can be eliminated. Sonolysis and sonophotocatalytic processes can also be utilized to eliminate R195 dye in solution and on a catalyst's surface. During these processes, the heated spot event (resulting from the cavitation effect) can separate water molecules into •OH and H• (Eq. (25))^6,22,48. US radiation, via the sonoluminescence mechanism, produces visible light radiation for the generation of electron/hole pairs in the valence and conduction bands of particles along the same pathway²⁸. Under UV radiation, however, Scendesmus/Fe₃O₄/TiO₂ nanoparticles generate electron–hole pairs by absorbing light (Eq. (26))⁵⁰. In addition to directly degrading the contaminant, the holes in the valence band can decompose H₂O molecules and hydroxyl ions (OH^-) to generate ^•OH (Eqs. (27) and (28))⁶. All species generated in the solution and solid phases are capable of transforming pollutants into CO₂, H₂O, and biodegradable products (Eq. (29))²².

$${\text{H}}_2\text{O + )))}\to ·\text{OH}+\text{H}·$$ 25

$$Scendesmus/{\text{Fe}}_3{\text{O}}_4/{\text{TiO}}_2+)))+\text{UVA}\to {\text{h}}_{\text{VB}+}+{\text{e}}_{{\text{CB}}^{-}}$$ 26

$${\text{h}}_{\text{VB}+}+{\text{H}}_2\text{O}\to {\text{H}}^{+}+·\text{OH}$$ 27

$${\text{h}}_{\text{VB}+}+{\text{OH}}^{-}\to ·\text{OH}$$ 28

$$\text{R195}+\text{active radicals}\to {\text{CO}}_2+{\text{H}}_2\text{O}+\text{byproducts}$$ 29

Isotherm, kinetcs and thermodinamics model

As depicted in Fig. 6, the Langmuir, Freundlich, Temkin, and Harkins–Jura isotherm adsorption models were implemented. The Freundlich (R² = 0.9782), Harkins Jura (R² = 0.9438), Temkin (R² = 0.9687), and Langmuir (R² = 0.9584) models (Table 5) provided a more accurate description of the equilibrium adsorption data. Freundlich's isotherm is an empirical model that depicts photocatalyst-pollutant interactions on heterogeneous surfaces and in multilayer adsorption⁵. With 1/n and K_F values of 0.4036 and 12.68 mg1^-n g^-1 L^-n, respectively, the adsorption process and reaction's intensity were favorable. In addition, the Harkins–Jura model confirmed the adsorption of R195 molecules onto the heterogeneous surface³³. In contrast, the presence of exothermic and physical adsorption between R195 molecules and Scendesmus, Fe₃O₄, and TiO2 was indicated by the positive value of b_T (43.266 J/mol) in the Temkin isotherm³². The optimal adsorption capacity (q_m) predicted by the Langmuir isotherm was close to the experimental value, indicating that the photocatalyst had a uniform surface with the same activation energy³¹. In addition, the R_L value between 0 and 1 (R_L = 0.0269) indicated that the adsorption procedure was successful. Using pseudo-first-order, pseudo-second-order, Elovich, and intra-particle diffusion kinetic models, the R195 removal mechanism was predicted⁵. According to Fig. 7 and Table 5, the equilibrium condition for R195 removal was stabilized after 60 min for all concentrations tested, ranging from 50 to 500 mg/l, as shown in Fig. 7 and in Table 5. At 300 mg/l of R195, the empirical data were best described by the pseudo-first-order (PFO) model with R² = 0.9925. These findings reveal a correlation between the quantity of physical R195 adsorption and the increased driving force responsible for the efficient diffusion of R195 molecules to the surface of Scendesmus/Fe₃O₄/TiO₂ and their occupation of the remaining active sites³³. The pseudo-second-order (PSO) model best described the adsorption process of 100, 200, and 400 mg/l of initial R195 concentrations, with R² values of 0.9983, 0.9731, and 0.9722, respectively, when considering chemisorption as the predominant adsorption process with electron donor–acceptor and dispersal interactions⁵¹. The Elovich model also demonstrated the chemical adsorption of R195 molecules on the solid surfaces of exceedingly heterogeneous adsorbents (R2 > 0.9871)⁵. The intra-particle diffusion model provided the best fit to the adsorption data (Table 5, R² = 0.9857 for 50 mg/l R195 and R² = 0.9398 for 500 mg/l R195, respectively). Since the relationship between qt and t0.5 is linear, intra-particle diffusion should be the rate-regulating process ^35,36.

Figure 6.

Langmuir (a), Freundlich (b), Temkin (c), and Harkins–Jura (d) isotherm models for R195 removal.

Table 5.

Parameters of isotherm, kinetics and thermodynamics model.

Kinetic	Parameters/Value
Pseudo-first-order	K1 (min-1)	qe (mg/g)	R2
50	− 0.0251	241.815	0.9812
100	− 0.0263	153.394	0.9925
200	− 0.0289	664.230	0.9731
300	− 0.0338	1738.095	0.9752
400	− 0.0374	3385.488	0.9352
500	− 0.0295	1487.73	0.9324

Pseudo-second-order	K2 (g.mg-1 min-1)	qe (mg/g)	R2
50	4604.777	90.29	0.9557
100	44,976.76	107.29	0.9983
200	53,273.72	323.52	0.9731
300	33,598.76	276.26	0.9589
400	18,786.43	537.32	0.9722
500	26,125.04	600.01	0.9424

Elovich	α (mg g-1 min-1)	β (g/mg)	R2
50	1.396	0.056	0.9652
100	12.976	0.052	0.9871
200	22.922	0.019	0.9573
300	11.121	0.008	0.9384
400	14.004	0.007	0.9091
500	273.723	0.005	0.9347

Intra particle diffusion	C (mg/g)	Kint (mg.g- 1.min-0.5)	R2
50	− 8.8121	4.3797	0.9857
100	− 32.921	4.7259	0.9623
200	− 33.598	13.942	0.8869
300	− 44.076	28.138	0.9583
400	− 23.943	29.758	0.9494
500	− 31.195	40.165	0.9398

Isotherm	Parameters	Value
Langmuir	qm (mg/g)	1.42
	b (l/mg)	36.09
	R2	0.9584
	RL	0.0269
Freundlich	KF (mg1-n g-1 L-n)	12.68
	1/n	0.4036
	R2	0.9782
Harkins–Jura	A	+ 3.368
	B	2.338
	R2	0.9438
Temkin	bT (J/mol)	43.26
	AT (l/g)	0.1308
	R2	0.9687

T, K	Kapp(*10–3), min-1	Ln(Kaaph/KBT)	ΔGo, KJ mol-1
Transition theory
288.15	0.3293	− 48.4941	− 105.69
293.15	0.4300	− 48.2445	− 457.192
298.15	0.5546	− 48.0069	− 1287.11
303.15	0.6066	− 47.9340	− 2099.44
308.15	0.7799	− 47.6990	− 3241.03
313.15	0.8146	− 47.6716	− 3852.97
318.15	0.8666	− 47.6256	− 4948.46

ΔHo, KJ mol-1	ΔSo, KJ mol-1 k	Ea, kJ mol-1	A, s-1	R2
Transition theory
− 25.368	+ 21.167	− 69.121	7.151	0.9810

Ea, kJ mol-1	A, s-1	R2
Arrhenius theory
+ 72.414	37.326	0.9844

Figure 7.

Pseudo-first-order (a), pseudo-second-order (b), and Elovich (c) and Intra particle diffusion (d) kinetic models for the R195 concentrations of 50 ( ), 100 ( ), 200 ( ), 300 ( ), 400 ( ), and 500 ( ) mg/100 ml. Enthalpy and entropy change for the photocatalytic decomposition of R195, (e) Arrhenius plot and (f) Henry Eyring plot.

As shown in Table 5, the activation energy was calculated to be 69.12 kJ mol^-1. The exothermic adsorption mechanism was revealed by the negative standard enthalpy of activation (ΔH^o = −23.368)⁵. Moreover, the increasing value of the standard Gibbs free energy of activation (ΔG^o) with increasing temperature demonstrated that the process was not spontaneous²². The positive value of standard entropy of activation (ΔS^o =  + 21.167) was related to the transient molecular configuration at the summit of the energy barrier, indicating an increase in the degree of loss of freedom when the activated complex is formed from the reactants^6,33.

Potential scendesmus/Fe₃O₄/TiO₂ recycle

Under constant conditions (pH = 5, photocatalyst dosage = 100 mg, initial R195 concentration = 100 mg/l, ultrasound power = 38W, and exposure time = 20 min), the reusability of the synthesized Scendesmus/Fe₃O₄/TiO₂ photocatalyst was evaluated (Fig. 8). After five cycles, the photocatalytic efficiency of Scendesmus/Fe₃O₄/TiO₂ remained above 95% without any discernible decline. Due to its stability, the synthesized Scendesmus/Fe₃O₄/TiO₂ composite is economically viable for use in the effluent treatment process²². Future product development and convincing investors and stakeholders could increase the renewability and cost-effectiveness of the final photocatalyst⁶ .

Figure 8.

The reusability of the Scendesmus/Fe₃O₄/TiO₂ within five cycles.

Comparison of sonophotocatalytic degradation with other methods

Numerous techniques for degrading textile dyes have been investigated. Table 6 compares these techniques for the degradation of R195. The comparison demonstrates that sonophotocatalysis of R195 using Scendesmus/Fe₃O₄/TiO₂ as a photocatalyst yields superior results in comparison to other techniques. According to the obtained data, the present photocatalyst (Scendesmus/Fe₃O₄/TiO₂) is novel, relatively effective, cost-effective, and broadly accessible. Scendesmus was used as a precursor for the first time in this study to produce a magnetic photocatalyst and eliminate R195 dye. In this investigation, garbage was used as a photocatalyst to remove pollutants from farm effluent. From an ecological standpoint, this matter is of the utmost importance.

Table 6.

Comparison with various Methods for the Removal of R195 Dyes.

Dye	Method	Time(min)	Degredation(%)	Refrencess
Rhodamine B (RhB)	photocatalytic removal	35	84.5	52
Methyl red (MR)	Adsorption	60	85	53
Rhodamine B (RhB)	photocatalytic removal	30	73	54
black 5	membrane	40	70.7	55
Red195	adsorption- photodegradation	35	89.5	56
Red195	ultrafiltration membranes	40	88	57
yellow dyes	photodegration	60	91	58
Methylene blue	Biodegration	60	85	59
Methylene blue	photodegration	75	85	60
Methylene blue	Photodegration–visible light	120	90	61
Organic dye	Sonophotocatalyst	20	98	13
Red195	Sonophotocatalyst	20	92	20
Rhodamine b	Sonophotocatalyst	240	92	19
Acid red 14	Sonophotocatalyst	21	100	49
Victoria blue	Sonophotocatalyst	60	71.97	18
Yellow AB and Remazol brilliant Violet-5R	Sonophotocatalyst	30	95.5–88.9	17

Conclusion

In the present investigation, Scendesmus/Fe₃O₄/TiO₂ was synthesized as a novel sonophotocatalyst for degrading R195 dye. Diagnostic analyses such as SEM, mapping, FTIR, and VSM confirmed the efficacy of the TiO₂ coating on Scendesmus/Fe₃O₄ and the resulting photocatalyst. Scendesmus/Fe₃O₄/TiO₂ nanoparticles are effective against sonolysis, photolysis, adsorption, and photocatalytic processes when exposed to ultraviolet light and ultrasonic waves. The R195 removal efficiency increases as operating parameters such as photocatalyst dosage, ultrasound power, radiation power, and exposure time are increased, but decreases as initial pH and initial R195 concentration are increased. Under optimal conditions, such as a pH of 5, a photocatalyst dosage of 62.5 mg/l, an exposure duration of 22 min, an initial R195 concentration of 125 mg/m3, and a US power of 65W, the maximum R195 removal was 100%. According to the proposed quadratic model, the concentration of R195 was the most significant variable because of its high F-value. The Freundlich isotherm model and the intra-particle diffusion model best fit the experimental data when taking into account the heterogeneous surface of the photocatalyst and multilayer adsorption. Thermodynamic analysis has confirmed that endothermic and nonspontaneous adsorption processes occur. Under repeated irradiation from the United States, the recycled Scendesmus/Fe₃O₄/TiO₂ demonstrates exceptional activity and regular stability for pesticide removal. The addition of different scavengers to evaluate the active species of the sonophotocatalytic process revealed that all three species, O₂, ^•OH, and h⁺, were produced during the process and that h⁺ is the active species in the degradation of R195 into CO₂ and H₂O. The Scendesmus/Fe₃O₄/TiO₂ photocatalyst was deemed a novel sonophotocatalyst for the mineralization of R195 based on analyses of various parameters and stability experiments. In conclusion, the transformation of scendesmus into a photocatalyst can not only eliminate the need for additional R195 degradation and reduce the cost of wastewater treatment, but also provide a valuable and efficient photocatalyst at a lower cost than commercial Microalgae that contributes to environmental preservation.

Author contributions

W.Z. and S. R. Generated the idea, Methodology, Data curation, Investigation Writing- Original draft preparation, A.H.: Conceptualization, Validation, Investigation, Writing – review & editing. All authors have read and agreed to the published version of the manuscript.

Data availability

The data and materials from the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare no competing interests.