# Production and Optimization of Bio-Based Silica Nanoparticle from Teff Straw (Eragrostis tef) Using RSM-Based Modeling, Characterization Aspects, and Adsorption Efficacy of Methyl Orange Dye

Authors: Temesgen Abeto Amibo; Surafel Mustefa Beyan; Tsegaye Markos Damite
Journal: Journal of Chemistry
 (2022)

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## Abstract

The brown teff straw was utilized in this study to produce silica using the sol-gel technique. After pretreatment, the raw material of brown teff straw was characterized. The data were analyzed using the central composite design and response surface technique, and four independent parameters, namely, temperature, NaOH concentration, rotational speed, and extraction time, were evaluated for process optimization. Before extracting silica with an alkaline solution, the silica content in the ash was determined using an AAS spectrometer. The silica content of teff straw ash is around 92.89%. The ash was treated with NaOH solution in the concentrations range of 1 M to 3 M (0.5 M interval). The extraction time varied at intervals of 55, 70, 85, 100, and 115 minutes. Temperatures were changed using magnetic stirrer equipment in the range of 80°C to 100°C (5°C interval). At 350 rpm, 400 rpm, 450 rpm, 500 rpm, and 550 rpm, the rotating speed was adjusted. The best extraction conditions for amorphous silica were 1.50 M NaOH, 109.99 min, 94.98°C, and a rotating speed of 499.57 rpm, with a maximum yield of 85.85%. XRD and FTIR analyses were used to assess the physicochemical characteristics of the extracted silica. The aqueous solutions of methyl orange were used to test the adsorption efficiency of silica. The percent of removal efficiency for methyl orange was 90.48%.


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## Body

## 1. Introduction

Teff is a fine-stemmed and tufted annual grass with a broad crown, a shallow varied root system, and a dense shoot system. Its grain is oval and is 0.7–1.0 mm in diameter and 0.9–1.7 mm in length. Individual teff grains weigh between 0.2 and 0.4 mg, and 1 gram of teff contains 2500–3000 seeds. One hundred fifty teff grains weigh the same as one grain of wheat, making it the world’s smallest grain among carbohydrate-rich kernels teff containing nutrients [1]. Although it is popular in Ethiopia, teff grain is threshed, and the straw is utilized as animal feed, particularly during the dry season [2]. Teff straw is also used as mulch, and it is combined with mud to create the walls of buildings and grain storage facilities. Teff straw (Eragrostis tef) has recently been investigated as a biosilica source. Every year, more than 2 million tons of teff straw are discarded like garbage in Ethiopia [3].According to Bunker et al. [4], the majority of silica used in commercial applications comes from naturally occurring sources, quartz and quartzite rocks are the most stable and reasonably pure type of silica that can be found in virtually all mineralogical rocks, and these mineralogical rocks are treated at high temperatures to generate sodium silicate. Silica can be categorized as crystalline or amorphous based on its structure, according to Vareda et al. [5]. Crystalline silica is a kind of silica that has a highly structured framework pattern. The most prevalent crystalline form of silica found in nature is quartz. Crystalline silica is carcinogenic to humans and poses a risk to their health. However, crystalline silica in the form of quartz is stable under most earth surface conditions, has extremely low solubility under a wide variety of environmental variables such as (PH, salinity, and redox potential), and so prefers to persist in environmental conditions. In the study conducted by Kyono et al. [6], X-ray diffraction studies show that amorphous silica lacks a crystalline structure. Amorphous silica can exist naturally or be synthesized. Synthetic amorphous silica is classified into two types of stable materials: vitreous silica or glass and microamorphous silica. Vitreous silica is created by fusing quartz at temperatures above 1700°C. Silica sols, gels, powders, and porous glasses are examples of microamorphous silica.In general, there are two traditional ways for producing reactive silica from biomass, known as biosilica: chemical and thermal approaches. In the combustion technique, the biomass is thermally destroyed at high temperatures to extract its carbonaceous components. In this case, the combustion might be immediately or after pretreatment. The chemical technique includes the digestion of biomass with alkali or other chemicals to extract silica in the form of sodium silicate. In a chemical approach, the ash can react with sodium hydroxide, sodium carbonate, or hydrogen fluoride, or it can be treated hydrothermally [7].According to the study reported by Setiawan and Chiang [8], the sol-gel technique refers to the reaction of teff straw biomass with sodium hydroxide to produce sodium silicate, which is then precipitated using an acid solution. Various researches on various biomasses have been conducted utilizing the sol-gel technique. Teff straw may be used to make biosilica using the sol-gel technique. During the procedure, several factors such as sodium hydroxide concentration, extraction duration, and extraction temperature can all affect this technique. A thorough search of the literature reveals that no investigations on the influence of process factors on silica synthesis from teff (Eragrostis tef) straw using the sol-gel technique have been published [9, 10]. In the current study, silica was synthesized from teff straw using the sol-gel technique, and the impacts of process factors on silica yield and physicochemical characteristics such as composition, structure, and functional quality were investigated.From the study reported by Hynes et al. [11], modern wastewater effluent treatment management might include physical, chemical, and biological techniques. Trapping pollutants to avoid release and contamination of uncontaminated regions can be accomplished by a variety of physical processes such as encapsulation, filtration, gravity, settling, adsorption, and stabilization [12]. Wastewater produced during the processing of many industries has an excessive biological oxygen demand and chemical oxygen requirement. Improper wastewater treatment is one source of environmental concerns that can exacerbate human health issues. As a result, the effective treatment of effluents produced by various sectors is a global concern [12, 13]. Adsorption of wastewater using silicon oxide is a low-cost, innovative, efficient, and simple technique of removing contaminants from wastewater. Silicon oxide, derived from agricultural waste biomass, is one of the adsorbents utilized in a variety of sectors today [14]. It possesses a suitable pore size distribution, large specific surface area, and strong surface reactivity. In comparison with other nanoparticles, the silicon oxide manufacturing technique is very inexpensive, and its regeneration is simple. In recent years, this has led to the development of novel low-cost and efficient adsorbent materials [14, 15]. It has been discovered that silicon dioxide derived from different agricultural wastes has a great potential for pollution effluent removal. Several agricultural byproducts have been utilized in the preparation of silicon dioxide synthesis, including rice husks, teff straw, corn cobs, banana peels, floral wastes, and sugarcane bagasse [14]. To reduce contaminants from wastewater effluents, low-cost materials that are highly efficient and can be utilized with simple technology are required. Recently, researchers have focused on better, more readily available, yet less expensive materials for producing silicon dioxide [16]. Teff straw, with its high silicon concentration, is unquestionably a major agroindustrial waste. As a result, they are appealing since they are cheap and effective adsorbents. Several studies have been conducted utilizing agricultural residues to create silicon oxides, but teff straw is an indigenous plant in Ethiopia, and this area is a relatively new notion for wastewater treatment. Several studies have been conducted to examine the possible use of agricultural waste for the manufacture of silicon dioxide and the treatment of wastewater discharge [17].Design of Expert (V.11) software was used for product, and process improvement aids in achieving the interaction effects of each variable, 2D visuals, and 3D plots for this study. The surface methodology’s central composite design (CCD) was utilized to assess the experimental outcomes. The goal of this research is to extract, characterize, and optimize silica synthesis from teff straw using an alkali solution, describe the raw teff straw and identify the compositional analysis of teff straw ash after burning, characterize the extracted silica using FTIR spectroscopy analysis and XRD analysis, optimize the extraction of silica process parameters such as NaOH concentration, extraction duration, rotational speed, and extraction temperature for maximum silica production, and investigate the removal effectiveness of methyl orange solution using the extracted silica. A total of thirty tests were carried out using five levels and four variables for this study. The two responses such as yield and density of silica were investigated by combining the aforementioned variables. For this investigation, the temperature was set at 80°C, 85°C, 90°C, 95°C, and 100°C. For agitation, the rotating speeds were 350 rpm, 400 rpm, 450 rpm, 500 rpm, and 550 rpm. The sodium hydroxide solution (alkali concentration) was diluted to 1 M, 1.5 M, 2.0 M, 2.5 M, and 3 M concentrations. It was tweaked at 55, 70, 85, 100, and 115 minutes. Finally, utilizing the response surface technique, the yield and density response of silica were investigated.


## 2. Materials and Methods

### 2.1. Raw Materials and Chemicals Used

Brown teff straw (Eragrostis tef) was agricultural waste gathered from farmers at the time of harvest and crop maturity. Muffle furnace (model number L31M), sieve analysis, beaker, hot plate, the crucible, flask, balance, pH meter (model number pH−9202), oven dryer (model number DHG-9203A), plastic bag, grinder machine, electronic beam balance, mortar, and filter cloth were used for testing. FTIR (Make and Model: PerkinElmer spectrum 2, 8300–350 cm−1) was used for functional group analysis, XRD (Make and Model: Drawell XRD 7000) for crystalline index determination, and UV-light spectra (Make and Model: PerkinElmer Lambda 25) for methyl orange concentration determination.At the time of the experiment, substances such as sodium hydroxide (solid crystal), hydrochloric acid (36.46%), and distilled water (conductivity 0.6 mho/cm) were used in the synthesis of silica, while methyl orange was used to measure the efficacy of silica adsorption. KBr (solid) was utilized to prepare pellets for FTIR examination.


### 2.2. Methods

#### 2.2.1. Sample Collection

Teff is farmed in most regions of Ethiopia; therefore, teff straw is readily available across the country [18]. Brown teff straw was gathered in Yebu, Jimma, Ethiopia, and sent to JIT, the School of Chemical Engineering laboratory, and the Faculty of Material Science and Engineering laboratory.


#### 2.2.2. Raw Material Analysis

(1) Moisture Content of Teff Straw. Equation (1) was used to calculate the moisture content of raw teff straw. The amount of raw teff straw kept below 2 mm weighed 5 g. The prepared teff straw was dried in an oven at 105°C until it became a consistent mass. The experiment was carried out three times.(1)MCTS=WBD−WADWBD×100%,where MCTS denotes the moisture content of raw teff straw, WBD denotes the weight of the teff straw in its natural condition, and WAD is the weight of the oven-dried sample.(2) Determination of Ash Content. The ash content was calculated using the L31M muffle furnace (Model 1507074). A 3 g sample of teff straw is placed in a preweighted crucible and burned at 1000°C in a muffle furnace until the full ashing process is accomplished. The crucible is then placed in a desiccator to cool. Three replicates were created, and the mass was measured using a mass balance. The ash content was determined using the following equation:(2)ACTS=WCSAD−WCWCSBD−WC×100%,where WC stands for the weight of the crucible, WCSBD stands for the weight of the crucible + sample before thermal decomposition, and WCSAD stands for the weight of the crucible + sample after thermal decomposition.


#### 2.2.3. Sample Preparation

Teff straw is a biomass of teff; it may include a variety of contaminants. The sample has to be processed to improve the extraction rate and purity of biosilica in the downstream procedures.(1) Cleaning, Soaking, and Washing. The sample was physically sorted by hand to remove large impurities such as nonteff straw, grasses, sand, leaves, and soil. The teff straw was then soaked overnight in tap water. The next day, the soaked teff straw was washed three times to eliminate soluble contaminants using distilled water generated in material engineering facilities using reverse osmosis.(2) Drying, Grinding, and Sieving. The washed teff straw was sun-dried for 2 days to remove the moisture absorbed for ease of grinding. The next process was grinding the dried teff straw using a grinding machine and sieved by sieve analysis with 2.0 to 1.0 mm mesh openings, and the particle sizes were below 2 mm and greater than 1 mm. The sample was grounded for ease of thermal treatment and maximum biosilica recovery.


### 2.3. Acid Leaching

Raw materials were dried in the sun, and then acid was used to leach the teff straw. Impurities in teff straw include metals such as sodium, calcium, potassium, magnesium, aluminum, iron, and others [19]. These metals can either deposit in the cell or bind to lignin or hemicellulose. Acid leaching is necessary to eliminate such metals. The elimination of trace metals improves the surface area of the straw [19]. In addition, chemical activation of carbonaceous material occurs as a result of the removal of ionic bound metals from lignin or hemicellulose. In the high-temperature ashing process, this aids in the removal of both organic and carbonaceous materials. Overall, if not avoided early on, these contaminants may have an impact on the final product’s (silica gel) key characteristics such as porosity, color, and specific surface area. The pulverized teff straw was treated with HCl of 2.5 N (analytical grade of 36.46%). The solid sample to liquid solvent mixing ratio is one to ten weights by volume (1 : 10 w/v). The 60 g of teff straw was measured using a digital mass balance and placed in a 1000 ml beaker, to which 600 ml of HCl solution was added. The prepared solution was heated for 1 hour at 80°C using a hot plate and agitated at 550 rpm with an agitator. The trace metals were soluble in the HCl solution that had been produced. The method used was a batch stirred lab-sized beaker agitated with coaxial impellers. The agitator’s primary duty was to replenish the teff straw with any remaining solvent. The volume of the HCl solution was sufficient to provide a high surface area per unit volume. Because the teff straw could settle during the process, vigorous stirring (600 rpm) was required to prevent this. Finally, the HCl used in the experiments was neutralized with NaOH before it was discharged into the environment.


### 2.4. Cooling, Filtering, Washing, and Drying

The leached solution was allowed to spontaneously cool to room temperature. The acid-leached teff straw was then separated from the wastewater using a filter cloth. The filtered substance was then washed with water until the pH of the water reached neutral. The washed sample was dried in an oven set to 105°C for 24 hours.


### 2.5. Teff Straw Ash Preparation

The pretreated teff straw was put in ten crucibles and heated in an L31M muffle furnace. The temperature was set to 750°C, and the calcination time was set to 2 hours. Thermal decomposition was applied to the sample. The chosen temperature and duration are sufficient for achieving a consistent mass of samples while also producing amorphous biosilica. After calcination, the crucibles were put in a desiccator with a tong for cooling and ambient temperature absorption. The ash was then put in an airtight plastic bag. The goal of this phase is to raise the relative proportion of silicon oxide in the samples by reducing the carbonaceous elements present, as well as burn out any unwanted components discovered by chemical analysis.


### 2.6. Biosilica Extraction

Several NaOH concentration solutions were generated before commencing the extraction operation using equation (3). The molarity of the NaOH solution was calculated using the formula below. The calculated mass was then dissolved in 1 liter of distilled water in a conical flask, which was swirled with a stirring rod until the pellets were completely dissolved.(3)molarity=mass of NaOHmolar mass of NaOH×volume of solution.The amorphous silica was extracted by leaching it in NaOH extraction solution with concentrations of 1 M to 3 M with 0.5 M intervals.A 10 g of teff straw ash was put into a beaker, followed by a NaOH solution. The beaker was put on a heated plate, and then the extraction temperatures were 80°C to 100°C (5°C interval), respectively, while the extraction times were 55, 70, 85, 100, and 115 minutes. The rotating speed may be changed to 350 rpm, 400 rpm, 450 rpm, 500 rpm, or 550 rpm. After extraction, the mixture was allowed to cool naturally to room temperature. The combination was then filtered using filter paper, and the residual cake was washed with hot distilled water to maximize biosilica recovery. The liquid portion was collected in a beaker, while the remainder was discarded. Then the reaction was shown below in reaction one:(4)4NaOH+2nSiO2ash⟶2H2O+2Na2O⋅nSiO2R1


### 2.7. Biosilica Gel Preparation

The pH of the sodium silicate solution was titrated by adding 2.5 N HCl solution drop by drop with vigorous swirling until it reached 10. The biosilica begins to precipitate when the pH reaches 10. The precipitated biosilica solution was then heated on a hot plate for 1 hour at 80°C and vigorously stirred with a 600 rpm agitator. To encourage gel formation, the precipitated biosilica solution was allowed to cool to ambient temperature before the gel was aged for 20 hours intact. The gel was then filtered and rinsed five times to eliminate any soluble salts. Finally, the produced biosilica gel was oven-dried at 60°C for 24 hours, and the sample was kept in a polyethylene bag before being utilized for characterization. The reaction for biosilica gel formation is shown in reaction 2 (5). The silica particles were substantially dispersed at this stage, and the collision of silica monomers initiated the agglomeration of massive silica precipitators.(5)4HCl+2Na2O⋅nSiO2⟶4NaCl+2H2O+2nSiO2SR2


### 2.8. Characterization of Teff Straw Ash and Biosilica

#### 2.8.1. FTIR Analysis

FTIR (make and model: PerkinElmer spectrum 2; wavenumber range 8300–350 cm−1) was used to identify the functional groups contained in teff straw ash and biosilica. To identify the functional groups, pellets were prepared using KBr. In this work, the functional group was studied within a wavenumber range of 4500–400 cm−1, and the functional group peak was assessed utilizing origin software [20].


#### 2.8.2. XRD Analysis

According to Mi et al. [21], X-ray diffraction was utilized to determine the crystalline and amorous phases of generated teff straw ash, as well as biosilica created from teff straw ash. During this investigation, the angle of diffraction (2-theta) on an XRD (make and model: Drawell XRD 7000) fluctuated from 5° to 80°. The crystalline peak was divided by the overall peak to calculate the crystallinity index (both crystallinity index and amorphous peak).


#### 2.8.3. Morphological Analysis

The morphological changes that occurred when teff straw ash was transformed to biosilica were studied using a scanning electron microscope (SEM). As a result, the size of the created biosilica was determined using the “ImageJ” software [22].


#### 2.8.4. UV-Spectrophotometer Analysis

According to El Maguana et al., the UV-spectrophotometer (PerkinElmer Lambda 25; wavenumber range 190–1100) helps to measure the concentration of methyl orange dye solution. The UV-spectrophotometer emits light, which is absorbed by the methyl orange. Their absorbance varied with concentration, which aids in determining the ultimate concentration of methyl orange for this study using the Beer–Lambert equation [23].


#### 2.8.5. Atomic Adsorption Spectrophotometer Analysis

To determine the components contained in teff straw ash, an atomic absorption spectrophotometer (model number: CB-AAS-3510; wavelength range: 190–900 nm) was employed. The elements present were first created as a liquid solution and then vaporized or atomized by employing a flame burner to evaporate each element present in a sample, resulting in each element having its unique absorbance between 190 and 900 nm light emitted from the source [24].


### 2.9. Methyl Orange Adsorption Experiment

The first stage in the methyl orange adsorption experiment was to create a standard curve. The absorbance of methyl orange was measured using UV-visible spectroscopy, and five distinct concentrations of methyl orange were 1 × 10−5 M, 2 × 10−5 M, 3 × 10−5 M, 4 × 10−5 M, and 5 × 10−5 M solution. The concentration versus adsorption standard curve is then shown. Methyl orange adsorptions were carried out in a magnetic stirrer at room temperature, with 25 ml of methyl solution, methyl orange supplied to a 50 ml beaker with an initial concentration of different concentrations that was previously prepared. The amount of adsorbent used was 0.1 g. It was swirled in a magnetic stirrer at 250 rpm for 4 hours. For 10 minutes, the solution was centrifuged in a centrifuge machine. UV-visible spectroscopy at 460 nm was used to assess the absorbance capacity of the centrifuged solution. The standard curve was used to calculate the residual concentration of methyl orange [25]. Equation (6) was used to compute the % elimination of methyl orange:(6)R%=Co−CtCo,where R (%) denotes the proportion of removal percent and the starting concentration of methyl orange is denoted by Co, while the concentration of methyl orange after adsorption is denoted by Ct.


### 2.10. Experimental Design

Design of Expert (v.11) software was used to assess the response surface approach to evaluate the experimental impacts. The response surface methodology is the most effective strategy for optimizing the process variable. It was utilized to determine which factor had the most impact on silica yields. This allows determining which factors have a major impact on the yield. To resolve such problems, the response surface technique (CCD) was used to determine linear interaction and quadratic connections between independent and dependent variables during silica optimization. The CCD creates 5-level (different points), 4-factor (independent variable), and 30 data points, including 16-factorial points, 8-axial points, and 6 points as a center, based on the following equation:(7)N=2n+2n+nc,where N is the number of experiments performed, n is the number of independent variables, and nc is the number of repetitions used to determine whether the preceding experiment was accurate or not.(8)Y=bo+∑i=1nbixi+∑i=1nbiixi2+∑i=1n−1∑j=i+1nbijxij,where Y denotes the anticipated silica yield reaction. The value n denotes the number of independent variables utilized in silica optimization. Constant coefficients, first-order (linear) coefficients, second-order (quadratic) interaction coefficients, and second-order (quadratic) noninteraction coefficients are represented by the coefficients bo, bi, bii, and bij.


## 2.1. Raw Materials and Chemicals Used

Brown teff straw (Eragrostis tef) was agricultural waste gathered from farmers at the time of harvest and crop maturity. Muffle furnace (model number L31M), sieve analysis, beaker, hot plate, the crucible, flask, balance, pH meter (model number pH−9202), oven dryer (model number DHG-9203A), plastic bag, grinder machine, electronic beam balance, mortar, and filter cloth were used for testing. FTIR (Make and Model: PerkinElmer spectrum 2, 8300–350 cm−1) was used for functional group analysis, XRD (Make and Model: Drawell XRD 7000) for crystalline index determination, and UV-light spectra (Make and Model: PerkinElmer Lambda 25) for methyl orange concentration determination.At the time of the experiment, substances such as sodium hydroxide (solid crystal), hydrochloric acid (36.46%), and distilled water (conductivity 0.6 mho/cm) were used in the synthesis of silica, while methyl orange was used to measure the efficacy of silica adsorption. KBr (solid) was utilized to prepare pellets for FTIR examination.


## 2.2. Methods

### 2.2.1. Sample Collection

Teff is farmed in most regions of Ethiopia; therefore, teff straw is readily available across the country [18]. Brown teff straw was gathered in Yebu, Jimma, Ethiopia, and sent to JIT, the School of Chemical Engineering laboratory, and the Faculty of Material Science and Engineering laboratory.


### 2.2.2. Raw Material Analysis

(1) Moisture Content of Teff Straw. Equation (1) was used to calculate the moisture content of raw teff straw. The amount of raw teff straw kept below 2 mm weighed 5 g. The prepared teff straw was dried in an oven at 105°C until it became a consistent mass. The experiment was carried out three times.(1)MCTS=WBD−WADWBD×100%,where MCTS denotes the moisture content of raw teff straw, WBD denotes the weight of the teff straw in its natural condition, and WAD is the weight of the oven-dried sample.(2) Determination of Ash Content. The ash content was calculated using the L31M muffle furnace (Model 1507074). A 3 g sample of teff straw is placed in a preweighted crucible and burned at 1000°C in a muffle furnace until the full ashing process is accomplished. The crucible is then placed in a desiccator to cool. Three replicates were created, and the mass was measured using a mass balance. The ash content was determined using the following equation:(2)ACTS=WCSAD−WCWCSBD−WC×100%,where WC stands for the weight of the crucible, WCSBD stands for the weight of the crucible + sample before thermal decomposition, and WCSAD stands for the weight of the crucible + sample after thermal decomposition.


### 2.2.3. Sample Preparation

Teff straw is a biomass of teff; it may include a variety of contaminants. The sample has to be processed to improve the extraction rate and purity of biosilica in the downstream procedures.(1) Cleaning, Soaking, and Washing. The sample was physically sorted by hand to remove large impurities such as nonteff straw, grasses, sand, leaves, and soil. The teff straw was then soaked overnight in tap water. The next day, the soaked teff straw was washed three times to eliminate soluble contaminants using distilled water generated in material engineering facilities using reverse osmosis.(2) Drying, Grinding, and Sieving. The washed teff straw was sun-dried for 2 days to remove the moisture absorbed for ease of grinding. The next process was grinding the dried teff straw using a grinding machine and sieved by sieve analysis with 2.0 to 1.0 mm mesh openings, and the particle sizes were below 2 mm and greater than 1 mm. The sample was grounded for ease of thermal treatment and maximum biosilica recovery.


## 2.2.1. Sample Collection

Teff is farmed in most regions of Ethiopia; therefore, teff straw is readily available across the country [18]. Brown teff straw was gathered in Yebu, Jimma, Ethiopia, and sent to JIT, the School of Chemical Engineering laboratory, and the Faculty of Material Science and Engineering laboratory.


## 2.2.2. Raw Material Analysis

(1) Moisture Content of Teff Straw. Equation (1) was used to calculate the moisture content of raw teff straw. The amount of raw teff straw kept below 2 mm weighed 5 g. The prepared teff straw was dried in an oven at 105°C until it became a consistent mass. The experiment was carried out three times.(1)MCTS=WBD−WADWBD×100%,where MCTS denotes the moisture content of raw teff straw, WBD denotes the weight of the teff straw in its natural condition, and WAD is the weight of the oven-dried sample.(2) Determination of Ash Content. The ash content was calculated using the L31M muffle furnace (Model 1507074). A 3 g sample of teff straw is placed in a preweighted crucible and burned at 1000°C in a muffle furnace until the full ashing process is accomplished. The crucible is then placed in a desiccator to cool. Three replicates were created, and the mass was measured using a mass balance. The ash content was determined using the following equation:(2)ACTS=WCSAD−WCWCSBD−WC×100%,where WC stands for the weight of the crucible, WCSBD stands for the weight of the crucible + sample before thermal decomposition, and WCSAD stands for the weight of the crucible + sample after thermal decomposition.


## 2.2.3. Sample Preparation

Teff straw is a biomass of teff; it may include a variety of contaminants. The sample has to be processed to improve the extraction rate and purity of biosilica in the downstream procedures.(1) Cleaning, Soaking, and Washing. The sample was physically sorted by hand to remove large impurities such as nonteff straw, grasses, sand, leaves, and soil. The teff straw was then soaked overnight in tap water. The next day, the soaked teff straw was washed three times to eliminate soluble contaminants using distilled water generated in material engineering facilities using reverse osmosis.(2) Drying, Grinding, and Sieving. The washed teff straw was sun-dried for 2 days to remove the moisture absorbed for ease of grinding. The next process was grinding the dried teff straw using a grinding machine and sieved by sieve analysis with 2.0 to 1.0 mm mesh openings, and the particle sizes were below 2 mm and greater than 1 mm. The sample was grounded for ease of thermal treatment and maximum biosilica recovery.


## 2.3. Acid Leaching

Raw materials were dried in the sun, and then acid was used to leach the teff straw. Impurities in teff straw include metals such as sodium, calcium, potassium, magnesium, aluminum, iron, and others [19]. These metals can either deposit in the cell or bind to lignin or hemicellulose. Acid leaching is necessary to eliminate such metals. The elimination of trace metals improves the surface area of the straw [19]. In addition, chemical activation of carbonaceous material occurs as a result of the removal of ionic bound metals from lignin or hemicellulose. In the high-temperature ashing process, this aids in the removal of both organic and carbonaceous materials. Overall, if not avoided early on, these contaminants may have an impact on the final product’s (silica gel) key characteristics such as porosity, color, and specific surface area. The pulverized teff straw was treated with HCl of 2.5 N (analytical grade of 36.46%). The solid sample to liquid solvent mixing ratio is one to ten weights by volume (1 : 10 w/v). The 60 g of teff straw was measured using a digital mass balance and placed in a 1000 ml beaker, to which 600 ml of HCl solution was added. The prepared solution was heated for 1 hour at 80°C using a hot plate and agitated at 550 rpm with an agitator. The trace metals were soluble in the HCl solution that had been produced. The method used was a batch stirred lab-sized beaker agitated with coaxial impellers. The agitator’s primary duty was to replenish the teff straw with any remaining solvent. The volume of the HCl solution was sufficient to provide a high surface area per unit volume. Because the teff straw could settle during the process, vigorous stirring (600 rpm) was required to prevent this. Finally, the HCl used in the experiments was neutralized with NaOH before it was discharged into the environment.


## 2.4. Cooling, Filtering, Washing, and Drying

The leached solution was allowed to spontaneously cool to room temperature. The acid-leached teff straw was then separated from the wastewater using a filter cloth. The filtered substance was then washed with water until the pH of the water reached neutral. The washed sample was dried in an oven set to 105°C for 24 hours.


## 2.5. Teff Straw Ash Preparation

The pretreated teff straw was put in ten crucibles and heated in an L31M muffle furnace. The temperature was set to 750°C, and the calcination time was set to 2 hours. Thermal decomposition was applied to the sample. The chosen temperature and duration are sufficient for achieving a consistent mass of samples while also producing amorphous biosilica. After calcination, the crucibles were put in a desiccator with a tong for cooling and ambient temperature absorption. The ash was then put in an airtight plastic bag. The goal of this phase is to raise the relative proportion of silicon oxide in the samples by reducing the carbonaceous elements present, as well as burn out any unwanted components discovered by chemical analysis.


## 2.6. Biosilica Extraction

Several NaOH concentration solutions were generated before commencing the extraction operation using equation (3). The molarity of the NaOH solution was calculated using the formula below. The calculated mass was then dissolved in 1 liter of distilled water in a conical flask, which was swirled with a stirring rod until the pellets were completely dissolved.(3)molarity=mass of NaOHmolar mass of NaOH×volume of solution.The amorphous silica was extracted by leaching it in NaOH extraction solution with concentrations of 1 M to 3 M with 0.5 M intervals.A 10 g of teff straw ash was put into a beaker, followed by a NaOH solution. The beaker was put on a heated plate, and then the extraction temperatures were 80°C to 100°C (5°C interval), respectively, while the extraction times were 55, 70, 85, 100, and 115 minutes. The rotating speed may be changed to 350 rpm, 400 rpm, 450 rpm, 500 rpm, or 550 rpm. After extraction, the mixture was allowed to cool naturally to room temperature. The combination was then filtered using filter paper, and the residual cake was washed with hot distilled water to maximize biosilica recovery. The liquid portion was collected in a beaker, while the remainder was discarded. Then the reaction was shown below in reaction one:(4)4NaOH+2nSiO2ash⟶2H2O+2Na2O⋅nSiO2R1


## 2.7. Biosilica Gel Preparation

The pH of the sodium silicate solution was titrated by adding 2.5 N HCl solution drop by drop with vigorous swirling until it reached 10. The biosilica begins to precipitate when the pH reaches 10. The precipitated biosilica solution was then heated on a hot plate for 1 hour at 80°C and vigorously stirred with a 600 rpm agitator. To encourage gel formation, the precipitated biosilica solution was allowed to cool to ambient temperature before the gel was aged for 20 hours intact. The gel was then filtered and rinsed five times to eliminate any soluble salts. Finally, the produced biosilica gel was oven-dried at 60°C for 24 hours, and the sample was kept in a polyethylene bag before being utilized for characterization. The reaction for biosilica gel formation is shown in reaction 2 (5). The silica particles were substantially dispersed at this stage, and the collision of silica monomers initiated the agglomeration of massive silica precipitators.(5)4HCl+2Na2O⋅nSiO2⟶4NaCl+2H2O+2nSiO2SR2


## 2.8. Characterization of Teff Straw Ash and Biosilica

### 2.8.1. FTIR Analysis

FTIR (make and model: PerkinElmer spectrum 2; wavenumber range 8300–350 cm−1) was used to identify the functional groups contained in teff straw ash and biosilica. To identify the functional groups, pellets were prepared using KBr. In this work, the functional group was studied within a wavenumber range of 4500–400 cm−1, and the functional group peak was assessed utilizing origin software [20].


### 2.8.2. XRD Analysis

According to Mi et al. [21], X-ray diffraction was utilized to determine the crystalline and amorous phases of generated teff straw ash, as well as biosilica created from teff straw ash. During this investigation, the angle of diffraction (2-theta) on an XRD (make and model: Drawell XRD 7000) fluctuated from 5° to 80°. The crystalline peak was divided by the overall peak to calculate the crystallinity index (both crystallinity index and amorphous peak).


### 2.8.3. Morphological Analysis

The morphological changes that occurred when teff straw ash was transformed to biosilica were studied using a scanning electron microscope (SEM). As a result, the size of the created biosilica was determined using the “ImageJ” software [22].


### 2.8.4. UV-Spectrophotometer Analysis

According to El Maguana et al., the UV-spectrophotometer (PerkinElmer Lambda 25; wavenumber range 190–1100) helps to measure the concentration of methyl orange dye solution. The UV-spectrophotometer emits light, which is absorbed by the methyl orange. Their absorbance varied with concentration, which aids in determining the ultimate concentration of methyl orange for this study using the Beer–Lambert equation [23].


### 2.8.5. Atomic Adsorption Spectrophotometer Analysis

To determine the components contained in teff straw ash, an atomic absorption spectrophotometer (model number: CB-AAS-3510; wavelength range: 190–900 nm) was employed. The elements present were first created as a liquid solution and then vaporized or atomized by employing a flame burner to evaporate each element present in a sample, resulting in each element having its unique absorbance between 190 and 900 nm light emitted from the source [24].


## 2.8.1. FTIR Analysis

FTIR (make and model: PerkinElmer spectrum 2; wavenumber range 8300–350 cm−1) was used to identify the functional groups contained in teff straw ash and biosilica. To identify the functional groups, pellets were prepared using KBr. In this work, the functional group was studied within a wavenumber range of 4500–400 cm−1, and the functional group peak was assessed utilizing origin software [20].


## 2.8.2. XRD Analysis

According to Mi et al. [21], X-ray diffraction was utilized to determine the crystalline and amorous phases of generated teff straw ash, as well as biosilica created from teff straw ash. During this investigation, the angle of diffraction (2-theta) on an XRD (make and model: Drawell XRD 7000) fluctuated from 5° to 80°. The crystalline peak was divided by the overall peak to calculate the crystallinity index (both crystallinity index and amorphous peak).


## 2.8.3. Morphological Analysis

The morphological changes that occurred when teff straw ash was transformed to biosilica were studied using a scanning electron microscope (SEM). As a result, the size of the created biosilica was determined using the “ImageJ” software [22].


## 2.8.4. UV-Spectrophotometer Analysis

According to El Maguana et al., the UV-spectrophotometer (PerkinElmer Lambda 25; wavenumber range 190–1100) helps to measure the concentration of methyl orange dye solution. The UV-spectrophotometer emits light, which is absorbed by the methyl orange. Their absorbance varied with concentration, which aids in determining the ultimate concentration of methyl orange for this study using the Beer–Lambert equation [23].


## 2.8.5. Atomic Adsorption Spectrophotometer Analysis

To determine the components contained in teff straw ash, an atomic absorption spectrophotometer (model number: CB-AAS-3510; wavelength range: 190–900 nm) was employed. The elements present were first created as a liquid solution and then vaporized or atomized by employing a flame burner to evaporate each element present in a sample, resulting in each element having its unique absorbance between 190 and 900 nm light emitted from the source [24].


## 2.9. Methyl Orange Adsorption Experiment

The first stage in the methyl orange adsorption experiment was to create a standard curve. The absorbance of methyl orange was measured using UV-visible spectroscopy, and five distinct concentrations of methyl orange were 1 × 10−5 M, 2 × 10−5 M, 3 × 10−5 M, 4 × 10−5 M, and 5 × 10−5 M solution. The concentration versus adsorption standard curve is then shown. Methyl orange adsorptions were carried out in a magnetic stirrer at room temperature, with 25 ml of methyl solution, methyl orange supplied to a 50 ml beaker with an initial concentration of different concentrations that was previously prepared. The amount of adsorbent used was 0.1 g. It was swirled in a magnetic stirrer at 250 rpm for 4 hours. For 10 minutes, the solution was centrifuged in a centrifuge machine. UV-visible spectroscopy at 460 nm was used to assess the absorbance capacity of the centrifuged solution. The standard curve was used to calculate the residual concentration of methyl orange [25]. Equation (6) was used to compute the % elimination of methyl orange:(6)R%=Co−CtCo,where R (%) denotes the proportion of removal percent and the starting concentration of methyl orange is denoted by Co, while the concentration of methyl orange after adsorption is denoted by Ct.


## 2.10. Experimental Design

Design of Expert (v.11) software was used to assess the response surface approach to evaluate the experimental impacts. The response surface methodology is the most effective strategy for optimizing the process variable. It was utilized to determine which factor had the most impact on silica yields. This allows determining which factors have a major impact on the yield. To resolve such problems, the response surface technique (CCD) was used to determine linear interaction and quadratic connections between independent and dependent variables during silica optimization. The CCD creates 5-level (different points), 4-factor (independent variable), and 30 data points, including 16-factorial points, 8-axial points, and 6 points as a center, based on the following equation:(7)N=2n+2n+nc,where N is the number of experiments performed, n is the number of independent variables, and nc is the number of repetitions used to determine whether the preceding experiment was accurate or not.(8)Y=bo+∑i=1nbixi+∑i=1nbiixi2+∑i=1n−1∑j=i+1nbijxij,where Y denotes the anticipated silica yield reaction. The value n denotes the number of independent variables utilized in silica optimization. Constant coefficients, first-order (linear) coefficients, second-order (quadratic) interaction coefficients, and second-order (quadratic) noninteraction coefficients are represented by the coefficients bo, bi, bii, and bij.


## 3. Results and Discussions

### 3.1. Raw Material Characterization

#### 3.1.1. Teff Straw Moisture Content

The moisture of the teff straw was tested as soon as it was received and calculated using equation (1). The experiment was carried out three times, and the results are shown in Table 1. The starting mass of the teff straw was 10 g, and it was dried in an oven until it reached a consistent mass. To assess the moisture content, four trials were performed with a 10 g quantity of teff straw. The results are virtually identical, 9.34 g, 9.42 g, 9.4 g, and 9.49 g, indicating a moisture content of about 7.5% on average. According to Amibo et al. [26], the average moisture content of raw teff straw was 7.5%. The moisture level of the teff straw was identical to the works of the literature reviewed, and the teff straw includes a small amount of moisture, which provides a significant benefit in the ashing process.Table 1
Chemical composition of TSA.
Chemical component present in TSAComposition in percentSiO292.89LOI2.45CaO1.67H2O1.34MgO0.82P2O50.29Fe2O30.23K2O0.19Al2O3, Na2O, MnO, and TiO2<0.01


### 3.2. Reaction Mechanism

The procedure continues with several reactions after the production of teff straw ash. Because sodium silicate, also known as water glass, is the precursor for the sol-gel process, the step after heat breakdown was the synthesis of sodium silicate solution [27]. The process continues with the reactions of recovery, hydrolysis, and condensation. When teff straw ash interacted with sodium hydroxide, the reaction was known as the recovery stage. The silica in the ash reacts with sodium hydroxide in this process, producing sodium silicate and water as shown in reaction 3 (9). Titration of sodium silicate with hydrochloric acid to create a silica group and sodium chloride was the second step. Finally, the silica precipitated, and the condensation reaction was the final stage following washing as shown in the following reaction(9)SiO2+2NaOH⟶Na2SiO3+H2OR3


### 3.3. Characterization of the TSA and Extracted Silica

#### 3.3.1. Chemical Content Analysis of the Teff Straw Ash

Table1 shows the major and minor oxides of the teff straw ash sample. The major component of the ash sample, according to the atomic absorption spectrophotometer data, was SiO2. It makes up around 93% of the overall content of teff straw ash. A small amount of Fe2O3, CaO, K2O, P2O5, H2O, and traces of Al2O3, Na2O, TiO2, and MgO was also found. The term LOI refers to the amount of energy lost during the process of determining the percentage composition of silica. The element concentrations were determined using an atomic absorption spectrophotometer, whereas the oxide concentrations were evaluated using Calibration-free laser-induced breakdown spectroscopy (CF-LIBS). This approach identified CaO, MgO, FeO, Fe2O3, K2O, Al2O3, TiO2, H2O, SiO2, Na2O, Cr2O3, and P2O5 [28].According to Setiawan and Chiang [8], the crops included a high concentration of silicon ash compounds. The teff straw ash is chemically constituted of a high amount of silicon compounds. Based on this, the silica content of brown teff straw was 92.89% at 750°C ashing temperature and 2-hour ashing duration. The amount of silicon ash obtained as a result of soil chemistry, biomass nature, and climatic conditions changes the content of the biomass. As a result, the teff straw ash’s composition varied. CaO, H2O, MgO, P2O5, Fe2O3, and K2O are also present in trace amounts in proportions of 1.67, 1.34, 0.82, 0.29, 0.23, and 0.19, respectively.


#### 3.3.2. FTIR, XRD, and SEM Analysis of Biosilica Nanoparticles

The important functional groups that are found in the silica are analyzed using FTIR and are presented in Figure1. A sharp peak is usually seen in the range between 3100 and 3800 cm−1 if the synthesized silica contains H2O [29]. This occurred because the prepared silica had been dried in the oven before the analysis. Therefore, the biosilica contains a small O-H group. The lower peak (2900 cm−1) in Figure 1 signposted the existence of a weak O-H group. In the region between 1850 and 3100 cm−1, there are no strong peaks apart from a very little peek at 2630 cm−1. This indicated the absenteeism of the Si-C vibrational functional group. This approves that there is no substantial organic compound in the synthesized material, and this shows that the extraction and combustion process has been done in a controlled manner. A strong Si-O-Si asymmetric band stretching functional group was found in the region of the 1050–1230 cm−1 range. The moderate concentrated sharp peak in the region of 700–800 cm−1 indicated a strong Si-O bending with a vibrational functional group. The small peak at 420 indicates the existence of a halo compound that has a strong C-I vibration. From Figures 1(a) and 1(b), teff straw ash (TSA) and teff straw-based silica nanoparticle (TSAS) were shown, additional peaks were available on silica nanoparticles, and these additional fictional groups increase the adsorption efficiency of silica nanoparticles at a lower concentration. The FTIR analysis was similar to that of previous studies reported by Peerzada and Chidambaram [30] and Bathla et al. [31].Figure 1
FTIR spectra of (a) biosilica nanoparticle from teff straw and (b) teff straw ash.The XRD patterns of the prepared biosilica nanoparticles from teff straw are presented in Figure2, revealing that the afghanite is the predominate peak at 2 thetas = 21.0848°. The broad angled peak around 2 thetas of 21.9° designates the characteristics future of amorphous silica, and it also validates that the arrangement of this silica coordination is tetrahedral. Other peaks apart from afghanite were found such as cordierite, tanteuxenite, and Na2SO4.7H2O. From Figures 2(a) and 2(b), the XRD images for TSA and TSAS are somewhat similar; however, in TSA, their crystalline peaks are around 29 and 30°; this is due to some metal oxides present within teff straw ash, but this teff straw ash was removed from the silica nanoparticles; due to this, the crystalline peak was removed. The current XRD analysis was similar to that of the study reports conducted by Hsieh et al. [32], Patel et al. [33], and Franco et al. [34].Figure 2
XRD spectra of (a) biosilica nanoparticle from teff straw and (b) teff straw ash.The SEM image of silica is given in Figure3. As it is elucidated, the calcination temperature increases the agglomeration of the particle and also shows the high porosity of the particle. Using software called “ImageJ,” the average particle size was found to be 167 nm. The SEM pictures of unaltered silica nanoparticles in their dry condition revealed that they were essentially monodisperse with spherical shape and a narrow particle size range.Figure 3
SEM image of a biosilica nanoparticle.


### 3.4. Silica Yield Obtained from Teff Straw Ash

As mentioned in the technique to identify the optimal operating process variables of pure silica as maximum, the yielding mass must be weighed after the final drying process for each run. The mass percentage yield is shown in Table2. The highest yield was 85.85%, while the lowest was 59.38%. The biosilica yield calculation was carried out to determine the optimal values of experimental variables such as (NaOH concentration, extraction duration, number of rotations, and extraction temperature) as well as investigate the influence of each variable. For the production of biosilica, 10 g of ash was utilized. As a result, the biosilica yield was calculated by using equation (10), and this helps to determine the SiO2 yield derived from teff straw ash:(10)Y%=mSiO2mTSA×100%,where Y (%) is the yield of silica obtained after extraction, mSiO2 is the mass of silica finally obtained, and mTSA is the weight of total teff ash obtained.Table 2
Experimental results of silica yield runs.
RunCoded variableIndependent variableDependent variableABCDTem. (°C)NaOH (M)RPMTime (min)Yield of silica (%)Density of silica (g.cm−3)1000−α9024505561.621.3220α009034508571.221.333−1−1−1−1851.54007059.381.41411−1−1952.54007068.511.22500009024508568.121.406−1−11−1851.55007068.161.33700009024508570.121.368α00010024508578.261.37900−α09023508562.941.2210111−1952.55007066.511.2811−1−1−11851.540010062.711.261211−11952.540010069.891.2913−1111852.550010073.221.3414−1−111851.550010076.211.391500009024508568.511.281600009024508568.481.24171−111951.550010085.851.40181−11−1951.55007078.651.391900009024508568.491.2620−11−11852.540010066.671.2421000α90245011571.321.3622−101−1852.55007066.111.242300009024508568.461.26241111952.550010073.181.37251−1−1−1951.54007073.451.35260−α009014508579.781.3727−α0008024508564.501.242800α09025508574.791.36291−1−11951.540010075.911.3730−11−1−1852.54007064.111.26


### 3.5. Experimental Design Values

#### 3.5.1. Statistical Analysis for the Yield of Biosilica

This experimental design of the response surface methodology allows improving the process parameters for more than two levels by minimizing an experimental error, resulting in higher experimental accuracy [35]. To get all interaction effects, single effects, 3D diagram, and model equation, the response surface technique and experimental designs of central composite design were employed. To avoid systematic error, the trials were carried out in random order. Analysis of variance was used to determine the significance of the finding (ANOVA). The coded variable is listed in terms of the decoded variable, A stands for temperature, B stands for NaOH concentration, C stands for rotational speed, and D stands for time for silica extraction. The results obtained from the laboratory experiment are shown in Table 2. The results were obtained by using a combination of decoded variables. The coded variable is a variable that is assigned in a symbol, and the decoded variable is a variable that has a full name [36]. The four independent factors, namely, temperature, NaOH concentration, rotational speed, and extraction time, were used to determine the dependent variable yield and density of the basilica.


### 3.6. ANOVA for Quadratic Model

These values obtained were analyzed by using analysis of variance (ANOVA). The experimental results were analyzed by using the level of significance (α value) at 5%. In Table 3, the F-value and p value for the models are listed. The p value helps to determine the significance and insignificance of all single factors as well as the interaction effects of each factor [37, 38]. For this study, the quadratic model is suggested; as shown in Table 3, the p values for the effects of coded variables like A, B, C, D, AB, AC, AD, BC, BD, CD, A2, B2, C2, and D2 were used as a tool to check the significance of each of the variables, which in turn are necessary to understand the pattern of the mutual interactions between the test variables. The p-values for each coded variable for A, B, C, D, AB, AC, BD, CD, A2, B2, and D2 were less than 0.0001; this shows that the single factor and the interaction effects had a significant effect on the yield of silica. However, the p values for the interaction effects of AD, BD, and C2 were 0.0697, 0.0712, and 0.6364, which are greater than 0.05, indicating that the interaction effects have no significant effect on the yield of silica. In this case, the four factors such as NaOH concentration, extraction time, rotational speed, and extraction temperature had significant effects on the yield of the biosilica.Table 3
ANOVA of fitted model for the yield of biosilica.
SourceSum of squaresdfMean squareF-valuep valueModel1026.121473.29401.21<0.0001SignificantA-temperature286.351286.351567.45<0.0001B-NaOH101.021101.02553.00<0.0001C-RPM209.811209.811148.45<0.0001D-time140.941140.94771.50<0.0001AB97.12197.12531.63<0.0001AC12.96112.9670.94<0.0001AD0.697210.69723.820.0697BC47.54147.54260.23<0.0001BD0.688910.68893.770.0712CD23.28123.28127.44<0.0001A212.24112.2467.02<0.0001B279.09179.09432.95<0.0001C20.042510.04250.2328<0.0001D28.5818.5846.98<0.0001Residual2.74150.1827Lack of fit0.1779100.01780.03471.0000Not significantFrom Table3, the model analyzed by using central composite design was highly significant, and this indicates that the regression of data fitting between experimental results and predicted values was in good agreement. From Table 4, fit statistics data results of standard deviation, mean, CV (%), R2, adjusted R2, predicted R2, and Adeq. precision were obtained. The results obtained for a standard deviation and coefficient of variation obtained for the yield of biosilica were 0.4274 and 0.6091. According to Amibo [39], the standard deviation and coefficients of variation were very low, and the data were accepted with less variation between the experimental results. For this study, the CV and standard deviation were low and acceptable with good agreement. According to El Ouadrhiri et al. [40], the adjusted R2 and predicted R2 were in good agreement below a 20% variance. The results of the modified R2 and the expected R2 were in the percentage of deviation given above. R2 is the approached one, and the experimental results and predicted values had a good fitting [10, 41–43]. For this analysis, the findings were approached to 1; therefore, the data had good fitting and were highly acceptable.Table 4
Modified ANOVA of the fitted model for the yield of biosilica.
Std. dev.MeanCV (%)R2AdjustedR2PredictedR2Adeq. precision0.427470.170.60910.99730.99490.995487.5439


#### 3.6.1. The Actual and Predicted Value of an Independent Variable

Figures4(a) and 4(b) show the actual value and the expected value of each dependent variable (response) obtained. The actual and expected pulp yield values are shown in Figures 4(a) and 4(b). Actual and expected values are strongly aligned with each other in Figures 4(a) and 4(b), with an R2 value of 0.9973. The regression model equation (11) provides a very accurate description of the experimental data, in which all points are very close to the line of a perfect fit. This result indicates that it was successful in capturing the correlation between the silica production process variables to the silica yield. The adequacy of the model was further checked with the analysis of variance (ANOVA) as shown in Tables 3–5. Based on a 95% confidence level, F-value is a test for comparing model variance with residual (error) variance. If the variances are close to the same, the ratio was close to one, and any of the factors likely have a significant effect on the response with the p value less than 0.05. It was calculated by a model mean square divided by the residual mean square. From Table 3, the model F-value was 401.21, implying that the model was significant relative to the noise.Figure 4
(a) Predicted versus actual yield of silica. (b) Normal plot of residuals.
(a)(b)Table 5
Coefficients in terms of coded factors.
FactorCoefficient estimatedfStandard error95% CI low95% CI highVIFIntercept68.6910.174568.3269.07A-temperature3.4510.08723.273.641.0000B-NaOH concentration−2.0510.0872−2.24−1.871.0000C-RPM2.9610.08722.773.141.0000D-time2.4210.08722.242.611.0000AB−2.4610.1069−2.69−2.241.0000AC−0.900010.1069−1.13−0.67221.0000AD−0.208710.1069−0.43650.01901.0000BC−1.7210.1069−1.95−1.501.0000BD−0.207510.1069−0.43530.02031.0000CD1.2110.10690.97851.431.0000A20.668110.08160.49420.84211.05B21.7010.08161.521.871.05C20.039410.0816−0.13460.21331.05D2−0.559410.0816−0.7333−0.38541.05(11)Y%=68.69+3.45A−2.05B+2.96C+2.42D−2.46AB−0.9000AC−1.72BC+1.21CD+0.6681A2+1.70B2−0.5594D2.


### 3.7. The Effects of Single Factor on Biosilica Production

Temperature is the most important element influencing the extraction and entire manufacturing process of biosilica [44]. The influence of temperature on silica production varies depending on the experiment. To conduct the trials for this investigation, five data points were used: 80°C, 85°C, 90°C, 95°C, and 100°C. The temperature has a major influence on biosilica formation, according to numerous studies. When the temperature was below 80°C, the production of biosilica was minimal. This was owing to the fact that there was no effective collision between sodium and silicon present in teff straw ash. Then, when the temperature rises, there is an effective collision of molecules during the process. As a result, when the temperature rises between 80 and 100°C, the production of biosilica rises. For this study, the NaOH solution was adjusted at five different data points, and this was 1 M, 1.5 M, 2.0 M, 2.5 M, and 3 M. In these experiments, the amount of silica gel was highly dependent on.


### 3.8. Optimization of Biosilica Yield

The 3D response surface plot was displayed in Figures5(a)–5(f). According to Figure 5, the optimal yield varied from 59.38 to 85.85%. The minimum yield of 59.38% was achieved at 85°C, 1.5 M NaOH concentration, 400 rpm rotating speed, and 70 minute extraction time. The highest yield biosilica of 85.85% was achieved at 95°C, 1.5 M NaOH concentration, 500 rpm rotating speed, and 100 minute extraction period.Figure 5
3D interactive surface plot for biosilica yield: (a) NaOH and temperature, (b) rpm and temperature, (c) time and temperature, (d) NaOH and rpm, (e) NaOH and time, and (f) time and rpm.
(a)(b)(c)(d)(e)(f)


### 3.9. Numerical and Graphical Optimization

According to Table6, the numerical optimization was carried out by adjusting the all-process factors in the range of temperature, NaOH concentration, speed of rotation, and extraction time. However, the yield of silica was adjusted at optimum points. From Table 7, the optimized results for all process variables such as temperature, NaOH concentration, speed of rotation, and extraction time were 94.99°C (≈95°C), 1.5 M, 499.56 rpm (500 rpm), and 99.99 (100 minutes), respectively. For these process variables, the optimum yields obtained were 85.85, and the desirability for all process variables such as temperature, NaOH concentration, speed of rotation, and extraction time was one. In addition to this, desirability for yield biosilica was also one, and the combined desirability for all was one and good. Based on the optimization, the experiments were conducted at this point three times, and the obtained result was similar to the optimization results. These experiments help to explore the optimum conditions for the maximum of silica produced from teff straw; the concentration of sodium hydroxide solution varied systematically. As shown in Figure 5, the concentration varied from 1 M to 3 M. The optimal concentration of sodium hydroxide for producing biosilica was 1.5 M. If the NaOH concentration is less than 1.5 M, the teff straw ash generated does not dissolve completely in the solution. In other words, there was a sodium ion restriction when preparing sodium silicate solution (2Na2.nSiO2). However, when the concentration of sodium hydroxide is raised to 1.5 M, the extracted amount of biosilica increases significantly. However, as the concentration of sodium hydroxide exceeds 1.5 M, the extracted amount of silica falls substantially. This was attributed to the development of viscous sodium silicate solution when the concentration of NaOH increased from 1.5 M to 3 M solution. During titration, extra NaCl and OH− are produced in the solution. By neutralizing the charge of silicate oligomers and micelles, increasing the molar concentration of NaCl above that of silicate causes an increase in solution viscosity. This increase in solution viscosity appears to limit molecule dispersion and prevent silicate oligomer’s contact, preventing polymerization during the gelification process.Table 6
Constraints.
NameGoalLower limitUpper limitImportanceA: temperatureIs in range85953B: [NaOH]Is in range1.52.53C: RPMIs in range4005003D: timeIs in range701003Yield of silicaMaximize59.3885.853Table 7
The optimum yield was obtained.
NumberTemperature[NaOH]RPMTimeYield of silicaDesirability194.9881.500499.57299.99085.8531.000SelectedThe minimum amount is determined by thepH of the sodium hydroxide solution. According to the authors of the early research, silica is only soluble in sodium hydroxide solutions with a pH greater than 10. Even though the pH of 0.5 M sodium hydroxide is 13.69 at ambient temperature, the pH of the solution drops as the temperature rises. As a result, the pH of 0.5 M NaOH solution drops to nearly 10, because the lowest temperature utilized in this investigation was 80°C. The maximum level is determined by the viscosity of the sodium silicate solution. The sodium silicate solution gets more viscous as the concentration of NaOH solution exceeds 1.5 M. The yield of silica decreases as the sodium silicate solution becomes more viscous.Another element influencing biosilica extraction is the rotational speed. The influence of rpm on biosilica production varies depending on the experiment. To perform the tests for this study, five data points were used: 350 rpm, 400 rpm, 450 rpm, 500 rpm, and 550 rpm. According to several studies, rpm has a substantial impact on biosilica formation. According to Joharwan [45], the teff straw ash was laid down to the lowest portions, and the yield of biosilica was minimal. Then, as revolutions per minute rise, there is an effective collision between molecules during the process. As a result, the rpm increases from 350 rpm to 550 rpm, and so does the production of biosilica. One of the major parameters that might impact the yield of biosilica production is the extraction time [1]. Time is an independent variable that helps to identify biosilica production and ranges from 55 minutes to 115 minutes. Five different times were used to conduct the experiments: 55, 70, 85, 100, and 115 minutes. Time has a major impact on biosilica yield, and when the extraction time was shorter than 50 minutes, the production rate was poor, implying that only a small amount of biosilica was produced. This was owing to insufficient time for teff straw ash solubility for biosilica extraction during titration. Extending the extraction time beyond 120 minutes may result in the production of additional side products or a reverse reaction. Because there was ample time to react the NaOH and teff straw ash to create sodium silicate solution (2Na2.nSiO2), the extraction period increased the yield of biosilica. Finally, at higher temperatures, higher NaOH concentrations, longer contact times, and faster rotational speeds, the yield obtained was not optimum. This was due to the formation of side products, the development of viscous sodium silicate solution, the formation of intermediate products, and the interaction effects of each factor, which resulted in the formation of minimum yields.


### 3.10. The Yield of Biosilica and Physicochemical Properties

In this study, the optimization was conducted, the obtained result ranged from 59.38% to 85.85%, and the raw material utilized for this study was teff straw. The purity and surface area measured with BET (Brunauer–Emmett–Teller) for nanosilica produced were 97.63% and 305 m2/g, respectively. The density of silica nanoparticles produced under this study ranged from 1.22 to 1.40 gcm−3. In the different studies, the biosilica nanomaterials were produced from rice husk, rice straw, and other agricultural wastes [33]. According to the prior findings of Selvakumar et al. [46], the silica produced had an 85% of yield, which was equivalent to the current findings, although the manufacturing techniques were considerably different. The rice husk was leached with HCl in this investigation, and the NaOH concentration employed varied from 0.1 to 1 mol/L (M), with an extraction duration of 2 hours. According to previous research by Mehta and Ugwekar [47], the silica generated from rice husk varied from 66.11 to 71.15% at 2 mol/L(M) NaOH concentration with a 2 hr extraction period using the HCl leaching procedure. Similarly, in a study reported by Steven et al. [44], the biosilica nanoparticle was produced from rice husk with a purity of 99.7% and a maximum yield of 98%. In this study, the combustion temperature for the ashing process was 700°C, and other variables such as NaOH and HCl were considered, with a surface area of 400.69 m2/g. Fernandes et al. [48] generated biosilica nanoparticles from rice husk with a purity of 99.61% and a surface area of 290.03 m2/g, which was equivalent to the current study surface area.


### 3.11. Methyl Orange Adsorption

The XRD and AAS analyses show that the prepared samples contain a high amount of silica. It is also seen in the FTIR analysis that the samples possess silica functionality. Because the silica functionality can interact with the polar groups of other pollutants through strong H-bonds and complex mechanisms, the prepared silica sample was tested for the adsorptive removal of methyl orange from an aqueous solution. The first step in the adsorption experiment was the preparation of a standard graph. The graph consists of methyl orange concentration versus its adsorption. The result is shown in Table8.Table 8
Adsorption of methyl orange at different concentration.
Before adsorptionAfter absorption% removalInitial conc.AbsorbanceFinal conc.Absorbance1 × 10−50.1916.86 × 10−60.17531.52 × 10−50.2215.81 × 10−60.17170.953 × 10−50.2635.29 × 10−60.16982.374 × 10−50.2995.03 × 10−60.16887.435 × 10−50.3434.76 × 10−60.16790.48From Figure6, the R2 value is 99.65%, which implies that 99% of the total variation in the adsorption is attributed to the experimental variables studied. The model equation is(12)y=0.0382x+0.1488,where y is the absorbance of methyl orange dye value and x is the concentration of methyl orange.Figure 6
Methyl orange dye concentrations versus adsorption.After the adsorption experiment was performed, the adsorption capacity of the treated methyl orange solution was measured using UV-visible spectroscopy, and the concentration of the residual methyl orange in the solution was calculated using the model equation (9). To know the removed percentage of methyl orange by the prepared silica, equation (8) was used. From Table 8, the average removal efficiency of methyl orange using the prepared silica was 90.40%. The teff straw ash silica adsorbs methyl orange because it is a porous material and has an active group that is Si-O-Si and Si-OH [49].


## 3.1. Raw Material Characterization

### 3.1.1. Teff Straw Moisture Content

The moisture of the teff straw was tested as soon as it was received and calculated using equation (1). The experiment was carried out three times, and the results are shown in Table 1. The starting mass of the teff straw was 10 g, and it was dried in an oven until it reached a consistent mass. To assess the moisture content, four trials were performed with a 10 g quantity of teff straw. The results are virtually identical, 9.34 g, 9.42 g, 9.4 g, and 9.49 g, indicating a moisture content of about 7.5% on average. According to Amibo et al. [26], the average moisture content of raw teff straw was 7.5%. The moisture level of the teff straw was identical to the works of the literature reviewed, and the teff straw includes a small amount of moisture, which provides a significant benefit in the ashing process.Table 1
Chemical composition of TSA.
Chemical component present in TSAComposition in percentSiO292.89LOI2.45CaO1.67H2O1.34MgO0.82P2O50.29Fe2O30.23K2O0.19Al2O3, Na2O, MnO, and TiO2<0.01


## 3.1.1. Teff Straw Moisture Content

The moisture of the teff straw was tested as soon as it was received and calculated using equation (1). The experiment was carried out three times, and the results are shown in Table 1. The starting mass of the teff straw was 10 g, and it was dried in an oven until it reached a consistent mass. To assess the moisture content, four trials were performed with a 10 g quantity of teff straw. The results are virtually identical, 9.34 g, 9.42 g, 9.4 g, and 9.49 g, indicating a moisture content of about 7.5% on average. According to Amibo et al. [26], the average moisture content of raw teff straw was 7.5%. The moisture level of the teff straw was identical to the works of the literature reviewed, and the teff straw includes a small amount of moisture, which provides a significant benefit in the ashing process.Table 1
Chemical composition of TSA.
Chemical component present in TSAComposition in percentSiO292.89LOI2.45CaO1.67H2O1.34MgO0.82P2O50.29Fe2O30.23K2O0.19Al2O3, Na2O, MnO, and TiO2<0.01


## 3.2. Reaction Mechanism

The procedure continues with several reactions after the production of teff straw ash. Because sodium silicate, also known as water glass, is the precursor for the sol-gel process, the step after heat breakdown was the synthesis of sodium silicate solution [27]. The process continues with the reactions of recovery, hydrolysis, and condensation. When teff straw ash interacted with sodium hydroxide, the reaction was known as the recovery stage. The silica in the ash reacts with sodium hydroxide in this process, producing sodium silicate and water as shown in reaction 3 (9). Titration of sodium silicate with hydrochloric acid to create a silica group and sodium chloride was the second step. Finally, the silica precipitated, and the condensation reaction was the final stage following washing as shown in the following reaction(9)SiO2+2NaOH⟶Na2SiO3+H2OR3


## 3.3. Characterization of the TSA and Extracted Silica

### 3.3.1. Chemical Content Analysis of the Teff Straw Ash

Table1 shows the major and minor oxides of the teff straw ash sample. The major component of the ash sample, according to the atomic absorption spectrophotometer data, was SiO2. It makes up around 93% of the overall content of teff straw ash. A small amount of Fe2O3, CaO, K2O, P2O5, H2O, and traces of Al2O3, Na2O, TiO2, and MgO was also found. The term LOI refers to the amount of energy lost during the process of determining the percentage composition of silica. The element concentrations were determined using an atomic absorption spectrophotometer, whereas the oxide concentrations were evaluated using Calibration-free laser-induced breakdown spectroscopy (CF-LIBS). This approach identified CaO, MgO, FeO, Fe2O3, K2O, Al2O3, TiO2, H2O, SiO2, Na2O, Cr2O3, and P2O5 [28].According to Setiawan and Chiang [8], the crops included a high concentration of silicon ash compounds. The teff straw ash is chemically constituted of a high amount of silicon compounds. Based on this, the silica content of brown teff straw was 92.89% at 750°C ashing temperature and 2-hour ashing duration. The amount of silicon ash obtained as a result of soil chemistry, biomass nature, and climatic conditions changes the content of the biomass. As a result, the teff straw ash’s composition varied. CaO, H2O, MgO, P2O5, Fe2O3, and K2O are also present in trace amounts in proportions of 1.67, 1.34, 0.82, 0.29, 0.23, and 0.19, respectively.


### 3.3.2. FTIR, XRD, and SEM Analysis of Biosilica Nanoparticles

The important functional groups that are found in the silica are analyzed using FTIR and are presented in Figure1. A sharp peak is usually seen in the range between 3100 and 3800 cm−1 if the synthesized silica contains H2O [29]. This occurred because the prepared silica had been dried in the oven before the analysis. Therefore, the biosilica contains a small O-H group. The lower peak (2900 cm−1) in Figure 1 signposted the existence of a weak O-H group. In the region between 1850 and 3100 cm−1, there are no strong peaks apart from a very little peek at 2630 cm−1. This indicated the absenteeism of the Si-C vibrational functional group. This approves that there is no substantial organic compound in the synthesized material, and this shows that the extraction and combustion process has been done in a controlled manner. A strong Si-O-Si asymmetric band stretching functional group was found in the region of the 1050–1230 cm−1 range. The moderate concentrated sharp peak in the region of 700–800 cm−1 indicated a strong Si-O bending with a vibrational functional group. The small peak at 420 indicates the existence of a halo compound that has a strong C-I vibration. From Figures 1(a) and 1(b), teff straw ash (TSA) and teff straw-based silica nanoparticle (TSAS) were shown, additional peaks were available on silica nanoparticles, and these additional fictional groups increase the adsorption efficiency of silica nanoparticles at a lower concentration. The FTIR analysis was similar to that of previous studies reported by Peerzada and Chidambaram [30] and Bathla et al. [31].Figure 1
FTIR spectra of (a) biosilica nanoparticle from teff straw and (b) teff straw ash.The XRD patterns of the prepared biosilica nanoparticles from teff straw are presented in Figure2, revealing that the afghanite is the predominate peak at 2 thetas = 21.0848°. The broad angled peak around 2 thetas of 21.9° designates the characteristics future of amorphous silica, and it also validates that the arrangement of this silica coordination is tetrahedral. Other peaks apart from afghanite were found such as cordierite, tanteuxenite, and Na2SO4.7H2O. From Figures 2(a) and 2(b), the XRD images for TSA and TSAS are somewhat similar; however, in TSA, their crystalline peaks are around 29 and 30°; this is due to some metal oxides present within teff straw ash, but this teff straw ash was removed from the silica nanoparticles; due to this, the crystalline peak was removed. The current XRD analysis was similar to that of the study reports conducted by Hsieh et al. [32], Patel et al. [33], and Franco et al. [34].Figure 2
XRD spectra of (a) biosilica nanoparticle from teff straw and (b) teff straw ash.The SEM image of silica is given in Figure3. As it is elucidated, the calcination temperature increases the agglomeration of the particle and also shows the high porosity of the particle. Using software called “ImageJ,” the average particle size was found to be 167 nm. The SEM pictures of unaltered silica nanoparticles in their dry condition revealed that they were essentially monodisperse with spherical shape and a narrow particle size range.Figure 3
SEM image of a biosilica nanoparticle.


## 3.3.1. Chemical Content Analysis of the Teff Straw Ash

Table1 shows the major and minor oxides of the teff straw ash sample. The major component of the ash sample, according to the atomic absorption spectrophotometer data, was SiO2. It makes up around 93% of the overall content of teff straw ash. A small amount of Fe2O3, CaO, K2O, P2O5, H2O, and traces of Al2O3, Na2O, TiO2, and MgO was also found. The term LOI refers to the amount of energy lost during the process of determining the percentage composition of silica. The element concentrations were determined using an atomic absorption spectrophotometer, whereas the oxide concentrations were evaluated using Calibration-free laser-induced breakdown spectroscopy (CF-LIBS). This approach identified CaO, MgO, FeO, Fe2O3, K2O, Al2O3, TiO2, H2O, SiO2, Na2O, Cr2O3, and P2O5 [28].According to Setiawan and Chiang [8], the crops included a high concentration of silicon ash compounds. The teff straw ash is chemically constituted of a high amount of silicon compounds. Based on this, the silica content of brown teff straw was 92.89% at 750°C ashing temperature and 2-hour ashing duration. The amount of silicon ash obtained as a result of soil chemistry, biomass nature, and climatic conditions changes the content of the biomass. As a result, the teff straw ash’s composition varied. CaO, H2O, MgO, P2O5, Fe2O3, and K2O are also present in trace amounts in proportions of 1.67, 1.34, 0.82, 0.29, 0.23, and 0.19, respectively.


## 3.3.2. FTIR, XRD, and SEM Analysis of Biosilica Nanoparticles

The important functional groups that are found in the silica are analyzed using FTIR and are presented in Figure1. A sharp peak is usually seen in the range between 3100 and 3800 cm−1 if the synthesized silica contains H2O [29]. This occurred because the prepared silica had been dried in the oven before the analysis. Therefore, the biosilica contains a small O-H group. The lower peak (2900 cm−1) in Figure 1 signposted the existence of a weak O-H group. In the region between 1850 and 3100 cm−1, there are no strong peaks apart from a very little peek at 2630 cm−1. This indicated the absenteeism of the Si-C vibrational functional group. This approves that there is no substantial organic compound in the synthesized material, and this shows that the extraction and combustion process has been done in a controlled manner. A strong Si-O-Si asymmetric band stretching functional group was found in the region of the 1050–1230 cm−1 range. The moderate concentrated sharp peak in the region of 700–800 cm−1 indicated a strong Si-O bending with a vibrational functional group. The small peak at 420 indicates the existence of a halo compound that has a strong C-I vibration. From Figures 1(a) and 1(b), teff straw ash (TSA) and teff straw-based silica nanoparticle (TSAS) were shown, additional peaks were available on silica nanoparticles, and these additional fictional groups increase the adsorption efficiency of silica nanoparticles at a lower concentration. The FTIR analysis was similar to that of previous studies reported by Peerzada and Chidambaram [30] and Bathla et al. [31].Figure 1
FTIR spectra of (a) biosilica nanoparticle from teff straw and (b) teff straw ash.The XRD patterns of the prepared biosilica nanoparticles from teff straw are presented in Figure2, revealing that the afghanite is the predominate peak at 2 thetas = 21.0848°. The broad angled peak around 2 thetas of 21.9° designates the characteristics future of amorphous silica, and it also validates that the arrangement of this silica coordination is tetrahedral. Other peaks apart from afghanite were found such as cordierite, tanteuxenite, and Na2SO4.7H2O. From Figures 2(a) and 2(b), the XRD images for TSA and TSAS are somewhat similar; however, in TSA, their crystalline peaks are around 29 and 30°; this is due to some metal oxides present within teff straw ash, but this teff straw ash was removed from the silica nanoparticles; due to this, the crystalline peak was removed. The current XRD analysis was similar to that of the study reports conducted by Hsieh et al. [32], Patel et al. [33], and Franco et al. [34].Figure 2
XRD spectra of (a) biosilica nanoparticle from teff straw and (b) teff straw ash.The SEM image of silica is given in Figure3. As it is elucidated, the calcination temperature increases the agglomeration of the particle and also shows the high porosity of the particle. Using software called “ImageJ,” the average particle size was found to be 167 nm. The SEM pictures of unaltered silica nanoparticles in their dry condition revealed that they were essentially monodisperse with spherical shape and a narrow particle size range.Figure 3
SEM image of a biosilica nanoparticle.


## 3.4. Silica Yield Obtained from Teff Straw Ash

As mentioned in the technique to identify the optimal operating process variables of pure silica as maximum, the yielding mass must be weighed after the final drying process for each run. The mass percentage yield is shown in Table2. The highest yield was 85.85%, while the lowest was 59.38%. The biosilica yield calculation was carried out to determine the optimal values of experimental variables such as (NaOH concentration, extraction duration, number of rotations, and extraction temperature) as well as investigate the influence of each variable. For the production of biosilica, 10 g of ash was utilized. As a result, the biosilica yield was calculated by using equation (10), and this helps to determine the SiO2 yield derived from teff straw ash:(10)Y%=mSiO2mTSA×100%,where Y (%) is the yield of silica obtained after extraction, mSiO2 is the mass of silica finally obtained, and mTSA is the weight of total teff ash obtained.Table 2
Experimental results of silica yield runs.
RunCoded variableIndependent variableDependent variableABCDTem. (°C)NaOH (M)RPMTime (min)Yield of silica (%)Density of silica (g.cm−3)1000−α9024505561.621.3220α009034508571.221.333−1−1−1−1851.54007059.381.41411−1−1952.54007068.511.22500009024508568.121.406−1−11−1851.55007068.161.33700009024508570.121.368α00010024508578.261.37900−α09023508562.941.2210111−1952.55007066.511.2811−1−1−11851.540010062.711.261211−11952.540010069.891.2913−1111852.550010073.221.3414−1−111851.550010076.211.391500009024508568.511.281600009024508568.481.24171−111951.550010085.851.40181−11−1951.55007078.651.391900009024508568.491.2620−11−11852.540010066.671.2421000α90245011571.321.3622−101−1852.55007066.111.242300009024508568.461.26241111952.550010073.181.37251−1−1−1951.54007073.451.35260−α009014508579.781.3727−α0008024508564.501.242800α09025508574.791.36291−1−11951.540010075.911.3730−11−1−1852.54007064.111.26


## 3.5. Experimental Design Values

### 3.5.1. Statistical Analysis for the Yield of Biosilica

This experimental design of the response surface methodology allows improving the process parameters for more than two levels by minimizing an experimental error, resulting in higher experimental accuracy [35]. To get all interaction effects, single effects, 3D diagram, and model equation, the response surface technique and experimental designs of central composite design were employed. To avoid systematic error, the trials were carried out in random order. Analysis of variance was used to determine the significance of the finding (ANOVA). The coded variable is listed in terms of the decoded variable, A stands for temperature, B stands for NaOH concentration, C stands for rotational speed, and D stands for time for silica extraction. The results obtained from the laboratory experiment are shown in Table 2. The results were obtained by using a combination of decoded variables. The coded variable is a variable that is assigned in a symbol, and the decoded variable is a variable that has a full name [36]. The four independent factors, namely, temperature, NaOH concentration, rotational speed, and extraction time, were used to determine the dependent variable yield and density of the basilica.


## 3.5.1. Statistical Analysis for the Yield of Biosilica

This experimental design of the response surface methodology allows improving the process parameters for more than two levels by minimizing an experimental error, resulting in higher experimental accuracy [35]. To get all interaction effects, single effects, 3D diagram, and model equation, the response surface technique and experimental designs of central composite design were employed. To avoid systematic error, the trials were carried out in random order. Analysis of variance was used to determine the significance of the finding (ANOVA). The coded variable is listed in terms of the decoded variable, A stands for temperature, B stands for NaOH concentration, C stands for rotational speed, and D stands for time for silica extraction. The results obtained from the laboratory experiment are shown in Table 2. The results were obtained by using a combination of decoded variables. The coded variable is a variable that is assigned in a symbol, and the decoded variable is a variable that has a full name [36]. The four independent factors, namely, temperature, NaOH concentration, rotational speed, and extraction time, were used to determine the dependent variable yield and density of the basilica.


## 3.6. ANOVA for Quadratic Model

These values obtained were analyzed by using analysis of variance (ANOVA). The experimental results were analyzed by using the level of significance (α value) at 5%. In Table 3, the F-value and p value for the models are listed. The p value helps to determine the significance and insignificance of all single factors as well as the interaction effects of each factor [37, 38]. For this study, the quadratic model is suggested; as shown in Table 3, the p values for the effects of coded variables like A, B, C, D, AB, AC, AD, BC, BD, CD, A2, B2, C2, and D2 were used as a tool to check the significance of each of the variables, which in turn are necessary to understand the pattern of the mutual interactions between the test variables. The p-values for each coded variable for A, B, C, D, AB, AC, BD, CD, A2, B2, and D2 were less than 0.0001; this shows that the single factor and the interaction effects had a significant effect on the yield of silica. However, the p values for the interaction effects of AD, BD, and C2 were 0.0697, 0.0712, and 0.6364, which are greater than 0.05, indicating that the interaction effects have no significant effect on the yield of silica. In this case, the four factors such as NaOH concentration, extraction time, rotational speed, and extraction temperature had significant effects on the yield of the biosilica.Table 3
ANOVA of fitted model for the yield of biosilica.
SourceSum of squaresdfMean squareF-valuep valueModel1026.121473.29401.21<0.0001SignificantA-temperature286.351286.351567.45<0.0001B-NaOH101.021101.02553.00<0.0001C-RPM209.811209.811148.45<0.0001D-time140.941140.94771.50<0.0001AB97.12197.12531.63<0.0001AC12.96112.9670.94<0.0001AD0.697210.69723.820.0697BC47.54147.54260.23<0.0001BD0.688910.68893.770.0712CD23.28123.28127.44<0.0001A212.24112.2467.02<0.0001B279.09179.09432.95<0.0001C20.042510.04250.2328<0.0001D28.5818.5846.98<0.0001Residual2.74150.1827Lack of fit0.1779100.01780.03471.0000Not significantFrom Table3, the model analyzed by using central composite design was highly significant, and this indicates that the regression of data fitting between experimental results and predicted values was in good agreement. From Table 4, fit statistics data results of standard deviation, mean, CV (%), R2, adjusted R2, predicted R2, and Adeq. precision were obtained. The results obtained for a standard deviation and coefficient of variation obtained for the yield of biosilica were 0.4274 and 0.6091. According to Amibo [39], the standard deviation and coefficients of variation were very low, and the data were accepted with less variation between the experimental results. For this study, the CV and standard deviation were low and acceptable with good agreement. According to El Ouadrhiri et al. [40], the adjusted R2 and predicted R2 were in good agreement below a 20% variance. The results of the modified R2 and the expected R2 were in the percentage of deviation given above. R2 is the approached one, and the experimental results and predicted values had a good fitting [10, 41–43]. For this analysis, the findings were approached to 1; therefore, the data had good fitting and were highly acceptable.Table 4
Modified ANOVA of the fitted model for the yield of biosilica.
Std. dev.MeanCV (%)R2AdjustedR2PredictedR2Adeq. precision0.427470.170.60910.99730.99490.995487.5439


### 3.6.1. The Actual and Predicted Value of an Independent Variable

Figures4(a) and 4(b) show the actual value and the expected value of each dependent variable (response) obtained. The actual and expected pulp yield values are shown in Figures 4(a) and 4(b). Actual and expected values are strongly aligned with each other in Figures 4(a) and 4(b), with an R2 value of 0.9973. The regression model equation (11) provides a very accurate description of the experimental data, in which all points are very close to the line of a perfect fit. This result indicates that it was successful in capturing the correlation between the silica production process variables to the silica yield. The adequacy of the model was further checked with the analysis of variance (ANOVA) as shown in Tables 3–5. Based on a 95% confidence level, F-value is a test for comparing model variance with residual (error) variance. If the variances are close to the same, the ratio was close to one, and any of the factors likely have a significant effect on the response with the p value less than 0.05. It was calculated by a model mean square divided by the residual mean square. From Table 3, the model F-value was 401.21, implying that the model was significant relative to the noise.Figure 4
(a) Predicted versus actual yield of silica. (b) Normal plot of residuals.
(a)(b)Table 5
Coefficients in terms of coded factors.
FactorCoefficient estimatedfStandard error95% CI low95% CI highVIFIntercept68.6910.174568.3269.07A-temperature3.4510.08723.273.641.0000B-NaOH concentration−2.0510.0872−2.24−1.871.0000C-RPM2.9610.08722.773.141.0000D-time2.4210.08722.242.611.0000AB−2.4610.1069−2.69−2.241.0000AC−0.900010.1069−1.13−0.67221.0000AD−0.208710.1069−0.43650.01901.0000BC−1.7210.1069−1.95−1.501.0000BD−0.207510.1069−0.43530.02031.0000CD1.2110.10690.97851.431.0000A20.668110.08160.49420.84211.05B21.7010.08161.521.871.05C20.039410.0816−0.13460.21331.05D2−0.559410.0816−0.7333−0.38541.05(11)Y%=68.69+3.45A−2.05B+2.96C+2.42D−2.46AB−0.9000AC−1.72BC+1.21CD+0.6681A2+1.70B2−0.5594D2.


## 3.6.1. The Actual and Predicted Value of an Independent Variable

Figures4(a) and 4(b) show the actual value and the expected value of each dependent variable (response) obtained. The actual and expected pulp yield values are shown in Figures 4(a) and 4(b). Actual and expected values are strongly aligned with each other in Figures 4(a) and 4(b), with an R2 value of 0.9973. The regression model equation (11) provides a very accurate description of the experimental data, in which all points are very close to the line of a perfect fit. This result indicates that it was successful in capturing the correlation between the silica production process variables to the silica yield. The adequacy of the model was further checked with the analysis of variance (ANOVA) as shown in Tables 3–5. Based on a 95% confidence level, F-value is a test for comparing model variance with residual (error) variance. If the variances are close to the same, the ratio was close to one, and any of the factors likely have a significant effect on the response with the p value less than 0.05. It was calculated by a model mean square divided by the residual mean square. From Table 3, the model F-value was 401.21, implying that the model was significant relative to the noise.Figure 4
(a) Predicted versus actual yield of silica. (b) Normal plot of residuals.
(a)(b)Table 5
Coefficients in terms of coded factors.
FactorCoefficient estimatedfStandard error95% CI low95% CI highVIFIntercept68.6910.174568.3269.07A-temperature3.4510.08723.273.641.0000B-NaOH concentration−2.0510.0872−2.24−1.871.0000C-RPM2.9610.08722.773.141.0000D-time2.4210.08722.242.611.0000AB−2.4610.1069−2.69−2.241.0000AC−0.900010.1069−1.13−0.67221.0000AD−0.208710.1069−0.43650.01901.0000BC−1.7210.1069−1.95−1.501.0000BD−0.207510.1069−0.43530.02031.0000CD1.2110.10690.97851.431.0000A20.668110.08160.49420.84211.05B21.7010.08161.521.871.05C20.039410.0816−0.13460.21331.05D2−0.559410.0816−0.7333−0.38541.05(11)Y%=68.69+3.45A−2.05B+2.96C+2.42D−2.46AB−0.9000AC−1.72BC+1.21CD+0.6681A2+1.70B2−0.5594D2.


## 3.7. The Effects of Single Factor on Biosilica Production

Temperature is the most important element influencing the extraction and entire manufacturing process of biosilica [44]. The influence of temperature on silica production varies depending on the experiment. To conduct the trials for this investigation, five data points were used: 80°C, 85°C, 90°C, 95°C, and 100°C. The temperature has a major influence on biosilica formation, according to numerous studies. When the temperature was below 80°C, the production of biosilica was minimal. This was owing to the fact that there was no effective collision between sodium and silicon present in teff straw ash. Then, when the temperature rises, there is an effective collision of molecules during the process. As a result, when the temperature rises between 80 and 100°C, the production of biosilica rises. For this study, the NaOH solution was adjusted at five different data points, and this was 1 M, 1.5 M, 2.0 M, 2.5 M, and 3 M. In these experiments, the amount of silica gel was highly dependent on.


## 3.8. Optimization of Biosilica Yield

The 3D response surface plot was displayed in Figures5(a)–5(f). According to Figure 5, the optimal yield varied from 59.38 to 85.85%. The minimum yield of 59.38% was achieved at 85°C, 1.5 M NaOH concentration, 400 rpm rotating speed, and 70 minute extraction time. The highest yield biosilica of 85.85% was achieved at 95°C, 1.5 M NaOH concentration, 500 rpm rotating speed, and 100 minute extraction period.Figure 5
3D interactive surface plot for biosilica yield: (a) NaOH and temperature, (b) rpm and temperature, (c) time and temperature, (d) NaOH and rpm, (e) NaOH and time, and (f) time and rpm.
(a)(b)(c)(d)(e)(f)


## 3.9. Numerical and Graphical Optimization

According to Table6, the numerical optimization was carried out by adjusting the all-process factors in the range of temperature, NaOH concentration, speed of rotation, and extraction time. However, the yield of silica was adjusted at optimum points. From Table 7, the optimized results for all process variables such as temperature, NaOH concentration, speed of rotation, and extraction time were 94.99°C (≈95°C), 1.5 M, 499.56 rpm (500 rpm), and 99.99 (100 minutes), respectively. For these process variables, the optimum yields obtained were 85.85, and the desirability for all process variables such as temperature, NaOH concentration, speed of rotation, and extraction time was one. In addition to this, desirability for yield biosilica was also one, and the combined desirability for all was one and good. Based on the optimization, the experiments were conducted at this point three times, and the obtained result was similar to the optimization results. These experiments help to explore the optimum conditions for the maximum of silica produced from teff straw; the concentration of sodium hydroxide solution varied systematically. As shown in Figure 5, the concentration varied from 1 M to 3 M. The optimal concentration of sodium hydroxide for producing biosilica was 1.5 M. If the NaOH concentration is less than 1.5 M, the teff straw ash generated does not dissolve completely in the solution. In other words, there was a sodium ion restriction when preparing sodium silicate solution (2Na2.nSiO2). However, when the concentration of sodium hydroxide is raised to 1.5 M, the extracted amount of biosilica increases significantly. However, as the concentration of sodium hydroxide exceeds 1.5 M, the extracted amount of silica falls substantially. This was attributed to the development of viscous sodium silicate solution when the concentration of NaOH increased from 1.5 M to 3 M solution. During titration, extra NaCl and OH− are produced in the solution. By neutralizing the charge of silicate oligomers and micelles, increasing the molar concentration of NaCl above that of silicate causes an increase in solution viscosity. This increase in solution viscosity appears to limit molecule dispersion and prevent silicate oligomer’s contact, preventing polymerization during the gelification process.Table 6
Constraints.
NameGoalLower limitUpper limitImportanceA: temperatureIs in range85953B: [NaOH]Is in range1.52.53C: RPMIs in range4005003D: timeIs in range701003Yield of silicaMaximize59.3885.853Table 7
The optimum yield was obtained.
NumberTemperature[NaOH]RPMTimeYield of silicaDesirability194.9881.500499.57299.99085.8531.000SelectedThe minimum amount is determined by thepH of the sodium hydroxide solution. According to the authors of the early research, silica is only soluble in sodium hydroxide solutions with a pH greater than 10. Even though the pH of 0.5 M sodium hydroxide is 13.69 at ambient temperature, the pH of the solution drops as the temperature rises. As a result, the pH of 0.5 M NaOH solution drops to nearly 10, because the lowest temperature utilized in this investigation was 80°C. The maximum level is determined by the viscosity of the sodium silicate solution. The sodium silicate solution gets more viscous as the concentration of NaOH solution exceeds 1.5 M. The yield of silica decreases as the sodium silicate solution becomes more viscous.Another element influencing biosilica extraction is the rotational speed. The influence of rpm on biosilica production varies depending on the experiment. To perform the tests for this study, five data points were used: 350 rpm, 400 rpm, 450 rpm, 500 rpm, and 550 rpm. According to several studies, rpm has a substantial impact on biosilica formation. According to Joharwan [45], the teff straw ash was laid down to the lowest portions, and the yield of biosilica was minimal. Then, as revolutions per minute rise, there is an effective collision between molecules during the process. As a result, the rpm increases from 350 rpm to 550 rpm, and so does the production of biosilica. One of the major parameters that might impact the yield of biosilica production is the extraction time [1]. Time is an independent variable that helps to identify biosilica production and ranges from 55 minutes to 115 minutes. Five different times were used to conduct the experiments: 55, 70, 85, 100, and 115 minutes. Time has a major impact on biosilica yield, and when the extraction time was shorter than 50 minutes, the production rate was poor, implying that only a small amount of biosilica was produced. This was owing to insufficient time for teff straw ash solubility for biosilica extraction during titration. Extending the extraction time beyond 120 minutes may result in the production of additional side products or a reverse reaction. Because there was ample time to react the NaOH and teff straw ash to create sodium silicate solution (2Na2.nSiO2), the extraction period increased the yield of biosilica. Finally, at higher temperatures, higher NaOH concentrations, longer contact times, and faster rotational speeds, the yield obtained was not optimum. This was due to the formation of side products, the development of viscous sodium silicate solution, the formation of intermediate products, and the interaction effects of each factor, which resulted in the formation of minimum yields.


## 3.10. The Yield of Biosilica and Physicochemical Properties

In this study, the optimization was conducted, the obtained result ranged from 59.38% to 85.85%, and the raw material utilized for this study was teff straw. The purity and surface area measured with BET (Brunauer–Emmett–Teller) for nanosilica produced were 97.63% and 305 m2/g, respectively. The density of silica nanoparticles produced under this study ranged from 1.22 to 1.40 gcm−3. In the different studies, the biosilica nanomaterials were produced from rice husk, rice straw, and other agricultural wastes [33]. According to the prior findings of Selvakumar et al. [46], the silica produced had an 85% of yield, which was equivalent to the current findings, although the manufacturing techniques were considerably different. The rice husk was leached with HCl in this investigation, and the NaOH concentration employed varied from 0.1 to 1 mol/L (M), with an extraction duration of 2 hours. According to previous research by Mehta and Ugwekar [47], the silica generated from rice husk varied from 66.11 to 71.15% at 2 mol/L(M) NaOH concentration with a 2 hr extraction period using the HCl leaching procedure. Similarly, in a study reported by Steven et al. [44], the biosilica nanoparticle was produced from rice husk with a purity of 99.7% and a maximum yield of 98%. In this study, the combustion temperature for the ashing process was 700°C, and other variables such as NaOH and HCl were considered, with a surface area of 400.69 m2/g. Fernandes et al. [48] generated biosilica nanoparticles from rice husk with a purity of 99.61% and a surface area of 290.03 m2/g, which was equivalent to the current study surface area.


## 3.11. Methyl Orange Adsorption

The XRD and AAS analyses show that the prepared samples contain a high amount of silica. It is also seen in the FTIR analysis that the samples possess silica functionality. Because the silica functionality can interact with the polar groups of other pollutants through strong H-bonds and complex mechanisms, the prepared silica sample was tested for the adsorptive removal of methyl orange from an aqueous solution. The first step in the adsorption experiment was the preparation of a standard graph. The graph consists of methyl orange concentration versus its adsorption. The result is shown in Table8.Table 8
Adsorption of methyl orange at different concentration.
Before adsorptionAfter absorption% removalInitial conc.AbsorbanceFinal conc.Absorbance1 × 10−50.1916.86 × 10−60.17531.52 × 10−50.2215.81 × 10−60.17170.953 × 10−50.2635.29 × 10−60.16982.374 × 10−50.2995.03 × 10−60.16887.435 × 10−50.3434.76 × 10−60.16790.48From Figure6, the R2 value is 99.65%, which implies that 99% of the total variation in the adsorption is attributed to the experimental variables studied. The model equation is(12)y=0.0382x+0.1488,where y is the absorbance of methyl orange dye value and x is the concentration of methyl orange.Figure 6
Methyl orange dye concentrations versus adsorption.After the adsorption experiment was performed, the adsorption capacity of the treated methyl orange solution was measured using UV-visible spectroscopy, and the concentration of the residual methyl orange in the solution was calculated using the model equation (9). To know the removed percentage of methyl orange by the prepared silica, equation (8) was used. From Table 8, the average removal efficiency of methyl orange using the prepared silica was 90.40%. The teff straw ash silica adsorbs methyl orange because it is a porous material and has an active group that is Si-O-Si and Si-OH [49].


## 4. Conclusions

The higher yield biosilica was obtained from teff straw by combining various parameters using a sol-gel process. The central composite design was used in evaluating the interaction effects of all parameters, and the quadratic model was used. The temperature has the most critical effect on the yield of silica. The optimum extraction conditions for amorphous silica were 1.50 M NaOH, 109.99 minutes, 94.98°C, and a rotating speed of 499.57 rpm, with a maximum yield of 85.85%. XRD and FTIR analyses were used to assess the physicochemical characteristics of the extracted silica. The aqueous solution of methyl orange was used to test the adsorption efficiency of silica. The percent of removal efficiency for methyl orange dye was 90.48%.



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